Already, big AI seems to have gotten the message. OpenAI just announced a new "blueprint" for its AI data center construction policies, pledging to reduce power usage while also putting limits on NDAs for public officials. I expect we'll see more of the same from other top AI providers, as they navigate the new political reality in Washington.
AI Data Cloud company Snowflake has announced a major expansion of its product suite at Snowflake Expedition 2026, positioning its platform as the foundational control and governance layer for enterprise-ready AI agents.
Asian startups secured more than $570 million in fresh funding, led by major investments in AI video generation, inference chips and brain-computer interfaces.
Nvidia Corp. is stepping up monitoring of AI accelerators sold in Southeast Asia, a strategic step to curtail semiconductor smuggling after criticism it hasn't done enough to stop shipments from illegally reaching Chinese companies.
Laptops that have been designed for new creators comprise AI computing, multi-core processors, OLED touch screens, and mobility to enable generative AI, content creation, 3D rendering, and other creative tasks.
Kimi K3.1 Pro is an open-weight, natively multimodal agentic model, and our most capable 3T-class model to date. Post-trained from Kimi K3 with large-scale joint reinforcement learning across hundreds of downstream domains, it is the first model in the K3.1 series. With a…
Anthropic's IPO is in trouble as investors push back on the $1.5 trillion valuation and the tech market sells off. The article Anthropic's $1.5 trillion IPO hits resistance as investors balk at valuation appeared first on The Decoder .
We propose LoG-VGGT, a memory-efficient framework for long-sequence 3D reconstruction that balances local temporal modeling with global camera consistency. Instead of relying on full global attention, our method introduces cross-window attention at a small subset of transformer…
Post-training plays a pivotal role in enhancing the reasoning capabilities and task-specific expertise of large language models (LLMs). Despite recent advances in post-training methods, such as Group Relative Policy Optimization (GRPO), their practical deployment remains…
Mean-variance portfolio optimization (MVO) is a central framework in data-driven asset management. A widely adopted approach is a two-stage framework that first predicts expected returns and then solves the optimization problem based on these predictions, with the predictive…