Image created with Ideogram 3.0. Image prompt: Lower-East-Side street-corner photograph reminiscent of a late-80s album cover: weathered red-brick tenement with exterior fire-escapes, canvas awning shading racks of vintage clothes; above the awning, a hand-painted board reads ‘DeepSeek SPORTSWEAR’; a hanging blade sign in cursive script reads ‘DeepSeek Boutique’; an antique brass telescope leans against the clothes rack, its lens aimed skyward like a seeker; warm golden-hour light, subtle 35mm film grain, muted yet punchy color palette, gritty NYC vibe.
Meta just released KernelLLM 8B on Hugging Face ⚡ > On KernelBench-Triton Level 1, our 8B parameter model exceeds models such as GPT-4o and DeepSeek V3 in single-shot performance 🤯 > With multiple inferences, KernelLLM’s performance outperforms DeepSeek R1 https://x.com/reach_vb/status/1924478755898085552
Really cool how DeepSeek is now the benchmark for Nvidia”” / X https://x.com/teortaxesTex/status/1924588309688267139
[2505.09343] Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures https://arxiv.org/abs/2505.09343
DeepSeek presents: Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures Elaborates on hardware architecture and model design in achieving cost-efficient large-scale training and inference https://x.com/arankomatsuzaki/status/1922844556430581761
Insights into DeepSeek-V3 Scaling Challenges and Reflections on Hardware for AI Architectures https://x.com/_akhaliq/status/1923001697498006016
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures Overview: DeepSeek-V3 which is an LLM trained on 2,048 H800 GPUs, utilizes hardware-aware co-design incorporating Multi-head Latent Attention, MoE, FP8 training, and a Multi-Plane https://x.com/TheAITimeline/status/1924232113101890003
Designing models and hardware together — is it a new shift for the best cost-efficient models? This idea is used in DeepSeek-V3 that is trained on just 2,048 powerful NVIDIA H800 GPUs. A new research from @deepseek_ai clarifies how DeepSeek-V3 works using its key innovations: https://x.com/TheTuringPost/status/1924631209050833205
Do LLMs Really Understand Cell Biology? Interesting paper evaluating LLMs potential in understanding cell biology. Finding: It finds that specialist models don’t work so great. Generalist models, such as Qwen and DeepSeek, exhibit preliminary understanding capabilities within https://x.com/omarsar0/status/1922662317986099522
Everything you need to know to understand GRPO: GRPO (Group Relative Policy Optimization) is a reinforcement learning algorithm created by DeepSeek specifically for LLMs. It drops the need to use critic network like in PPO and so it doesn’t use absolute value estimate to https://x.com/TheTuringPost/status/1925146257372381485
