Auto Added by WPeMatico
Prime Intellect has released prime-rl version 0.6.0. The framework targets reinforcement learning on trillion-parameter Mixture-of-Experts (MoE) models. It focuses on heavy agentic workloads, like long-horizon software-engineering tasks. The research team trained GLM-5 on SWE tasks at up to 131k sequence length. Step times stayed under five minutes. The batch size was 256 rollouts. The run […]
Today, Sakana AI launched Sakana Fugu. It is a multi-agent orchestration system that behaves like one model. You send a request to a single endpoint. Fugu decides how to handle it internally. It solves a task directly when that is enough. It also assembles and coordinates a team of expert models when needed. The complexity
MoonMath AI team has released a bf16 forward attention kernel for AMD’s MI300X GPU. It is written in HIP, not hand-written assembly. The code is open-source under the MIT license. The MoonMath.ai team reports it beats AITER v3, AMD’s own optimized kernel, on every tested shape. Bare-metal access came from HotAisle, an AMD cloud provider.
Getting prompts right is still the hardest part of shipping reliable LLM applications. Small wording changes can swing accuracy by 20 percent. What works on a few examples often breaks at scale. When a multi-step pipeline returns a wrong answer, finding the failing step means inspecting intermediate outputs by hand. Cisco AI introduced FAPO to
Nous Research has added a Blank Slate setup mode to its open-source Hermes Agent. It inverts the usual onboarding. Instead of a fully loaded default, you start with almost nothing. Hermes Agent is the self-improving agent framework from Nous Research. It runs on your own machine. The team announced the new mode on X. Blank
TLDR YaFF is Yandex’s open-source zero-copy wire format for Protobuf — Apache 2.0, currently C++, v0.1.0. The .proto file stays the source of truth; only the physical memory layout changes. On Yandex’s benchmarks, the Flat Layout reads hot data ~3.8× faster than FlatBuffers, within 1.2× of a raw C++ struct. Four layouts — Fixed, Flat,
NVIDIA Research has released SpatialClaw, a training-free framework for spatial reasoning. It targets a persistent weakness in vision-language models (VLMs). These models still struggle to judge where objects are, how they relate, and how they move in 3D. SpatialClaw does not retrain the model. Instead, it changes the action interface the agent uses to call
While recent breakthroughs in AI reasoning have largely been driven by massive scale, pouring in billions of parameters to cross complex cognitive thresholds—VibeThinker-3B is charting a completely different path. Created by researchers from Sina Weibo Inc (China), this 3-billion-parameter model proves that efficiency can punch far above its weight class. Released under an open-source MIT
This week, Liquid AI released two new retrieval models. They are LFM2.5-ColBERT-350M and LFM2.5-Embedding-350M. Both hold 350M parameters. Both are the first bidirectional members of the LFM family. They build on LFM2.5-350M-Base, released in March. The pair targets fast multilingual and cross-lingual search across 11 languages. Their footprint is small enough to run almost anywhere.
Most AI memory remembers the user. It stores your preferences, your tastes, and your role. Perplexity is taking a different path. Today, Perplexity launched Brain, a self-improving memory system for its agent product, Computer. Brain does not focus on remembering you. It remembers what the agent did. That reframes what memory in AI is for.
