2023-11-14: GraphCast, word leading weather prediction model, published in Science
2023-11-15: Student of Games: unified learning algorithm, major algorithmic breath-through, published in Science
2023-11-16: Music generation model, seemingly SOTA
2023-11-29: GNoME model for material discovery, published in Nature
2023-12-06: Gemini, the most advanced LLM according to own benchmarks
Where it has fallen down (compared to its relative performance in relevant research) is public generative AI products [0]. It is trying very hard to catch up at that, and its disadvantage isn't technological, but that doesn't mean it isn't real and durable.
[0] I say "generative AI" because AI is a big an amorphous space, and lots of Google's products have some form of AI that is behind important features, so I'm just talking about products where generative AI is the center of what the product offers, which have become a big deal recently and where Google had definitely been delivering far below its general AI research weight class so far.
In such cases, I actually prefer Google over OpenAI. Monetization isn’t everything
For, what, moral kudos? (to be clear, I'm not saying this is a less important thing in some general sense, I'm saying what is preferred is always dependent on what we are talking about preferences for.)
> Monetization isn’t everything
Providing a user product (monetization is a different issue, though for a for-profit company they tend to be closely connected) is ultimately important for people looking for a product to use.
Other interests favor other things, sure.
Google is locked behind research bubbles, legal reviews and safety checks.
Mean while OpenAI is eating their lunch.
Sharing fundamental work is more impactful than sharing individual models.
Advancing products that use AI and getting a consumer/public conversation started? That’s clearly (to me) in OpenAIs court
They’re both impactful, interlinked, and I’m not sure there’s some real stack ranking methodology.
Gemini does nothing. Even if it were comparable to GPT-4, they’re late to the party.
OpenAI is blazing the path now.
Google has lots of people tagging search rankings, which is very similar with RLHF ranking responses from LLMs. It's interesting that using LLMs with RLHF it is possible to de-junk the search results. RLHF is great for this task, as evidenced by its effect on LLMs.
A few reasons partially (if not fully) responsible for it might be:
- Google is a hot target of SEO, not Phind.
- If Google stops indexing certain low quality without a strong justification, there would be lawsuits, or people saying how "Google hasn't indexed my site" or whatever. How would you authoritatively define "low quality"?
- Having to provide search for all spectrum of users in various languages, countries and not just for "tech users".
The Internet is basically a rubbish dump now imo.
There's a constant arms race between shitty SEO, walled gardens, low-quality content farms and search engines.
It will be interesting to see how this percolates through the existing systems.
We are just seeing remnants of that battleground.
