Image created with Flux Pro v1.1 Ultra. Image prompt: Giant “100” as pure white negative‑space cutout dominating the frame; minimalist poster style; GPU die pattern and tensor‑core schematic visible through the cutout; neon‑green on black backdrop; high contrast, crisp edges, soft studio light, no other text, no logos
AI world models & why they matter… in 20 minutes. The holodeck is closer than you think, and the implications for robotics, AR/VR and content creation are staggering. In this video, I’ll breakdown everything from Google Genie 3 and NVIDIA Cosmos to startups powering https://x.com/bilawalsidhu/status/1958320179714150824
A big milestone for Hermes. We did a lot of work to make a frontier level openmodel that does not dictate what expression you can elicit from the model. Super strong at math, coding, STEM, and creativity. Model Weights: https://x.com/Teknium1/status/1960420619620901135
Hermes 4 – Nous Research https://hermes4.nousresearch.com/
Hermes 4 technical breakdown: ▫️ Open Source LLM ▫️ Fine-tune of Llama 3.1 ▫️ 405B & 70B params ▫️ Hybrid reasoning ▫️ Trained on 3.5 million reasoning samples ▫️ Trained using 192 NVIDIA B200 GPUs ▫️ Uncensored ▫️ Steerable, aligned to the user ▫️ Creativity enhanced (like”” / X https://x.com/vectro/status/1960734604601569560
Nous Research presents Hermes 4, our latest line of hybrid reasoning models. https://x.com/NousResearch/status/1960416954457710982
Fourth model launch of the day 🔥 – introducing Hermes 4, from @NousResearch Hermes 4 is trained for steerability and lower refusal rates, topping RefusalBench and beating Grok 4 https://x.com/OpenRouterAI/status/1960436262923592065
Introducing the Environments Hub RL environments are the key bottleneck to the next wave of AI progress, but big labs are locking them down We built a community platform for crowdsourcing open environments, so anyone can contribute to open-source AGI https://x.com/PrimeIntellect/status/1960783427948699680
slurm support just dropped on prime for our h100, h200 and b200 multi node setups https://x.com/jannik_stra/status/1960375622003196127
🤖 From this week’s issue: The NVIDIA team released the NVIDIA Nemotron Nano 2 family of accurate and efficient hybrid Mamba-Transformer reasoning models. https://x.com/dl_weekly/status/1960321337248944130
Efficient Language Model with PostNAS NVIDIA’s recent research on LLMs has been fantastic. Jet-Nemotron is the latest in efficient language models, which significantly improves generation throughput. Here are my notes: https://x.com/omarsar0/status/1960724749790929009
NVIDIA has released Nemotron Nano 9B V2, a small 9B reasoning model that scores 43 on the Artificial Analysis Intelligence Index, the highest yet for <10B models Nemotron 9B V2 is the first Nemotron model pre-trained by @NVIDIA. Previous Nemotron models have been developed by https://x.com/ArtificialAnlys/status/1960504310309249045
NVIDIA release announcement with all the technical details: https://x.com/ArtificialAnlys/status/1960504316550373657
We just released Nemotron-CC-Math 🚀 Equations on web aren’t just LaTeX-they’re in MathML,<pre> tags,inline,even images.Code shows up just as many ways. Most parsers drop it. Nemotron-CC-Math(133B tokens) reprocesses CommonCrawl math pages to capture math equations +code reliably”” / X https://x.com/KarimiRabeeh/status/1960682448867426706
Results Jet-Nemotron-2B outperforms or matches small full-attention models on MMLU, MMLU-Pro, BBH, math, commonsense, retrieval, coding, and long-context tasks. All this while delivering up to 47x decoding throughput at 64K and as high as 53.6x decoding and 6.14x prefilling https://x.com/omarsar0/status/1960724855709688053
