31–40 of 159 posts
Are Googlers themselves happy using Gemini coding agent instead of Claude Code or Codex? (no snark, I'm really asking)
Last month, Steve Yegge suggested that they are not: https://xcancel.com/Steve_Yegge/status/2043747998740689171
If internal staff aren't happy with the tools they build, typically that should drive improvements to their own tools
Earlier quoted context omitted.
Demis Hassabis chimed in on that thread and called it what it is: clickbait.
I’m not so sure. From talking to some of my own friends at google they feel that antigravity/gemini models are handicapping them and would much rather be using claude code (which only deepmind gets to use)
This reminds me of Antirez's "Don't fall into the anti-AI hype" [0] In a sentence: These foundation models are really good at optimizing these extremely high level, extremely well defined problem spaces (ie multiply matrices faster). In Antirez's case, it's "make Redis faster". There have been two reactions: "Oh it would never work for me" and "I have seen months of my life accomplished in an hour", and I think they'…
What if (when?) (AI-assisted) research moves AI beyond LLMs? Do you think that can't happen?
This reminds me of Antirez's "Don't fall into the anti-AI hype" [0] In a sentence: These foundation models are really good at optimizing these extremely high level, extremely well defined problem spaces (ie multiply matrices faster). In Antirez's case, it's "make Redis faster". There have been two reactions: "Oh it would never work for me" and "I have seen months of my life accomplished in an hour", and I think they'…
I don't believe that anymore, to be honest. Models are starting to get good at ambiguity. Claude Code now asks me when something is ambiguous. Soon, all meetings will be recorded, transcribed and stored in a well-indexed place for the agents to search when faced with ambiguity (free startup idea here!). If they can ask you now, they'll be able to search for the answers themselves once that's possible. In fact, they already do it now if you have a well-documented Notion/Confluence, it's just that nobody has.
It's probably harder to RL for "identify ambiguity" than RL'ing for performance algorithms, sure, but it's not impossible and it's in the works. It's just a matter of time now.
This reminds me of Antirez's "Don't fall into the anti-AI hype" [0] In a sentence: These foundation models are really good at optimizing these extremely high level, extremely well defined problem spaces (ie multiply matrices faster). In Antirez's case, it's "make Redis faster". There have been two reactions: "Oh it would never work for me" and "I have seen months of my life accomplished in an hour", and I think they'…
1. Amazing, you just tweaked 1% efficiency
2. You idiot, you just spent an hour trying to trouble shoot a hallucinated api.
On average, it's really hard to tell which ones going to win here.
AI improving itself (or at least the architecture it runs on), the singularity is near as they say. Do we have other examples of AI being used to improve the LLMs, apart for the creation of synthetic data and the testing of the models?
I mean, if you can create aharrness to filter these two, sure, singularity away; it's really hard to see how someones gonna do that.
This reminds me of Antirez's "Don't fall into the anti-AI hype" [0] In a sentence: These foundation models are really good at optimizing these extremely high level, extremely well defined problem spaces (ie multiply matrices faster). In Antirez's case, it's "make Redis faster". There have been two reactions: "Oh it would never work for me" and "I have seen months of my life accomplished in an hour", and I think they'…
I'd say it's a malefactor of: 1. Amazing, you just tweaked 1% efficiency 2. You idiot, you just spent an hour trying to trouble shoot a hallucinated api. On average, it's really hard to tell which ones going to win here.
Imagine going back to 2020 and tell people in 6 years going to be able to spend $200.00 a month and be able to spin up $2mm in GPUs at full throttle to respond to your emails. None of this makes sense.
Earlier quoted context omitted.
I'd say it's a malefactor of: 1. Amazing, you just tweaked 1% efficiency 2. You idiot, you just spent an hour trying to trouble shoot a hallucinated api. On average, it's really hard to tell which ones going to win here.
Its not hard to tell at all, just look at how much it costs to run a 10T param model (especially with parallelized agents). Those costs are not worth the occasional slot machine-eque jackpot you get. For an entity like Google it might be worth it, but that's it. They definitely aren't going to let us use these things for cost they are now for much longer. Imagine going back to 2020 and tell people in 6 years going to…
This reminds me of Antirez's "Don't fall into the anti-AI hype" [0] In a sentence: These foundation models are really good at optimizing these extremely high level, extremely well defined problem spaces (ie multiply matrices faster). In Antirez's case, it's "make Redis faster". There have been two reactions: "Oh it would never work for me" and "I have seen months of my life accomplished in an hour", and I think they'…
A Statement all but guaranteed to look incredibly short sighted by 2030.