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Notes -
Grok 3 just came out, and early reports say it’s shattering rankings.
Now there is always hype around these sorts of releases, but my understanding of the architecture of the compute cluster for Grok 3 makes me think there may be something to these claims. One of the exciting and interesting revelations is that it tends to perform extremely well across a broad range of applications, seemingly showing that if we just throw more compute at an LLM, it will tend to get better in a general way. Not sure what this means for more specifically trained models.
One of the most exciting things to me is that Grok 3 voice allegedly understands tone, pacing, and intention in conversations. I loved OpenAIs voice assistant until it cut me off every time I paused for more than a second. I’d Grok 3 is truly the first conversational AI, it could be a game changer.
I’m also curious how it compares to DeepSeek, if anyone knows more than I?
Very interesting to me about this whole thing is how there's still plenty of space for new contenders to pop up and beat actual established players at their own game.
I thought Grok was just purely a derivative of existing products with some of the safety measures stripped off. And now they've done made an updated version that crushes all the cutting edge products in, feels like, about a year?
It sure seems like OpenAI has no meaningful "moat" (hate that term, honestly) that keeps them in the lead DESPITE being the first mover, having the highest concentration of talent, and more money than God.
Doesn't mean they won't win in the end, or that any of these other companies are in an inherently better position, but it is becoming less clear to me what the actual 'secret sauce' to turning out better models is.
Data quality? The quality of the engineers on staff? The amount of compute on tap?
What is it that gives any given AI company a real edge over the others at this point?
Apparently Elon and company made some important advances in how to string together an unprecedented number of GPUs into one cluster, meaning they were able to throw more compute at the problem.
The advance was in building the cluster not in improving algos.
So it make sense that they were able to take established methods and get a better result. P(doom) just increased since this provides evidence that scaling still works.
Agreed. OpenAI is just one of several foundational models with no real differentiation. What they do have is brand recognition in the consumer space, but I'm not sure how valuable that is. Sure, meemaw might use them for her banana bread recipes, but big corps will use the service that provides the best reasoning at the lowest price. Right now, it looks like DeepSeek and XAI are ahead.
The meltdown on hackernews about Elon delivering is quite something. EDS seems to make even TDS pale in certain circles.
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