> Thanks John for an extraordinary partnership and wonderful collaboration over the past 9 years! What we achieved with AlphaFold changed the world, and showed the field what was possible with AI for science and medicine, lighting the way for how AI can benefit humanity.
Anthropic legit builds one the strongest if not the strongest IC team in the history of computational technology. They are insanely stacked on talent, and either we will witness a legendary run, or a new LTCM
Their newest model wasn’t really SOTA. And honestly fable 5 was the most human like model I’d ever tried. It was an incredible jump.
And recently lots of Claude users at r/ClaudeAI are noticing Opus 4.8 has really increased in capability. Not new things but maybe redirected compute. It just feels like one of the best models ever, maybe because the compute that was previously assigned to Fable has been redirected? It feels incredible.
The idea of "falling behind" when you can leapfrog each other every six months leads me to believe it has to be more than just "falling behind" for one cycle. It's a culture, process, red tape, focus, or mandate problem of some sort. Something not as easily correctable preparing for next launch.
>from the looks of it, 3.5 Flash is still better than most models
Define "better". I guess it depends on what you're using it for. I use it almost daily as an alternative to google search and it's great for that, but I think it's absolute garbage for coding and reasoning.
For questions related to coding, solving Arch Linux and WINE Lutris issues, helping me with MXLinux issues, and wifi issues on an old rooted huawei tablet running LineageOS, it was consistently wrong, constantly giving out confident but outdated or misinformation, or hallucinating stuff while gaslighting me. Every time I would point out it was wrong, it would re-check and keep apologizing and then repeat giving me wrong answers, and then apologising again and so on. It doesn't matter what prompts or jailbreaks you give it to get 3.5 Flash to chew longer on complex problems for better reasoning and accuracy, it just defaults to being lazy and giving you the quick and easy answer from its weights, which can be totally wrong. Same for asking it to write me a cover letter based on my resume and the job description I wanted to apply to. It massively sucked at that too and made up a bunch of unusable fake sounding BS.
Basic free tier ChatGPT 5.5 would blow it out of the water on all of those tasks. Hell, even Grok free is better at that, it gave me a one-shot Arduino code that blew Gemini 3.5 flash away.
3.5 Flash seems tuned to just eyeballing basic answers to general purpose questions that resemble Google searches like "give me a recipe" or "give me a workout plan", or "what's the difference between Arch and Fedora based distros", not to solving complex issues that require cognition and accuracy. That's what the 3.1 Pro is better for according to Gemini. Oh and it is also gaslights you by starting the answers with first telling you how amazing things from your question are, which is insanely annoying but I guess Google's A/B testing found out the majority of Average Joe midwits love it when "the AI" reinforces their choices and decisions like a fake friend.
I think Google just doesn't care about being the SOTA for coding, reasoning and accuracy, since they're in the ads and search business for everyone, not in the agentic coding business for pro-sumers, so if the answers are some hallucinations that sound "good enough" to its clueless search user base, but is at least dirt cheap to run on their datacenter hardware, then it's already more than enough for them and they can all it a day.
Meanwhile OpenAI and Anthropic don't have search and ads monopolies, so they need to perform well at certain task for people and businesses to give them their hard earned money for them to survive. For them, nailing stuff like coding and writing accuracy is an existential threat, not a hobby sideproject like it is for Google.
The thing about Gemini is that it never chews on a problem. Claude and GPT will regularly churn on a prompt for 10-15 minutes. I don't think I have ever seen Gemini think for more than a 2 minutes.
Google seems more interested in fast models that can quickly turn responses, which kind of fits with a company that needs to serve AI on a mass scale.
It also fits with ad delivery, if that is the route they are going to go with consumer (non-API usage) gemini. Their cash cow is still ads, and will likely remain ads they aren't suddenly going to be come a frontier lab selling access to a model.
Fast answers, using their search as grounding, that can parse keywords and spit out a few ads is where Gemini Flash is going to head. That, and the agentic actions stuff they showed off at I/O with Google shopping, ordering food, etc. Speed is important there.
They almost certainly wanted 3.5 Pro out for Google IO a few weeks ago. They're still crunching on it. No ETA given. Would be fascinating to read about the behind the scenes stories (failed training run?) if they ever get told.
Thank God. I'd rather companies ship something when engineers say it's actually ready rather than when the suits want something to show on stage to pump their egos and career exposure but turn out to be a massive disappointment covered in fluff.
Although it does feel very embarrassing for Google who invented transformers and has more money than both Anthropic and OpenAI combined, to fall behind them at the LLM race.
I think its google doing what theve always done, make a great *thing then ignore it. The models are great their agentic harness systems are really poor though, compared to codex cli and claude code cli its a mess.
I am guessing this is related to Anthropic’s recent acquisition of Coefficient Bio, and their interest on essentially using AGI to discover novel drugs
Can you go into a bit more detail about what exactly it is that you are predicting? This is interesting, and definitely cuts against the grain that the rest of these comments are going with.
A lot depends on whether the z.ai CEO, who just released the first freely-available Opus-class model weights, is blowing smoke when he claims he's less than a year away from achieving Fable-level performance.
If he walks the talk, I really do not understand how either OpenAI or Anthropic is going to justify the twelve-digit valuations they are hoping for. They will just be some people who bought a domain name and rented some GPUs.
That was when they realized the deep learning was largely unnecessary, and they could just use their massive compute resources to brute force the problem space.
Proving that we would greatly benefit from using our compute resources for science rather than showing ads, and then we just kept showing ads.
> Thanks John for an extraordinary partnership and wonderful collaboration over the past 9 years! What we achieved with AlphaFold changed the world, and showed the field what was possible with AI for science and medicine, lighting the way for how AI can benefit humanity.
Extreme investor desire for return on capital investment, and quickly
Their newest model wasn’t really SOTA. And honestly fable 5 was the most human like model I’d ever tried. It was an incredible jump.
And recently lots of Claude users at r/ClaudeAI are noticing Opus 4.8 has really increased in capability. Not new things but maybe redirected compute. It just feels like one of the best models ever, maybe because the compute that was previously assigned to Fable has been redirected? It feels incredible.
I've definitely noticed it, at least for doing backend C#/dotnet. Its insanely good, I haven't had to babysit much at all this week.
https://artificialanalysis.ai/articles/glm-5-2-is-the-new-le...
The idea of "falling behind" when you can leapfrog each other every six months leads me to believe it has to be more than just "falling behind" for one cycle. It's a culture, process, red tape, focus, or mandate problem of some sort. Something not as easily correctable preparing for next launch.
Define "better". I guess it depends on what you're using it for. I use it almost daily as an alternative to google search and it's great for that, but I think it's absolute garbage for coding and reasoning.
For questions related to coding, solving Arch Linux and WINE Lutris issues, helping me with MXLinux issues, and wifi issues on an old rooted huawei tablet running LineageOS, it was consistently wrong, constantly giving out confident but outdated or misinformation, or hallucinating stuff while gaslighting me. Every time I would point out it was wrong, it would re-check and keep apologizing and then repeat giving me wrong answers, and then apologising again and so on. It doesn't matter what prompts or jailbreaks you give it to get 3.5 Flash to chew longer on complex problems for better reasoning and accuracy, it just defaults to being lazy and giving you the quick and easy answer from its weights, which can be totally wrong. Same for asking it to write me a cover letter based on my resume and the job description I wanted to apply to. It massively sucked at that too and made up a bunch of unusable fake sounding BS.
Basic free tier ChatGPT 5.5 would blow it out of the water on all of those tasks. Hell, even Grok free is better at that, it gave me a one-shot Arduino code that blew Gemini 3.5 flash away.
3.5 Flash seems tuned to just eyeballing basic answers to general purpose questions that resemble Google searches like "give me a recipe" or "give me a workout plan", or "what's the difference between Arch and Fedora based distros", not to solving complex issues that require cognition and accuracy. That's what the 3.1 Pro is better for according to Gemini. Oh and it is also gaslights you by starting the answers with first telling you how amazing things from your question are, which is insanely annoying but I guess Google's A/B testing found out the majority of Average Joe midwits love it when "the AI" reinforces their choices and decisions like a fake friend.
I think Google just doesn't care about being the SOTA for coding, reasoning and accuracy, since they're in the ads and search business for everyone, not in the agentic coding business for pro-sumers, so if the answers are some hallucinations that sound "good enough" to its clueless search user base, but is at least dirt cheap to run on their datacenter hardware, then it's already more than enough for them and they can all it a day.
Meanwhile OpenAI and Anthropic don't have search and ads monopolies, so they need to perform well at certain task for people and businesses to give them their hard earned money for them to survive. For them, nailing stuff like coding and writing accuracy is an existential threat, not a hobby sideproject like it is for Google.
Google seems more interested in fast models that can quickly turn responses, which kind of fits with a company that needs to serve AI on a mass scale.
Fast answers, using their search as grounding, that can parse keywords and spit out a few ads is where Gemini Flash is going to head. That, and the agentic actions stuff they showed off at I/O with Google shopping, ordering food, etc. Speed is important there.
Thank God. I'd rather companies ship something when engineers say it's actually ready rather than when the suits want something to show on stage to pump their egos and career exposure but turn out to be a massive disappointment covered in fluff.
Although it does feel very embarrassing for Google who invented transformers and has more money than both Anthropic and OpenAI combined, to fall behind them at the LLM race.
When personal finance is not the bottleneck anymore, the new criteria becomes "vision" and "stacked talent".
Seems like everyone here is easily fooled by the Anthropic hype. After the IPO, Anthropic won't be like the daycare it is today.
Their main competitors are the chinese labs which are racing all their prices down close to $0.
If he walks the talk, I really do not understand how either OpenAI or Anthropic is going to justify the twelve-digit valuations they are hoping for. They will just be some people who bought a domain name and rented some GPUs.
Not a bad playbook. If you’re important to the company, leave and start your own company. Then play the M&A game and you can clean up nicely.
That was when they realized the deep learning was largely unnecessary, and they could just use their massive compute resources to brute force the problem space.
Proving that we would greatly benefit from using our compute resources for science rather than showing ads, and then we just kept showing ads.