NEW paper from Google on multi-agent research agents. It's one of the first systems that handles end-to-end LaTeX generation, targeted literature reviews, and conceptual diagrams as a decoupled, standalone writer. Automated research frameworks can run experiments, but their
MACHINE LEARNING
-
ACM Prize Honors Matei Zaharia for Distributed Data Systems
By
–
We're incredibly proud to congratulate our co-founder and CTO, @matei_zaharia
, on receiving the ACM Prize in Computing for his development of distributed data systems that have enabled large-scale machine learning, analytics, and AI. Matei's open-source contributions have -
Why AI Scaling Skeptics Misunderstand Exponential Growth
By
–
We're not hitting an AI ceiling. Here's why the AI scaling skeptics are wrong. Exponentials help us understand everything that's going on in AI. For thousands of years, we lived in a linear world. Two apple trees produced about twice as many as one did. Walking half as far took
-
DISCO: AI-Designed Enzymes for Novel Chemical Transformations
By
–
Such an incredible journey building DISCO 🪩. Love working with this team. DISCO is a co-design model with functional, de novo, new-to-nature enzymes. Huge shoutout to my co-authors for making this a reality! 🚀👇 https://t.co/xb6XGotQz4
— Alex Tong (@AlexanderTong7) 8 avril 2026Such an incredible journey building DISCO 🪩. Love working with this team. DISCO is a co-design model with functional, de novo, new-to-nature enzymes. Huge shoutout to my co-authors for making this a reality! 🚀👇 Jarrid Rector-Brooks (@jarridrb) What if AI could invent enzymes that nature hasn’t seen? 👩🔬🧑🔬 Introducing 🪩 DISCO: Diffusion for Sequence-structure CO-design 14 rounds of directed evolution and over a year of wet lab work. That's what it took to engineer an enzyme for selective C(sp³)–H insertion, one of the most challenging transformations in organic chemistry. DISCO surpasses this with a single plate. No pre-specified catalytic residues, no template, no theozyme, no inverse folding, just joint diffusion over protein sequence and structure. 📝 Blog: disco-design.github.io/ 📄 Paper: arxiv.org/abs/2604.05181 💻 Code: github.com/DISCO-design/DISC… — https://nitter.net/jarridrb/status/2041893841301860542#m
-
Critiquing Vector Database Dependence in RAG Systems
By
–
Someone removed the vector database from RAG and accuracy jumped to 98.7%. Most RAG systems chunk your documents, embed them as vectors, then retrieve by similarity. The core assumption: similar text means relevant text. That assumption fails on professional documents. Ask
-
Context Engineering: Organizing Unstructured Data for AI Reasoning
By
–
What is “Context Engineering”? It’s the discipline of stitching your unstructured mess—logs, chats, docs, images—into something an AI can actually reason over. → Vector DBs + hybrid search + embeddings to retrieve by meaning, not keywords. → Decisions anchored in your data, not generic pretraining.
→ View original post on X — @ronald_vanloon, 2026-04-08 15:00 UTC
-
BiMotion: B-spline Method Generates Expressive 3D Character Animations
By
–
Tired of stiff, janky 3D character animations from text descriptions?
— 机器之心 JIQIZHIXIN (@jiqizhixin) 8 avril 2026
Researchers from University of Edinburgh, Cornell University, University of Michigan, and Voxel51 present BiMotion.
This novel method transforms text prompts into truly continuous and expressive 3D… pic.twitter.com/Q1ArAvsIPhTired of stiff, janky 3D character animations from text descriptions? Researchers from University of Edinburgh, Cornell University, University of Michigan, and Voxel51 present BiMotion. This novel method transforms text prompts into truly continuous and expressive 3D character movements by using smooth mathematical curves (B-splines) instead of choppy, frame-by-frame animation. The result? BiMotion generates far more expressive, higher-quality, and precisely prompt-aligned motions than current state-of-the-art methods like AnimateAnyMesh, all at a faster speed! BiMotion: B-spline Motion for Text-guided Dynamic 3D Character Generation Paper: arxiv.org/abs/2602.18873 Project: wangmiaowei.github.io/BiMoti… Code: github.com/wangmiaowei/BiMot… Hugging Face: huggingface.co/datasets/miao… Our report: mp.weixin.qq.com/s/KP5klDevL… 📬 #PapersAccepted by Jiqizhixin
-
Snorkel AI Launches Frontier Dataset Engineering Manager Role
By
–
Great launch AI Foundations Engineering Manager @Ryfeus
’ take: "At Snorkel AI, we are focused on building frontier datasets. Our work spans the full AI lifecycle, from curated datasets like Snorkel Data Series for the most challenging agent tasks to evaluation, reinforcement -
Mitigating AI Hallucinations via Inference Redundancy and Voting
By
–
95% reliable is ~100% reliable if the hallucinations are uncorrelated across runs/systems/etc. It just means you spend a bit of extra effort on implementing a voting/etc layer and spend more on inference redundantly. This is almost boring.
-
Custom Kernels Reduce GPU Memory Requirements for AI Models
By
–
Yeah the custom kernels make the difference, most setups need 15-20GB for similar models