SarvagyaPorwal

AI Researcher

[SarvagyaPorwal @sarp0424]

@Aniket1836020 Only open to students?

[SarvagyaPorwal @sarp0424]

@sahilgo6801 @LumaLabsAI 😂

[NeurIPS Conference @NeurIPSConf]

📢 NeurIPS 2026 Call for Educational Resources is now open!

The NeurIPS 2026 Education Track invites researchers and educators to create accessible, reusable materials that teach emerging AI concepts to broad audiences.

We welcome submissions in many formats, including code notebooks, short videos, lecture notes, slide decks, interactive demos, visual explanations, and other self-contained learning resources.

Accepted submissions will be presented at the main conference in Sydney as talks or posters, made available through the NeurIPS website, and curated into the official NeurIPS 2026 Education Track repository.

🗓 Submission deadline: September 4, 2026 (AOE)
🔗 Learn more and submit: https://t.co/d6cFTAfZoQ

[Kai Arulkumaran @kaixhin]

PSA: If you're applying for a research position at @SakanaAILabs (intern/full-time), we have a guide on what we look for

Researchers here pursue different directions - and may disagree - but have thought deeply about why

Over-reliance on LLMs to do your thinking isn't good

[SarvagyaPorwal @sarp0424]

@novasarc01 @Dorialexander Yeah, recently i realized all power rests in tokenizer. All compute and quality lies in how tokenizer is designed.

Models can be less data hungry if tokenizers are designed well. I recently created tokenizer for Hindi based on akshara... Blah blah...

More coming...

[SarvagyaPorwal @sarp0424]

@novasarc01 Yeah, everything when abstracted enough shows it's traces in OT...

Btw what pilled mean?

[Ibragim @ibragim_bad]

🔥 Nebius AI R&D is hiring AI Research Interns for short, high-impact RL projects.

Exclusive to X right now — no LinkedIn mass postings yet.

In 2019, I was a fresh dental grad with 3 months of runway left, begging for an AI shot. I know the grind.

We’re looking for sharp early-career folks (students, grads, career-switchers) to join us and work on:
> Agent trajectories analysis at scale
> Long-horizon tasks for coding agents
> Pushing open RL environments
> Any other data / RL env / eval project that will benefit open-source community

What you get:
💰 Fully paid internship (3-6 month)
📦 100% open-source shipping
📄 Co-author research papers
⚡️ Access to Nebius compute infra
🌍 Remote-friendly (EU/US) or Amsterdam/London/other office.

If you’ve done any cool AI/ML/RL stuff, dm me with your most impressive project + 1-sentence summary + cv

Sharing appreciated!🤝

[SarvagyaPorwal @sarp0424]

@adithya_s_k @huggingface Congrats bro

[dylan ツ @demian_ai]

We are aggressively hiring at @nebiusai. If you see a job and you think you are a match, my DMs are open

https://t.co/gMjurEEDHZ

[Joël Niklaus @joelniklaus]

Cool opportunity for students interested in legal AI!

University of Cambridge LLMxLaw has two tracks running:

Hackathon: Build LLM solutions for real legal challenges from law firm sponsors. £20,000 prize pool plus sponsor prizes.
https://t.co/RT29FxCYM8

Research: Pitch your research idea to Stanford fellows and compete for a one-month placement at Stanford University LiftLab this summer.
https://t.co/h0RVwVOLJr

Both are solid ways to get hands-on experience in this space.

[SarvagyaPorwal @sarp0424]

@neural_avb Rate limit is there ig

[Neel Nanda @NeelNanda5]

Announcing the ICML 2026 Mechanistic Interpretability Workshop!

Papers due May 8th

NeurIPS submissions encouraged, accepted ICML 2026 papers also welcome.

If you're working on advancing our understanding of neural networks, please submit! We'd love to see your work

[Phong Nguyen-Ha @PhongStormVN]

🌟 We’re Hiring a PhD Research Intern – Qualcomm AI Research! 🌟
I’m looking for a PhD intern to join me in pushing the boundaries of efficient AI, from 3D/4D data generation to next‑gen generative models and on‑device intelligence.
At Qualcomm AI Research, interns work alongside world‑class researchers, contribute to fundamental ML advances, and often publish at top conferences.

🔬 You’ll work on:
• ⚡ Efficient generative models (quantization, compression, sparsity)
• 🌀 3D/4D perception & generation
• 🧠 Multimodal / LLM / LVM efficiency
• 🤖 Robotics‑related AI algorithms

🎓 You’re a great fit if you:
• Are a current PhD student in ML/AI/CV/Robotics
• Have strong research experience & PyTorch/TensorFlow skills
• Are excited about impactful, publishable AI research

📩 Interested?
Apply via Qualcomm Careers: https://t.co/ngLjMwo8qo
Or message me directly with your CV + publications.
Let’s build the future of efficient AI together! 🚀🤝

[Moummar @MoummarNawafleh]

we're working with an AI lab looking to hire MLE, MLR, SWEs

comp: up to $400k cash + 1.5%-2.5% equity

A+++ team

[jpark @ icml @jparkjmc]

if you're an independent researcher and need

- compute
- tokens
- travel stipends
- any other resources

DM me! hillclimb grant releasing soon😁

[Hadi Vafaii @hadivafaii]

Free energy minimization is interesting, because it unifies various theories in neuroscience with machine learning models 👇

("Control/RL as inference" is also free energy minimization)

Different distributional and optimization choices yield different architectures (fig from: https://t.co/fpdzUipv33)

[3/11] 🧵

[Haocheng Xi @HaochengXiUCB]

𝗞-𝗺𝗲𝗮𝗻𝘀 𝗶𝘀 𝘀𝗶𝗺𝗽𝗹𝗲. 𝗠𝗮𝗸𝗶𝗻𝗴 𝗶𝘁 𝗳𝗮𝘀𝘁 𝗼𝗻 𝗚𝗣𝗨𝘀 𝗶𝘀𝗻’𝘁.

That’s why we built Flash-KMeans — an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks.

By attacking the memory bottlenecks directly, Flash-KMeans achieves 30x speedup over cuML and 200x speedup over FAISS — with the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds.

A classic algorithm — redesigned for modern GPUs.

Paper: https://t.co/z0z0d3vrlp
Code: https://t.co/BqRfVKGH0K

[SarvagyaPorwal @sarp0424]

@Gauri_the_great NGMI means?