AI Insider·
General Compute, a new AI inference neocloud, has raised a $15 million seed round at a $60 million valuation led by FUSE VC, betting that specialised inference chips will outcompete GPUs as AI workloads shift from training to real-time agent and model deployment. CEO Finn Puklowski and CTO Jason Goodison have secured $300 million worth […]
Read full articleXCENA, a chip startup with offices in South Korea and the US, has raised $135 million in a Series B at a $570 million valuation, led by Seoul-based firms Atinum and IMM Investment, to commercialise a chip that processes AI data directly within memory rather than routing it through expensive CPUs and GPUs. Founded in […]
Chipmaker Groq is looking to raise $650 million in internal funding as it pivots from hardware to focus more on AI inference, the process of refining the way AI models respond to prompted requests, per Axios.
Chipmaker Groq is looking to raise $650 million in internal funding as it pivots from hardware to focus more on AI inference, the process of refining the way AI models respond to prompted requests, per Axios.
General Compute is betting SambaNova will be the next breakout chipmaker.
Stability AI has released Stable Audio 3, a family of latent diffusion models for instrumental music and sound effects generation. The release includes open weights for the small and medium variants. Small runs on a MacBook Pro M4 CPU. Medium fits on consumer GPUs with 8 GB of VRAM. Both generate stereo audio at 44.1 kHz using a three-stage training pipeline: flow matching, distillation warmup, and adversarial post-training. On the BBC Sound Effects benchmark at 5 seconds, SA3 medium scores FAD 0.369 — lower than every open-weight baseline evaluated in the paper. The post Stability AI Releases Stable Audio 3: A Family of Fast Latent Diffusion Models for Audio Generation and Editing appeared first on MarkTechPost.
Booz Allen and Future Tech leaders share how using hybrid design, edge AI and GPUs can accelerate secure federal AI deployment.
The cypherpunks wrote that privacy has to be built, not granted. Venice is applying that logic to AI inference.
In the world of artificial intelligence, the focus used to be on training AI models. Now, increasingly, it's on "inference" – the actual execution of the tasks we ask these systems to perform. David Gurlé is a French tech entrepreneur whose startup Antimatter aims to service the inference boom with energy solutions, mini data centres that fit inside a container and appropriate software – for only a fraction of the cost and time.
