361–370 of 616 posts
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Anything Sam Rose is worth reading: https://ngrok.com/blog/prompt-caching but the implementation will be up to your provider and harness, for deepseek, they expose some numbers: https://api-docs.deepseek.com/guides/kv_cache/ and Anthropic has a list of actions invalidating your cache: https://platform.claude.com/docs/en/build-with-claude/prompt... Basically, you avoid anything dynamic: model change, tool change, etc…
Sam Rose here. Thank you <3
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> Claude Code has largely won individual developer mindshare and has been on top ever since it came out. Claude Code's success is not due to the agent but because the model is considered the best for programming and is very heavily subsidized, compared to pay as you go API prices. Consumers and Enterprise are not really locked in and will go where it makes the most sense. I think they have almost no loyalty by actual…
There is no reason to be loyal....There is no moat. Basically you may choose to drink brand A water bottle, brand B water bottle or tap water. Oh and you might choose the glass water bottle if you use API/Fable.
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If enough people agreed with you, simonw's top level comment would be grey. It isn't. Not every comment is for every person, that is fine and normal. He didnt hijack a popular thread in here to make his post. He doesnt have a tin can in your face shouting from a soapbox that makes it hard to ignore. Flag or ignore are reasonable options that can be used.
People aren't supposed to upvote or downvote posts for these kinds of reasons here. Most people are downvoting far too much on this website, and it leads to significant echo-chamber dynamics that are worse than even reddit. The pelican test continuing to be taken seriously is a great example of that kind of echo chamber. "He doesn't have a tin can in your face shouting from a soapbox that makes it hard to ignore." He…
Agreed, but scrolling past or hitting - were apparently off the table for the complainers. So flagging was yet another tool in their toolbelt and I bet a powerful one at that. If simonw's pelican posts routinely went dead from flagging, he would not make them. You know that, I know that.
> The pelican test continuing to be taken seriously is a great example of that kind of echo chamber.
You can try and support that argument if you like. But I would implore you to realize that it has been had many times recently and the other side does in fact find value and do not see it that way.
> He metaphorically does because people upvote his pelicans to the top and the ensuing comment threads are massive/bloated.
Users upvote the pelicans because they find it interesting. they arent paid trolls or simonw fanatics.
> Huge amounts of the readership of this website are lurkers who don't even know how to hide these giant posts.
They can learn... it's called hackernews. For those interested, that is what the [-] link is for above the comment. Use it and move on.
I wonder how big the Pro model is that Google is using behind the scenes to train these smaller ones. Going on baseless speculation, the lack of accompanying pro models with these flash releases either means: 1) the model is too big to be economical, 2) google doesn't have the compute to serve the big model, 3) their big model has too many alignment issues to serve to the public. edit: looks like benchmarks are up on…
It seems like there are some credible rumors that Google is actually winning in terms of actually building models that work and don't lose money- between how they're able to price them, the TPU advantage and their capex advantage (being able to raise debt + just having a lot of cash - well I said not lose money... more like not go bankrupt). From the outside they look like they're behind in terms of frontier models,…
Porting CUDA-based research, debugging, and overall experimentation speed is likely slower.
The GPU is still king for training.
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It's literally the meme of the MS org chart pointing guns at each other. The GCP team wants their slice, the other team wants some otjer slice, and so on. Everyone wants some crap for their promotion package. It's no wonder Meta has shit the bed even worse. It's also why Google still releases actually decent, useful models despite the product being such a hilarious mess. A lot of the time Gemini models have actually…
> The GCP team wants their slice, the other team wants some otjer slice, and so on. Everyone wants some crap for their promotion package. I got a Google One plan for Gemini, but it came bundled with YT Premium lite, and that somehow made it impossible to renew YT Premium for 30 days. I suspect different teams stealing customers from each other.
Like when you try to give Google money they try to squeeze you as much as possible.
At the same time you can get 5 time more limits for free just by registering 10 free Google accounts.
Google subscriptions are one big mess.
Otherwise, this news feels like a tiny incremental improvement on Gemini Flash series to make it more efficient with token usage, subagent and cost. Nothing big.
Regarding their benchmark scores on CyberGym, I wonder why they didn't compare their 3.5 Flash Cyber model with Fable 5. I mean they included Mythos and GPT-Cyber, so why not Fable 5 too?
They also mentioned Gemini 3.5 Pro is in testing and its about to become available very soon. Another thing maybe worth discussing is the announcement of pre-training Gemini 4. Sadly, not much technical details to discuss on. Many comments in here seem to mostly be about how Google is behind the others, but honestly, is it really worth the investment to be #1 in Artifical Analysis every week?
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Small open source models shouldn't be used for world knowledge, that's not their purpose.
Why not? Seems like a cop out. Being able to ask questions to small open models seems.... obviously useful?
Use the right tool for the job. It's like asking why a screwdriver isn't good at sawing wood, or calling C a terrible language because it's hard to make CRUD apps with it.
Google somehow managed to snatch defeat from the jaws of success with their AI products. They literally forced me and my company out of Antigravity by phasing out AI Ultra subscription without any proper product follow-up. Antigravity IDE cannot even have poweruser subscriptions now from Google Workspace an Gemini Enterprise Agent Platform cannot be attached to Antigravity IDE. Gemini Enterprise Agent Platform has an…
This is what happens when you put a McKinsey consultant in the role of CEO of an organization where product managers run the asylum instead of engineers.
It's scary relying on Google's models. I have a very price sensitive workload that used to run on flash 2.5 lite - it's deprecated now. The replacement 3.1 flash lite is a lot more expensive, but now also has a sunset date. 3.5 flash lite is even more expensive. So the price is rising and you have no choice but to keep paying more and more.
I'd be low-keying the release if anything, given how lame they are compared to their competition.
What am I missing?