Skip to content
Sunday, 4 October 2026
enltpl
Tenesys AI News
Subscribe

All News

TENESYS AI NEWS tracks the most important AI news and explains what changed, why it matters and whether a technology is worth testing.

All NewsModelsAgentsVoice AIAutomationBusinessResearchCyber Security
Any timeTodayThis WeekThis Month🔴 Breaking🟠 Important🧪 Worth Testing

#Research — 4 articles ✕

Models

Ai2 Open-Sources AstaBrief, a Fast 8B Model for Scientific Report Generation

Allen Institute for AI (Ai2) has open-sourced AstaBrief 8B, a model built on Qwen3-8B that turns research questions and retrieved literature excerpts into cited scientific reports. It's now live in Ai2's Asta platform as a 'Fast mode' alongside a Claude-powered 'Thinking mode', generating reports in about 51.1 seconds on average compared to 178.5 seconds for the Claude pipeline — roughly 3.5x faster. Ai2 trained the model using supervised fine-tuning on 47K examples (from 90K filtered real research queries) followed by DPO on about 6K preference pairs, and found that filtering training data for citation density was the single most effective lever for improving grounding quality.

Hugging Face
Research

Microsoft Research launches Quine, an AI world model built for biological discovery

Microsoft Research has unveiled Quine, a research system combining a multimodal 'world model' of biology with an interactive harness linking AI models, scientific literature, lab tools, and researchers. Built jointly across data types such as genomics, proteins, chemistry, RNA/cell state, and bioimaging, the model aims to predict how biological systems respond to interventions before costly lab experiments are run. Working with the Broad Institute of MIT and Harvard, Microsoft used Quine to rank thousands of compounds for their potential to shift pancreatic cancer cells between therapeutic states, and the top-ranked candidates were validated in wet-lab assays within a single weekend. Microsoft is now opening a 'Quine Fellows' program to give selected scientists early access, while cautioning that the system is experimental, research-only, and not intended for clinical use.

Microsoft Research
Research

Google Shows How to Speed Up Video Diffusion Attention on TPUs by 2.4x

Google engineers describe how they implemented sparse spatio-temporal attention for video diffusion models on TPU v6e chips, converting the theoretical sparsity of the Sparse VideoGen (SVG) approach into real hardware speedups. Through a progression of kernel optimizations (full/boundary tile specialization, tile-size tuning, and mask-tile alignment), they reduced attention kernel latency from 96.37ms (naive sparse) to 32.76ms, a 2.40x speedup over dense Splash Attention on a single TPU v6e chip, using 75.6K tokens, 10 heads, and head dimension 128.

Google Developers
Research

Google DeepMind Introduces SynthID Bio to Watermark AI-Generated Proteins

Google DeepMind unveiled SynthID Bio, a watermarking technology that embeds an imperceptible, verifiable signature into AI-designed proteins and 3D structures without compromising their biological function. The system was tested on protein binders (VEGF-A, SARS-CoV-2 spike RBD, PD-L1) using AlphaProteo and a modified ProteinMPNN, and also fine-tuned into AlphaFold 3's diffusion network for watermarking predicted 3D structures. DeepMind is also collaborating with Stanford's Hie lab and Arc Institute to apply the approach to Evo 2, a genomic model, to watermark designed bacteriophage genomes. The goal is to strengthen biosecurity by helping DNA synthesis screening providers and public databases verify the provenance of AI-generated biological designs.

Google DeepMind