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CategoryAll AI safety & security 16 AI industry 12 Malware 11 Phishing & fraud 11 Industry 11 Tools 7 AI tools & infra 6 Advisory 5 Exploit / PoC 5 Threat actor 5 Research 4 Model release 4 Data breach 4 AI research 3

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Introducing agentic video understanding with Gemini

Google DeepMind launches agentic video understanding for Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite, cutting video-analysis tokens up to 88%.

Google DeepMind launched agentic video understanding across Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite via the Gemini API in Google AI Studio and the Gemini Enterprise Agent Platform. The feature replaces static fixed-FPS ingestion with an agentic loop that dynamically searches frames, audio, and transcripts, cutting token consumption by up to 88%, reducing costs by up to 66%, and improving accuracy by up to 7%. Gemini 3.7 Flash with the feature sits at the accuracy-to-cost Pareto frontier on tested video benchmarks, and the capability will later power YouTube's Ask YouTube feature.

Google DeepMindSep 1, 17:08 UTC · 15d agoAI tools & infra

Ask HN: How do you manage skills files?

A Hacker News thread debates whether agent skill files are worth managing, citing 2–4x output-token reductions on flagship models in one company's testing.

Commenters argue skills are stored prompts that help less-technical users compensate for weak prompting, while one participant reports company testing found skills reduce flagship-model output tokens by roughly 2–4x, a gap growing with newer models. Others note skills can bundle reusable scripts and inline commands for deterministic context building, and that harnesses now execute backticked commands before the agent sees the skill. Some argue improving model capability makes downloadable skills redundant.

Hacker News · securitySep 6, 19:27 UTC · 10d agoAI tools & infra HN 303↑ · 271 comments1

NVIDIA Announces CUDA Rust with cuda-oxide (SIMT) and cutile-rs (Tile) for Compile-Time-Safe GPU Kernels

NVIDIA launches CUDA Rust via open-source cuda-oxide (SIMT) and cutile-rs (Tile), bringing compile-time-safe Rust GPU kernels.

NVIDIA announced CUDA Rust, making Rust a first-class language for GPU kernels through two NVlabs open-source projects: cuda-oxide for the SIMT model and cutile-rs for the Tile model. Both use Rust's ownership and borrow checker to catch buffer aliasing bugs at compile time. cutile-rs is published on crates.io, runs on stable Rust 1.89+ with CUDA 13.3, and is already used in Hugging Face's Grout inference engine and mistral.rs; cuda-oxide is early alpha requiring nightly Rust, CUDA 12.x, and compute capability 8.0+. cuda-oxide compiles Rust MIR through the community Pliron IR framework and LLVM to PTX, while cutile-rs JIT-compiles kernels via CUDA Tile IR.

MarkTechPostSep 8, 19:51 UTC · 8d agoAI tools & infra2

Introducing the Agents API

OpenAI launched the Agents API in public beta, exposing the Codex agent harness, managed sandboxes, and multi-agent orchestration to developers.

OpenAI introduced the Agents API in public beta, giving developers the same agent harness and infrastructure that powers Codex through a single API call specifying task, model, tools, and environment. It supports OpenAI-managed sandboxes, customer infrastructure, or partner environments from providers including Cloudflare, Modal, E2B, Vercel, Oracle, DigitalOcean, Blaxel, Daytona and Runloop. Features include automatic context compaction for long sessions, tool search and programmatic tool calling to reduce token usage, and multi-agent support for parallel subagents. The harness is open-source Codex code; there are no extra API fees during beta, with developers paying only for tokens and tools used.

OpenAI NewsSep 10, 00:00 UTC · 7d agoAI tools & infra

NVIDIA Details BioNeMo Inference Runtime (BioIR): 2.90x Higher Boltz-2 Folding Throughput and 58.5K Residues per GPU-Hour on 8xH100

NVIDIA released BioNeMo Inference Runtime (BioIR), an open-source PyTorch-compatible library delivering 2.90x higher Boltz-2 protein-folding throughput on 8xH100 GPUs.

NVIDIA detailed BioIR, a Python library that accelerates Boltz-2, OpenFold2, and OpenFold3 structure-prediction inference on NVIDIA GPUs while preserving standard PyTorch workflows. On a matched benchmark of 1,000 human dimers on 8xH100 80GB GPUs, BioIR delivered 58.5K folded residues per GPU-hour versus 20.2K for a torch.compile baseline, a 2.90x throughput gain. BioIR already powered the AlphaFold Database expansion, generating about 31 million candidate complexes across 4,777 proteomes, with 1.81 million released as high-confidence predictions. Extrapolated to 1 million targets, estimated folding energy drops from 35 MWh to 11 MWh at 8-GPU TDP equivalents.

MarkTechPostSep 10, 21:57 UTC · 6d agoAI tools & infra1

The VMs Powering Mobile Agents (Instinct, Claude Code)

A teardown reveals Claude Code runs in Firecracker microVMs with a Rust PID 1 and MITM'd egress, while Instinct rents E2B sandboxes with git-based memory.

The author inspects the virtual machines hosting cloud agents: Claude Code runs in a Firecracker microVM with a custom Rust init (process_api) as PID 1, a 324 MB Bun harness on a read-only disk, and 443-only MITM'd SSE egress to api.anthropic.com with host-rotated OAuth tokens and no inbound access. Instinct rents E2B sandbox-as-a-service Firecracker microVMs (Ubuntu 22.04, 2 vCPU, 1.9 GB RAM) where agent memory is a git repo of Markdown committed by the agent and pushed to S3 as a single bundle, using short-lived STS credentials. Both platforms rely on Firecracker, differing mainly in fleet operator and guest boot configuration.

Hacker News · AISep 8, 04:36 UTC · 9d agoAI tools & infra HN 58↑ · 19 comments1