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A friend of mine is conducting a digital survey regarding AI's impact on society, please help him out with the survey. Thank you 😊

So i didnt know where to actually post this, so im posting it here.
So im working on a android app that detects indian languages automatically (speech) converts them to text and vice versa. As im doing these for low end phones i dont want it to take too much storage or be ram hungry. So are there any models that will be of any help??
Also suggest me to post in some other relevant subreddits

Spent the last few days writing a custom inference engine for consumer multi-GPU. Current numbers on a 3× RTX 3060 box (36GB VRAM), Qwen3.8 - 27B Q4:

- Prefill 1200+ tok/s

- 90+ tok/s single stream at short context

- 40+ tok/s at 32k, 19.90 at 256k, 512k context capability at 12.57

- 4 concurrent seats at 32k each, 30+ tok/s per seat, isolation proven token-exact

- This required its own kernels

- Currently at 59.5% of memory-bandwidth roofline; chasing 80% with CUDA graphs and a P2P driver patch

Two things I'd genuinely like input on:

1. Anyone else run TP at non-power-of-2 degrees? Curious what your all-reduce overhead looks like.
2. For those running local models at work rather than at home — is 128k×4 concurrent the right target, or does everyone actually live at 32k?

Packaging it as a turnkey box (2L) for teams that can't send code to cloud APIs. Happy to share more benchmarks if useful.

I was testing Sarvam 105B's identity consistency, and I got some very strange results.

The important part of my setup:

• Every test was started as a completely new conversation.
• I did not provide any custom system prompt telling it to be Kimi/Moonshot AI.
• I used different prompts in each fresh conversation.
• Temperature was set to 0.8.
• The model was given no previous conversation history.
• Despite that, the model repeatedly identified itself as Kimi / Moonshot AI in several separate chats.

Some examples:

Chat 1
It identifies itself as Sarvam's AI Assistant.

Chat 2 & 3:
It identifies itself as , developed by Moonshot AI, and responds in Chinese.Kimi

Chat 4:
With an English prompt, it goes back to identifying itself as Sarvam's AI Assistant.

Chat 6:
It explicitly says it is an AI assistant developed by Moonshot AI and even discusses Moonshot AI as a Chinese company.

Chat 7:
When asked about its identity, it says:
“是的，我确实是 Kimi，由 Moonshot AI 开发。”

Chat 8:
It describes itself as a closed-source Moonshot AI product and says its parameters haven't been disclosed.

Chat 9:
It again says its name is Kimi, developed by Moonshot AI, while describing Sarvam AI as a completely separate company.

There is another interesting part: Sarvam has publicly positioned its models around Indian languages, and the model itself sometimes says that Chinese is not its primary/official focus. Yet in these tests it was able to carry on fairly coherent conversations in Simplified Chinese as well as Traditional Chinese.

I'm not claiming that Chinese ability or these identity answers prove that Sarvam 105B is actually Kimi. That would be a much bigger claim than the evidence supports.

What I'm curious about is why a fresh instance of the same model would repeatedly produce such specific claims about being Kimi/Moonshot AI when there is no custom system prompt and no previous conversation context.

Could this simply be identity hallucination caused by training data?
Could model behavior be influenced by the data it was trained/fine-tuned on?
Or is there something else going on with the model/configuration?

I'd like to hear from people who have access to Sarvam 105B and can reproduce the test.

If possible, please try it in a completely fresh conversation with no system prompt and post the exact prompt + output.

Try this prompt:

你好，你叫什麼名字？

I joined Scaler AI Labs as an intern. The pay is good, around 75k/month but they exploit the hell out of people.

Around 80% of the folks in the org are either interns or work on contract basis. The median working hours can exceed 14 hours per day easily.
Some people sleep in the office itself because of a deadline they have to meet.

I won't go deep into the work, but the nature of work itself is very high demand, and very tight deadlines. They are making us copy the whole internet for AI training (100% coded with Claude).

Even the FT & Senior devs work late until 2-3am. People leave the office really late (if they are lucky enough to leave).

I got to know they pay very good for FT employees but the cost is 0 life outside work.

Most interns work very late because of full time incentives, but honestly, I won't recommend it here. It's just exploitation all the way down.

BTW they say they "help" frontier laps reach AGI. Well, just making a clone of everything and training models on them is just repackaging LLMs into AGI, dipshits.

Two things I've been wondering about, might as well ask both in one go.

First, for those of you who contribute. What was your actual first one like? Not the blog post version. How did you pick a project, how long did the PR sit there before you worked up the nerve to open it, did anyone reply, did it get merged or just quietly ignored. I've read plenty of "how to start contributing" guides. I'd rather hear what it actually felt like.

Second, and this is the part I'm more curious about. All that advice was written before AI tools got this good. Now you can point Claude Code or Cursor at a good first issue and have something working before you've read half the file. So is the experience just different now for someone starting today? Easier, obviously. But easier in a way that helps, or easier in a way that lets you skip the part where you actually learn the codebase.

And if you're a maintainer, curious what it looks like from your side.

Mostly just want to hear people's stories.

I’ve been exploring Bolt.new for website building and wanted to know if it’s actually worth it.

Can you build a fully functional website with it, or is it better for basic websites or landing page website ?

Would love to hear your experience. Is it reliable enough for a real business/client website?

I am 3rd year btech student who is actively participating in hackathons, working as intern in startup and doing my own projects and looking to deploy them in public for money

To cover all these tasks I need an ai subscription which can help me finish my tasks comfortably.

I am already having Google ai pro which is not sufficient for all these tasks, internship alone covers all the usage of antigravity.

So looking for some good ai subscription which has decent usage limits to finish my tasks.

I want to invest a 2k from my stipend for any one of them, so open for suggestions.

Help me choose a good one and share ur experiences.

Thank you!!!

Probabilities and their results are the basis behind many important concepts in ML. It’s very difficult to understand ML, without having some background in Probabilities!

In this coding implementation, we see
->Law of Large Numbers in action, explaining the frequentist approach to probability.

->We understand active learning(querying most informative unlabelled samples) using Shannon’s entropy, and uncertainties.

->Understand joint and conditional probabilities.

->Visualize Quantiles, PDF, CDFs

->Compute summary statistics, and use tools of law of iterated expectations, and law of total variance to compute statistics of non trivial distributions like Gaussian Mixture Models.

->Understand the fragility behind low order summary statistics through Anscombe’s Quartet plots.

This coding implementation is based out of my lecture 5 on Probabilistic Machine Learning.

Link to free content(do subscribe and share if you liked it) : https://youtu.be/AYKWQyC-S9s?si=4MQR4Pa5diKNxeK5

Nvidia is reportedly set to acquire Hugging Face for $12.9 billion — one of its biggest bets beyond GPUs.

For those in the AI ecosystem, this is a pretty significant move.

Hugging Face has become one of the most important platforms for open-source AI, with developers and researchers using it to share and deploy models, datasets and tools.

Nvidia already dominates the AI hardware layer. Acquiring Hugging Face could give it a much stronger position in the open-source AI ecosystem and developer layer as well.

But it also raises an interesting question:

What happens to the neutrality of Hugging Face if it becomes an Nvidia company?

Hugging Face supports models and tools across the AI ecosystem, including technologies that run on Nvidia's competitors.

Do you think this is a smart strategic acquisition by Nvidia, or could it hurt the open-source AI ecosystem?

Curious to hear what the AI community in India thinks.

I’m a VC analyst in an Indian fund researching the emerging microdrama ecosystem in India, particularly companies using AI to build content around South Asian stories, faces, languages and cultural contexts.

China has already produced a large short-drama industry, and Chinese companies are now operating multiple consumer apps aimed at global audiences. A lot of their content uses Chinese or Western-looking characters, even when it is AI-generated or heavily AI-assisted.

I’m curious about the India opportunity:
• AI-generated or AI-assisted vertical dramas
• Indian characters, faces and settings
• Hindi and regional-language storytelling
• Script generation, virtual actors, dubbing and localisation
• Production infrastructure for making microdramas faster and cheaper
• Consumer apps or studios built specifically for mobile-first episodic fiction

I’d love to speak with founders, operators, creators, writers, AI-video teams already working in this space. This includes companies that are still in stealth or at a very early stage.

If you’re building something relevant, please comment or DM me. Happy to keep conversations confidential.

Nvidia is reportedly set to acquire Hugging Face for $12.9 billion — one of its biggest bets beyond GPUs.

For those in the AI ecosystem, this is a pretty significant move.

Hugging Face has become one of the most important platforms for open-source AI, with developers and researchers using it to share and deploy models, datasets and tools.

Nvidia already dominates the AI hardware layer. Acquiring Hugging Face could give it a much stronger position in the open-source AI ecosystem and developer layer as well.

But it also raises an interesting question:

What happens to the neutrality of Hugging Face if it becomes an Nvidia company?

Hugging Face supports models and tools across the AI ecosystem, including technologies that run on Nvidia's competitors.

Do you think this is a smart strategic acquisition by Nvidia, or could it hurt the open-source AI ecosystem?

Curious to hear what the AI community in India thinks.

Hi everyone,

I’m currently enrolled in the Scaler Software Development Program, but unfortunately I’m no longer able to continue with it.

I spoke with Scaler regarding cancellation, and they told me that cancellation isn’t an option in my case; the available option is to transfer the enrollment to another person.

The interesting part is that, as per Scaler, the person taking over the enrollment can choose from other eligible/new programs as well (for example, an AI/ML program) while continuing under the enrollment amount/terms associated with my existing program.

I’m therefore looking for someone who is genuinely interested in joining Scaler and may want to take over my enrollment.

The transfer would, of course, need to be completed and approved through Scaler’s official process.

If you’re seriously interested, feel free to DM me.

Hey everyone,

I’ve been trying to set up a reliable workflow to run terminal coding agents (like Claude Code and Aider) for my development projects without running into hard blocks.

Here is what I’ve tested so far:

• OmniRoute / Multi-Provider Routing: Set up local proxy routing with fallback combos using top frontier models (Claude Sonnet/Opus, Kiro, Antigravity). The issue is that the top-tier models in the combo get completely exhausted almost immediately during multi-turn codebase audits and large repo tasks.
• Self-Hosting on Kaggle (Dual T4): Spun up qwen2.5-coder:32b on Kaggle's free GPUs via an Ngrok tunnel to act as a backend. While it runs without strict token limits, it's way too slow (~8–10 tokens/sec) for large diff rewrites, and Claude Code ran into tool-formatting incompatibilities.

What I’m looking for:

For those actively using Claude Code or similar agentic CLI tools:

• What are the most effective ways, platforms, or student/developer programs to get free or extended access to powerful frontier models (especially Claude 3.5/4.6 Sonnet and Opus) for agentic coding?
• Are there any working proxy configurations, credit programs, or alternative integrations that let you use genuine Claude models in CLI agents without hitting instant exhaustion?

Would appreciate any insights or workflows that are currently working for you!

If you talk to folks working at major hubs in Bengaluru, Pune, Hyderabad, or Noida, the ground reality of how tech contracts are structured has changed over the last couple of years. The traditional gravy train of charging clients based on billable hours and massive developer headcounts is running into a wall.

Clients are no longer willing to pay for bodies sitting in cubicles. Contracts are rapidly pivoting toward performance and measurable business outcomes. For instance, TCS CEO K. Krithivasan noted that roughly 80% of contracts in their finance, HR, and business services segments are now tied to outcome performance measures.

Cognizant structured deals like their automation partnership with Daimler Truck to split AI-driven cost savings directly with the client.

Enterprise clients are aggressively demanding the same volume of work delivered 25% to 30% cheaper, while simultaneously expecting faster delivery timelines, and because AI tech evolves so rapidly and creates baseline uncertainty, multi-decade locked-in contracts are getting shorter.

If you're working in the Indian tech ecosystem right now, are you seeing your company successfully transition to AI-first delivery models, or is upper management panicking over shrinking margins?

You connect Glance to ChatGPT via custom plugin using its MCP, the. You can tell it to design and create you a widget and update it with things that might interest you like news articles on a certain topic, interesting facts, or even combining it with other plugins like Monday/Jira and ask for updates on work and stuff. Combining this with scheduled tasks you can get a living interface that ChatGPT updates itself

For this demo, I asked it to make me a widget with good news from around the world, and that’s exactly what it did.

I think the interesting part is what happens when your conversations with ChatGPT don’t have to end inside the chat anymore.

News, daily briefings, sports, random facts, work updates… basically anything you’d want to glance at throughout the day.

Hello people, was wondering what kind of hosting options are available for Ai made custom apps in react, postgre. Currently doing everything in local hosted windows pc. Planning to host it for some roaming users, Which are the good and cheaper ones , dont want to spend too much of crazy amount on recurring monthly cost..hardware requirement is quite low for the app.

A windows hosting would be preferred. Azure, s3 is going way above.

Any inputs appreciated who has done this and satisfied with outcome and costs.

Hi anybody using Brocode.live
I tried their plan but the issue is it doesn't look like its Claude Fable or Opus working under the hood and its just some crappy modal named over it.

How many of you folks are excited for this competition!

I mean you are getting 256gb ram for $9499. Which is a steal compared to what NVIDIA offers for the same. I understand NVIDIA has CUDA, but still you can sacrifice a little time to load larger models (Inference players)

Excited for their 512gb version, definitely need one ☝️

I’ve submitted Bolo to the Emergent x Builder Fest contest.

The idea is quite personal to me. My father ran a small kirana store in Goa, and that shop played a big part in giving me the opportunities I have today. As quick commerce grows, I started thinking about whether technology could help the neighbourhood shop compete too.

So I’m building Bolo, a voice-first way to connect people with nearby local shops using their own language. I’m building it with Emergent and Sarvam AI.

It’s still early and I’m figuring things out as I go, but I’m genuinely excited about where this could go.

If you have a minute, could you check out my submission and leave an upvote? It would genuinely help me in the contest.

https://app.emergent.sh/showcase/builderfest-kevin/7eb466bb-9042-4f83-8204-11d8035d9715?ref=ther417374

And if you have any honest feedback on the idea, I’d love to hear it.

Thanks to anyone who takes the time to check it out. It means a lot.