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The Hacker News

Google Launches Gemini 3.5 Flash Cyber AI to Find and Fix Software Vulnerabilities

Google's DeepMind on Tuesday announced the release of Gemini 3.5 Flash Cyber, a specialized artificial intelligence (AI) model built atop 3.5 Flash that's designed to discover, validate, and patch vulnerabilities quickly and efficiently. According to the tech giant, the model will be exclusively available to governments and trusted partners via CodeMender as part of a limited-access pilot

The Hacker NewsRead original
ExternalSoftware Engineering
GitHub Changelog

Gemini 3.6 Flash is now available in GitHub Copilot

Gemini 3.6 Flash, Google’s latest Flash model, is now rolling out in GitHub Copilot. It is designed for web and app development, coding, and longer-horizon agentic tasks. It has configurable… The post Gemini 3.6 Flash is now available in GitHub Copilot appeared first on The GitHub Blog.

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ExternalAI
NVIDIA Technical Blog

Inside NVIDIA Rubin GPU Architecture: Powering the Era of Agentic AI

What began as discrete AI model training and human-facing chat interfaces has evolved into always-on AI factories dedicated to producing intelligence at scale.... What began as discrete AI model training and human-facing chat interfaces has evolved into always-on AI factories dedicated to producing intelligence at scale. These factories are now tasked with powering agentic workflows that reason, plan, use tools, verify intermediate results, and execute complex multistep tasks across vast context

NVIDIA Technical BlogRead original
ExternalAI
NVIDIA Technical Blog

NVIDIA Vera CPU: Olympus Cores Built for Maximum Single-Thread Performance in Agentic AI

Agentic AI shifts more of the critical execution path onto the CPU. Agents operate in sandboxes to execute code, invoke tools, retrieve context, interact with... Agentic AI shifts more of the critical execution path onto the CPU. Agents operate in sandboxes to execute code, invoke tools, retrieve context, interact with databases, and analyze results before returning information to the model. As these loops run concurrently across an AI factory, CPU performance increasingly shapes both per-agent

NVIDIA Technical BlogRead original
ExternalAI
NVIDIA Technical Blog

Setting a World Record for MoE Pre-Training on NVIDIA GB300 NVL72

Frontier model pre-training has converged on mixture of experts (MoE), which is fundamentally changing what limits large-scale AI training. As compute per token... Frontier model pre-training has converged on mixture of experts (MoE), which is fundamentally changing what limits large-scale AI training. As compute per token falls, communication increasingly determines how efficiently models scale across thousands of GPUs. NVIDIA GB300 NVL72 set a world record for pre-training DeepSeek-V3 671B at

NVIDIA Technical BlogRead original

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