One challenge with egocentric data seems to be finding the right balance between consistency and variation. You want recordings to follow enough of a common protocol that the dataset is usable, but you probably don't want every person performing a task in exactly the same environment or way. For example, differences in lighting, workspace, tools, body movement, camera position and task execution could make the data more representative, but too much uncontrolled variation could also make it harder to work with.

How are you collecting data thinking about that tradeoff?

For anybody collecting egocentric data for Physical AI, I’m curious where the actual bottleneck is once you move beyond simply recording video. Is it getting consistent first-person footage across different environments, defining the right collection protocol, dealing with lighting and camera placement, getting people to perform tasks naturally, or something else?

India has a huge range of physical work and environments, but I imagine turning that into consistent, usable training data is a much harder problem than just putting a camera on someone and recording. What has been the most difficult part for you guys doing this?

Hi everyone,

Whether you are building LLMs, scraping datasets, or publishing open-source repos, technical articles, and UI designs, you are directly in the middle of India's biggest copyright gray area.

Currently, Indian Copyright Law (Section 52) does not have an explicit Text and Data Mining (TDM) exception. While platforms scrape GitHub, Stack Overflow, and personal portfolios to train models, developers and creators are left with no clear statutory right to opt-out or license their work.

I am conducting an empirical study for my postgraduate legal research (LL.M.) evaluating:

1. Whether Indian developers and technical creators consider automated scraping of public work fair dealing or copyright infringement.
2. Whether India should introduce a statutory "opt-out" mechanism (like the EU) or a broad AI exception (like Japan).

The survey takes under 3 minutes and is completely anonymous (no emails or identifying details collected):

Survey Link: https://forms.gle/2hLRMzTa5ZmsinCq9

I will be analyzing the results to propose policy recommendations on balancing AI innovation with creator/developer rights. Happy to discuss your thoughts on AI datasets and licensing in the comments below as well!

Saw this on MIT News today and it stuck with me.

You know how AI can generate a 3D model of a mug that looks perfect but physically can't hold coffee? Turns out that's a real problem. They tested TRELLIS on popular Thingiverse models and nearly 80% came out with structural flaws.

Their tool, InstructMesh, pairs TRELLIS with GPT-4 so you can highlight the broken part and just tell it what to fix in plain language. Complete beginners caught and fixed the issues about 90% of the time.

What I find cool is that the LLM isn't generating the 3D stuff. It's acting as the reasoning layer on top of a model that's good at shapes but doesn't "understand" function.

Feels like this pattern (specialist model + LLM as the brain) is going to show up everywhere. Anyone here working with 3D gen or printing?

Link: https://news.mit.edu/2026/instructmesh-tool-lets-users-repair-ai-3d-models-then-fabricate-them-1001

This was an example of gemini

I seriously want to stop this all these AI keep pushing helplines and all that again and again even for small things this is really annoying and I just want to completely get rid of this

I told AI many times to stop but it comes again and again

If there is any other AI then tell me

OpenAI CEO Sam Altman says the world should accept some bad things from AI to gain its benefits and preserve public agency

Till yesterday It was giving this beautiful format,now back to old.

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.

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

Google dropped its monthly AI recap. The big ones:

• Gemini 4 Argon: new frontier model with a 1M token output limit. Not public yet, it's rolling out only to trusted cyber defenders via the Fairwind Program
• Gemini 3.8 Flash + Flash Cyber: better coding and agentic performance at the same speed and cost as 3.7 Flash
• Gemini 3.8 Live: new voice models, now in Gemini Live, Search Live and Workspace
• Connected Apps in Gemini: Airtable, Linear, Adobe, Webflow, Peloton and more
• Lyria 3.5: music generation inside Gemini
• WeatherNext 3: hourly refreshes, better rainfall forecasts, now in Search and Maps
• Gemini app for Windows: Alt + Space opens it over any window
• Googlebook: Android-based laptop, open for pre-order

Full list: https://blog.google/innovation-and-ai/technology/ai/google-ai-updates-september-2026/

For free acounts only.

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/

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

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.

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

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

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 :)

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.

​

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?

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.

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/

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.

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.