From the source

Unlocking asynchronicity in continuous batching

Image published with the post by Hugging Face — Image from huggingface.co

Asynchronous batching for continuous batching in LLM inference, which separates CPU and GPU workloads to improve GPU utilization, and has been implemented in the transformers library.

From the source
we explain how to separate CPU and GPU workloads to get a massive performance boost for inference.
huggingface.co

Most covered

Meta Muse Wonder: A Frontier Model For Personal & Professional AI Agents
SiliconANGLE: “Meta releases Muse Wonder AI models built to run personal and professional agents”
Reporting · 29 outlets
Meta· 12 Oct
Muse Wonder: A Frontier Model For Personal & Professional AI Agents
Google Antigravity Gemini 4 Argon in Google Antigravity
9to5Google: “Google Antigravity is now built into Gemini app for macOS”
Reporting · 29 outlets
Image from antigravity.google
Google Antigravity· 13 Oct
Gemini 4 Argon in Google Antigravity
Microsoft Deep dive into Azure Maia 300 architecture
Axios: “Every major Nvidia customer is now a competitor as Microsoft reveals new Maia chip”
Reporting · 14 outlets
Image from azure.microsoft.com
Microsoft· 12 Oct
Deep dive into Azure Maia 300 architecture
xAI Introducing Grok Voice 3.0
SiliconANGLE: “Grok Voice 3.0 from SpaceXSI outscores OpenAI and Google on speech-to-speech index”
Reporting · 8 outlets
Image from x.ai
xAI· 14 Oct
Introducing Grok Voice 3.0
TypeSafe AI TypeSafe A raises Series AI
Bloomberg: “Andreessen Horowitz Backs Jev Maker at $7.5 Billion Value”
Reporting · 3 outlets
TypeSafe AI· 9 Oct
TypeSafe A raises Series AI

Other stories

Other stories

Other stories

Unlocking asynchronicity in continuous batching

From the source

Other stories

The model that didn't exist, so you made it yourself

AutoSynthData: Generating Training Data for Enterprise Agents

Open TTS Leaderboard: Scalable Evaluation for Multilingual Text-to-Speech and Voice Cloning

Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents

Welcome RL Environments to the hub

How UK AISI and EvalEval Are Making Benchmark Results Reproducible