2026: The Year #AI Gets Real by @Khulood_Almani #ArtificialIntelligence #MachineLearning #ML
→ View original post on X — @ronald_vanloon, 2026-04-09 17:23 UTC
MACHINE LEARNING
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Small model makers increase but performance gap with large models persists
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There are more competitive small model makers, but there is still a very big gap between what small models can do and what large models can accomplish (even if the small model benchmarks say otherwise)
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Wetware AI: Living Brain Cells Trained for Chaos Math
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Wetware #AI: Living Brain Cells Trained to Run Chaos Math by @NeuroscienceNew Learn more: bit.ly/4ccpW5J #HealthTech #ArtificialIntelligence #MachineLearning #ML
→ View original post on X — @ronald_vanloon, 2026-04-09 16:53 UTC
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NVIDIA launches 1.7 million AI-predicted protein complexes
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Amazing BioAI resource! From Nvidia in collaboration with @GoogleDeepMind @emblebi and @SeoulNatlUni https://t.co/m6KbjsRDra https://t.co/U4dJqHLJVS
— Derya Unutmaz, MD (@DeryaTR_) 9 avril 2026Amazing BioAI resource! From Nvidia in collaboration with @GoogleDeepMind @emblebi and @SeoulNatlUni nvda.ws/4tFuskk NVIDIA Healthcare (@NVIDIAHealth) 🚀 The largest-ever open‑source protein‑complex treasure trove – 1.7 million of AI‑predicted complexes now live in the AlphaFold Database In collaboration with @emblebi, @GoogleDeepMind, and @SeoulNatlUni, we have added millions of predicted complexes to the AlphaFold Database to accelerate global health research. 🧵👇 — https://nitter.net/NVIDIAHealth/status/2042263769959522635#m
→ View original post on X — @ceobillionaire, 2026-04-09 16:34 UTC
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Large AI Community List Management: 35,000 Accounts Organized
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My lists include EVERYONE. The small accounts are on "AI Community." 35,000 of them.
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MIT Researchers Cut AI Model Training Costs With CompreSSM
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Training a large AI model is expensive, but MIT CSAIL researchers have helped develop a new approach that cuts compute costs. Using control theory, "CompreSSM" compresses models during training, shedding complexity. It makes models leaner & faster: https://
bit.ly/4sU2Sjc -
Deploy Ultralytics YOLO Models on Axelera Metis AIPUs
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The recording of our live session with @ultralytics and Innowise is now up. See how to deploy Ultralytics YOLO models on Axelera Metis AIPUs in minutes using a single command. Read the technical blog: https://
eu1.hubs.ly/H0tm6sp0
Watch the session: https://
eu1.hubs.ly/H0tm3BT0 #EdgeAI -
AI agent autonomously probes its own multi-GPU setup and stats
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running Qwen3.5 397B MoE (17B active/token)
— Ahmad (@TheAhmadOsman) 9 avril 2026
on 4x DGX Sparks in FP8 (~400GB)
> OpenCode driving
> agent exploring its own config
> probing all 4 Sparks (via ssh) + reporting thermals
> inspecting how vLLM is serving it
> collecting + analyzing its own stats
local AI is awesome https://t.co/KU9u30GgXk pic.twitter.com/yPWSbSKto8running Qwen3.5 397B MoE (17B active/token) on 4x DGX Sparks in FP8 (~400GB) > OpenCode driving
> agent exploring its own config
> probing all 4 Sparks (via ssh) + reporting thermals
> inspecting how vLLM is serving it
> collecting + analyzing its own stats local AI is awesome -
AI system aggregates and ranks 40,000 curated AI sources
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I have 40,000 in AI all arranged in lists: https://
x.com/scobleizer/lis
ts
… But I built you an AI that reads them all and finds the best: