Models 🇺🇸

Google DeepMind Unveils Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

Google DeepMind announced three new AI models: Gemini 3.6 Flash, 3.5 Flash-Lite, and a specialized 3.5 Flash Cyber. These models aim to boost efficiency, reduce latency, and improve performance in agentic workflows. Gemini 3.6 Flash uses 17% fewer output tokens and is cheaper than its predecessor. 3.5 Flash-Lite is the fastest model in the 3.5 series, while 3.5 Flash Cyber is designed for cybersecurity.

Google/DeepMindGoogle/DeepMind Google DeepMindGoogle DeepMind
Google DeepMind24.07 · 06:03
Regulation 🇨🇳

Jointly Shaping the Future of Global AI — China's Initiative Gives Powerful Impetus to Artificial Intelligence Development

In a special report by Xinhua, it is highlighted that China has put forward an initiative aimed at jointly shaping the future of global artificial intelligence. This initiative is designed to give a powerful impetus to the development of AI worldwide, promoting international cooperation and coordination in this field.

GNews ZH — 人工智能24.07 · 06:02
Models 🇺🇸

Self-Distilled Reasoning for Fine-Tuning Amazon Nova

Amazon has introduced the Self-Distilled Reasoning (SDR) method for supervised fine-tuning (SFT) of Amazon Nova 2 models. SDR generates chain-of-thought (CoT) reasoning paths for datasets lacking them, using the model itself. This addresses the problem of reasoning suppression and reduces catastrophic forgetting, improving target performance while retaining general capabilities.

Amazon Web ServicesAmazon Web Services
AWS ML blog24.07 · 05:06

Former Intel CEO Pat Gelsinger wants to revive Moore's law using light

After leaving Intel, Pat Gelsinger became a partner at venture firm Playground Capital, which invests in deep technology. He is betting on startups in the field of lithography to overcome the physical limitations of semiconductors and revive Moore's law. Gelsinger believes that the key to progress lies in improving light sources for lithography and supports the company xLight.

ASMLASML NVIDIANVIDIA GroqGroq Cerebras SystemsCerebras Systems
Wired AI24.07 · 05:05
Research 🇺🇸

Simulation for Physical AI: A Review

Gathering data for physical AI in the real world is a slow, expensive, and risky process. Simulation enables generating large volumes of photorealistic physical data through GPU parallelism. This article reviews popular simulation engines: MuJoCo, MuJoCo Warp, NVIDIA Isaac Sim and Isaac Lab, as well as the new physics engine Newton, developed by NVIDIA, Google DeepMind, and Disney Research.

NVIDIANVIDIA Google DeepMindGoogle DeepMind MuJoCoMuJoCo
Hugging Face blog24.07 · 05:05

MSI Launches EdgeXpert MS-C931 Based on NVIDIA DGX Spark: Detailed Review of a Compact AI Supercomputer

MSI has introduced the EdgeXpert MS-C931, a compact version of the NVIDIA DGX Spark (Project DIGITS) powered by the Grace Blackwell GB10 SoC, delivering up to 1000 TOPS in FP4. The device features 128 GB LPDDR5x, a 4 TB NVMe SSD, 10GbE, and an optional 200GbE ConnectX-7 for clustering. The review includes performance tests, power consumption, and capabilities for working with large language models.

NVIDIANVIDIA Micro-Star International (MSI)Micro-Star International (MSI) RealtekRealtek MediaTekMediaTek
ServerNews24.07 · 05:05

Wistron Opens First US Factory for NVIDIA Superchips in Fort Worth

Taiwan-based Wistron has launched a 324,000-square-foot factory in Texas to produce NVIDIA GB300 Grace Blackwell Ultra and Vera Rubin superchips. The $700 million investment has created over 500 jobs, with plans to hire 1,000 employees by year-end. The project is part of NVIDIA's commitment to building AI infrastructure in the United States.

NVIDIANVIDIA
NVIDIA blog24.07 · 05:04
Models 🇺🇸

Poolside Releases Laguna S 2.1 — an Open-Weight Model for Agentic Coding That Punches Above Its Weight Class in SWE-Bench Multilingual

Poolside released Laguna S 2.1, an open-weight model with 11.8 billion parameters and 8 billion active per token, designed for agentic coding. Based on a Mixture-of-Experts (MoE) architecture, it supports up to 1 million tokens of context and can run on a single NVIDIA DGX Spark. Laguna S 2.1 ranks first among open models with known size on Terminal-Bench 2.1 (70.2%) and SWE-Bench Multilingual (78.5%), outperforming many larger competitors.

PoolsidePoolside DeepSeekDeepSeek NVIDIANVIDIA TencentTencent Moonshot AIMoonshot AI Alibaba/QwenAlibaba/Qwen AnthropicAnthropic
MarkTechPost24.07 · 05:04
Fresh news