TLDRocket
Sign in
Latest Quoting The New York Times — Simon Willison’s Weblog Anthropic can’t reliably control its AI agents. It’s cutting off its i... — TechCrunch IBM connects enterprise AI orchestration to production readiness ahead... — SiliconANGLE Doctor Evidence Search Tool “Evidence Finder” Adds Sakana Namazu — Sakana AI Ukraine’s drones knock out AI data center belonging to "Russia’s Googl... — Ars Technica The maker of non-text AI model Jev valued at $7.5B just weeks after la... — TechCrunch I expect rapid progress but not towards general superintelligence — Interconnects Alibaba Qwen Releases Qwen-Image-2.1-Turbo, an 8-Step 7B Image Model — MarkTechPost

The AI intelligence platform

Every AI story that matters — and the intelligence behind it.

TLDRocket reads all relevant sources, removes duplicate coverage, and publishes a short neutral summary of every story, linking back to the original. Free, no spam, unsubscribe anytime.

Add to Slack

Every story also updates live profiles event timelines weekly rankings the AI Market Index

Saturday, 3 February 2024

SegMoE: Segmind Mixture of Diffusion Experts

Hugging Face 2 years ago 19

Segmind released SegMoE, a framework that creates Mixture-of-Experts diffusion models by combining multiple expert models through a router network that selectively activates them during inference. Three pre-built models are available on Hugging Face (SegMoE-2x1, SegMoE-4x2, and SegMoE-SD-4x2), with SegMoE-4x2 requiring 24GB of VRAM in half-precision. Users can now create custom MoE diffusion models by configuring a YAML file specifying base and expert models, though inference speed decreases when multiple experts process tokens simultaneously.

The daily briefing

Every AI story that matters, in your inbox by 8am.

TLDRocket reads all relevant sources, removes duplicate coverage, and summarises the day in two minutes. Follow companies and topics for alerts, or get the briefing in Slack. Free, no spam, unsubscribe anytime.