481–490 of 582 posts
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Just curious, what tool do you use to interface with these LLMs? Cursor? or Aider? or...
I’m on GitHub Copilot with VsCode Insiders, mostly because I don’t have to subscribe to one more thing. They pretty quick to let you use the latest models nowadays.
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LibGen already exists, and all the top LLM publishers use it. I don't know if Google's own book index provides a big technical or legal advantage.
I'd be very surprised if the Google books index wasn't much bigger and more diverse than libgen.
Google's scanning project basically stalled after the legal battle. It's a very fascinating read [2].
[1] https://annas-archive.org/
[2] https://web.archive.org/web/20170719004247/https://www.theat...
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>obsequious Thanks for the new word, I have to look it up. "obedient or attentive to an excessive or servile degree" Apparently it means an AI that mindlessly follow your logic and instructions without reasoning and articulation is not good enough.
I wonder if anyone here will know this one; I learned the word "obsequious" over a decade ago while working the line of a restaurant. I used to listen to the 2p2 (2 plus 2) poker podcasts during prep and they had a regular feature with David Sklansky (iirc) giving tips, stories, advice etc. This particular one he simply gave the word "obsequious" and defined it later. I remember my sous chef and I were debating what…
Google making Gemini 2.5 Pro (Experimental) free was a big deal. I haven't tried the more expensive OpenAI models so I can't even compare, only to the free models I have used of theirs in the past. Gemini 2.5 Pro is so much of a step up (IME) that I've become sold on Google's models in general. It not only is smarter than me on most of the subjects I engage with it, it also isn't completely obsequious. The model push…
It's probably great for lots of things but it doesn't seem very good for recent news. I asked it about recent accusations around xAI and methane gas turbines and it had no clue what I was talking about. I asked the same question to Grok and it gave me all sorts of details.
Google making Gemini 2.5 Pro (Experimental) free was a big deal. I haven't tried the more expensive OpenAI models so I can't even compare, only to the free models I have used of theirs in the past. Gemini 2.5 Pro is so much of a step up (IME) that I've become sold on Google's models in general. It not only is smarter than me on most of the subjects I engage with it, it also isn't completely obsequious. The model push…
> 100% of my casual AI usage is now in Gemini and I look forward to asking it questions on deep topics because it consistently provides me with insight. It's probably great for lots of things but it doesn't seem very good for recent news. I asked it about recent accusations around xAI and methane gas turbines and it had no clue what I was talking about. I asked the same question to Grok and it gave me all sorts of de…
You are missing the point here. The LLM is just the “reasoning engine” for agents now. Its corpus of facts are meaningless, and shouldn’t really be relied upon for anything. But in conjunction with a tool calling agentic process, with access to the web, what you described is now trivially doable. Single shot LLM usage is not really anything anyone should be doing anymore.
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done pretty much inline with the price elo pareto frontier https://x.com/swyx/status/1912959140743586206/photo/1
So if I see it right flash 2.5 doesn't push the pareto front forward, right? It just sits between 2.5 pro and 2.0 flash. https://storage.googleapis.com/gweb-developer-goog-blog-asse...
Gemini flash models have the least hype, but in my experience in production have the best bang for the buck and multimodal tooling. Google is silently winning the AI race.
100% agree. I had Gemini flash 2 chew through thousands of points of nasty unstructured client data and it did a 'better than human intern' level conversion into clean structured output for about $30 of API usage. I am sold. 2.5 pro experimental is a different league though for coding. I'm leveraging it for massive refactoring now and it is almost magical.
Can you share more about your strategy for "massive refactoring" with Gemini?
Like the steps in general for processing your codebase, and even your main goals for the refactoring.
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Prompt engineering is a thing. Learning how to "speak llm" will give you great results. There's loads of online resources that will teach you. Think of it like learning a new API.
LLM's whole thing is language. They make great translators and perform all kinds of other language tasks well, but somehow they can't interpret my English language prompts unless I go to school to learn how to speak LLM-flavored English? WTF?
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Reddit was an interesting case here. They knew that they had particularly good AI training data, and they were able to hold it hostage from the Google crawler, which was an awfully high risk play given how important Google search results are to Reddit ads, but they likely knew that Reddit search results were also really important to Google. I would love to be able to watch those negotiations on each side; what a craz…
Particularly good training data? You can't mean the bottom-of-the-barrel dross that people post on Reddit, so not sure what data you are referring to? Click-stream?
Of course, that's also a big reason why Google search results suggest putting glue on pizza.