Want an advice from the techies out here to know the ground reality of how far has AI developed to replace doctors (especially radiologists) in terms of reading scans and making diagnosis?
I'm building an AI-powered learning platform for school students (classes 6-12). I have about 2 years of hands-on experience integrating LLMs into the product, but to take it to the next level I need input from people who've built agents, RAG pipelines, and large-scale AI systems in production.
Over the last 1-2 months I've reached out to 50-60 senior AI engineers on LinkedIn. A few replied and a couple said they'd help, but nothing stuck and most went quiet. I'm not blaming anyone. I know senior folks are busy and a cold message from a stranger is a hard sell.
So I'd love some guidance on:
I'm happy to pay for time on a trial or consulting basis, and open to equity conversations for the right person. Any advice or pointers are appreciated, thanks!
How's the AI usage like in WITCH companies? Do they give claude code and copilot licenses to developers?
Product companies I know are mostly having unlimited AI or not much restrictions in token usage.
But service companies operate on tight billing margins and they have clients from banking and finance domains with strict regulations.
Anybody have any info on AI usage in these WITCH companies or they're still following manual coding?
Saw the NYT piece. They are saying an unreleased model worked on around 377 problems across algebra, number theory, logic etc. and put out a pile of papers. Some of them have already been checked in Lean so those might actually hold up. The rest will take people months to go through.
This comes right after the navier stokes thing last month. I am not sure if this is a real step forward or just a flood of stuff that still needs proper checking.
Edit: Correction. The AI runs on Meta's servers, not on the chip. The chip only connects to it. My title is wrong.
Nat Friedman (ex GitHub CEO) released free software that lets a cheap ESP32 chip connect to Meta's AI assistant, Muse.
Basically you can now build your own AI device at home.
The chip costs INR 300-500 on Amazon or Robu. Every engineering college already has them. The expensive part of building AI gadgets was never the chip, it was the software.
That just became free….Compare that with Rabbit R1 and Humane Pin. They burned millions trying to sell a finished product. This does the opposite. Gives you the parts, you build what you need.
What would you build? A voice helper for parents who don't type? Something for a kirana shop? A tool for farmers? Feels like the good ideas will come from tier 2 cities, not Silicon Valley.
Hey guys I am a full stack engineer still now I don't have any AI subscriptions. I just have a few project ideas wanted to vibecode it. I just want some opinions on buying an AI subscription.
There are a lot of them in the market so I'm a bit confused.
GitHub copilot
Antigravity
Cursor
Claude
Codex
I just want to know which is cheap and best for building small to medium scale applications
Most of the AI stuff I see here is about models, llms, coding, or gpus. I recently started looking into the data side and realized there’s a whole process around collecting and preparing real-world data before it can actually be useful for AI. We’re building a community in India around learning how to collect better datasets, including pov data, and understanding what makes the data valuable. From what I’ve seen, there are also companies in the US looking for this kind of data, which could make this an interesting skill to learn here. Has anyone in India already looked into this side of AI?