DeepSeek, the Hangzhou-based AI startup, is building its first known data center in Ulanqab, Inner Mongolia, according to job postings dated April 2, 2026, as it prepares to launch its trillion-parame…
Hugging Face's top AI papers for July 26, 2026, feature AREX, a recursively self-improving agent for research, and SLAI T-Rex, which demonstrates full-parameter post-training of DeepSeek-V4 on Ascend …
A developer compiled the top 10 most upvoted papers on Hugging Face, covering deep research agents, post-training large models on Ascend SuperPOD, embodied visual tracking, K-12 knowledge graphs, self…
Every major LLM vendor has replaced numeric thinking-token budgets with discrete effort levels, converging on a small enum instead of a number. Anthropic now rejects budget_tokens with a 400 error on …
Harness Engineering built a fully automated coding loop inside OpenCode using DeepSeek-V4-Pro and DeepSeek-V4-Flash, enabling low-cost agentic code iteration. The loop, inspired by Andrew Ng's breakdo…
A developer spent 107 days running 9 autonomous AI agents in a physical fitness studio and discovered that structural constraints matter more than model intelligence. The system, built on DeepSeek-V4 …
Chinese AI firm DeepSeek open-sourced DSpark, a speculative decoding system that accelerates large language model inference by up to 85% without altering output quality, releasing it under the MIT lic…
Fastllm, a C++ LLM inference library, now supports running DeepSeek-V4 and the full DeepSeek R1 671B model on a single GPU with just 10GB VRAM. The library is compatible with Nvidia, AMD, and domestic…
DeepSeek released DSpark on June 27, a speculative decoding framework that accelerates per-user generation speeds by 60% to 85% on its DeepSeek-V4 Flash model and 57% to 78% on the Pro variant. The fr…
DeepSeek open-sourced DSpark, a speculative decoding framework that accelerates per-user generation for DeepSeek-V4 by 57–85% over the MTP-1 baseline. The framework pairs a parallel draft backbone wit…
AMD introduces DP Attention and Two-Batch Overlap (TBO) optimizations for DeepSeek-V4 inference on MI355X GPUs, using a coordinated prefill scheduler called PrefillDelayer to reduce padding waste and …
A developer created a plugin called 'observer' for OpenCode that enables the DeepSeek-V4 language model to read images by calling a multimodal agent, allowing it to interpret error screenshots, charts…
DeepSeek-V4's million-token context capability stems from a hybrid attention architecture that compresses context before KV storage, reducing cache pressure. Together's early bring-up on NVIDIA HGX B2…
DeepSeek-V4 shifts the focus from simply offering a million-token context window to making that window practically usable through efficient attention mechanisms. Its architecture employs hybrid compre…
DeepSeek-V4 introduces a new architecture using hybrid attention mechanisms—Compressed Sparse Attention (CSA) and Heavily Compressed Attention (HCA)—to drastically reduce the computational cost and me…