Gradient (@Gradient

Gradient

496 posts

Gradient

@Gradient_HQ

Open infrastructure for open intelligence. Lattica · Parallax · Echo

Joined May 2024

Affiliates Replies Media

Pinned
Gradient
@Gradient_HQ
Jun 29
A self-evolving agent + a 428B model + 3 Macs = ? Your own AI lab. We ran @MiniMax_AI M3 locally with @tryParallax, right on our desk. Then @GA_agent_ai took over to create a 5-stock portfolio and write it to disk. No cloud. No API bills. Nothing left the machine. Wild to
00:00
Gradient reposted
Bill
@Bill58861938368
Jul 6
The Bitter Lesson of Asynchronous RLHF: Why Staleness Matters and How to Control It
The Bitter Lesson of Asynchronous RLHF: Why Staleness Matters and How to Control It
From linkedin.com
Gradient
@Gradient_HQ
Jun 29
This is why we built Parallax @tryParallax As open models get stronger and agents get more capable, local-first AI becomes much more than a privacy story. It becomes a new way to build with open intelligence that stays close to your data, your tools, and your machines.
MiniMax (official)
@MiniMax_AI
Jun 29
This is a glimpse of where local AI is heading and we are glad to be part of it. Really impressive work by all the teams involved @Gradient_HQ, @tryParallax, and @GA_agent_ai
Gradient reposted
MiniMax (official)
@MiniMax_AI
Jun 29
This is a glimpse of where local AI is heading and we are glad to be part of it. Really impressive work by all the teams involved @Gradient_HQ, @tryParallax, and @GA_agent_ai
Gradient
@Gradient_HQ
Jun 29
A self-evolving agent + a 428B model + 3 Macs = ? Your own AI lab. We ran @MiniMax_AI M3 locally with @tryParallax, right on our desk. Then @GA_agent_ai took over to create a 5-stock portfolio and write it to disk. No cloud. No API bills. Nothing left the machine. Wild to
00:00
Gradient reposted
Parallax
@tryParallax
Jun 1
nvidia going all in on local ai. here's our take: it shouldn't depend on which chip you bought. sparks, macs, the 5090 already on your desk, we cluster across all of it and split your favorite model pipeline-parallel so it runs fully private and local.
NVIDIA
@nvidia
Jun 1
NVIDIA RTX Spark: a 1-petaflop superchip, the full CUDA and RTX ecosystem, and Windows-native agents. A new beginning for personal computers.
Gradient
@Gradient_HQ
May 1
CHOI
@arrakis_ai
Apr 30
This GPT Image 2 prompt is going insanely viral right now. “Redraw the attached image in the most clumsy, scribbly, and utterly pathetic way possible. Use a white background, and make it look like it was drawn in MS Paint with a mouse. It should be vaguely similar but also not
Made with AI
Gradient reposted
Eric
@0xEricYang
Apr 29
We're hiring at Gradient. Building open-source environment infrastructure for our distributed RL training stack — reproducible, scalable to thousand-GPU runs Looking for 1–2 RL Environments engineers / tech leads: You've designed verifiers, built sandboxes for agentic RL
Gradient reposted
Yuan ./
@yuangao
Apr 22
Thrilled to see @tryParallax live in production on @Theta_Network. This is exactly why @Gradient_HQ built Parallax: turning the world’s GPU mesh into a sovereign, distributed token factory. Congrats on the milestone! 🫡
Theta Network
@Theta_Network
Apr 20
Replying to @Theta_Network
To make this work, we adapted Parallax, @Gradient_HQ's distributed inference framework, to run across EdgeCloud's global node network. One API endpoint, model split across many machines, no centralized cluster required.
Gradient reposted
Parallax
@tryParallax
Apr 22
glad we could help! with the agentic adoption soaring, privacy and token cost are already the top concerns for both agent and human users. that's what parallax's built for.
Theta Network
@Theta_Network
Apr 20
Replying to @Theta_Network
To make this work, we adapted Parallax, @Gradient_HQ's distributed inference framework, to run across EdgeCloud's global node network. One API endpoint, model split across many machines, no centralized cluster required.
Gradient
@Gradient_HQ
Apr 15
Catch @alex_mirran on DevNTell this Friday. He’ll break down the infrastructure we're building at Gradient and show you exactly how to get started today. RSVP below👇
Developer DAO (🧱, 🚀)
@developer_dao
Apr 13
Ready to learn about the Open Intelligence Stack? 🎙️ This week on DevNTell, we'll be joined by @alex_mirran who is Head of BD at @Gradient_HQ, who'll be giving us an overview of the platform and more! 📅 April 17th 📋 RSVP today luma.com/tdmfpby7
Gradient
@Gradient_HQ
Apr 8
Our cofounder @0xEricYang sat down with @yacinelearning to walk through Echo-2’s distributed RL architecture. Dive in to learn about async RL with distributed infra, and how we are scaling this for businesses to win in the agentic era.
Yacine Mahdid
@yacinelearning
Apr 7
for those interested in distributed reinforcement learning I just finished a ~1h tutorial on the echo2 framework by @Gradient_HQ we check: - how to do async RL - infra split between rollout workers and centralized learner - interview with gradient cofounder eric yang himself!
Gradient
@Gradient_HQ
Apr 8
Full tutorial (~1h) youtu.be/eJL8RoubSKU
Gradient
@Gradient_HQ
Apr 8
When you scale parallel agents, prompt updates degrade fast. The more trajectories you process concurrently, the more generic your learned prompts become. Our researchers worked with @lihanc02 and team on Combee to rethink how aggregation works at scale. Results held up across
Hanchen Li
@lihanc02
Apr 7
Prompt Learning does not scale for parallel agents. More parallel agents 🤖 = worse prompts 😭 Why? Processing too many trajectories concurrently damages the prompt update process 🐝 We fix this with Combee : → preserves high-quality learnt system prompt → scales to more
Gradient reposted
Commonstack
@commonstack_ai
Apr 4
If software no longer needs you to operate it, what does an “application” even mean? That’s what we’re digging into at The Agentic Shift with panels, demos, and speakers from Google, PixVerse, MiniMax + more. SF | Apr 8 Sign up here:
The Agentic Shift · Luma
From luma.com
Gradient
@Gradient_HQ
Mar 31
As fellow training nerds, UniPat AI’s approach caught our eyes. Synthesizing future-event data to fix outcome bias and actually beat human prediction markets is defined something worth checking out!
UniPat AI
@UniPat_AI
Mar 30
Today we’re introducing Echo — our full-stack prediction intelligence system, which turns uncertainty🔮 into profit📈. We Make Prediction General, Evaluable, Trainable and Profitable. 🌐Website: echo.unipat.ai