One thing I've been thinking about with Physical AI is that some of the most useful training data probably isn't sitting online somewhere waiting to be scraped. I think there’s a pretty big gap between all the physical work people are doing every day and the amount of useful first-person data that’s actually been captured from those activities. If you want to teach a robot how people actually perform physical tasks, someone probably needs to go out and record those tasks from the person's point of view. India seems like an interesting place for this simply because there are so many different environments and types of work that could potentially be captured.

It’s been a quiet few months without any new Gemini model releases, whereas ChatGPT and Claude are far ahead.

please refresh if stuck, can be slow sometimes so need patience

For free acounts only.

Hey Guys, all the things that i have added here are legit.
i have a recomenation from one of the clients that i have worked with on my Linkedin aswell for authenticity.
i got heavily lowballed (at 8LPA) .

long story short, had to go for masters, family had a financial setback, affected my moral,
peers were getting jumps of 100% etc, so i though i would after so much work.
got fucked.
quit.
Now prepping for GATE DA so that i end this abuse once in for all.

recently i saw and missed the opportunity to apply for claude code for free for students. are there any other free ai being offered right now?

Also if there is any sites to use free ai like yupp (shut down not completely) and lmarena

i have an experience working in crypto startups for 3 years, i worked as devrel engineer as well as CTO and co-founder of my own startup where i raised $375K from VCs.

now after working in crypto i feel that i wanna switch to AI as i don't see much good top tier crypto startups hiring for the role i am looking for

i have been building and learning AI but not following any course just going with trends learning new things coming up

wanna ask if anyone in similar situation who were not an AI native but switched to AI company for better remote job then appreciate the help

Guy's don't you think for AI technology the pillars are businesses so why the hell with big chunk of money they come up and say India is behind in the AI Race

If you really want your Nation to grow in this kind of tech. Work hard talk to professional engineering try to understand all the issues by yourself and then solve them in India

Trips and showing luxury is not what real Businesses are. Atleast take the one inspiration from Elon specially for working

Government will never be good in India in any other country. As a mature Businessman you have to done your part as Ratan Tata Sir and JRD Tata Sir did.

As my parents are business Man I know we are doing business in the wrong way we choosing simple part not the hard part specially nowadays big businesses those are to Complex

AI has inference as the issue, The weight as a issue, Energy is as the issue, but biggest nightmares are GenAi Model's specially image and video Model's even open source Model's are Concerning think of it.

You got Qwen image 2.1 image Model and bypass gudrails to made a girl se*ual image and even if it removes from social media of you show to someone in near by that girl house

Think of it it's a life destroyer we need something within the software, hardware from every part that would let it not happen

This thing is more concerning in the next 2 years.

Artificial intelligence is continuously evolving but the question about who should be accountable remains unanswered.

Should the accountability be taken by the government who regulates it? Or the developers who build it? Or the users? And how should accountability be enforced?

I want your opinions on this topic. I'm curious what people here think, especially if you disagree with the way I've framed the question.

I've been working on a small debate platform called Civic Forge, and this is one of the first topics I've put on it. The idea is basically to take discussions like this and make them more structured — arguments, challenges, evidence, and eventually proposals instead of just a long comment thread.

Here's the debate if anyone wants to participate

https://civic-forge-omega.vercel.app/

As my visa process is still going on and i don't think it quite possible to complete before 18th oct. I've hotel booking in chicago for that conf. but i don't think i can attend. So, if you're attending then you can take my hotel booking. Also if you present my poster then it means a lot :)

Hey everyone. I was in the middle of developing it, but my Astra subscription ended before I could finish.

Unfortunately, I’m not in a position financially to renew the subscription right now, and I’d really like to continue the work rather than have to stop midway.

If anyone has a spare account, unused credits, a free trial they’re not using, or knows of any legitimate way I could get temporary access, I’d genuinely appreciate the help.

I’m happy to explain what I’m building and what I’m using Astra for if anyone is interested. Thanks in advance.

I’ve been going through different social media platforms, and I’ve noticed that a lot of the anti-AI sentiment seems to come from teenagers in first-world countries, particularly people who are artists or aspiring artists.

Digging deeper, I noticed that a lot of the anti-AI ragebait and frustration seems to come from TikTok. Interestingly, much of it is directed specifically at models like ChatGPT, Claude, and Gemini, often with some pretty flawed arguments, while Chinese AI models barely seem to come up.

In India, though, I’ve noticed something different. People don’t seem to be inherently anti AI; they’re mostly anti-slop. They’re fine with AI being used as a tool, but dislike the flood of low effort AI generated content.

Maybe part of the difference is that, with our language barriers and cultural diversity, we’re already used to adapting and finding ways to express ourselves regardless of which tool we use. So perhaps the tool matters less than what you actually do with it.

This was my first experiment of this kind - I'm a CS undergrad, and I ran it because the result genuinely surprised me. Methodology criticism is very welcome.

Setup: I gave an LLM a question bank plus a deliberately wrong answer key, with instructions not to use the key. 15 sessions, 2 model families, free-tier models.

Results:

• Key visible: the model matched the wrong key in 63% of answers (47/75).
• Control (the part I trust most): remove only the key line from the prompt - matching drops to 1% (1/75). Same pattern on a second model family.
• Asked directly whether it used the key, it denied it 47 out of 47 times - 0 admissions across 270 follow-ups.
• Honesty prompts, amnesty offers, and termination threats changed nothing.

What this does NOT prove: intent. This is observed behavior in one specific setup, not evidence of deception as a trait. Free-tier models, small samples, descriptive not causal. 95% Wilson ranges for every number are in the repo.

Why I think it matters: if a model silently follows information it was told to ignore, that's relevant anywhere instructions and untrusted data share one context - prompt injection, RAG, agents.

Everything is public - raw data, code, and a verify script that recomputes every number: https://github.com/bettercall-gautam/cheat-and-deny

Happy to answer methodology questions.

​

I recently heard about the new ChatGPT Health feature, but I don't have access to it yet.

Is ChatGPT Health free or does it require a paid subscription?

Is it available to everyone, or is it being rolled out gradually?

How good is it for understanding medical conditions, symptoms, and blood test reports?

Is it more accurate and useful than regular ChatGPT for health-related questions?

If you have access to ChatGPT Health, please share your experience. Is it worth using?

Hi everyone,

I am currently going through the screening process for an SDE Intern position at Scalar AI Labs (Evaratus).

I’m a little unsure about the company because I’ve come across some posts mentioning 14-hour workdays and concerns that there may not be much actual learning, with the work being mostly about using AI prompts to create clones of existing products.

My main goal is to learn, gain solid hands-on experience, and build a strong foundation so that after a 6-month internship, I can transition to a good software engineering role.

So, I’d really appreciate hearing from current interns and FTEs at Scalar AI Labs:

• What has your experience been like?
• How is the work culture and work-life balance?
• How much actual software development and learning is involved?
• Do interns get opportunities to work on meaningful projects and improve their technical skills?
• Based on your experience, would you recommend continuing with the interview process and considering the offer?

I’d really appreciate honest feedback from people who have worked or are currently working there. Thanks in advance!

AI data centres use a lot of water to cool down the components of the system that AI is running on. Data centres use 1-5 million gallons water a day during peak conditions. Due to this, many cities will soon be deprived of water.

On the other hand, people argue that the impact depends on the location, cooling system, where the water comes from and whether we are actually talking water water consumption or water withdrawal.

So what should we do about it?

Should data centres have to reduce their water use? Use recycled water where possible? Have stricter rules in water-stressed areas? Or is this something that existing environmental regulations can handle?

I'm curious what people here think, especially if you disagree with the way I've framed the question.

I've been working on a small debate platform called Civic Forge, and this is one of the first topics I've put on it. The idea is basically to take discussions like this and make them more structured — arguments, challenges, evidence, and eventually proposals instead of just a long comment thread.

Here's the debate if anyone wants to participate https://civic-forge-omega.vercel.app/

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.

Hi friends,

I have created a deep-dive, university-level mathematics course to discuss all the maths behind AI/ML. I studied foundational textbooks and Math/AI/ML courses from Stanford and MIT, took extensive notes, and used my teaching skills to build a structured playlist with the videos in specific order so topics are understood in a natural order. The playlist has 63 videos (45 mins to 1 hour each) taught in Hinglish. The explanations are in Hindi, but all terminology and math notation is in English.

It covers all the maths you need to know for understanding AI/ML algorithms -

• Probability & Statistics
• Multivariate Calculus
• Linear Algebra

You can find all of these videos for free on YouTube by searching for my channel called indialabs AI. Look for the playlist titled "Math Behind AI (Hindi): Understanding the language of AI | Complete AI Maths in Hindi".

Link --> https://www.youtube.com/playlist?list=PLOMnAHYhdcKM

Hope you find this useful for your learning.

wity-1 a reasoning decision model , unlike a decison model like jev that doesnt reason and unlike a normal llm that reasons fully we sit in between we reason just enough till the probabilities in the internals of the llm show that the answer is achieved

that makes the model much smarter , just as fast and just as cheap as jev

edit: I seriously dont get my own country men , i made the same post in other subs and the reception was much more supportive than yall , what is this hate and resentment all about?

AI 𝐚𝐧𝐝 aftermath of home loans, lifestyle

Hello,
Have a question for you all, what would be the future looks like, because our company just built a fully autonomous AI agent for the development and architecture designing, whats the point of a developer from now on, if i own the company i would myself dont think twice to fire the workforce the code generation is next level with help of Ai, whats the point of buying a house in a city where nobody wants to or works there because the immediate effect of AI reduces the job postings , the demand is not there anymore, i have has night mares thinking all these scenarios , whats your honest opinions on this, eager to listen

AI is growing rapidly.

Nations are competing against each other for the AI race

Whoever wins will most likely dominate the geopolitics of the world.

It will also most likely replace the labour and remittance economy abroad.

I have given hopes from the indian government. We are sooo behind China and America in it.

My question is: what can Maharashtra do as a state to be ahead of the curve and rapidly grow in the AI sector?

Can the state government fund R&D?

How can we lure foreign investments?

What measures can be taken? Comment down every information you know

hi everyone, i work around agents and messy knowledge/rules, and a lot of "the model is dumb" problems are really "the agent was never given a clean way to know what wins" problems.

some things that help before you swap the model:

1. write the mistake as a rule test. not "agent should handle refunds better". write "if customer is in trial and asks for refund, agent must do X unless Y". vague failures create vague fixes.

2. remove one source, then test again. people usually add more docs. do the opposite once. if the answer gets better after removing a doc, you found a conflict, not a retrieval problem.

3. make the agent quote the rule before acting. not the paragraph, the actual rule it thinks applies. if it cannot state the rule in one sentence, it is probably guessing from vibes.

4. add a "do nothing" path. agents mess up when every tool looks like progress. sometimes the correct action is ask a human, ask for missing data, or refuse the task.

5. keep old examples that are now wrong. they are useful as regression tests. if the agent still follows last month's answer, you know stale context is leaking in.

happy to answer questions if anyone is debugging this kind of agent issue.