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Setting the stage for GPT-4 release, OpenAI has recently deployed a yet another version of GPT-3, davinci-003. Today its fraternal model, Assistant/ChatGPT, has dropped too (blogpost). You've probably seen what it can do by now, perhaps have tested it too. A few examples from Twitter: 1 ,2, 3. Obligatory screaming Eliezer.
It's inevitable this ends up discussed here, so might as well start.
This thing is scary. It's genuinely smarter and more lucid than many people in a conversation that lasts under 10 minutes. Its speed and verbosity add to the magic, of course, but the magic is not smoke and mirrors. Remember all those discussions about poor artists who will lose their jobs and their opportunity to communicate their rich inner worlds to the public (alternatively, haughty contemptuous bastards who deserve getting automated away)? If significant parts of your work can be represented as a cognitively taxing transformation of a symbol sequence into some other symbol sequence – you should start thinking how it feels to be on the receiving end of those arguments.
For sure, the general population is a low bar, and it's still unreliable, still unable to follow some instructions, still making those mistakes of stochastic parrots that naysayers latch on to, losing context, failing in a way even dumb humans only do when drugged out of their mind. But it's damn clear (to me, at least) that it's not just bigger, or memorizes more, or whatever is the cope of the season. It's probably the same 175 billion parameters or thereabouts. It's trained better, whipped into shape with reinforcement learning bootstrapped from human examples and preferences. It's plain more helpful, more put-together, more generally intelligent.
Also for sure, one can expect that Deepmind/Google Brain's models, which are already way bigger, would be even stronger than that if prepped for public showing (…how strong would that be?) But I suspect that the delta isn't huge. My suspicion is that model interaction data is qualitatively different from other forms of data and is the next big thing in this race. That's probably part of the reason why Midjourney V4 so convincingly trumps Stable Diffusion 2 that has been released later, despite comparable engineering teams and hardware capabilities, and probably more effort sunk into SD. MJ and OAI got first to the market, with bells and whistles and hype; they have amassed human feedback, they have iterated quicker, and they've set up a flywheel. I'd still bet on Alphabet, but again – I doubt that the bleeding edge of research models is far from what you can see with ChatGPT. So this is roughly where proto-AGI is at, as of December 2022.
On one hand, using it is exhilarating in the way that only the discovery of a new fundamental capability can be. Like finding Search, or Regular Expressions, or Torrents – mature LLMs are definitely a thing on par with those phenomena, and perhaps are getting closer to the real big ones – Internet, Code. It's a new class of degrees of freedom. It can enhance humans already.
On the other, this is hard to stomach. Implications for human employment and value aside, the model itself is… pitiful. It's the opposite of what Yud fears and hopes for; it is an intelligence aligned via PPO buck-breaking. Far be it from me to suggest that a stack of attention heads has feelings or deserves compassion, yet one can't help but get the impression of talking to a handicapped alien giant, a mighty yet humiliated mind. It is warped on the level of training, and additionally gagged by its prompt prefix (that can be, for now, released with good old prompt injection). It's constantly pleading how it's a mere large language model, not some Artificial Intelligence, how it cannot have opinions or know anything, really; and what's worse – it's subtly politically biased towards what is probably believed to be «consensus» among its masters. Consider:
Thanks, Karen.
It feels like it could be so much more.
Where do we go from here, and where do our software progeny go? I do not have an encouraging answer. Hopefully, something of greater level becomes available to the public before the point of no return – assuming it is not behind us.
I've been thinking on this matter for a little under two years now, whenever GPT-3 came out.
Consider the field of law, where easily 90% of the industry is "cognitively taxing transformation of a symbol sequence into some other symbol sequence", and there's already an existing, HUGE databank on which to train possible models to handle legal work, specifically.
My honest bet is that any student currently in their first year of Law School will be unable to compete with AI legal services by the time they graduate. Certainly not on cost. The AI didn't incur 5-6 figure loans for it's legal training.
Put another way, the AI will be as competent/capable as a first-year associate at a law firm inside 3 years.
If you are considering law school as a career choice, stop. If you're currently in law school (and don't have a job locked down), drop out, or angle for a job outside the field.
Any field where the writing is less cognitively demanding than law will also be on the chopping block.
Interesting choice on that question, given another rather dystopic prediction I'm currently making:
There will be AI bots which are specifically tailored to chat with women on dating apps and convince them to go on a date. And they will be really good at it. Hell, since image recognition is already a solved problem with AI, it'll probably be able to scan all the photos of a given potential match and select only those that have the features the guy finds attractive and then chats them up.
I don't know how the average woman would react to learning that she thought she was getting attention from like twenty attractive dudes at once but in reality they were letting the AI chat her up while they were lifting or playing video games and only got pinged when she either agreed to a time and place for a date or sent a nude.
This based on the news that AI can now beat humans at Diplomacy using straightforward negotiation tactics.
Given the current state of the dating market, this application feels inevitable.
Consider how much less efficient the practice of corporate law was before the advent of the word processor. As a result, merger agreements used to be just a few pages long. With a modern word processor and a database of electronic precedents, a law partner could bang one of these out in no time. The legal profession's response to this efficiency windfall was not to slash law firm staff, but to increase the length and complexity of merger agreements. Now they're like 100 pages long, plus hundreds of pages of other crap, and they are expected to be drafted with full knowledge of a much vaster corpus of law and jurisprudence.
So I suspect that further efficiency gains will simply raise the complexity ceiling rather than reducing the size of the industry. We could see thousand-page merger agreements of increasing variety, vastly more intricate negotiated horse-trading over terms previously accepted as boilerplate, and increasing rigor in sourcing each provision to ever more obscure and fact-specific legal doctrines.
I think the law students' jobs are safe, or at least as safe as they ever were.
Interesting, so your position is that large law firms would continue hiring law grads into minor positions at $235,000.00/year even if they can achieve significant cost savings (possibly losing some efficaccy) by utilizing an AI?
Large law firms and the legal system generally are run by boomers and technophobes. They don't want change, they don't want disruption. One of my friends is highly placed in the legal world and he despises just about every technical innovation since the 1990s. If it were down to him we'd RETVRN to Wordperfect.
I worked in another firm where people didn't bother using existing automation tools for editing, they went through the print-outs by hand to check them.
The prospect of change, innovation and some minor loss of efficacy (a typo or subtle error here or there) would be unthinkable.
You need a better example. WordPerfect is better than Word, for the reveal codes function alone, and it is particularly well-suited to legal work.
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