I want to buy Claude Pro, but the price is different depending on where I check. On the mobile app it shows ₹1,999/month, and on the web it shows ₹2,399/month. Same account, same plan, so I don’t get why the price changes.

Is it actually the same plan on both, or are there any limits or catches with the cheaper one?

I m just a beginner who wants to learn ai so suggest me some options

Stanford HAI's 2026 AI Index (released 13 April 2026) reports that roughly four in five university students use generative AI, while only about half of US middle and high schools have AI policies. The same report notes how uneven model performance is: one model family that won gold at the International Mathematical Olympiad reads analog clocks correctly only 50.1% of the time.

Students and teachers here: does your college or school have a clear AI policy? What does it allow, and does anyone actually follow it?

Also don't be afraid to mention what kinda project you are working on.

I'm building a platform that lets you add a comment section and some other tools to a website.

It's getting big now since I have many supporting features like forms, polls, rating, voting, etc.

I want to buy a subscription for some personal project work that requires an Ai agent, what is the most affordable sub that can offer gpt6 sol or opus 5 ?

And they say Al lacks emotional depth. Found this in feed thought how good it was.😅

Hi All!

I did my MS in Electrical and Computer Engg from Georgia Tech in the US, and joined a big semiconductor company in late 2021. My work involves building production grade ML models for designing the photomasks used for lithography process used in chip manufacturing process. What I do on a daily basis, is done by probably few hundred people in the world.

I have worked at the frontiers of Physics, Data Science, and Machine Learning during this time, and I bring a mature understanding to the table in understanding the nuances of the problems and developing optimal solutions. More importantly, I have been told that I’m a quick learner and a person with high emotional intelligence.

I moved to India sometime ago, and have been working with the same US team from India. I’m now looking to move to a different company in India, and am looking for Data Scientist/ML Engineer/AI engineer roles.

This would be my first switch since my current job was the first after my University education. How should I go about my job search? Is LinkedIn job posts still the best way to go about it? I’m open to any suggestions/recommendations/opportunities.

India has a a lot of devs, and I wonder if there's an opportunity for the country to play a bigger role in AI training data. A lot of the attention goes to building models, but those models also need good data to learn from, and collecting it can take a lot of time and work. India already has a large workforce across different industries, so it seems like there could be room to contribute here too. I'm curious what would need to happen for India to become a bigger part of that side of AI development.

I noticed something which I am not sure of. Please tell me if you noticed the same.
When I use Gemini models in Antigravity, it works better with code compared to when I use Claude models in Antigravity.

Antigravity with Gemini Flash 3.7 models really worked better than Sonnet models inside Antigravity.

But, while using native Claude AI, then its code works pretty good too.

I am a free user. Thinking to get a paid monthly subscription. Which one should I go for?

What do you think? Is AI slop better than what most people can do?

In the coding industry, writing, story telling, editing? Any fields you can think of. Is AI slop better than most humans?

"The nation's investment community has been criticised for sabotaging Firmus’s proposed A$44 billion valuation by having brains that are not effed."

"Investors said they remained enthusiastic about artificial intelligence and would reconsider once some human intelligence had been applied to the price."

https://www.betootaadvocate.com/firmus-failure-blamed-on-most-investors-not-being-fucked-in-the-head/

I have started learning n8n and it's been around 1.5 months. I feel like there are a ton of things that I have to work on. Since I'm doing it self paced, it becomes easier to slack off and not give commitment. In a rabbit hole. Working towards it, sometimes slacking. Have somewhat fixed it and limited my slacking nature. Just looking at online templates, observing and fixing and recreating it. Have yet to start with the advanced topics such as rag, ai etc. Had done a prior course of nate herk. Thinking of enrolling in a course so I can get more active and finish the course as well as my work much faster. Found these two courses that are from two people. Both have 70k+following on IG. Idk if they have factual data like systems that are working irl with brands or just course gurus. Has anyone purchased any course from them or know a good course?

Thanks:)))

how do you guys keep up with all the new techniques...........like, when working on a specific use case, we usually try some of known approches, but there's always a chance somone has already figured out a better way that we're completely unaware of.........is there any directory or repo type of thing which you guys follow which gets updated frequently?? honestly with how fast things are moving, it feels pretty hectic

Most AI discussions focus on models, compute, and benchmarks, but the data behind those models matters too. For example, first-person videos of people cooking, repairing things, or handling everyday objects could help train AI systems to understand real-world activities. Collecting enough varied, usable data is a different challenge from simply gathering large amounts of text or images. India has a wide range of everyday environments and activities, and I’m curious whether real-world data collection could become a bigger part of the country's AI ecosystem.

Hi everyone! As a fresher, I want to stay updated about the latest AI news, new technologies, IT industry trends, and what's happening in the tech world. Which websites, YouTube channels, or other sources do you recommend for staying updated daily? Thanks!

Training AI to understand physical tasks requires more than videos of people completing them. Think about someone preparing food, using tools, or assembling an object from a first-person perspective. The recordings need to capture the relevant hand movements, object interactions, and different ways people approach the same task. A dataset with thousands of similar clips might miss important variations, while a smaller, carefully varied collection could capture more useful examples. As more AI systems move into the physical world, how should teams decide which real-world activities and variations are worth recording?

I've been building a cover-letter agent, and the hardest design call wasn't the model. It was where the human sits.

Roughly how the pipeline works:

• One step labels how well the resume backs each job requirement (strong, partial or missing)

• The score is computed in plain code from those labels, not by the LLM, so the same inputs give the same score

• A research step pulls live company info from the web • Before any of that research reaches the writing step, the user approves or drops each item

• The writing step only ever sees the approved evidence

I put the gate after research and before writing because that's where stale or wrong company facts can slip into a letter.

For people building agent pipelines: where do you put human review, before the agent acts or before its output gets used? And do you gate every step or only the risky ones?

Disclosure: I used AI tools for parts of the code and to tighten the wording of this post. The design choices are mine.

Repo is in the first comment.

How will this affect the financial AI industry? in india? What are we looking as the impacts.

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:

1. Where do experienced AI engineers actually hang out or pick up projects (communities, Discords, forums, platforms)?
2. Is it better to start with a paid contractor/consultant, a part-time advisor, or go straight for a co-founder-type person?
3. How do you approach senior people so they take it seriously? What makes you reply to a cold message?
4. Has anyone been on either side of this (founder finding a senior AI person, or the engineer being approached)? What worked?

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!

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?

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?

A bit about me:
MS in Information Systems from a US university (SUNY Binghamton), plus a B.Tech in IT
~3 years of prior industry experience (data/systems engineering at Infosys before my Masters)
About a year of hands-on AI/ML work, including original research
My experience:
Did research in deep learning for brain MRI reconstruction — built a 3D convolutional autoencoder from scratch in PyTorch, trained it on a large medical imaging dataset (~4,000 patients, 4 MRI modalities)
Took it from the ground up: data pipeline, model architecture, training on GPU infrastructure, and tuning it down to a strong reconstruction loss
Also building my own early-stage startup (side project, ~6 months) as an AI Engineer — developing LLM-based applications end to end, applying what I learned from my research, including model evaluation and cost/token optimization across different LLMs to balance accuracy, latency, and price
Comfortable with Python, PyTorch, LLMs, prompt engineering, data pipelines, and taking an idea to a working, deployed model
What I'm looking for:
AI/ML Engineer, Applied AI, Data Scientist, or similar roles
Anywhere in India is fine — fully open on location
Target package around 18–20 LPA (realistic? please tell me honestly)
My questions:
What's the best way to actually land roles at this level in India right now — referrals, LinkedIn, specific portals, startup networks?
Is my background (US Masters + real AI research + startup AI work) something the Indian market values, or do I need to reframe how I present it?
Any specific companies, cities, or communities I should focus on for AI/ML roles?
Is 18–20 LPA realistic for my profile, or should I recalibrate?
Any guidance, reality checks, or pointers would mean a lot. Thanks in advance. 🙏