TL;DR: A new research from Apple, formalizes what “mid-training” should do before reinforcement learning RL post-training and introduces RA3 (Reasoning as Action Abstractions)—an EM-style procedure that learns temporally consistent latent actions from expert traces, then […]
The same connectivity that made Anthropic's Model Context Protocol (MCP) the fastest-adopted AI integration standard in 2025 has created enterprise cybersecurity's most dangerous blind spot. Recent research from Pynt quantifies the growing threat in clear, […]
A new paper from a Samsung AI researcher explains how a small network can beat massive Large Language Models (LLMs) in complex reasoning. In the race for AI supremacy, the industry mantra has often been […]
What if an AI agent could localize a root cause, prove a candidate fix via automated analysis and testing, and proactively rewrite related code to eliminate the entire vulnerability class—then open an upstream patch for […]
For many enterprises, there continue to be barriers to fully adopting and benefiting from agentic AI. IBM is betting the blocker isn't building AI agents but governing them in production. At its TechXchange 2025 conference […]
Google DeepMind has deployed a new AI agent designed to autonomously find and fix critical security vulnerabilities in software code. The system, aptly-named CodeMender, has already contributed 72 security fixes to established open-source projects in […]
Why treat LLM inference as batched kernels to DRAM when a dataflow compiler can pipe tiles through on-chip FIFOs and stream converters?StreamTensor is a compiler that lowers PyTorch LLM graphs (GPT-2, Llama, Qwen, Gemma) into […]
In the race to automate everything – from customer service to code – AI is being heralded as a silver bullet. The narrative is seductive: AI tools that can write entire applications, streamline engineering teams […]
Optimizing only for Automatic Speech Recognition (ASR) and Word Error Rate (WER) is insufficient for modern, interactive voice agents. Robust evaluation must measure end-to-end task success, barge-in behavior and latency, and hallucination-under-noise—alongside ASR, safety, and […]
A cycle-accurate alternative to speculation — unifying scalar, vector and matrix compute For more than half a century, computing has relied on the Von Neumann or Harvard model. Nearly every modern chip — CPUs, GPUs […]
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