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Claude Integrations

anthropic.com

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Re: Claude Integrations

#191

Post by scargrillo »

emorning3 wrote: post #169
greymalik wrote: post #142

Earlier quoted context omitted.

Out of curiosity - can you give any examples of the programming questions you are using deep research on? I’m having a hard time thinking of how it would be helpful and could use the inspiration.

I often use Chrome to valid what I think I know. I recently asked Chrome to show me how to apply the Knuth-Bendix completion procedure to propositional logic, and I had already formed my own thoughts about how to proceed (I'm building a rewrite system that does automated reasoning). The response convinced me that I'm not a total idiot. I'm not an academic and I'm often wrong about theory so the validation is really u…

That’s a perfect example of LLMs providing epistemic scaffolding — not just giving you answers, but helping you check your footing as you explore unfamiliar territory. Especially valuable when you’re reasoning through something structurally complex like rewrite systems or proof strategies. Sometimes just seeing your internal model reflected back (or gently corrected) is enough to keep you moving.

Re: Claude Integrations

#192

Post by antupis »

spaceman_2020 wrote: post #186
throwup238 wrote: post #16

The leap frogging at this point is getting insane (in a good way, I guess?). The amount of time each state of the art feature gets before it's supplanted is a few weeks at this point. LLMs were always a fun novelty for me until OpenAI DeepResearch which started to actually come up with useful results on more complex programming questions (where I needed to write all the code by hand but had to pull together lots of d…

Gemini 2.5 pro was the moment for me where I really thought “this is where true adoption happens” All those talks about AI replacing people seemed a little far fetched in 2024. But in 2025, I really think models are getting good enough

You still need "human in the loop" because with simple tasks or some tasks that have lots of training material, models can one-shot answer and are like super good. But if the domain grows too complex, there are some not-so-obvious dependencies, or stuff that is in bleeding edge. Models fail pretty badly. So you need someone to split those complex tasks to more simpler familiar steps.

Re: Claude Integrations

#193

Post by snewman »

fastball wrote: post #178
user_7832 wrote: post #26

Earlier quoted context omitted.

I agree with your overall message - rapid growth appears to encourage competition and forces companies to put their best foot forward. However, unfortunately, I cannot shower much praise on Claude 3.7. And if you (or anyone) asks why - 3.7 seems much better than 3.5, surely? - Then I’m moderately sure that you use Claude much more for coding than for any kind of conversation. In my opinion, even 3.5 Haiku (which is a…

Seems clear to me that Claude 3.7 suffers from overfitting, probably due to Anthropic seeing that 3.5 was a smash hit in the LLM coding space and deciding their North star for 3.7 should be coding benchmarks (which, like all benchmarks, do not properly capture the process of real-world coding). If it was actually good they would've named it 4.0, the fact that they went from 3.5 to 3.7 (weird jump) speaks volumes imo.

The numbering jump is because there was "Claude 3.5" and then "Claude 3.5 (new)" and they decided to retroactively stop the madness and rename the later to 3.6 (which is what everyone was calling it anyway).

Re: Claude Integrations

#194

Post by miki_oomiri »

emorning3 wrote: post #169
greymalik wrote: post #142

Earlier quoted context omitted.

Out of curiosity - can you give any examples of the programming questions you are using deep research on? I’m having a hard time thinking of how it would be helpful and could use the inspiration.

I often use Chrome to valid what I think I know. I recently asked Chrome to show me how to apply the Knuth-Bendix completion procedure to propositional logic, and I had already formed my own thoughts about how to proceed (I'm building a rewrite system that does automated reasoning). The response convinced me that I'm not a total idiot. I'm not an academic and I'm often wrong about theory so the validation is really u…

"Chrome" ? What do you mean? Gemini?

Re: Claude Integrations

#195

Post by _1tem »

Finally I can do something simple that I’ve wanted to do for ages: paste in a poster image or description of an event and tell the AI to add it to my calendar.

Re: Claude Integrations

#198

Post by onel »

notgiorgi wrote: post #39
WhitneyLand wrote: post #19

The integrations feel so rag-ish. It talks, tells you it’s going to use a tool, searches, talks about what it found… Hope one day it will be practical to do nightly finetunes of a model per company with all core corporate data stores. This could create a seamless native model experience that knows about (almost) everything you’re doing.

why is finetuning talked about so much less than RAG? is it not viable at all?

You usually fine tune when you want to add capabilities (an output style, json output, function calling, etc). You use RAG to add knowledge

Re: Claude Integrations

#199

Post by iLoveOncall »

throwup238 wrote: post #16

The leap frogging at this point is getting insane (in a good way, I guess?). The amount of time each state of the art feature gets before it's supplanted is a few weeks at this point. LLMs were always a fun novelty for me until OpenAI DeepResearch which started to actually come up with useful results on more complex programming questions (where I needed to write all the code by hand but had to pull together lots of d…

Calling some APIs is leap-frogging? You could do this with GPT-3, nothing has changed except it's branded under a new name and tries to establish a (flawed) standard.

If there was truly any innovation still happening in OpenAI, Anthropic, etc., they would be working on models only, not on side features that someone could already develop over a weekend.

Re: Claude Integrations

#200

Post by therein »

Balgair wrote: post #150
85392_school wrote: post #135

Earlier quoted context omitted.

The funny thing is that if your request only needed the top 100's temperature or the top 33's precipitation, it could just read "List of cities by average temperature" or "List of cities by average precipitation" and that would be it, but the top 250 requires reading 184x more pages. My perspective on this is that if Deep Research can't do something, you should do it yourself and put the results on the internet. It'l…

Yeah, that was intentional, well, somewhat. The project requires the full list of every known city in the western hemisphere and also Japan, Korea, and Taiwan. But that dataset is just maddeningly large, if it is possible at all. Like, I expect it to take me years, as I have to do a lot of translations. So, I figured that I'd be nice and just as for the top 250 for the various models. There's a lot more data that we'…

Sounds like the you're having it conduct research and then solve the Knapsack problem for you on the collected data. We should do the same for the traveling salesman one.

How do you validate its results in that scenario? Just take its word for it?

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