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Claude Integrations

anthropic.com

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Re: Claude Integrations

#261

Post by kordlessagain »

kostas_f wrote: post #114

Anthropic's strategy seems to go towards "AI as universal glue". They want to tie Claude into all the tools teams already live in (Jira, Confluence, Zapier, etc.). That's a smart move for enterprise adoption, but it also feels like they're compensating for a plateau in core model capabilities. Both OpenAI and Google continue to push the frontier on reasoning, multimodality, and efficiency whereas Claude's recent rele…

What they are doing is taking the model and elevating it to the level of attention controller in the conversation. It can run tools, spout inferences, etc. If they can control the UI in the CLIENT, they win. If they don't, they have to rely on someone putting their API integration into another project.

Re: Claude Integrations

#262

Post by dakshgupta »

game_the0ry wrote: post #257
dakshgupta wrote: post #251

Earlier quoted context omitted.

Co-founder of Greptile - that was a bad feature that we since deprecated to focus entirely on AI code reviews

Genuinely curious -- Why pivot to code reviews?

Of the things we had built it was the most useful for us, and the early users found it very useful too

Re: Claude Integrations

#263

Post by mattlondon »

atonse wrote: post #252
mattlondon wrote: post #106

Earlier quoted context omitted.

Do you really think Apple can catch up with and then surpass all these SOTA AI labs? They bet big and got distracted on VR. It was obviously the wrong choice at the time, and even more so now. They're going to have to abandon all that VR crap and pivot hard to AI to try and catch up. I think the more likely case is they can't catch up now and will just have to end up licensing Gemini from Google/Google paying them to…

No I’m not saying Apple even has to build their own model. I’m saying Apple can build a stellar _product_ experience around it. As others have pointed out, if that’s what App Intents are, have they started to integrate this as part of Apple Intelligence?

So what is Apple Intelligence then? Just using CharGPT for Siri's backend?

Bit uninspiring really isn't it?

Re: Claude Integrations

#264

Post by riku_iki »

omneity wrote: post #136
riku_iki wrote: post #127

Earlier quoted context omitted.

> But one cannot deny RAG is a lot more accessible to teams which are likely developers / AI engineers compared to ML engineers/researchers. It looks like major vendors provide simple API for fine-tuning, so you don't need ML engineers/researchers: https://platform.openai.com/docs/guides/fine-tuning Setting RAG infra is likely more complicated than that.

You are certainly right, managed platforms make finetuning much easier. But managed/closed model finetuning is pretty limited and in fact should be named “distribution modeling” or something. Results with this method are significantly more limited compared to all the power open-weight finetuning gives you (and the skillset needed in return). And in either case don’t forget alignment and evals.

> Results with this method are significantly more limited compared to all the power open-weight finetuning gives you (and the skillset needed in return).

I am not sure I understand why you are so certain that finetuned top market models, built by top researchers will be significantly worse than whatever open source model you pick.

Re: Claude Integrations

#265

Post by subpixel »

garrickvanburen wrote: post #158
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…

My current hypothesis: the more familiar you are with a topic the worse the results from any LLM.

The more familiar you are with the state of “Jira hygiene” in the megacorp environment, the less hope you have that LLMs will be able to make sense of things.

That said, the “AI all the things” mandates could be the lever that ultimately accomplishes what 100+ PjMs couldn’t - making people write issues as if they really mattered. Because garbage in, garbage out.

Re: Claude Integrations

#266

Post by danw1979 »

parineum wrote: post #245
startupsfail wrote: post #244

Earlier quoted context omitted.

Yes, it’s particularly bad when the information found on the web is flawed. For example, I’m not a domain expert, but I was looking for an RC motor for a toy project and OpenAI had happily tried to source a few, with Deep Research. Only the best candidate it had picked contained an obvious typo in the motor spec (68 grams instead of 680 grams), which is just impossible for a motor of specified dimensions.

> Yes, it’s particularly bad when the information found on the web is flawed. It's funny you say that because I was going to echo your parents sentiment and point out it's exactly the same with any news article you read. The majority if content these LLMs are consuming is not from domain experts.

Right, but LLMs are also consuming AWS product documentation and Terraform language docs, some things I have read a lot of and they’re often badly wrong on things from both of those domains, which are really easy for me to spot.

This isn’t just “shit in, shit out”. Hallucination is real and still problematic.

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