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Good morning everyone, I am once again returning to Hem and Haw about something I care about. In last months episode, I told you all to be like Davy Crockett. [https://www.themotte.org/post/1635/why-you-should-shoot-black-powder] In today's installment, I am going to do what my friends call "Clocking in as the VP of Finance" for Major League Baseball. We say this because we all love to moan and complain about what we would do to change the game like we are on the board of directors, even though we do not have any power to do so. I have loved the game of baseball since I was a small boy. I still play now as an adult - albeit poorly - but as long as I can, I always will. I am hoping in the next few minutes I can mostly get you to agree with the following opinions:
The Mound should be moved back
Strikeouts do suck actually
A return of .300+ hitters would be a good thing for baseball
Baseball traditionally hates change. Since the very beginning, people have fought, bitched, moaned, complained, and damned every single change to the game. Candy Cummings invented the Curveball throwing Oyster Shells with his friends down at the docks; hitters demanded its ban. Billy Hamilton reading the rulebook one night realized the ball was always in play and the next day simply ran to second base while the pitcher stood on the mound; people laughed and told him to return to first. Black men were told they simply could not cut it for years and years, now they occupy Cooperstown just like those from all other walks of life. My point being every time the game has a change proposed to it that ends up becoming something we can't imagine the game without, we still end up fighting it for years.
Bill James is a very smart man, I do not think anyone can discredit him for that. He came up with a very visionary system in the mid 1970's called Sabermetrics that challenged traditional baseball thinking to its core. Basically the tenets of his idea are that all points of the game of baseball can be quantified and an optimal strategy can be made to get a team to win games. His argument comes down to outs, outs are what is valuable in a game and it does not really matter how they are made as long as they are held onto for dear life. For years this idea was ignored. Of course there are ways an out matters! People would say putting the ball in play is all that matters - swing and put it in play. If you played baseball as a kid, you probably remember being taught that Striking out was basically the worst thing you could do. Central to Bill James' idea is that this is simply not true. It took a while, but about 25 years after He started writing about this, Major League Baseball was forced to take notice after the Oakland A's put this idea into practice and made a winning ballclub. I do think that the logic of get on base any way you can makes sense and it has been proven that it can win ballgames, but it has also created a brand of baseball that is just flat out boring to watch.
With the addition of Sabermetrics to baseball Professional players are being taught now that strikeouts don't matter, Walks are very important, hitting the ball hard if you do swing is all that matters. This has lead to a rise in what are called "Three true outcome" hitters. If you liked baseball as a kid but now think it is rather boring it is probably because you dislike these without realizing it. The three true outcomes are Walk, Strikeout, and Homerun. In the 1970s it was very rare to see a player like this; Dave Kingman is an example: Huge power, bad average. They were the exception, but now they have become the rule. It is normal, if not totally expected, for a player to hit .240 with 15 home runs a season now with 150+ strikeouts. If you go over baseball stats you will find dozens of guys just like this. Personally, I think this should go the way of the Dodo. You can't make them unlearn an idea obviously though so how do you go about fixing this? This is where my argument for the mound moving back comes from.
Recently there have been other changes to the game. If you have not watched in a while you may be surprised by the speed of a game now; they are about 50 mins shorter than before that's to the addition of a pitch clock. I am a true believer of the pitch clock. Some say that it has ruined the game (see above to see what people used to say) but in reality it is a return to normalcy. Over the last 30 years or so, another revelation a lot of clubs had was that with no clock there was nothing stopping the hitter or pitcher from setting the pace. This lead to players doing all sorts of things between pitches - nut scratch, play with batting gloves, walk in a circle - really just brutal to watch as a fan. I am so glad this is dead and buried - good riddance!
OK so I have covered a little prehistory and now you are up to speed as to why we are where we are today. Let's talk about why I think moving the mound back is a good idea.
Pitching has gotten more powerful as the years have gone by but especially so in the last 15 years. Pitchers are bigger and stronger than before. In the early days of baseball they had almost the same exact problem we have today. Pitchers threw underhand out of a box 50 feet from the plate, but in 1884 due to increasing pressure overhand pitching as you know it today was made legal. What basically happened was overnight the Pitcher went from an irrelevant part of the game to the most important man on the Diamond. If you want to see an example of how dramatic of a change this was let's look at a player and see how his numbers changed. Charlie Sweeney in 1883 (last underhand year) had a 3.13 ERA with 48 Strikeouts in 140-odd innings pitched - honestly, not bad numbers. In 1884 Charlie Sweeney had a 1.70 ERA with 337 Strikeouts in a little under 500 Innings pitched. He also set a record 19 strikeouts in a game that stood for over 100 years until it was beaten by Roger Clemens. Pitchers were simply outmatching all hitters they faced and in 1893 to help deal with this the mound was moved back 10 feet 6 inches to where it is today to give hitters a better chance; just a little more time to see the ball.
So ok yeah sure I know you are saying "these guys also fought at the battle of Gettysburg for spring training how hard could they have really been throwing?" Well the short answer is: we really don't know. The long answer is, probably about what you would see today at your local Varsity Highschool baseball game; right around the Mid 80s. This was probably true up through about the 1950s. Pitchers that were truly great threw in the 90s, even 100s, way back in the 1920s. Walter Johnson was measured throwing about 95; so was Bob Feller, and we all know about Nolan Ryan. So since the early days pitching was pretty constant and for years it stayed that way. But since about 2005 speeds have creeped and now the average fastball is about 94MPH. I think this tied in with our previous discussion about three true outcome hitters has created a perfect storm.
I think it is time we move the mound back another 10 feet, with the speeds pitchers are touching now these days it is to the point I think hitters are simply outmatched. We have been trending this way for the better part of 70 years, there has not been a .400 hitter since Ted Williams in 1941 and I don't think its because hitters are simply worse than he was; I think it is just because our players are starting to outgrow the confines of their current field. so lets go over some pro's and con's of what moving the mound back would do:
Wouldn't this just kill pitchers' fastballs and make every game a hit-a-thon?
I think this will definitely take some zip out of peoples fastballs sure, but you also have to think a pitchers big hammer curve will also then have another 10 feet to break. Think of how much more breaking stuff will be effective! I think it will let the pros get an extra half second to see and swing at a ball helping hitters sure but also probably working in favor of "stuff guys" as well giving them more real estate to work with. I think the cream always rises to the top and the best pitchers will still be the best pitchers, same with the hitters. I think this will just make offense a more common occurrence. Plus think if Vlad Guerrero Jr can hit .323 with 30 home runs while seeing 100 mph from 60 feet imagine what he could do from 70.
So Pitchers will stop striking guys out all the time?
Ideally, yes this is what moving the mound back should do. A return to the offense of the 1920s-1960s: stolen bases, high averages, this was a time when baseball players were household names. In fact, I bet if you asked a random person on the street they could probably name you one from that 40 years faster than they could one guy today.
Would this lead to more injuries?
This was the argument made as well for keeping the clock out but there has not been an uptick and everyone is still playing just fine.
All in all I will always love this game but I think it might be time to really think about addressing this and maybe making a step forward by taking about 10 steps back, also to this point if you are a I miss steroids guy im telling you man you don't miss steroids you miss offense!
Here some people have expressed interest in my take on AI broadly, and then there's Deepseek-Coder release, but I've been very busy and the field is moving so very fast again, it felt like a thankless job to do what Zvi does and without his doomer agenda too (seeing the frenetic feed on Twitter, one can be forgiven for just losing the will; and, well, I suppose Twitter explains a lot about our condition in general). At times I envy Iconochasm who tapped out. Also, this is a very niche technical discussion and folks here prefer policy.
But, in short: open source AI, in its most significant aspects, which I deem to be code generation and general verifiable reasoning (you can bootstrap most everything else from it), is now propped up by a single Chinese hedge fund (created in the spirit of Renaissance Capital) which supports a small, ignored (except by scientists and a few crackpots on Twitter) research division staffed with some nonames, who are quietly churning out extraordinarily good models with the explicit aim of creating AGI in the open. These models happen to be (relatively) innocent of benchmark-gaming, but somewhat aligned to Chinese values. The modus operandi of DeepSeek is starkly different from that of either other Chinese or Western competitors. In effect this is the only known group both meaningfully pursuing frontier capabilities and actively teaching others how to do so. I think this is interesting and a modest cause for optimism. I am also somewhat reluctant to write about this publicly because there exist lovers of Freedom here, and it would be quite a shame if my writing contributed to targeted sanctions and even more disempowerment of the small man by the state machinery in the final accounting.
But the cat's probably out of the bag. The first progress prize of AI Mathematical Olympiad had just been taken by a team using their DeepSeekMath-7B model, solving 29 out of 50 private test questions «less challenging than those in the IMO but at the level of IMO preselection»; Terence Tao finds it «somewhat higher than expected» (he is on the AIMO Advisory Committee, along with his fellow Fields medalist Timothy Gowers).
The next three teams entered with this model as well.
I. The shape of the game board
To provide some context, here's an opinionated recap of AI trends since last year. I will be focusing exclusively on LLMs, as that's what matters (image gen, music gen, TTS etc largely are trivial conveniences, and other serious paradigms seem to be in their embryonic stage or in deep stealth).
- We have barely advanced in true out-of-distribution reasoning/understanding relative to the original «Sparks of AGI» GPT-4 (TheDag, me); GPT-4-04-29 and Sonnet 3.5 were the only substantial – both minor – steps forward, Gemini was a catch-up effort, and nobody else has yet credibly reached the same tier. We have also made scant progress towards consensus on whether that-which-LLMs-do is «truly» reasoning or understanding; sensible people have recoursed to something like «it's its own kind of mind, and hella useful».
- Meanwhile there's been a great deal of progress in scaffolding (no more babyAGI/AutoGPT gimmicry, now agents are climbing up the genuinely hard SWE-bench), code and math skills, inherent robustness in multi-turn interactions and responsiveness to nuanced feedback (to the point that LLMs can iteratively improve sizable codebases – as pair programmers, not just fancy-autocomplete «copilots»), factuality, respect of prioritized system instructions, patching badly covered parts of the world-knowledge/common sense manifold, unironic «alignment» and ironing out Sydney-like kinks in deployment, integrating non-textual modalities, managing long contexts (merely usable 32K "memory" was almost sci-fi back then, now 1M+ with strong recall is table stakes at the frontier; with 128K mastered on a deeper level by many groups) and a fairly insane jump in cost-effectiveness – marginally driven by better hardware, and mostly by distilling from raw pretrained models, better dataset curation, low-level inference optimizations, eliminating architectural redundancies and discovering many "good enough" if weaker techniques (for example, DPO instead of PPO). 15 months ago,"$0.002/1000 tokens" for gpt-3.5-turbo seemed incredible; now we always count tokens by the million, and Gemini-Flash blows 3.5-turbo out of the water for half that, so hard it's not funny; and we have reason to believe it's still raking in >50% margins whereas OpenAI probably subsidized their first offerings (though in light of distilling and possibly other methods of compute reuse, it's hard to rigorously account for a model's capital costs now).
- AI doom discourse has continued to develop roughly as I've predicted, but with MIRI pivoting to evidence-free advocacy, orthodox doomerism getting routed as a scientific paradigm, more extreme holdovers from it («emergent mesaoptimizers! tendrils of agency in inscrutable matrices!») being wearily dropped by players who matter, and misuse (SB 1047 etc) + geopolitical angle (you've probably seen young Leopold) gaining prominence.
- The gap in scientific and engineering understanding of AI between the broader community and "the frontier" has shrunk since the debut of GPT-4 or 3.5, because there's too much money to be made in AI and only so much lead you can get out of having assembled the most driven AGI company. Back then, only a small pool of external researchers could claim to understand what the hell they did above the level of shrugging "well, scale is all you need" (wrong answer) or speculating about some simple methods like "train on copyrighted textbooks" (spiritually true); people chased rumors, leaks… Now it takes weeks at most to trace a yet another jaw-dropping magical demo to papers, to cook up a proof of concept, or even to deem the direction suboptimal; the other two leading labs no longer seem desperate, and we're in the second episode of Anthropic's comfortable lead.
- Actual, downloadable open AI sucks way less than I've lamented last July. But it still sucks. And that's really bad, since it sucks most in the dimension that matters: delivering value, in the basest sense of helping do work that gets paid. And the one company built on the promise of «decentralizing intelligence», which I had hope for, had proven unstable.
To be more specific, open source (or as some say now, given the secretiveness of full recipes and opacity of datasets, «open weights») AI has mostly caught up in «creativity» and «personality», «knowledge» and some measure of «common sense», and can be used for petty consumer pleasures or simple labor automation, but it's far behind corporate products in «STEM» type skills, that are in short supply among human employees too: «hard» causal reasoning, information integration, coding, math. (Ironically, I agree here with whining artists that we're solving domains of competence in the wrong order. Also it's funny how by default coding seems to be what LLMs are most suited for, as the sequence of code is more constrained by preceding context than natural language is).
To wit, Western and Eastern corporations alike generously feed us – while smothering startups – fancy baubles to tinker with, charismatic talking toys; as they rev up self-improvement engines for full cycle R&D, the way imagined by science fiction authors all these decades ago, monopolizing this bright new world. Toys are getting prohibitively expensive to replicate, with reported pretraining costs up to ≈$12 million and counting now. Mistral's Mixtral/Codestral, Musk's Grok-0, 01.Ai's Yi-1.5, Databricks' DBRX-132B, Alibaba's Qwens, Meta's fantastic Llama 3 (barring the not-yet-released 405B version), Google's even better Gemma 2, Nvidia's massive Nemotron-340B – they're all neat. But they don't even pass for prototypes of engines you can hop on and hope to ride up the exponential curve. They're too… soft. And not economical for their merits.
Going through our archive, I find this year-old analysis strikingly relevant:
I think successful development of a trusted open model rivaling chatgpt in capability is likely in the span of a year, if people like you, who care about long-term consequences of lacking access to it, play their cards reasonably well. […] Companies whose existence depends on the defensibility of the moat around their LM-derived product will tend to structure the discourse around their product and technology to avoid even the fleeting perception of being a feasibly reproducible commodity.
That's about how it went. While the original ChatGPT, that fascinating demo, is commodified now, competitive product-grade AI systems are not, and companies big and small still work hard to maintain the impression that it takes
- some secret sauce (OpenAI, Anthropic)
- work of hundreds of Ph.Ds (Deepmind)
- vast capital and compute (Meta)
- "frontier experience" (Reka)
– and even then, none of them have felt secure enough yet to release a serious threat to the other's proprietary offers.
I don't think it's a big exaggerion to say that the only genuine pattern breaker – presciently mentioned by me here – is DeepSeek, the company that has single-handedly changed – a bit – my maximally skeptical spring'2023 position on the fate of China in the AGI race.
II. Deep seek what?
AGI, I guess. Their Twitter bio states only: «Unravel the mystery of AGI with curiosity. Answer the essential question with long-termism». It is claimed by the Financial Times that they have a recruitment pitch «We believe AGI is the violent beauty of model x data x computing power. Embark on a ‘deep quest’ with us on the journey towards AGI!» but other than that nobody I know of has seen any advertisement or self-promotion from them (except for like 70 tweets in total, all announcing some new capability or responding to basic user questions about license), so it's implausible that they're looking for attention or subsidies. Their researchers maintain near-perfect silence online. Their – now stronger and cheaper – models tend to be ignored in comparisons by Chinese AI businesses and users. As mentioned before, one well-informed Western ML researcher has joked that they're the bellwether for «the number of foreign spies embedded in the top labs».
FT also says the following of their parent company:
Its funds have returned 151 per cent, or 13 per cent annualised, since 2017, and were achieved in China’s battered domestic stock market. The country’s benchmark CSI 300 index, which tracks China’s top 300 stocks, has risen 8 per cent over the same time period, according to research provider Simu Paipai.
In February, Beijing cracked down on quant funds, blaming a stock market sell-off at the start of the year on their high-speed algorithmic trading. Since then, High-Flyer’s funds have trailed the CSI 300 by four percentage points.
[…] By 2021, all of High-Flyer’s strategies were using AI, according to manager Cai Liyu, employing strategies similar to those pioneered by hugely profitable hedge fund Renaissance Technologies. “AI helps to extract valuable data from massive data sets which can be useful for predicting stock prices and making investment decisions,” …
Cai said the company’s first computing cluster had cost nearly Rmb200mn and that High Flyer was investing about Rmb1bn to build a second supercomputing cluster, which would stretch across a roughly football pitch-sized area. Most of their profits went back into their AI infrastructure, he added. […] The group acquired the Nvidia A100 chips before Washington restricted their delivery to China in mid-2022.
“We always wanted to carry out larger-scale experiments, so we’ve always aimed to deploy as much computational power as possible,” founder Liang told Chinese tech site 36Kr last year. “We wanted to find a paradigm that can fully describe the entire financial market.”
In a less eclectic Socialist nation this would've been sold as Project Cybersyn or OGAS. Anyway, my guess is they're not getting subsidies from the Party any time soon.
They've made a minor splash in the ML community eight months ago, in late October, releasing an unreasonably strong Deepseek-Coder. Yes, in practice an awkward replacement for GPT-3.5, yes, contaminated with test set, which prompted most observers to discard it as a yet another Chinese fraud. But it proved to strictly dominate hyped-up things like Meta's CodeLLaMA and Mistral's Mixtral 8x7b in real-world performance, and time and again proved to be the strongest open baseline in research papers. On privately designed, new benchmarks like this fresh one from Cohere it's clear that they did get to parity with OpenAI's workhorse model, right on the first public attempt – as far as coding is concerned.
On top of that, they shared a great deal of information about how: constructing the dataset from Github, pretraining, finetuning. The paper was an absolute joy to read, sharing even details on unsuccessful experiments. It didn't offer much in the way of novelty; I evaluate it as a masterful, no-unforced-errors integration of fresh (by that point) known best practices. Think about your own field and you'll probably agree that even this is a high bar. And in AI, it is generally the case that either you get a great model with «we trained it on some text… probably» tech report (Mistral, Google), or a mediocre one accompanied by a fake-ass novel full of jargon (every second Chinese group). Still, few cared.
Coder was trained, it seems, using lessons of the less impressive Deepseek-LLM-67B (even so, it was roughly Meta's LLaMA-2-70B peer that also could code; a remarkable result for a literally-who new team), which somehow came out a month after. Its paper (released even later still) was subtitled «Scaling Open-Source Language Models with Longtermism». I am not sure if this was some kind of joke at the expense of effective altruists. What they meant concretely was the following:
Over the past few years, LLMs … have increasingly become the cornerstone and pathway to achieving Artificial General Intelligence (AGI). … Guided by the scaling laws, we introduce DeepSeek LLM, a project dedicated to advancing open-source LMs with a long-term perspective.
- …Soon, we will release our technique reports in code intelligence and Mixture-of-Experts(MoE), respectively. They show how we create high-quality code data for pre-training, and design a sparse model to achieve dense model performance.
- At present, we are constructing a larger and improved dataset for the upcoming version of DeepSeek LLM. We hope the reasoning, Chinese knowledge, math, and code capabilities will be significantly improved in the next version.
- Our alignment team is dedicated to studying ways to deliver a model that is helpful, honest, and safe to the public. Our initial experiments prove that reinforcement learning could boost model complex reasoning capability.
…I apologize for geeking out. All that might seem normal enough. But, a) they've fulfilled every one of those objectives since then. And b) I've read a great deal of research papers and tech reports, entire series from many groups, and I don't remember this feeling of cheerful formidability. It's more like contemplating the dynamism of SpaceX or Tesla than wading through a boastful yet obscurantist press release. It is especially abnormal for a Mainland Chinese paper to be written like this – with friendly confidence, admitting weaknesses, pointing out errors you might repeat, not hiding disappointments behind academese word salad; and so assured of having a shot in an honest fight with the champion.
In the Coder paper, they conclude:
…This advancement underscores our belief that the most effective code-focused Large Language Models (LLMs) are those built upon robust general LLMs. The reason is evident: to effectively interpret and execute coding tasks, these models must also possess a deep understanding of human instructions, which often come in various forms of natural language. Looking ahead, our commitment is to develop and openly share even more powerful code-focused LLMs based on larger-scale general LLMs.
In the Mixture-of-Experts paper (8th January), they've shown themselves capable of novel architectural research too, introducing a pretty ingenuous «fine-grained MoE with shared experts» design with the objective of «Ultimate Expert Specialization» and economical inference: «DeepSeekMoE 145B significantly outperforms Gshard, matching DeepSeek 67B with 28.5% (maybe even 14.6%) computation». For those few who noticed it, this seemed a minor curiosity, or just bullshit.
On 5th February, they've dropped DeepSeekMath,of which I've already spoken: «Approaching Mathematical Reasoning Capability of GPT-4 with a 7B Model». Contra the usual Chinese pattern, it wasn't a lie; no, you couldn't in normal use get remotely as good results from it, but in some constrained regimes… The project itself was a mix of most of the previous steps: sophisticated (and well-explained) data harvesting pipeline, scaling laws experiments, further «longtermist» continued pretraining from Coder-7B-1.5 which itself is a repurposed LLM-7B, and the teased reinforcement learning approach. Numina, winners of AIMO, say «We also experimented with applying our SFT recipe to larger models like InternLM-20B, CodeLama-33B, and Mixtral-8x7B but found that (a) the DeepSeek 7B model is very hard to beat due to its continued pretraining on math…».
In early March they released DeepSeek-VL: Towards Real-World Vision-Language Understanding, reporting some decent results and research on building multimodal systems, and again announcing new plans: «to scale up DeepSeek-VL to larger sizes, incorporating Mixture of Experts technology».
III. Frontier minor league
This far, it's all been preparatory R&D, shared openly and explained eagerly yet barely noticed by anyone (except that the trusty Coder still served as base for labs like Microsoft Research to experiment on): utterly overshadowed in discussions by Alibaba, Meta, Mistral, to say nothing of frontier labs.
But on May 6th, 2024, the pieces began to fall into place. They released «DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model», which subsumed all aforementioned works (except VL).
It's… unlike any other open model, to the point you could believe it was actually made by some high-IQ finance bros from first principles. Its design choices are exquisite, just copying minor details can substantially improve on typical non-frontier efforts. It pushes further their already unorthodox MoE and tops it off with a deep, still poorly understood modification to the attention mechanism (Multi-head Latent Attention, or MLA). It deviates from industry-standard rotary position embeddings to accomodate the latter (a fruit of collaboration with RoPE's inventor). It's still so unconventional that we are only beginning to figure out how to run it properly (they don't share their internal pipeline, which is optimized for hardware they can access given American sanctions). But in retrospect, it's the obvious culmination of the vision announced with those first model releases and goofy tweets, probably a vision not one year old, and yet astonishingly far-sighted – especially given how young their star researchers are. But probably it's mundane in the landscape of AI that's actually used; I suspect it's close to how Sonnet 3.5 or Gemini 1.5 Pro work on the inside. It's just that the open-source peasants are still mucking around with stone age dense models on their tiny consumer GPUs.
I understand I might already be boring you out of your mind, but just to give you an idea of how impressive this whole sequence is, here's a 3rd April paper for context:
Recent developments, such as Mixtral (Jiang et al., 2024), DeepSeek-MoE (Dai et al., 2024), spotlight Mixture-of-Experts (MoE) models as a superior alternative to Dense Transformers. An MoE layer works by routing each input token to a selected group of experts for processing. Remarkably, increasing the number of experts in an MoE model (almost) does not raise the computational cost, enabling the model to incorporate more knowledge through extra parameters without inflating pre-training expenses… Although our findings suggest a loss-optimal configuration with Emax experts, such a setup is not practical for actual deployment. The main reason is that an excessive number of experts makes the model impractical for inference. In contrast to pretraining, LLM inference is notably memory-intensive, as it requires storing intermediate states (KV-cache) of all tokens. With more experts, the available memory for storing KV caches is squeezed. As a result, the batch size – hence throughput – decreases, leading to increased cost per query. … We found that MoE models with 4 or 8 experts exhibit more efficient inference and higher performance compared to MoE models with more experts. However, they necessitate 2.4x-4.3x more training budgets to reach the same performance with models with more experts, making them impractical from the training side.
This is basically where Mistral.AI, the undisputed European champion with Meta and Google pedigree (valuation $6.2B), the darling of the opensource community, stands.
And yet, apparently DeepSeek have found a way to get out of the bind. «4 or 8»? They scale to 162 experts, reducing active parameters to 21B, cutting down pretraining costs by 42.5% and increasing peak generation speed by 5.76x; and they scale up the batch size via compressing the KV cache by like 15 times with a bizarre application of low-rank projections and dot attention; and while doing so they cram in 3x more attention heads than any model this size has any business having (because their new attention decouples number of heads from cache size), and so kick the effective «thinking intensity» up a notch, beating the gold standard «Multihead attention» everyone has been lousily approximating; and they use a bunch of auxiliary losses to make the whole thing maximally cheap to use on their specific node configuration.
But the cache trick is pretty insane. The hardest-to-believe, for me, part of the whole thing. Now, 2 months later, we know that certain Western groups ought to have reached the same Pareto frontier, just with different (maybe worse, maybe better) tradeoffs. But those are literally inventors and/or godfathers of the Transformer – Noam Shazeer's CharacterAI, Google Deepmind's Gemini line… This is done by folks like this serious-looking 5th year Ph.D student, in under a year!
As a result, they:
- use about as much compute on pretraining as Meta did on Llama-3-8B, an utter toy in comparison (maybe worth $2.5 million for them); 1/20th of GPT-4.
- Get a 236B model that's about as good across the board as Meta's Llama-3-70B (≈4x more compute), which has the capacity – if not the capability – of mid-range frontier models (previous Claude 3 Sonnet; GPT-4 on a bad day).
- Can serve it at around the price of 8B, $0.14 for processing 1 million tokens of input and $0.28 for generating 1 million tokens of output (1 and 2 Yuan), on previous-gen hardware too.
- …and still take up to 70%+ gross margins, because «On a single node with 8 H800 GPUs, DeepSeek-V2 achieves a generation throughput exceeding 50K tokens per second… In addition, the prompt input throughput of DeepSeek-V2 exceeds 100K tokens per second», and the going price for such nodes is ≤$15/hr. That's $50 in revenue, for clarity. They aren't doing a marketing stunt.
- …and so they force every deep-pocketed mediocre Chinese LLM vendor – Alibaba, Zhipu and all – to drop prices overnight, now likely serving at a loss.
Now, I am less sure about some parts of this story; but mostly it's verifiable.
I can see why an American, or a young German like Leopold, would freak out about espionage. The thing is, their papers are just too damn good and too damn consistent over the entire period if you look back (as I did), so «that's it, lock the labs» or «haha, no more tokens 4 u» is most likely little more than racist cope for the time being. The appropriate reaction would be more akin to «holy shit Japanese cars are in fact good».
Smart people (Jack Clark from Anthropic, Dylan Patel of Semianalysis) immediately take note. Very Rational people clamoring for AI pause (TheZvi) sneer and downplay: «This is who we are worried about?» (as he did before, and before). But it is still good fun. Nothing extreme. There slowly begin efforts at adoption: say, Salesforce uses V2-Chat to create synthetic data to finetune small Deepseek-Coder V1s to outperform GPT-4 on narrow tasks. Mostly nobody cares.
The paper ends in the usual manner of cryptic comments and commitments:
We thank all those who have contributed to DeepSeek-V2 but are not mentioned in the paper. DeepSeek believes that innovation, novelty, and curiosity are essential in the path to AGI.
DeepSeek will continuously invest in open-source large models with longtermism, aiming to progressively approach the goal of artificial general intelligence.
• In our ongoing exploration, we are dedicated to devising methods that enable further scaling up MoE models while maintaining economical training and inference costs. The goal of our next step is to achieve performance on par with GPT-4 in our upcoming release.
In the Appendix, you can find a lot of curious info, such as:
During pre-training data preparation, we identify and *filter out contentious content, such as values influenced by regional cultures, to avoid our model exhibiting unnecessary subjective biases on these controversial topics. Consequently, we observe that DeepSeek-V2 performs slightly worse on the test sets that are closely associated with specific regional cultures. For example, when evaluated on MMLU, although DeepSeek-V2 achieves comparable or superior performance on the majority of testsets compared with its competitors like Mixtral 8x22B, it still lags behind on the Humanity-Moral subset, which is mainly associated with American values.
Prejudices of specific regional cultures aside, though, it does have values – true, Middle Kingdom ones, such as uncritically supporting the Party line and adherence to Core Values Of Socialism (h/t @RandomRanger). The web version will also delete the last message if you ask something too clever about Xi or Tiananmen or… well, nearly the entirety of usual things Americans want to talk to Chinese coding-oriented LLMs about.
And a bit earlier, this funny guy from the team presented at Nvidia's GTC24 with the product for the general case – «culturally sensitive», customizable alignment-on-demand: «legality of rifle» for the imperialists, illegality of Tibet separatism for the civilized folk. Refreshingly frank.
But again, even that was just a preparatory.
IV. Coming at the king
Roughly 40 days later they release DeepSeek-V2-Coder: Breaking the Barrier of Closed-Source Models in Code Intelligence, where they return to the strategy announced at the very start: they take an intermediate checkpoint of V2, and push it harder and further on the dataset enriched with code and math (that that've continued to expand and refine), for 10.2 trillion tokens total. Now this training run is 60% more expensive than Llama-3-8B (still a pittance by modern standards). It also misses out on some trivia knowledge and somehow becomes even less charismatic. It's also not a pleasant experience because the API runs very slowly, probably from congestion (I guess Chinese businesses are stingy… or perhaps DeepSeek is generating a lot of synthetic data for next iterations). Anons on 4chan joke that it's «perfect for roleplaying with smart, hard-to-get characters».
More importantly though, it demolishes Llama-3-70B on every task that takes nontrivial intelligence; bests Claude 3 Opus on coding and math throughout, Gemini 1.5-Pro on most coding assistance, and trades blows with the strongest GPT-4 variants. Of course it's the same shape and the same price, which is to say, up to 100 times cheaper than its peers… more than 100 times, in the case of Opus. Still a bitch to run, but it turns out they're selling turnkey servers. In China, of course. To boot, they rapidly shipped running code in browser (a very simple feature but going most of the way to Claude Artifacts that wowed people do much), quadrupled context length without price changes (32k to 128k) and now intend to add context caching that Google boasts of as some tremendous Gemini breakthrough. They have... Impressive execution.
Benchmarks, from the most sophisticated and hard to hack to the most bespoke and obscure, confirm that it's «up there».
- Aider (2nd, 1st at release)
- LMSYS Arena (low on Overall, but 5th rank on Coding and 7 ranks above Google and Meta's open source alternatives, respectively 11th and 3+ ranks above on Hard subsample)
- Arena-Hard-Auto(7th, surprisingly 2 more Chinese models narrowly get ahead)
- %compilable Golang programs (2nd)
- Livebench (7th, by virtue of being 5th-6th in coding and reasoning and 2nd in Math; everyone above is OpenAI/Anthropic)
- LiveCodeBench (4th, same order)
- BigCodeBench(2nd)
- Gaokao-Math, released days before its deployment (roughly above GPT-4o)
Etc etc, and crucially, users report similar impressions:
So I have pegged deepseek v2 coder against sonnet 3.5 and gpt4o in my coding tasks and it seems to be better than gpt4o (What is happening at OpenAI) and very similar to Sonnet 3.5. The only downside is the speed, it's kinda slow. Very good model and the price is unbeatable.
I had the same experience, this is a very good model for serious tasks. Sadly the chat version is very dry and uncreative for writing. Maybe skill issue, I do not know. It doesn't feel slopped, it's just.. very dry. It doesn't come up with things.
Some frustrating weak points, but they know of those, and conclude:
Although DeepSeek-Coder-V2 achieves impressive performance on standard benchmarks, we find that there is still a significant gap in instruction-following capabilities compared to current state-of-the-art models like GPT-4 Turbo. This gap leads to poor performance in complex scenarios and tasks such as those in SWEbench. […] In the future, we will focus more on improving the model’s instruction-following capabilities…
Followed by the list of 338 supported languages.
Well-read researchers say stuff like
DeepSeek-Coder-V2 is by far the best open-source math (+ coding) model, performing on par with GPT4o w/o process RM or MCTS and w/ >20x less training compute. Data contamination doesn't seem to be a concern here. Imagine about what this model could achieve with PRM, MCTS, and other yet-to-be-released agentic exploration methods. Unlike GPT4o, you can train this model further. It has the potential to solve Olympiad, PhD and maybe even research level problems, like the internal model a Microsoft exec said to be able to solve PhD qualifying exam questions».
Among the Rational, there is some cautious realization («This is one of the best signs so far that China can do something competitive in the space, if this benchmark turns out to be good»), in short order giving way to more cope : «Arena is less kind to DeepSeek, giving it an 1179, good for 21st and behind open model Gemma-2-9B».
And one more detail: A couple weeks ago, they released code and paper on Expert-Specialized Fine-Tuning, «which tunes the experts most relevant to downstream tasks while freezing the other experts and modules; experimental results demonstrate that our method not only improves the efficiency, but also matches or even surpasses the performance of full-parameter fine-tuning … by showing less performance degradation [in general tasks]». It seems to require that «ultimate expert specialization» design of theirs, with its supporting beam of generalist modules surrounded by meaningfully task-specific shards, to automatically select only the parts pertaining to some target domain; and this isn't doable with traditional dense of MoE designs. Once again: confident vision, bearing fruit months later. I would like to know who's charting their course, because they're single-handedly redeeming my opinion of the Chinese AI ecosystem and frankly Chinese culture.
V. Where does this leave us?
This might not change much. Western closed AI compute moat continues to deepen, DeepSeek/High-Flyer don't have any apparent privileged access to domestic chips, and other Chinese groups have friends in the Standing Committee and in the industry, so realistically this will be a blip on the radar of history. A month ago they've precluded a certain level of safetyist excess and corporate lock-in that still seemed possible in late 2023, when the argument that public availability of ≈GPT-4 level weights (with the main imaginary threat vectors being coding/reasoning-bottlenecked) could present intolerable risks was discussed in earnest. One-two more such leaps and we're… there, for the vague libertarian intuition of «there» I won't elucidate now. But they're already not sharing the silently updated Deepseek-V2-Chat (that somewhat improved its reasoning, getting closer to the Coder), nor the promised materials on DeepSeek-Prover (a quiet further development of their mathematical models line). Maybe it's temporary. Maybe they've arrived to where they wanted to be, and will turtle up like Stability and Mistral, and then likely wither away.
Mostly, I honestly just think it's remarkable that we're getting an excellent, practically useful free model with lowkey socialist sensibilities. Sadly, I do not foresee that this will inspire Western groups to accelerate open source and leave them in the dust. As Google says in Gemma-2 report:
Despite advancements in capabilities, we believe that given the number of larger and more powerful open models, this release will have a negligible effect on the overall risk landscape.
Less charitably, Google is not interested in releasing anything you might use to enhance your capabilities and become less dependent on Google or other «frontier company», and will only release it if you are well able of getting better stuff elsewhere. In my view, this is closer to the core value of Socialism than withholding info about Xinjiang reeducation camps.
I remain agnostic about the motivations and game plan of DeepSeek, but I do hope they'll maintain this policy of releasing models «with longtermism», as it were. We don't have many others to rely on.
Edits: minor fixes
This thread is for anyone working on personal projects to share their progress, and hold themselves somewhat accountable to a group of peers.
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DISCLAIMER: This piece has turned into something of a lengthy retrospective focused primarily on the evolution of various laws and regulations that affect mental health care and as such, may not satisfy your particular curiosity. Feel free to skim if you'd like, where you'd like, and to ask questions about the areas and issues that are important to you. My opinions are entirely my own and my hope is that this piece will nevertheless generate more robust discussion, perhaps leading to other, more comprehensive pieces if warranted, and that you'll read it all anyway, but it will probably take a long time--you might want to get some snacks.
I.
According to Wikipedia, deinstitutionalization in the United States began in earnest in the 1950s thanks to a combination of increasing social awareness of overcrowding, poor living conditions for the mentally ill and the like, the high cost to society of incarcerating the mentally ill, and the promise of new antipsychotic medications. On a side note, one of my coworkers had been a nurse at the time the first wave of antipsychotics came into wide usage at the mental hospitals of the mid-twentieth century and she informed me that the arrival of these medicines was widely known as "when the screaming stopped" to those in the field at the time. To further the process, the Community Mental Health Act was passed in 1963 to establish grants for states to build local community health centers under the overview of the National Institute of Mental Health. It was believed at the time that it was better, when possible, for the mentally ill to both live and receive treatment in their local communities and perhaps serve as fully functional members of society. Meanwhile, landmark lawsuits were being pursued, some of them by the ACLU, that would further alter the legal landscape pertaining to mental illness, culminating in O'Connor V. Donaldson, the landmark 1975 Supreme Court ruling that held that an individual could not be incarcerated against their will unless they were in imminent danger of harming themselves or others or could not care for themselves. The decision was unanimous.
I can't help but wonder if Stewart, Burger, Marshall, Douglas, White, Brennan, Powell, and Rehnquist understood or appreciated at the time the extent to which their ruling would transform issues of mental heath and institutional mistreatment into issues of law enforcement and homelessness.
It is 1999 and I have been hired as a computer technician by my local community service center. I have no idea what my employer actually does, but the answer is that we provide access to psychiatrists, case management services for the mentally ill and developmentally disabled, group therapy for substance abuse, screenings for those who might potentially require involuntary hospitalization, a parent-infant education program, two psychosocial day centers at the north and south ends of our territory, and additionally run three separate inpatient programs--one for children, one for adults, and one specifically to help patients discharged from state mental hospitals to live in a group setting and, if possible, transition to living independently. We serve several counties and one city.
My employer was founded in the early seventies and is funded mostly with Federal dollars through a combination of Community Service Block Grants, funneled through a state department specifically for the mentally ill,the developmentally disabled and those with substance use issues, Medicare and Medicaid dollars which are funneled through another state department, and (a small amount of) local tax dollars from the city and the various counties that we serve. Moreover, the Mental Health Parity Act has recently been signed into law, requiring insurance to cover mental health treatment at the same level of funding that the cover physical health treatment. Other localities differ in their services offered by virtue of receiving more/better local funding for their particular community service center. Our funding, by comparison, has always been lacking.
I don't know this at the time but despite our poor level of funding, these are the salad days four our mental health center and I have arrived just in time to witness them. Our various clinics seem to be run well and we provide a variety of services to our area, though they tend to be on the basic side aside from those that are funded by specific grants. Deinstitutionalization is still a big Thing and our state run mental hospitals are still working to discharge folks that are deemed to be no danger to themselves.
Of course, all is not sunshine and roses. Water cooler gossip is an easy vice and can range from the mostly harmless amusement at a particular client's peccadilloes (such as the client with the delusion that Jesus was a member of Kool and the Gang) to more busybody-like criticism and denigration. We have staff that get too directive, too aggressive, and too involved in the lives of their clients. HIPAA security rules are (presumably) still being written and argued over and for all practical purposes our client records are protected solely by the honor system with no checks and balances in place to protect client confidentiality. Most of the staff I interact with, however, are pleasant kindhearted, and earnest in their performance of their jobs.
Everything seems to be running smoothly at first. So smoothly, in fact, that the executive director resigns because he feels he has nothing major left to do or build. Soon afterwards, the dot com bubble pops and the economy tanks. In reaction, our funding is cut severely and even taken back in the midst of the current fiscal year. Salaries are frozen and layoffs are imminent. Funding and grants for many programs dry up, forcing us to close them. Throughout my tenure here, this pattern will cyclically repeat itself.
II.
It almost goes without saying that there is plenty of controversy surrounding pyschiatry specifically and the concepts of mental health and mental illness in general. One of these is the use of the medical model of mental illness, which is essentially the belief that mental illness and mental disorders are rooted in biological issues. The overwhelming success of the first wave of antipsychotics and the clear successes of the second wave of antidepressants has greatly bolstered this model of treatment. Accordingly, we are tasked with reporting many things that focus on behavioral and social issues by the department that controls the block grant funding, while also reporting the required medically focused data to the department of Medicare and Medicaid as we bill for our services. In fact, we are considered healthcare providers from a legal perspective and are bound by all relevant laws and regulations pertaining to the healthcare industry.
It is 2003 and I have been promoted from computer technician to MIS (Medical Information Systems) Specialist and we have hired another person into my old position. In the wake of the earlier fiscal shock, our new Executive Director is emphasizing running our service organization more like a business. Things are changing! Even now it is obvious that we will need more in the near future; HIPAA has mandated the move to EDI (Electronic Data Interchange) code sets and rules, which are a twisty maze of specifications and regulations which I would encourage you to peek at in the link just to get a feel for the complexity--the relevant parts are under the "transactions and code sets rule" in Title II. Fortunately for us, our medical practice based software, a sturdy old RPG based platform running on Unix, has been bought by $Big_Online_Company and is a planned centerpiece of their entry into the new world of EDIs and Electronic Medical Records (EMR). Implementing this will be a huge task and will involve things like deploying a wireless network, a fleet of powerful SCSI-based scanners to convert paper records into electronic records, almost tripling our PC inventory as each clinician will now be using Word to write electronic notes, etc.
On the clinical side, we are recovering from the rescinded funds of the dot com bust. Our only remaining residential program is the long-term inpatient group home for those discharged from state mental hospitals, though that is still going strong. Deinstitutionalization in general is about to wind down as the state reaches its target bed numbers but is still a Thing for the moment, and discharge assistance funds are still available. Some good people have left, and in some cases have been replaced by some not-as-good people and the clinics in question have suffered as support for clients and clinical staff has worsened. Time passes.
It is 2005 and my boss is making a presentation on the triumphs and challenges of implementing an EMR at a statewide conference on the bright new future of healthcare technology. Our experience has been a mixed bag at best, to put it kindly, and has taught us many lessons. Staff had a high level of uncertainty about using an entirely electronic system and likewise, a high level of resistance to changing the way they work. Some clinicians have been able to adopt to using PCs to do their work while others can not or will not adapt well to using a PC. Some staff quit outright, while others in the latter category remain and generally become a burden to support staff in general and our department specifically. Converting existing paper records to scanned records is an ongoing and tedious process, and has the benefit of being accessible by anyone but also can be harder to read, especially when the material is handwritten. Mistakes are still made in the electronic record but can sometimes be harder to correct due to the stringency of some rules and regulations surrounding the editing of data and notes. It is, however, easier for mistakes to be caught by reviews and compliance given the increased accessibility to all charts. It is also easier for staff to violate the privacy of clients by viewing client data that they shouldn't be viewing and in our particular case would require strong oversight and enforcement from compliance with the backing of upper management in order for us to maintain reasonable safeguards. Ultimately, it has made some things easier and some things harder, but overall it has definitely created a heavier burden for our entire organization, by at least an order of magnitude, than the old paper system that preceded it.
Aside from our presentation, however, most of the conference is abuzz about the positive impact that technology can and will have on healthcare in the future. Health Information Exchanges (HIE) will soon allow us to exchange client information with each other through the magic of a standardized data format, HL7! Federal funding will assist us with building and accessing this bright new future for healthcare! Other presentations from statewide efforts to share data with medicaid departments in other states are more positive than our own experience! Speaking of data, a statewide initiative to consolidate and standardize disparate data requests and requirements into a single, unified set of sixty to eighty-odd data elements is underway. The paper surveys that I initially collated as a bored junior staff member have mushroomed, often into Excel spreadsheets, and have become burdensome and difficult to complete in a timely fashion and it is hoped that a common data set will satisfy future requirements and alleviate some of the survey burden.
Moloch has entered the chat.
III.
The American Recovery and Reinvestment Act (ARRA, aka the Stimulus) has been passed. Because EMRs have been found to be costly, inefficient, and relatively user-unfriendly, the Health Information Technology for Clinical Heath Act (HITECH), enacted under Title XIII of the ARRA, provides funding for the healthcare industry at large to adopt systems that provide adoption of an Electronic Health Record (EHR-if you're wondering what the difference is between an EMR and an EHR, you're not alone). Additionally, it provides additional funds over the course of several years if doctors can meet the standard of Meaningful Use. Conversely, adopters of an EHR whose doctors do not demonstrate meaningful use will be docked a small but increasing amount of Medicare funds.
It is 2010 and I am attending another data conference. My boss has sent me here specifically to attend a presentation from another service center on the triumphs and challenges of moving on from their ancient database and implementing a modern EHR-based system. It turns out that staff had a high level of uncertainty about using an entirely electronic system and likewise, a high level of resistance to changing the way they worked. Some clinicians were able to adopt to using PCs to do their work while others could not or would not adapt well to using a PC. Some staff quit outright, while others in the latter category remained and generally became a burden to support staff in general and our department specifically. The presenter and implementation lead suffered a heart attack in the course of the implementation, in no small part due to his overall stress levels as project lead. Ultimately, it has made some things easier and some things harder, but overall it has definitely created a heavier burden for their entire organization, by at least and order of magnitude, as opposed to the old paper system that preceded it. It is all familiar to me and I strongly suspect that I was sent at least partly to gloat commiserate about the common difficulties of modernizing.
Despite being further down this path ourselves, dealing with our administrative burden is beginning to be a struggle. Medicaid regulations have begun to inexorably creep into our documentation requirements and to make matters worse, are often overlapping given the variety of services that we provide, contributing to staff confusion and clerical errors. The initial sixty-odd data elements that were standardized are growing quickly and are poorly understood by staff, and I am tasked with tidying up the data that we send on a monthly basis to minimize rejections. I frequently and shockingly encounter pushback from even supervisory level staff on things like the proper Axis for a diagnosis, how to classify drug diagnoses, and the difference in terms of art like Serious Emotional Disturbance and Serious Mental Illness, which in point of fact is a strictly age-based distinction. At this point, it is crystal clear to me that the majority of behavioral staff are terrible with concrete definitions and categories and that they are generally a poor fit for such precise data gathering. Worse still, the standard data set has not seemed to stem the tide of surveys that we are required to answer, often with short turnaround times, and in point of fact, said surveys often request data that we don't necessarily collect at all.
Client care suffers as staff are spending ever-increasing amounts of time doing documentation to meet the increased regulatory burdens. Despite trying to run our centers as a business, our funding has remained relatively stagnant. The populations of our counties and city, on the other hand, have continued to grow, also increasing our workload. Two of the counties we serve now qualify as suburbs! Another program has closed and worse still, an unhealthy us vs. them mentality has become pervasive throughout our organization. Staff are largely ignorant of the state and federal level legal and regulatory requirements that have led to the current administrative and staff burden, seeing this instead as the fault of our administrators. Lines have been drawn, leadership has clashed, and the losers either resign outright or engage in quiet quitting, pushing their unofficial support burdens to surrounding staff. Unofficial support itself is a huge burden as new staff are regularly hired with little or no technical skills and thus have to learn how to use Windows and Word and how to navigate our particular system on the fly, and most of this burden falls to the clerical staff that have used it since my time here, and the three of us in IT/MIS. We are accruing technical debt at an alarming pace. Things are strained to say the least.
The cherry on top of this unfortunate situation is that our medical practice system has ceased being developed. $Big_Online_Company, perhaps recognizing the size of the field they were playing on, divested themselves of our software and sold it to a $Solid_established_software_company that while good at supporting the existing codebase, has made minimal to no effort to fix bugs, release updates that address glitches and incompatibilities, and otherwise keep the software current, frequently requiring us to implement workarounds and/or stay on older versions of software in order to keep things running. And while $Big_Online_Company did develop a newer, more modern front end for their system, it's still the same old RPG-based code on the back end with all of its inherent limitations, and although it would technically meet the HITECH requirements, it would be an obvious disaster for us to implement absent a large and customized set of code designed just for us.
IV.
In August 2008, HHS proposed moving from ICD-9 diagnosis codes, which are used for billing purposes, to more modern ICD-10-CM codes. The new ICD codes were originally to be put in place by October 2013, then delayed to October 2014, and finally to October 2015. On the clinical side, the DSM-5 is released in 2015, which is an update to the DSM-IV-TR and changes many things and thus is an ongoing source of controversy.
It is 2013 and we have gone through a grueling Request For Proposal (RFP) process to replace our now long in the tooth medical practice system. Our three choices are the aforementioned update to our existing medical practice software based on ancient and hoary RPG, an old and crusty behavioral based system based on old, outdated, and niche Delphi, of all things, and a comparatively modern, web based behavioral system running on .asp and SQL and increasingly being adopted by other service centers around the state. The choice is an obvious one and we are now implementing the web based behavioral system. Staff have a high level of uncertainty about using a new web-based system and likewise, a high level of resistance to changing the way they work. Some workflows require significant change while others will be eliminated entirely. Some staff will quit outright, while others will remain, digging in their heels, and generally become a burden to support staff in general and our department specifically. Overall, however, the new system is more forgiving of mistakes and much more user-friendly than the previous and ultimately, it will make many things easier and only a few things harder. It will, unfortunately, require a much higher level of coordination between the various programs and clinical centers and administrative and MIS/IT staff in order to run smoothly. But wait! There's more! We have decided to demonstrate Meaningful Use with our new EHR, which is a twisty maze of specifications and medical codes that I would encourage you to peek at in the link just to get a feel for the complexity of meeting its requirements. Because I have become the de facto owner of our electronic forms, I am tasked with working with C-level staff in order to develop the required workflows and insert the required documentation into the required places.
Administrative burden continues to increase, as does our technical debt. Our CEO has resigned and a new CEO is incoming, with a desire to place more emphasis on expanding the services that we provide to the community through increased commitments from the various localities and grants and other forms of federal and state funding for various services. Things are changing! Worse still, our state has decided to outsource Medicaid billing to a private insurance company, a move which also will significantly increase our administrative burden. Our once manageable data set that we regularly report is pushing 100 individual client data elements, and in fact we are now reporting ever-more data to ever-more acronyms relevant to various state and federal initiatives in ever-more ways--there are 16 more initiatives requiring their own data, in fact, as counted by our statewide data committee.
Implementation progresses. There are many pain points, most of which are technical in nature and difficult for clinical staff to understand. In our new system. There is much concern for minimizing staff disruptions and minimizing change to workflow wherever possible. As a result, many potential gains are left unrealized. Despite all of this, and due in large part to extended hours worked by the staff involved in implementation, our roll-out is fairly smooth, and most of our major issues are ironed out within the first two days of going live.
Unfortunately, client care still suffers as staff are still spending ever-increasing amounts of time on documentation to meet the increased regulatory burdens. Substance use services are a vestigial remnant of their former selves, and we have dwindled to one staff member responsible for the whole of them, which mostly involves with facilitating inpatient treatment for clients. Worse still, our developmental disability data is lacking as a state, and we have been found negligent in discharge of our duties, resulting in a meticulous and vastly increased amount of paperwork and data reporting, some of which has been helpfully added in by the department of developmental disability itself in a prime example of friendly fire via lawsuit. This is further exacerbated when the developmental disability department funds a state website to authorize treatment for the developmentally disabled and to enter client treatment plans electronically, potentially leading to double entry as all state entities serving the developmentally disabled must send this data to the department. Additionally, the department signs a contract with a leading IT vendor to develop interoperability between their brand new website and the existing EHR systems that various state centers and agencies are using. The specifications are agreed upon, the contract is finalized, and the department promptly violates the contract and invokes financial penalties two weeks later when they change the data specifications. This will not be the last time that this happens before the interoperability project is completed. Time passes.
It is 2016 and my boss and I are attending a workshop about Government Reporting Modernization Act (GPRA) reporting that we must do as a part of our award of State Opioid Recovery (SOR) funding. It is entirely how-to and a complete waste of our time, and also exemplary of the growing expectation that we will administer anything and everything related to clinical functions. GPRAs have several flavors the flavor we use is detailed and invasive in its questions, as it involves substance use and sexual habits. As part of our SOR grant for Medication Assisted Treatment (MAT) for opioid use, we are expected to administer the GPRA to all incoming clients that are receiving MAT and to follow up with them periodically for two years after termination of services if possible. We bail on the second half of the presentation.
We are beginning to drown in a sea of unintelligible data, administrative burden and technical debt. It is so unintelligible, in fact, that even at the state level they are consulting with their foremost auditor, who had retired, to help them understand their own data requirements. Documentation is now for all intents and purposes a full-time job in and of itself and, just like their pure healthcare based counterparts, staff are compensating either by skimping on their documentation or by working unreported overtime. Developmental disability continues to be a rolling train wreck of continuous updates to data and documentation requirements and non-functioning interoperability between their website and the various EHRs; most service centers including our own have abandoned all attempts to use their own EHRs to document the individual service plans and use the state website exclusively and then simply attaching a copy of that documentation to a service or record in their respective EHR platforms.
Worse still, our state has decided that outsourcing Medicare and Medicaid reimbursement to private insurance has gone so well that they bring in over a dozen new insurance companies! Ostensibly, they all agree to common requirements but in practice this is not so true, leading to large billing and documentation headaches on the back end. Registration and admission forms are frequently changed, requiring increasing amounts of time both to update and understand. I am darkly amused when I find that different insurers are categorizing race and ethnicity, a data point that has mushroomed in the last decade or so, differently than the agreed-upon state standard as well as differently than each other. But wait! There's more! We are now required to do service specific provider intakes, meaning that if a client is enrolled in multiple services, each service must have its own intake and each intake is supposed to be performed by a Licensed Mental Health Professional (LMHP) type, which requires a graduate degree, significant amounts of time as a supervised resident providing services, and the passing of a test. This is a large and unwelcome change as we already have significant issues with hiring and keeping licensed professionals and even residents, as they largely leave for greener and easier to navigate pastures as soon as possible.
V.
The Excellence in Mental Health Act, a part of the Protecting Access to Medicare Act, was passed in 2014 and established a new model for treating mental health and substance use disorders within the community regardless of a client's ability to pay-the Certified Community Behavioral Health Clinic (CCBHC). The intention is to quickly provide clients with access to services regardless of their status and ability to pay.
It is 2018 and our state has passed legislation to implement the CCBHC model within the existing framework of our legislation and regulation. We're going to provide clients with same day access to intake and services! There won't be any more waiting lists! We're going to skip all the paperwork and use a standard assessment tool (which we must pay a fee to license each provider to use, natch) to assess a client's daily level of functioning. Why, there's all kinds of redundancy in data gathering and paperwork, don't you know? (Shut. Up!) We're going to eliminate all of that and just focus on getting clients in the door and into services! Staff can and should document their encounters collaboratively with clients! Better still, we can use more lightly credentialed peers to provide services instead of more expensive licensed staff!
The consultants responsible for the assessment have frequent calls with us to aid in implementing the required changes. They go on and on in our about how this is so great and how it's going to streamline everything. Pointed questions about existing regulations and laws that stand counter to the streamlining that is being evangelized by the consultants are are routinely brushed off with the refrain of, "well, the state of $State moves at the speed of the state of $State." They are also big on double-checking the law and regulations and like to tell stories about other centers and agencies that have been misled about what they should be doing to their detriment. While they are Not Wrong about this and many other things, the practical reality of the situation is that just as the law is whatever the judge says it is, the regulations and requirements are exactly what the auditors and Licensure say they are, and as we are highly unlikely to resort to litigation in order to resolve our differences, snitches getting stitches and all that, we will ultimately experience minimal gains from this.
As the Forms Guy, I am tasked with filling out a spreadsheet with every single form question in our EHR and identifying each of our forms in which it appears with the goal of deduplicating All of the Things. This turns out to be just shy of 4,000 unique questions, some of which are duplicated dozens of times, usually in free text fields like "notes" or "session details" that cannot be deduplicated. Worse still, many of the forms in question are State built forms and thus cannot practically be altered by those of us that are merely using them to report back to the state and so those data elements cannot be deduplicated either. I already ruthlessly cut redundancy and duplicity where I could; the low hanging fruit has been plucked and despite their insistence to the contrary, the reduction in duplicate effort and redundancy will be minimal at best. Of course, we do discover that absent consistent supervision and training on our existing workflows, staff and supervisors have developed their own procedures and documentation which needs to be brought into line, so the exercise as a whole does produce some positive results, it's just that ideally we'd be doing this ourselves anyway.
But wait! There's more! Medicaid requirements for clients have continued to evolve. Client intakes are no longer required to be service specific but are now expected to be a more comprehensive assessment of client needs. There is a hope among C-levels and supervisory staff that through the magic of Same Day Access (SDA) and the ability of clients to fill out their own forms in the client portal, clients will somehow provide the bulk of the necessary information themselves by filling out these forms! Given that many clients rely on our staff to help them navigate bureaucracy in the first place, and further that most of our staff do not understand the data they're supposed to be gathering from the clients I am beyond unimpressed with the shortsightedness of our collective management. Worse still, I am tasked with developing the client forms that will be created by a committee consisting of all program supervisors. When all is said and done, I have been given almost 100 questions that amount to a wish list of wants from each program. The majority of them are absurd, most especially the substance exposed infant questions that asks technical questions about the development of the baby. The darker, cynical cockles of my heart are thoroughly tickled by the whole affair and amongst those that I think can understand, I point to this episode as a prime example of Why We Can't Have Nice Things. I break down the questions into six separate client forms that clients will allegedly be filling out themselves while waiting to be seen. As. If.
This is not to say that the idea of same day access and getting clients into treatment as quickly as possible is flawed--far from it, in fact! And there are other good ideas in there as well! They have recommendations for dealing with chronic no-show clients, an issue endemic in our field and exacerbated by Medicaid regulations that disallow fees for clients that fail to show up. Neither do I disagree with the notion that engaging clients quickly and frequently leads to better outcomes than our current system of engaging them on at least a monthly basis. It is clear that more engagement is beneficial to clients on the whole! In the balance, however, this new model of providing services is not without its own issues and problems. Lower functioning clients, for example, tend to need dedicated case management just to be able to navigate their lives. And most tellingly, this new model requires complete commitment to its principle in order to have any reasonable chance of working well. And our state, as is its wont, is trying to graft it onto the existing structure and bureaucracies.
In other words, "Good luck, have fun!"
Apart from this fresh new hell, we are actively drowning in a sea of unintelligible data, administrative burden and technical debt. State level dashboards have become a Thing in and of themselves and are driving new and burdensome questions that are too technical for anyone outside of the MIS/IT department to understand with some exceptions for the COO and the CPO (Chief Program Officer). The three of us in said MIS/IT department are overwhelmed by our combination of help desk, clinical, MIS, and IT specific duties; it is hard to pay attention to server patching and security when also doing end-user support, EHR administration, and data analysis as required and none of us have the bandwidth to completely grok the entirety of the responsibilities of the others in our department. Developmental disability continues to be a rolling train wreck of continuous updates to data and documentation requirements and non-functioning interoperability between their website and the various EHRs. Our substance use program is growing with zero concerns about compliance or oversight for all intents and purposes. Medically assisted treatment has become Office Based Opioid Treatment (OBOT) and is flush with continued grant funding and consistent with this growth is widespread confusion amongst substance-use focused staff about how we report the services we're offering, particularly the difference between outpatient therapy, which is individual, and intensive outpatient therapy, which is group-based.
Time passes and with much effort and funding, Same Day Access manages to get off the ground. While we have managed to standardize our intake procedure, surprise, the clients are not in fact doing their own intakes when all is said and done. By virtue of serving disparate masters our new intake process is much more complicated and burdensome than the system that preceded However, we have several staff and a dedicated supervisor handling same day access at one clinic location and on a good day, each staff member can process several intakes each, netting perhaps a dozen intakes a day.
VI.
"Apres moi, le deluge." -Louis XV
It is 2021 and my boss and I are meeting with the supervisory staff of all programs and applicable C-levels to go over the data reporting requirements to which we are beholden. My boss, myself, and the special projects manager are the only ones in the agency left understanding how Same Day Access and its data gathering is supposed to work. It's on all the hot state dashboards and we are getting dinged for it regularly. Worse still, the data collection requirements have mushroomed, and we have gone from relatively straightforward things such as the date of first offered appointment after the same day access appointment to a twisty maze of collecting height, weight, and BMI, performing suicidality assessments on clients with diagnosis of depression and veterans, referring clients out for metabolic syndrome screening if they take psychotropic meds (and most of them either do or will) and reporting the results back to the state, performing primary care screenings, and the list goes on. We desperately want to convey this knowledge to the attendees, especially the complicated coordination that these workflows require in order for the data in question to even be reported at all, but most are busy texting on their phones, reading their emails, doing other work, and otherwise ignoring us. This is bad because not only are we drowning in a sea of unintelligible data and administrative burden, but there has been an exodus in upper management and the present staff are all that's left to pick up the pieces of responsibility that, at least on paper, was theirs all along.
The bill for serious amounts technical debt is now due and sending said debt to /dev/null is Bad Idea Jeans, which is of course exactly what we're doing. Every summer since the inception of the reporting of these outcomes I have multiple meetings where our system and documentation is blamed for our poor performance on the state dashboards. Every summer I explain that the outcomes in question are multi-step and require co-ordination between the staff filling out the forms and the staff doing the diagnosing in order for said outcomes to even be reported to the state. Lather, rinse, repeat.
If you're picturing an old-school flip clock changing its time display from 5:59 to 6:00 and I Got You Babe by Sonny and Cher playing on a radio, then you're picking up what I'm putting down.
AT this point, the level of client care we are giving varies based on which particular department is handling the client's needs. We have a spiffy new drug court program that is leveraging our OBOT program and clients in the counties where we have staff in place can enter pretty quickly. In other counties, not so much, but we'll get there. DD clients have their traditional barriers to access and crushing paperwork requirements, which is to say they generally wait years for any sort of significant aid. Traditional mental health client service is, in places, practically non-existent thanks to a nasty combination of COVID policies, which include dragooning case managers into managing telehealth appointments for the doctors and clients one day each week, the Great Resignation, and neglect on our part. Absent strong understanding and supervision, Same Day Access has dwindled and only several folks are able to be seen in an average day. A therapist I know had previously been a case manager a year ago and several of her clients still call her in an attempt to get services, stating that their case managers don't call them back and neither do their supervisors. Said therapist patiently explains that she can no longer even access their charts because HIPAA. She is working with a different population now and simply directs her former clients to file a human rights complaint with the State. This is not the only area where she is de facto performing the job duties for other staff, nor is she the only one I hear this from; my overall impression is that outside of the drug court services, traditional DD services, and access to psychiatrists, we don't seem to be doing much of anything for our clients these days.
It is 2022 and my boss has resigned. My interest in replacing him was tepid at its best and so the friend of $New_COO is brought in to manage IT. Thankfully, I really like $New_Boss as well, because I learn the hard way that I am too burned out to even get serious about finding another IT admin job. Even more thankfully, we've finally expanded the IT department to include a dedicated help desk position and another IT specialist and both are excellent--we might actually be able to leverage the more modern parts of our architecture to streamline some old processes! The CEO is retiring (for good!), however, at the end of the year and worse still, we are having serious problems recruiting and retaining staff for all of the reasons you'd expect, including the increased strain of the ever-evolving COVID lockdowns. We are still actively drowning in a sea of unintelligible data and administrative burden and our technical debt is still compounding at an alarming rate. Outside of the growth of OBOT and the drug courts, our client care is still at a low point. In true Orwellian fashion, potential clients are now showing up early in the morning, well before we open, in an attempt to be assessed through Same Day Access and actually get themselves into services. Worse still, the state has launched a new initiative to Unify All The Things and expects us to do their work for them participate in its implementation as the head of the project is not familiar with our existing bureaucracy. This, of course, bogs down quickly due to those pesky laws and regulations that command us to report things via specific processes and in specific formats that cannot be magically done away with. Time passes.
It is 2024 and I am attending yet another meeting pertaining to yet another attempt at Unifying All The Things. The first attempt, predictably, was retired quietly, but this time the state has hired The Pros From Dover and is implementing a data warehouse that is expected to be its source of truth moving forward. The ~120 data elements that we are currently reporting on a monthly basis, as well as a significant number other points of additional points of data from the TEDS dataset, are initially expected to be sent directly to the state on a real-time basis thanks to the magic of HL7. The timeline for implementation is about 18 months.
This time, they mean business.
We are still actively drowning in a sea of unintelligible data and administrative burden and our technical debt continues to compound despite the glaringly-obvious need in the approaching data warehouse implementation mentioned above. Worse still, the eye of Sauron is now upon us; the metrics on one of our dashboards is bad enough that we are on a PIP and will be expected to raise our performance in that metric in particular as well our metrics in general. But wait! There's more! The state is once again consulting with their foremost auditor, who had re-retired, to help them better understand their own data requirements. In addition to the increased burdens of making the sausage tidying our data on a daily instead of a monthly basis, it is reasonable for us to expect to be nit-picked on our inaccuracies and our failures as well!
Drug court and Office Based Addiction Treatment (Office Based Opioid Treatment, being so 2000-late, apparently) continues to chug along. DD clients have their traditional barriers to access and crushing paperwork requirements. Traditional mental health client service is, in places, almost nonexistent, but better than it was. In true Orwellian fashion, potential clients are still showing up early in the morning, well before we open, in an attempt to be assessed through Same Day Access and actually get themselves into services. On the bright side, COVID is officially over and at least our offices are open again, giving clients greater access to staff and better still, $New_New_CEO, in addition to wanting to run our organization more like a business (things are changing!), has implemented a "next business day" policy for returning phone calls and emails to further promote greater access to staff.
Why $New_New_CEO? Well that's a fun story in itself, but the essence is that $New_CEO turned out to be a disaster and a major disruptive force in her short-lived tenure, a powerful and terrible example of the Peter Principle. The bad news is that many senior figures have left for greener pastures during her tenure and though $New_new_CEO is much better (see above) the damage had been done and another large portion of our institutional knowledge is gone. Even scarier, amongst the new batch of senior figures in terms of institutional knowledge is... me. Like the previous senior figures, I am also still performing several jobs (the most concerning of which is the Maker of the Sausage Knower of the Data Specifications) and I, too, am burned out, tired of not being able to actually escape work, and frustrated with the constant stream of new and existing employees that are ignorant about the realities of our work (often deliberately so). And when $New_Management frequently bombards me with questions such as, "where is the workflow," and, "was this communicated," I want to scream at them that as a meager specialist, I have never been management, I have frequently pointed to where our existing documentation lies and have frequently communicated change in the past, and I have never had any actual authority to decide or enact any of this myself at all. And then follow that up with throwing a bunch of things and ragequitting.
$New_Boss recently said to me, "you know, when I first got here I thought there was no way it could be this bad and that you were just being a cynical asshole. Now I see that you were really just telling me the truth."
VII.
Whom the Gods would destroy, they first make mad. -Reverend William Anderson Scott
The sixties, for all intents and purposes, were a long time ago in a galaxy far, far away. The issue of mental health services is and always has been a quintessential wicked problem that we can really only try to improve at each iteration. As effective as the first and second wave drugs were in helping to treat mental illness, they have not lived up to the hopes that we had for them. Nor has deinstitutionalization led to universally better outcomes for clients and in fact, although I find the legal principle of O'Connor to be wonderful in theory, I believe that in practice and in the balance, it has been a cruelty to the more mentally ill among us. However, that's not to say that our outcomes are universally terrible. For all of their limitations, side effects, and potentially inflated prices, drugs are absolutely, positively the best bang for the buck treatment of mental illness at the community and society level. They provide relief from pervasive states of consciousness and a stability that clients simply cannot achieve without them. Unfortunately, I believe any greater outcome for any given individual would require that magical "willingness to change" that is, all too often, limited to nonexistent. Throw in a metric fuckton of data requirements that expect dust-speck fine levels of specificity and the whole rest of the medical bureaucracy with its various and sundry deep-reaching regulations and requirements, add in a staff that by and large doesn't have the technical chops to readily comprehend the difference between an assessment instrument and a diagnosis, and you've got a recipe for atrocious records and data that add up to little better than unreliable noise. Which means that practically speaking, a lot of this work is, to paraphrase the old Soviet joke, "we pretend to help and they pretend to be helped," with the real punchline being that on the national level, all of our data gathering is the garbage in, and the policies that result from that are the garbage out.
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In preparation for reading Trump's executive orders, I started reading Biden's. I think I just finished the backlog.
My goal in this report and subsequent reports is to get at concrete actions that are happening in government, rather than the emotional reactions and grandiose rhetoric on either side of the media. I'm looking for significant actions with long-term consequences which are under-reported along my axis of interests: competence in government, environmental regulation, science funding policy, AI, and other existential threats.
This means I will skip a lot of the rhetoric. If something is very likely to be challenged in court, I will note that and then wait for the courts to have their say.
Outgoing executive actions of the Biden administration
January 14, 2025: Proclamation 10881 "Establishment of the Chuckwalla National Monument"
This Proclamation goes on for five print pages about the history of a region in "southeastern California, where the Mojave and Colorado Deserts intersect," then declares (under the Antiquities Act) that the "objects" described in these pages need to be protected, "to ensure the preservation, restoration, and protection of the objects of scientific and historic interest identified above and to advance renewable energy in Development Focus Areas (DFAs)".
The area to be protected is five claims totaling 624,270 acres, between Joshua Tree National Park and Chocolate Mountain Aerial Gunnery Range.
I don't know anything about this region, but skipping all the rhetoric, the plain text of the Proclamation doesn't make sense to me. In my mind, either you preserve an area, or you develop it, but not both. Preserving "to advance renewable energy" is weird, unless this is the watershed for a hydroelectric dam.
January 15, 2025: Executive order 14141 "Advancing United States Leadership in Artificial Intelligence Infrastructure"
This executive order has eleven sections on more than 20 print pages, so I will summarize each section as a unit.
Section one: Preamble: "This order sets our Nation on the path to ensure that future frontier AI can, and will, continue to be built here in the United States."
Section two: Policy: Agencies should support AI development for national security and economic leadership, and energy development for such, as long as it doesn't raise energy prices. (How can using more energy not raise energy prices?)
Section three: Defines terms. Not too many surprises here, except that fossil fuel power with 90% permanent carbon capture falls under the definition of "clean energy."
Section four: (1) Three sites on Federal land will be leased to AI data centers and their supporting energy infrastructure by 2027. This section defines consideration and process for the Secretary of the Interior to do so, announcing sites by March 31, 2025, soliciting bids by June 30, 2025. (2) Five regions will be designated as "geothermal regions" for power generation and "thermal storage." A program for streamlining geothermal projects on federal land will be established by July 2025. (3) Construction of AI infrastructure is to begin by Jan 1, 2026 with full-capacity operation by December 31, 2027. This seems like slow timelines for AI. (4) These sites are to be secured within one year.
Section five: This whole section is about how the DoE should work with states to report on the impact of data centers on consumer energy prices. I predict this will slow AI development.
Section six: Requires electrical transmission providers to let the Federal government know about their remaining and planned capacity, and makes arrangements for agencies to power the three AI data centers of Section four. This is a good thing insofar as it is seeking to find underused infrastructure for placement of data centers. On the other hand, isn't this what price signals are for, and isn't it dangerous to have all this information in a single place which will undoubtedly be hacked by China?
Section seven: Requires agencies to do all the permitting quickly. Ex. EPA review is 30 days.
Section eight: Instructs the Secretary of Energy to include frontier AI data centers in its previously-scheduled nationwide energy and transmission needs analyses. Instructs agencies to who make infrastructure loans to inform the developers who win bids for AI related infrastructure on Federal land about loan and loan guarantee opportunities.
Section nine: (1) Plans to make a plan for promoting development of nuclear power. (2) Mandates a report on supply chain risks for data center components. (3) Develops model contracts for distributed energy. (4) Evaluate existing nationwide permits to see if they can be used for AI data center construction, and write new ones.[?] (5) Hold a voluntary "grand challenge" for power efficiency, computational efficiency, and water efficiency in data centers.
Section ten: Coordinate with geopolitical allies to build "trusted AI infrastructure" abroad.
Section eleven: Don't violate existing laws while doing any of this.
January 15, 2025: Executive order 14142 "Taking Additional Steps With Respect to the Situation in Syria"
This Executive Order (EO) modifies a 2019 (Trump) EO which declared a National Emergency in order to seize assets of individuals who had "directly or indirectly engaged in" "actions or policies that further threaten the peace, security, stability, or territorial integrity of Syria", but limited to "Turkish officials" who had sought to "obstruction, disruption, or prevention of a ceasefire in northern Syria".
Biden's EO strikes language which keeps it narrow to "in particular the recent actions by the Government of Turkey to conduct a military offensive into northeast Syria," and removes all clauses limiting enforcement to representatives of Turkey.
I read this seeking to allow sanctions on non-Turks who threaten the stability of Syria. Maybe Syrians, maybe Isrealis?
January 14, 2025: Notice 2025-01312. "Continuation of the National Emergency With Respect to the Situation in the West Bank"
This notice extends the national emergency of a previous executive order for one year, until Feb. 1, 2026. The previous executive order appears to sanction people involved in supporting violence in the West Bank, and prevents them from immigrating from the US. Not sure if it referrs to Israeli settlers or members of the Palestinian Authority.
January 15, 2025: "Continuation of the National Emergency With Respect to the Widespread Humanitarian Crisis in Afghanistan and the Potential for a Deepening Economic Collapse in Afghanistan"
The administration issues a declaration to extend a previous national emergency by one year. This national emergency allows freezing the assets of "Da Afghanistan Bank" held by US financial institutions, to keep the Taliban from using these assets.
Given that the asset freeze has been in place since February 11, 2022, this isn't a big deal.
January 16, 2025: Executive Order 14143 "Providing for the Appointment of Alumni of AmeriCorps to the Competitive Service".
This EO gives Americorps alumni with 1700 or more hours of service a fast-track to Federal employment, by making them elligible for "Non-Competitive Eligibility", for one year following their service. This gets them out of merit-based competition in federal hiring. This affects a population of about 80,000 people.
January 16, 2025: Executive Order 14144 "Strengthening and Promoting Innovation in the Nation's Cybersecurity"
This EO has a lot of parts, and each section was likely written by a team of subject-matter experts. There is no way I can do it justice.
Section two requires Federal contract software providers to submit "machine-readable secure software development attestations; high-level artifacts to validate those attestations; and a list of the providers' Federal Civilian Executive Branch (FCEB) agency software customers." It also provides that the government establish "practical and effective" security practices to require when it procures software," and implement "supply chain risk management programs" into their own enterprise software.
Section three requires federal agencies to implement security practices used in industry, then goes into protections (encryption) for the civil space system and space ground systems.
Section four requires "strong identity authentication and encryption using modern, standardized, and commercially available algorithms and protocols", including Border Gateway router security, Route Origin Authorizations, and DNS traffic encryption. I'm skeptical of digital identity documents, but if they were more privacy-preserving than physical documents that would be impressive.
Section five seeks to "Combat cybercrime and fraud" by requiring the implementation and use of "mobile driver's licenses", "remote digital identity verification using digital identity documents" which can be used on any "standards-compliant hardware." The focus seems to be on public benefit programs. Thankfully, there are provisions for "do not enable ... surveil and track presentation of the digital identity document" and "ensuring only the minimum information required for a transaction."
Section six directs DARPA to open a program using AI for cyber defense, and for other agencies to implement the program within a year or so.
Section seven is about making sure that IT systems introduced by agencies can be audited for security compliance. Mostly transparency and automatic attestation.
Section eight is about securing national security systems.
Section nine amends a previous executive order, enabling sanctions on foreign hackers and cybersecurity threatening entities named by the Secretary of the Treasury or Secretary of State.
This is an extremely technical EO, and I have no doubt it was written by several teams of specialists. This also means it is almost impossible for the layperson to evaluate. Implementation will take years, with many sequences of delays built in for agencies to develop and implement processes.
January 16, 2025: Memorandum: "Orderly Implementation of the Air Toxics Standards for Ethylene Oxide Commercial Sterilizers"
Ethylene Oxide is used to sterilize medical devices, but it also known to cause cancer when in the air. This Memorandum establishes a process for considering requests for exemptions to new EPA rules on EtO release.
Whether this is good or bad seems like it will depend on the implementation. The deadline for the process development here is two years.
January 15, 2025: Memorandum: "Extending and Expanding Eligibility for Deferred Enforced Departure for Certain Hong Kong Residents"
"I have determined that it is in the foreign policy interest of the United States to defer for 24 months the removal of any Hong Kong resident, regardless of country of birth, who is present in the United States on the date of this memorandum, except for those [who have returned to the PRC or been convited of crimes.]" This seems like a good thing.
January 19, 2025: Executive Order 14145 "Helping Left-Behind Communities Make a Comeback"
This executive order directs several agencies to coordinate to support local economic development and make it easier to find resources about economic development programs which may be useful to "covered communities", which are defined as "economically distressed" regions, "Community Disaster Resiliency Zones", rural communities, and regions served by existing regional development programs.
This doesn't look controversial at all, unless the communities in question are selected in a partisan manner.
January 19, 2025: Executive Order 14146 "Partial Revocation of Executive Order 13961"
This is a very short but cryptic executive order. "Sections 1, 3, 4, 5, and 7 of Executive Order 13961 of December 7, 2020 (Governance and Integration of Federal Mission Resilience), are hereby revoked."
Executive order 13961 is about continuity of the US government during emergencies. Section 1 establishes "the policy of the United States to maintain comprehensive and effective continuity programs that ensure national security and the preservation of government structure under the United States Constitution," and mandates that agencies must be able to continuously perform "National Essential Functions": mostly security, defense, health, and emergency services. Sections 3, 4, 5, and 7 establish a "Federal Mission Resilience Executive Committee".
I'm very confused. It looks like Section 2 (not revoked) defines the Federal Mission Resilience Strategy, and is untouched. So this EO is abolishing an Executive Committee.
While searching around to try to figure out what was going on, my search for Strategy document of Section two revealed a January 20 2025 Trump EO "Organization of the National Security Council and Subcommittees" which defines a National Security Council.
I'm going to guess this was some kind of parting shot by the Biden Admin, and it doesn't really matter because Trump's day 1 EOs overwrote it. But this last one leaves me just very very confused.
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There has been some recent usage of AI that has garnered a lot of controversy
- (top level comment) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/293580?context=8#context
- (top level comment, but now deleted post) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/292693?context=8#context
- (response to the deleted top level comment) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/292999?context=8#context
There were multiple different highlighted moderator responses where we weighed in with different opinions
- (@amadan) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/293601?context=8#context
- (@netstack) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/293094?context=8#context
- (@netstack) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/293068?context=8#context
- (@self_made_human) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/293159?context=8#context
- (@cjet79) https://www.themotte.org/post/1657/culture-war-roundup-for-the-week/292776?context=8#context
The mods have been discussing this in our internal chat. We've landed on some shared ideas, but there are also some differences left to iron out. We'd like to open up the discussion to everyone to make sure we are in line with general sentiments. Please keep this discussion civil.
Some shared thoughts among the mods:
- No retroactive punishments. The users linked above that used AI will not have any form of mod sanctions. We didn't have a rule, so they didn't break it. And I thought in all cases it was good that they were honest and up front about the AI usage. Do not personally attack them, follow the normal rules of courtesy.
- AI generated content should be labelled as such.
- The user posting AI generated content is responsible for that content.
- AI generated content seems ripe for different types of abuse and we are likely to be overly sensitive to such abuses.
The areas of disagreement among the mods:
- How AI generated content can be displayed. (off site links only, or quoted just like any other speaker)
- What AI usage implies for the conversation.
- Whether a specific rule change is needed to make our new understanding clear.
Edit 1 Another point of general agreement among the mods was that talking about AI is fine. There would be no sort of topic ban of any kind. This rule discussion is more about how AI is used on themotte.
I've been thinking about conflict vs mistake theory lately, especially since the events of October in Israel last year.
I've been particularly trying to understand where support for Palestine (and Hamas, implicitly or not) comes from. Much has already been written about this of course, whether it's the bigotry of small differences or the trap of the "oppressor/oppressed thinking," the hierarchy of oppression, and so on.
What I found striking and want to discuss here though is the strain of thought responding to "how can LGBT+ support Palestine" by declaring, e.g., from Reddit:
It's easier to focus on getting gay rights when you're not being genocided.
Or from a longer piece:
The interviewer asks him, “What’s your response to people who say that you’re not safe in Palestine as a queer person?” Dabbagh responded, “First and foremost, I would go to Palestine in a heartbeat. I have no fear. I love my people and my people love me. And I want to be there and be part of the movement that ends up leading to queer liberation for liberated Palestinian people. If you feel that such violence exists for queer people in the Middle East, what are you doing to change that for that community? The first step is the liberation of Palestine.
I don't claim it's the most common strain of thinking, but to me this largely cashes out as "they are homophobic because of oppression/imperialism/Jews." As an aside, contrast with the way "economic anxiety" plays out in the US.
The part I want to focus on is this kind of blend of mistake and conflict theory -- there's conflict, yes, but it has a cause which can be addressed and then we'll all be on the same side. I'm skeptical of this blend, which seems to essentially just be false consciousness: if not for an external force you would see our interests align.
I think this mode of thinking is becoming increasingly popular however and want to point to the two most recent video games I put serious time into (but didn't finish) as examples: Baldur's Gate 3 and Unicorn Overlord (minorish spoilers ahead)
[Again, minorish spoilers for Unicorn Overlord and Baldur's Gate 3 ahead]
Baldur's Gate 3 was part of a larger "vibe shift" in DnD which I won't get into here except to say I think a lot of it is misguided. Nevertheless, there are two major examples of the above:
The Gith'Yanki are a martial, fascist seeming society who are generally aggressive powerful assholes. A major character arc for one of your team Gith'Yanki team members however, is learning she had been brainwashed and fed lies not just about the leader of the society and her goals, but also the basic functioning of the society. For instance, a much-discussed cure for a serious medical condition turns out to be glorious euthanasia.
The Gith have been impressed with a false consciousness, you see, and your conflict with them is largely based on a misunderstanding of the facts.
More egregious is the character Omeluum, who you meet early in the adventure. Omeluum is a "mind flayer" or "illithid":
Mind flayers are psionic aberrations with a humanoid-like figure and a tentacled head that communicate using telepathy. They feast on the brains of intelligent beings and can enthrall other creatures to their will.
But you see, even these creatures turn out to be the victim of false consciousness--Omeluum is a mind flayer who has escaped the mind control of the "Elder Brain." After fleeing, he happily "joined the good guys." You might think it's an issue that his biology requires he consume conscious brains, but fortunately he only feeds
on the brains of creatures of the Underdark 'that oppose the Society's goals', and wishes to help others of his kind by discovering a brain-free diet.
In the world of DnD (which has consciously been made to increasingly mimic our own world with mixed results), it seems that but for a few bad actors we could all get along in harmony.
Anecdotally, the last time I ran a DnD campaign it eventually devolved into the party trying to "get to the root" of every conflict, whether it was insisting on finding a way to get goblins to stop killing travelers by negotiation a protection deal with the nearby village which served both, or trying to talk every single cultist out of being a cult member. I'm all for creative solutions, but I found it got pretty tedious after a while.
The other game, Unicorn Overlord, is even more striking, albeit a little simpler. Unicorn Overlord is a (very enjoyable) strategy game where you slowly build up an army to overthrow the evil overlord. What you quickly discover, however, is that almost without exception every follower of the evil overlord is literally mind-controlled. The main gameplay cycle involves fighting a lieutenant's army, then using your magical ring to undo the mind control. After, the lieutenant is invariably horrified and joins your righteous cause.
I should note this is far from unusual in this genre, which requires fights but also wants team-ups. It's a lot like Marvel movies which come up with reasons for heroes to fight each other then team up, like a misunderstanding or even mind control. Wargroove was especially bad at this, where you would encounter a new friendly and say something like "Hello, a fine field for cattle, no?" but the wind is strong or something so they hear "Hello, a fine field for battle, no?" and then you fight. Nevertheless, the mind control dynamic in Unicorn Overlord is almost exclusively the only explanation used.
Funnily enough, I think in these an other examples this is seen as "adding nuance," but I find it ultimately as childish as a cartoon-twirling villain. The villain is still needed in fact (Imperialists, the Evil Overlord, The Elder Brain, The Queen of the Gith), but it's easier to explain away one Evil person who controls everything than try to account for it at scale.
Taken altogether, I can't help but think these are all symptoms of the same thing: struggling to explain conflict. The "false consciousness" explanation is powerful, but seems able to explain anything about people's behavior.
My suspicion is that mistakes and genuine conflict can both occur, but this blended approach leaves something to be desired I think. I had an idea a while ago about a potential plot twist for Unicorn Overlord where it's revealed you aren't freeing anyone -- you're simply bringing them under your own control but you don't notice. That feels a bit like the fantasy all of this is getting at I think: I have my views because of Reasons or Ethics or Whatever, and you would agree with me if not for Factor I'm Immune To.
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About a month ago, as I was browsing twitter, I stumbled upon the following article by Cathy Young:
https://www.theunpopulist.net/p/the-making-of-the-maga-hoax-about
At the time, talk about pet-eating Haitian immigrants was all over twitter. Donald Trump had just referenced it in the latest presidential debate, and his his running mate, J.D. Vance had tweeted about it. It was fascinating how the story played out. Every day, I would see a new story that supposedly validated the claim. Also every day, I would find that an earlier story had been debunked. Either it wasn’t about a Hatian, wasn’t about an immigrant, wasn’t in Springfield, or wasn’t about a pet getting eaten. The article seemed like it would be an interesting read.
Early on in the article, I came across the following paragraph:
It started with an X hatefest I happened to catch at the outset. On Sept. 7, a full three days before the debate, I saw left-wing-crank-turned-right-wing-loon Naomi Wolf share a post from misinformation superspreader End Wokeness (an account that may be run by far-right troll and Pizzagater Jack Posobiec), containing what seemed like an obviously made-up story: “ducks and pets” in Springfield, Ohio being gobbled up by Haitian migrants. The evidence: an anonymized Facebook post about a “neighbor’s friend’s daughter” who had seen her lost cat being carved up by the Haitians next door. I decided to post a sarcastic comment, unaware that I was wading into a dumpster fire.
Nothing about this paragraph is factually incorrect as far as I know, but something in there caught my eye: “Misinformation superspreader End Wokeness”
I am familiar with the End Wokeness twitter account. They’re pretty prominent on twitter, and they are not exactly what I would call trustworthy. I can understand why they might be described as an misinformation superspreader. That characterization isn’t entirely wrong, but even so, it put me on alert.
I think what I’m sensitive to is the way this pattern judges a thing at the same time it’s introduced. It wants me to make up my mind about who End Wokeness is before I’ve had the chance to evaluate them and come to my own conclusion.
When I see that pattern, it always puts me on alert. I’m so sensitive to it, that it sticks out like a sore thumb even in articles that I’m predisposed to agree with (like this one). “Misinformation superspreader” isn’t the only example of it here; “hatefest” “left-wing-crank-turned-right-wing-loon” and “far-right troll” are all examples of this pattern.
Furthermore, it’s trying to persuade me of something without being an actual argument. It’s like when a movie plays sinister music just to let me know that a character supposed to be bad. If I didn’t already know who End Wokeness was, I shouldn’t just take Cathy’s word for it that they’re a misinformation superspreader. Any writer can introduce someone with whatever label they want to, regardless of whether or not it’s accurate.
It also indicates bias. It makes Cathy seem predisposed to be against them. With an introduction like that, it seem unlikely that she would give them a fair shake. It may be that they don’t deserve a fair shake, but I still need to get my bearings as a reader. I can’t always be expected to already know who they are, and I need a way to validate their trustworthiness for myself.
Right-wing publications do this too. I think that Cathy herself would be sensitive to it in these cases. Take this passage for instance:
Just when you think the barrel-bottom standards at Politico cannot get any more bottomer or barreler, the disgraced outlet publishes talking points from a man who is not only facing murder charges, but who is alleged to have tried to commit one of the worst crimes imaginable: assassinating an individual who represents the will, hope, and future of tens of millions of Americans — and I would say the same about Kamala Harris had she been a target.
Does that seem like a reliable narrator to you? Do you think they’ll accurately present what the Politico really said? I know I wouldn’t trust them after reading the above paragraph. You can read the full article here.
I’m sure this sort priming is persuasive to some people. That’s probably why It’s so common. Still, it makes me feel skeptical, and I think for good reason. When I get skeptical like this, I’ll occasionally have the patience to go thorough the article, validating and double-checking the whole way through. Most of the time, however, I’m not that motivated, and I will probably decide the article isn’t worth engaging with.
This is a phenomenon I’ve been meaning to write about for some time. I don’t have anything against Cathy young, but when I read the article, the pattern really just jumped out at me, and it seemed like a good anchor point for this article. It’s an even more interesting case due to the fact that it’s an article that I essentially agree with, which means my aversion to it was pure sensitivity to the pattern, and not bias against the content itself.
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Today is the day!
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