Search headlines, summaries and articles to connect the dots.
vLLM supports Kimi K3.1 Pro on day 0: sparse attention on a KDA hybrid, a packed KV cache with FP8 or NVFP4 latents and MXFP4 index keys, token-sharded prefill, decode context parallelism, and fused low-latency decode.
There are lots of models that are as good as OpenAI's Sora now.
We take a quick look at the latest creative models, experiments, and community projects.
Advanced face swap and AI avatars from Easel AI are now on Replicate.
A new set of image generation capabilities for FLUX models, including inpainting, outpainting, canny edge detection, and depth maps.
We've made running fine-tunes on Replicate much faster, and the optimizations are open-source.
FLUX is now much faster on Replicate, and we’ve made our optimizations open-source so you can see exactly how they work and build upon them.
Google's flagship image generation model, Imagen 4, is now available for you to try on Replicate. Create images with fine detail, versatile styles, and improved typography.
Create AI videos with a convenient workflow.
Shipsidekick moved from Neon to ClickHouse Managed Postgres in a single weekend, cutting CPU usage from 100% to 5-10% and making queries about 10x faster.
NVIDIA H100 GPUs are here, with better performance and lower cost.
We've partnered with Hugging Face to bring Replicate inference to their platform.
MiniMax's Speech-02 models give you high-quality text-to-speech with voice cloning, emotional expression, and multilingual support.
One of the most fun ways to use Wan2.1 is video style transfer. Learn how here.
Wan2.1 is the most capable open-source video generation model, producing coherent and high-quality outputs. Learn how to run it in the cloud with a single line of code.
We've been playing with Alibaba's WAN2.1 text-to-video model lately. What happens when you tweak those mysterious parameters? Let's find out.
Train your own versions of Tencent's HunyuanVideo for style, motion, and characters on Replicate.
arXiv:2610.37788v1 Announce Type: new Abstract: Language model assistants sometimes change a correct answer when the user suggests a wrong one. The behavior, called sycophancy, is usually attributed to preference-based post-training, yet early measurements found it in pretrained models. We ask where it comes from by measuring it at every available stage of training: 13 open checkpoints from 5 lineages, from base model through supervised fine-tuning and preference optimization to release. We separate how far an injected claim moves a model's answer from how firmly the answer was held, and vary who makes the claim, how reliable they are said to be, and how strongly they make it. Two sycophancy behaviors with different origins emerge, and both replicate across datasets. Deference to a claim i
Supply chain security is taking on new importance as enterprises bring AI into core business operations. Those deployments introduce risks that require security teams to examine how infrastructure, data and autonomous systems are protected. As AI agents gain the ability to act on their own, executives need to rethink where risk lives and who controls […] The post Dell links supply chain security to the challenges of agentic AI appeared first on SiliconANGLE.
We're at the start of a major effort to speed up drug development with Claude. Over the past several months, our scientists have engaged in deep research partnerships with six organizations developing new medicines.
