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Z.AI Introduces GLM-5.1: An Open-Weight 754B Agentic Model That Achieves SOTA on SWE-Bench Pro and Sustains 8-Hour Autonomous Execution

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Z.AI, the AI platform developed by the team behind the GLM model family, has released GLM-5.1 — its next-generation flagship model developed specifically for agentic engineering. Unlike models optimized for clean, single-turn benchmarks, GLM-5.1 is built for agentic tasks, with significantly stronger coding capabilities than its predecessor, and achieves state-of-the-art performance on SWE-Bench Pro while […]

Z.AI Introduces GLM-5.1: An Open-Weight 754B Agentic Model That Achieves SOTA on SWE-Bench Pro and Sustains 8-Hour Autonomous Execution Read More »

Meta AI Releases EUPE: A Compact Vision Encoder Family Under 100M Parameters That Rivals Specialist Models Across Image Understanding, Dense Prediction, and VLM Tasks

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Running powerful AI on your smartphone isn’t just a hardware problem — it’s a model architecture problem. Most state-of-the-art vision encoders are enormous, and when you trim them down to fit on an edge device, they lose the capabilities that made them useful in the first place. Worse, specialized models tend to excel at one

Meta AI Releases EUPE: A Compact Vision Encoder Family Under 100M Parameters That Rivals Specialist Models Across Image Understanding, Dense Prediction, and VLM Tasks Read More »

Meet MaxToki: The AI That Predicts How Your Cells Age — and What to Do About It

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Most foundation models in biology have a fundamental blind spot: they see cells as frozen snapshots. Give a model a single-cell transcriptome — a readout of which genes are active in a cell at a given moment — and it can tell you a lot about what that cell is doing right now. What it

Meet MaxToki: The AI That Predicts How Your Cells Age — and What to Do About It Read More »

Netflix AI Team Just Open-Sourced VOID: an AI Model That Erases Objects From Videos — Physics and All

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Video editing has always had a dirty secret: removing an object from footage is easy; making the scene look like it was never there is brutally hard. Take out a person holding a guitar, and you’re left with a floating instrument that defies gravity. Hollywood VFX teams spend weeks fixing exactly this kind of problem.

Netflix AI Team Just Open-Sourced VOID: an AI Model That Erases Objects From Videos — Physics and All Read More »

Google DeepMind’s Research Lets an LLM Rewrite Its Own Game Theory Algorithms — And It Outperformed the Experts

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Designing algorithms for Multi-Agent Reinforcement Learning (MARL) in imperfect-information games — scenarios where players act sequentially and cannot see each other’s private information, like poker — has historically relied on manual iteration. Researchers identify weighting schemes, discounting rules, and equilibrium solvers through intuition and trial-and-error. Google DeepMind researchers proposes AlphaEvolve, an LLM-powered evolutionary coding agent

Google DeepMind’s Research Lets an LLM Rewrite Its Own Game Theory Algorithms — And It Outperformed the Experts Read More »

TII Releases Falcon Perception: A 0.6B-Parameter Early-Fusion Transformer for Open-Vocabulary Grounding and Segmentation from Natural Language Prompts

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In the current landscape of computer vision, the standard operating procedure involves a modular ‘Lego-brick’ approach: a pre-trained vision encoder for feature extraction paired with a separate decoder for task prediction. While effective, this architectural separation complicates scaling and bottlenecks the interaction between language and vision. The Technology Innovation Institute (TII) research team is challenging

TII Releases Falcon Perception: A 0.6B-Parameter Early-Fusion Transformer for Open-Vocabulary Grounding and Segmentation from Natural Language Prompts Read More »

Salesforce AI Research Releases VoiceAgentRAG: A Dual-Agent Memory Router that Cuts Voice RAG Retrieval Latency by 316x

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In the world of voice AI, the difference between a helpful assistant and an awkward interaction is measured in milliseconds. While text-based Retrieval-Augmented Generation (RAG) systems can afford a few seconds of ‘thinking’ time, voice agents must respond within a 200ms budget to maintain a natural conversational flow. Standard production vector database queries typically add

Salesforce AI Research Releases VoiceAgentRAG: A Dual-Agent Memory Router that Cuts Voice RAG Retrieval Latency by 316x Read More »

NVIDIA AI Unveils ProRL Agent: A Decoupled Rollout-as-a-Service Infrastructure for Reinforcement Learning of Multi-Turn LLM Agents at Scale

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NVIDIA researchers introduced ProRL AGENT, a scalable infrastructure designed for reinforcement learning (RL) training of multi-turn LLM agents. By adopting a ‘Rollout-as-a-Service’ philosophy, the system decouples agentic rollout orchestration from the training loop. This architectural shift addresses the inherent resource conflicts between I/O-intensive environment interactions and GPU-intensive policy updates that currently bottleneck agent development. The

NVIDIA AI Unveils ProRL Agent: A Decoupled Rollout-as-a-Service Infrastructure for Reinforcement Learning of Multi-Turn LLM Agents at Scale Read More »

Meta Releases TRIBE v2: A Brain Encoding Model That Predicts fMRI Responses Across Video, Audio, and Text Stimuli

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Neuroscience has long been a field of divide and conquer. Researchers typically map specific cognitive functions to isolated brain regions—like motion to area V5 or faces to the fusiform gyrus—using models tailored to narrow experimental paradigms. While this has provided deep insights, the resulting landscape is fragmented, lacking a unified framework to explain how the

Meta Releases TRIBE v2: A Brain Encoding Model That Predicts fMRI Responses Across Video, Audio, and Text Stimuli Read More »

NVIDIA AI Introduces PivotRL: A New AI Framework Achieving High Agentic Accuracy With 4x Fewer Rollout Turns Efficiently

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Post-training Large Language Models (LLMs) for long-horizon agentic tasks—such as software engineering, web browsing, and complex tool use—presents a persistent trade-off between computational efficiency and model generalization. While Supervised Fine-Tuning (SFT) is computationally inexpensive, it frequently suffers from out-of-domain (OOD) performance degradation and struggles to generalize beyond its training distribution. Conversely, end-to-end reinforcement learning (E2E

NVIDIA AI Introduces PivotRL: A New AI Framework Achieving High Agentic Accuracy With 4x Fewer Rollout Turns Efficiently Read More »