AI Architect & Builder - Inference, LLMs, SLMs GSoC Org Admin - Jenkins | Docker Captain | CNCF Ambassador
New Delhi
Joined December 2018
- Tweets7.2K
- Following1.3K
- Followers8.4K
- Likes37.7K
Shivay Lamba retweeted
New research: We developed JOLT, a post-training method where one model acts as both teacher and student, with the teacher trained to give feedback the student can use.
On MATH, it matched GRPO's accuracy with 6.5x fewer training tokens.
perplexity.ai/hub/blog/a-goo…
Shivay Lamba retweeted
Today we release mammoth-1 and elephant-1!
We post-trained mammoth-1, the #1 ranked best decision model in the world, and elephant-1, which is the best model under 15B (and beats Jev).
We're open-sourcing all model weights and provide a technical report detailing all our training and data methods.
Shivay Lamba retweeted
We teamed up with @huggingface to give away $20,000 to anyone who's building with Beam 🤗
Use Beam for any project - make a demo or a dataset, benchmark the model, create an RL environment - and comment your link in the model's repo page by Monday, November 2.
We choose the winners. Winners choose cash or credits. Claim $25 in Hugging Face credits to build with Beam and enter the competition 👇
huggingface.co/reflection/Be…
Shivay Lamba retweeted
Inspired by @BhosalePratim's Macbrow, I built Winbrow: a Windows voice assistant.
@GradiumAI speech + @typesafeai Jev routing + browser automation adapted from @browser_use’s Jev Ultrafast project.
@Alibaba_Qwen 4B LLM handles replies. Phonon (TTS) speaks them both running locally on @Qualcomm_Dev X Elite’s NPU.
Built for Phonon’s OSS launch!
I've always wanted a way to talk to my Mac and do things on the go.
Until now, it was super slow.
So I built Macbrow.
Voice-controlled browser and computer-use agent.
Built using @GradiumAI @browser_use and @typesafeai
Still early and a work in progress.
github.com/timpratim/macbrow
Shivay Lamba retweeted
Model customization recipes are live on our website and in the cookbook repo.
Beam is now supported across RL and SFT stacks including @axolotl_ai, NeMo RL, NeMo AutoModel, Megatron Bridge (@NVIDIAAI), Miles (@radixark), SkyRL (@NovaSkyAI), and TRL (@huggingface).
Get cooking 🧑🍳
developers.reflection.ai/cus…
Shivay Lamba retweeted
I got to build with @GradiumAI Phonon on launch day!
A smart mirror that sees your outfit and gives spoken style recommendations - all running locally on @arduino Ventuno Q.
@Alibaba_Qwen VLM to understand what you’re wearing
Phonon TTS to talk through suggestions
Both accelerated by the @Qualcomm_Dev Hexagon NPU
A new frontier for on-device speech.
We're open-sourcing Phonon, a suite of TTS models under 50m parameters, setting a new standard for naturalness and accuracy across languages, with the broadest inference support to date.
Phonon-31m is available under Apache 2.0.
gradium.ai/phonon🧵
Shivay Lamba retweeted
Our latest model advances bring stronger capabilities for building and migrating software in low-resource programming languages such as COBOL, Fortran, and Visual Basic.
These languages power software that banks, governments, and businesses depend on. Progress here means understanding decades of business logic and helping developers modernize those systems while preserving what works.
We’re building these capabilities around the challenges developers and enterprise customers bring us. If your team is working on these systems, tell us which languages and workflows we should tackle next.
openai.com/index/low-resourc…
Shivay Lamba retweeted
How to cut coding-agent costs by ~78.5% using Jev to route between open models
All 32 selected coding tasks passed hidden tests.
Plus: Beam vs Muse Spark across 20 coding tasks - comparing cost, speed, and results 👇
Shivay Lamba retweeted
So cool to see @MLHacks giving out some @arduino UnoQs as part of prizes for their AI hackathon at @AllThingsOpen 🙌 – at Garner, NC
Shivay Lamba retweeted
Glad to be back at @AllThingsOpen after 2022! I am going to present a talk on how to improve security for running agents with @Docker Sandboxes - whether it is a coding agent or a multi agent system
Shivay Lamba retweeted
Continuous sensing creates memory bottlenecks on edge devices. Qualcomm & @ramin_m_h, Co-founder and CEO of @LiquidAI are advancing on-device AI with Liquid Context on @Snapdragon — compressing multimodal inputs for fast, low-power execution.
Shivay Lamba retweeted
Don’t forget about #PyTorchCon next week! We’ll be at booth D6 and hosting these events:
🔷 Keynote: MAX and Mojo: The Best Way to Extend @PyTorch — 10/20 @ 9:35 AM PT bit.ly/4yn0R0J
🔷 Demo: Scaling AI Across Devices: ExecuTorch — 10/20 @ 1 PM PT
bit.ly/4yjrAeG
Shivay Lamba retweeted
Muse Spark Open is on Nebius Token Factory from Day 0
It is the most capable US open-weight model to date.
Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning.
Try it: tokenfactory.nebius.com/play…
Shivay Lamba retweeted
Today we’re releasing Muse Spark Open, the most capable US open-weight model to date.
Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning.
Key Model Specs:
→ 816B total / 42B active parameters
→ 1M token context window
→ Natively multimodal across text, image, video, audio
Shivay Lamba retweeted
Gemini 4 Argon is now globally available.
Built to solve your hardest problems from start to finish, the model brings frontier capabilities across coding, enterprise workflows, and cyber defense.
Shivay Lamba retweeted
Today we are rolling out Gemini 4 Argon globally in the Gemini API, to Pro + Ultra in Gemini App, and Ultra subs in Antigravity!
Argon is a huge step forward for Gemini, and a labor of love. This model has been battle tested by over 100,000 people at Google over the last month, with so much new innovation, ambition, and hard work baked into this release. The team has been heads down over the last 6 months working to make this possible across the stack (research, infra, safety, eng, etc).
We rolled the model out to cyber defenders as part of our fairwind program and early access customers over the last 2 weeks, it has been amazing to see and talk to folks who are now using this model daily. Seeing the models writing capability, raw knowledge and persistence for coding, paired with new features like 1M token output when the model needs to work more has gotten me even more excited about our path ahead.
This is just the start of the Gemini 4 era. As you saw with 3.5, 3.6, 3.7, and 3.8 Flash, our iteration speed with Gemini is fast : ) Now with Gemini 4 Argon to work from, I am cannot wait to see the progress continue, and most importantly see what this new model enables for the world.
This is such a special moment in the arc of technology, as millions of people everyday tackle problems they could never have thought possible before. Gemini 4 Argon was built to help you tackle the hardest problems. I have personally felt this spark with Argon and hope you do too. Onwards!!