mentally exhausted emotionally tired socially drained

recently OpenAI released a report of productivity gains in AI power users. more time saved comes from higher usage. now imagine if you can post train models without heavy capex restrictions. productivity would be even greater when it’s geared towards what you do. 👀

♠️♥️ CROSS COMMUNITY POKER & FRIENDS♦️♣️ We’re going ALL IN. @Gradient_HQ has teamed up with the heavy hitters~ @soon_svm, @0xfairblock, @raikucom, and @SovaBTC~ for the ultimate Cross-Community Poker Tournament! 🃏 🗓 When: Today @ 4PM UTC 🏆 The Pot: Roles and Rewards from

Proud moment for the team 🚀 Our colleague delivered an oral presentation at AAAI, presenting our work on multi-agent collaborative reward design. This work shows how collective intelligence—coordinated specialist agents—can produce more robust, interpretable reasoning than

inference cost continues to decrease across the board. this is beneficial to supporting growth of AI in applications and services. overtime I believe we will see a mixture of heterogeneous machines serve its best suited workloads across different types of inferencing and

Reinforcement learning one of the fastest ways to improve LLMs for productive intelligence. Asynchronous training maximizes utilization of each machine. Async cleanly separates the training tasks and inferencing tasks during RL through an open infra. Train it faster than ever

in RL with transparency as a priority we need to solve “deceptive reasoning”. integrating process reward models where each thought is dissected to authenticate its process of looking at every thought. deceptive reasoning often removes alignment even if the thought looks aligned.

./ Gradient Smash Karts Race hard. Drift harder. Win it. Pull up to Gradient Smash Karts and show what you got on the track. Server links drop right when the event goes live 👀 Date/Time: Tuesday, January 20, 2026 at 11:00 UTC Rewards: Top 3 players in each server get the

./ Echo by @Gradient_HQ tackles a common weakness in reinforcement learning systems: the way training and inference often get tied together on the same GPUs. That setup makes everything depend on the slowest unit, so one failure can stall the whole process.   By splitting

sama said they knew how to build AGI. it seems to stand for ad generation initiative

./ make sure you free up some time tomorrow fam!

productivity intelligence will play a more significant role with RLVR (reinforcement learning with verifiable rewards) as integration of intelligence continues. for models powering agents you can scale these small models to outperform models much larger. task specific and

Reinforcement Learning towards Greater Intelligences 💭 📌 X Spaces 🗓️ January 18th 2AM UTC ./ explore trends, different approaches and RL focus @Gradient_HQ

./ training mode on.. @Gradient_HQ ./ ECHO ECHO ECHO ECHO 🔥🔥

@Gradient_HQ You definitely don't want to miss this, join now! 🚬 https://t.co/F8Vzxm8EmS

⬜️⬜️⬜️ ⬜️ ⬜️ ⬜️ ⬜️⬜️ ⬜️⬜️⬜️ ⬜️⬜️⬜️ ⬜️⬜️⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️⬜️⬜️ ⬜️⬜️⬜️ ⬜️ ⬜️ ⬜️⬜️⬜️ ◻️◻️ ./ training mode on... @Gradient_HQ

fairytale is imaginary. intelligence is forever. ./ asyncing echo rl… @Gradient_HQ

With Echo, we use Async RL to avoid single GPU failure letting down the entire fleet.

⚔️ multiverse clash royale tournament we are happy to invite you to the first community clash royale tournament. hosted w/ magicblock, re protocol, gradient and raiku 🗓️ january 15th 4pm utc. ./ join us for some fun prizes @Gradient_HQ 🎯🧵

everyone is going to have their own AI powered agents, services, applications or workflows. from small organizations to research labs to behemoth enterprises they will all need a place to develop their own. reinforcement learning is one of the best ways to improve models to