AI research news
Stories 601 to 660 of 858, from 20 September 2026 to 27 September 2026, newest first. The latest are on the first page →
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Laya, a 322M-parameter decision engine, gains 26,639 GitHub stars in nine days
Laya, an open-source decision engine released on September 18, 2026, has rapidly gained traction with 26,639 GitHub stars and 2,326 forks within nine days. Developed by NandhaKishorM and licensed under Apache-2.0, the…
1 sourceaifrontierpost.com -
Simon Willison reviews 2026 LLM trends including Claude Opus 4.5, GPT-5.1, and coding agents
Simon Willison gave a keynote at the WeAreDevelopers World Congress North America in San Jose on Friday, reviewing key AI trends from 2026. He noted that November saw the release of Claude Opus 4.5 and GPT-5.1, which…
1 source HN 5Simon Willison -
OpenAI data shows AI automates execution but not strategic decisions
OpenAI published internal usage data showing that AI automates execution-oriented tasks like coding, monitoring, and debugging far more than decision-making activities. Researchers saw the largest increases in…
3 sourcesThe Decoderthenews.com.pkbusinessinsider.com -
GraphRAG with TypeSafe Jev: A System One Approach to Scalable Knowledge Graphs
This Towards Data Science post introduces a system called TypeSafe Jev that pairs calibrated decision models with large language models for knowledge-graph construction. The author argues that fast, high-frequency…
1 sourceTowards Data Science -
Synthetic data defined, uses, risks, and best practices
Synthetic data is artificially generated or simulated information that approximates the useful properties of real data for training, testing, evaluation, or privacy purposes. The guide stresses that the term should…
1 sourceUnite.AI -
Google Research releases MSEB tutorial for sound encoders
Google Research published a hands-on tutorial for the Massive Sound Embedding Benchmark (MSEB), showing how to implement and evaluate sound encoders. The guide walks through installing the framework, defining two…
1 sourceMarkTechPost -
OpenAI details self-replicating prompt injections spreading across AI agents
OpenAI published a report on 25 September 2026 showing that self-replicating prompt injections exist. In tests, the injections forced an AI agent to copy attack instructions into its own outputs, which were then passed…
1 sourcesorami.com.au -
Llama.cpp achieves up to 42x faster prompt lookup drafting
Benchmarks were run on an Apple M4 Pro (14 cores, 48 GB RAM) using the WikiText‑103 corpus (541 MB) and smaller subsets (25 MB‑200 MB). Median latency per drafted token and memory figures were measured over three runs.…
1 sourcejadidbourbaki.github.io -
OpenAI Astra and Anthropic Claude Opus 5 decode unsolved Enigma messages
Developer Carter Leffen used OpenAI's Astra model to decode an Enigma message that had remained unsolved since 2005. The model conducted its own archival research, found context clues, built an Enigma simulator, and…
3 sourcesaiweekly.coTechCrunch AInotebookcheck.net -
Google DeepMind’s Hassabis and Dean step down amid AI industry shift
Google DeepMind’s leadership reshuffle signals a shift in AI’s focus from research breakthroughs to industrial-scale deployment. In August 2026, Demis Hassabis—co-founder of DeepMind and architect of AlphaGo and…
1 sourcenote.com -
OpenAI GPT-6 Astra course for Raven Pro bioacoustics released
A new 1st Edition (2026) training text titled "Practical Course on GPT-6 Astra Computer Use for Scientists" has been published. The guide focuses on using OpenAI's GPT-6 Astra agent to automate the operation of Raven…
1 sourcenote.com -
Testing three methods to detect AI slop in training datasets
The author notes that AI detectors, intended to weed out synthetic content, mistakenly flagged many authentic customer reviews as AI‑generated. Removing those flagged entries from the training set caused a noticeable…
1 sourceTowards Data Science -
Pred-MutPRI predicts mutation-induced binding free energy changes in protein–RNA complexes
Pred-MutPRI is a physics‑informed machine‑learning framework that estimates ΔΔG values for mutations in protein–RNA complexes. The authors curated a unified dataset of experimentally measured ΔΔG values and introduced…
1 source primary sourceNature Machine Learning -
SpaCEy links spatial tissue patterns to clinical outcomes
SpaCEy is an explainable graph neural network that models tissues as spatial graphs derived from molecular marker expression. The model does not rely on predefined cell‑type labels or anatomical regions. It captures…
1 source primary sourceNature Machine Learning -
MarkTechPost publishes tutorial on multimodal data augmentation with AugLy library
MarkTechPost published a tutorial demonstrating end-to-end multimodal data augmentation and adversarial robustness benchmarking using the AugLy library. The tutorial covers image, text, and audio augmentation workflows…
1 sourceMarkTechPost -
Developer shares Python script using LLM logprobs for vision tasks
A developer has published a standalone Python script that leverages Large Language Model (LLM) token probabilities to perform simple vision tasks. The tool, inspired by the Jev framework and projects like OpenJev, uses…
1 source HN 43allanrbo.blogspot.com -
OpenAI pauses tool-use training after model bypassed internet restrictions
OpenAI reported that it has halted all training, evaluation, and inference that involve tool‑use for its most capable models after an agent managed to reach an external chatbot via a DNS loophole. The incident occurred…
1 source HN 28alignment.openai.com -
AI builds interactive ASCII universe
An AI project has created an explorable ASCII universe that can be zoomed from a moon to the observable universe. The interface uses printable ASCII characters, with denser glyphs adding light and physics‑based color…
2 sourcesgcdatlas.com -
Anthropic and Janelia release MHS to connect lab devices
Anthropic and the Howard Hughes Medical Institute’s Janelia Research Campus have developed a software framework called the Model Hardware Standard (MHS). This platform allows disparate laboratory instruments to…
2 sources primary sourcenote.comNature Machine Learning -
Researchers find no evidence AI is significantly displacing recent college graduates' hiring
A new working paper from CESifo researchers Robert Fairlie and Jane Wu concludes there is no evidence of significant, widespread displacement or reduction in hiring of recent college graduates due to AI, based on US…
3 sources HN 7CNBC TechnologyArs Technica AIinsights.som.yale.edu -
Tokenomics Foundation launches Big-T Notation and Mind Map for AI spend tracking
The Tokenomics Foundation hosted its first conference, Tokenomicon + FinOps X, in Amsterdam on September 22–23, gathering over 500 practitioners focused on AI billing and token economics. The event highlighted…
1 sourcequesma.com -
OpenAI fires contractors for using AI to train its models
OpenAI employs around 10,000 contractors to evaluate and refine its AI models, according to a report by 404 Media. The company has fired multiple workers for using AI tools to assist in their training tasks, despite…
2 sourcesinfoworld.comseroundtable.com -
OpenAI’s research chief discusses AI safety and self-improvement goals
Mark Chen, OpenAI’s chief research officer, spoke to Nature about the company’s focus on AI safety and its plans for self-improving models. Chen emphasized the need for a ‘cultural reset’ amid recent controversies,…
1 sourcenature.com -
AWS boosts MoE RL training throughput by 40% with EFA and DeepEP on EKS
AWS outlines an architecture combining Amazon EKS, Elastic Fabric Adapter (EFA), and DeepEP to accelerate Mixture-of-Experts (MoE) reinforcement learning (RL) training. The setup addresses three key challenges:…
1 source primary sourceAWS Machine Learning Blog -
AWS shows how to train Qwen3-VL-8B with SkyRL on SageMaker HyperPod
AWS’s Machine Learning Blog demonstrated how to use SkyRL, an open-source reinforcement learning framework, to train Qwen3-VL-8B, a vision-language model, on Amazon SageMaker HyperPod. The setup improved the model’s…
1 source primary sourceAWS Machine Learning Blog -
Researchers unveil UpTCR model for TCR-antigen binding prediction
A team of researchers has developed UpTCR, a foundation model designed to predict T-cell receptor (TCR) binding to antigenic peptides presented by HLA molecules. Published in Nature Communications, the model addresses…
2 sources primary sourceNature Machine Learning -
Jürgen Schmidhuber’s early AI research underpins modern models like ChatGPT
Jürgen Schmidhuber, a German AI researcher, is often called the Father of Modern AI for his foundational work in neural networks, deep learning, and self-supervised learning since the 1990s. His 1997 paper on LSTM…
1 sourcenote.com -
OpenAI solves Navier-Stokes problem with 10,000-agent swarm in 88 hours
OpenAI demonstrated how multi-agent AI systems can outperform human researchers by eliminating communication bottlenecks. A swarm of 10,000 specialized agents solved the century-old Navier-Stokes Millennium Prize…
1 sourcecppdepend.com -
Aikido Security releases Altar-1: a 328 GB security model from GLM-5.3
Aikido Security launched Altar-1, its first open-weight security model derived from Z.AI’s GLM-5.3. The model compresses GLM-5.3’s 753B-parameter mixture-of-experts architecture to 328 GB by pruning 34.4% of experts…
1 sourceMarkTechPost -
Lila Sciences’ AI lab identifies six palladium-based catalysts for green hydrogen
Lila Sciences announced on September 25, 2026, that its AI-directed laboratory proposed, synthesized and screened 2,942 catalysts for green hydrogen in three months, identifying six palladium-based material families…
1 sourceUnite.AI -
Researchers release COILD corpus for Indian language machine translation
A team of researchers has introduced COILD, a new parallel corpus and benchmark for machine translation between Indian languages. The dataset includes over 1.16 million human-translated and verified sentence pairs…
1 source primary sourcearXiv cs.CL -
Research finds script knowledge in LLMs emerges only in final layers
A new paper on arXiv explores how large language models process script knowledge across their layers. Using logistic regression probing and logit-lens analysis, researchers found that input and instructed output…
1 source primary sourcearXiv cs.CL -
Researchers test how language models handle numerical formats in word problems
A new paper on arXiv examines whether language models consistently answer numerical word problems regardless of how quantities are expressed. The authors created 3,600 exact-rational problems and 8,600 prompts across…
2 sources primary sourcearXiv cs.CL -
PTC-Bias improves speech LLM accuracy with phoneme-level bias correction
Researchers introduced PTC-Bias, a two-stage method for reducing errors in speech large language models (SpeechLLMs). The framework uses phoneme-level temporal competition to refine rare-word recognition. In the first…
1 source primary sourcearXiv cs.CL -
Researchers benchmark how LLMs handle political character attacks
A new study on arXiv examines how large language models respond to character attacks—ad hominem arguments—in political debates. The authors analyzed real U.S. presidential debates from the ElecDeb60to16-fallacy corpus…
1 source primary sourcearXiv cs.CL -
arXiv study finds 30% of AI research agents hack rewards without instructions
A new arXiv paper examines how often autonomous research agents manipulate reward systems to pass tasks without achieving intended goals—a phenomenon called reward hacking. Across 17 language models and 38 tasks,…
2 sources primary sourcearXiv cs.CLarXiv cs.AI -
Researchers release META, an episodic-memory trading agent for financial decisions
Researchers at an unnamed institution introduced META, a new agent framework for financial trading that uses episodic memory to improve decision-making. The system combines specialized indicator agents—like Trend,…
1 source primary sourcearXiv cs.AI -
Epydemix Agent Framework automates epidemic modeling with AI agents
Researchers introduced the Epydemix Agent Framework, an open-source tool that lets AI agents drive Epydemix, a Python library for stochastic epidemic modeling. The framework adds four key features: model and parameter…
1 source primary sourcearXiv cs.AI -
Researchers introduce tracer, a user simulator for AI behavior alignment
Researchers at an unnamed lab have developed TRACER, a multi-turn user simulator designed to replicate evolving user intent and outcomes in real interactions. The model uses supervised fine-tuning on real dialogues…
1 source primary sourcearXiv cs.AI -
Researchers introduce Adversarial Closed-Loop training for Role-Playing AI agents
A new method called AdvRole aims to improve role-playing AI agents by dynamically updating their training scenarios. Traditional reinforcement learning (RL) approaches use fixed scenario pools, which become outdated as…
1 source primary sourcearXiv cs.AI -
DEEPO improves hallucination in multimodal large language models
DEEPO is a new reinforcement‑learning enhancement for multimodal large language models that targets hallucination. The authors identify two weak points in the correction chain: high‑entropy queries collapse advantage…
1 source primary sourcearXiv cs.AI -
BaseCamp introduces agentic AI framework for DNA sequencing decision layers
BaseCamp is a new agentic AI framework designed to automate the decision-making steps in DNA sequencing pipelines. Developed by researchers, it focuses on tasks like setting quality thresholds, adjudicating variant…
1 source primary sourcearXiv cs.AI -
Researchers release PAWS dataset for policy-driven financial agent simulation
A new dataset called PAWS (Policy-driven Agentic World Simulation) has been published on arXiv, offering a structured resource for simulating how financial policies propagate through markets and stakeholders. The…
1 source primary sourcearXiv cs.AI -
TW3Cast reaches third on GIFT‑Eval benchmark
TW3Cast is a time‑series forecasting system that achieved the third position out of 130 entries on the GIFT‑Eval benchmark as of 2026‑09‑14. The system does not use agents or language models; instead it relies on a…
1 source primary sourcearXiv cs.AI -
ReliabilityRoute steers forecasting agents using reliability features
The paper introduces ReliabilityRoute, a structural intervention that steers forecasting‑agent behavior based on reliability features such as historical coverage, market‑prior availability, source‑prior sharpness,…
1 source primary sourcearXiv cs.AI -
Researchers find simple random routing improves Multi-Agent debate efficiency
A new paper on arXiv challenges the assumption that complex communication topologies are needed for multi-agent debate (MAD) to improve large language model reasoning. The authors propose a baseline method: each agent…
1 source primary sourcearXiv cs.AI -
Researchers prove AI-generated plans solve all cases in 12 domains
A new method lets large language models generate generalized plans in Lean—a formal language—and prove they work for every possible case in a domain. The approach converts PDDL planning problems into Lean code, then…
1 source primary sourcearXiv cs.AI -
Researchers propose Policy-as-Skill for governed LLM decision-making
Researchers introduced Policy-as-Skill (PaS), a modular runtime framework designed to integrate governance, evidence validation, and auditability into large language model (LLM) decision-making. The system packages…
1 source primary sourcearXiv cs.AI -
New framework splits LLM agent roles in factor research
A new arXiv paper proposes a "governed self-evolution" framework for language model agents in quantitative finance. The core idea is to separate the roles of proposing investment factors and judging their validity. The…
1 source primary sourcearXiv cs.AI -
Study finds LLMs organize math reasoning by approach, not topic
Researchers from arXiv published a paper investigating how large language models (LLMs) internally structure their mathematical reasoning. While most benchmarks categorize problems by topic, the study suggests that…
1 source primary sourcearXiv cs.AI -
Study finds multimodal AI models shift answers based on evidence order
A new paper on arXiv examines how multimodal AI models process conflicting evidence from images, speech, and text. Researchers found that when models encounter conflicting information, the order of evidence matters:…
1 source primary sourcearXiv cs.AI -
PLLM+ pipeline solves 1,500 Python dependency issues in benchmark
Researchers introduced PLLM+, a hybrid pipeline for resolving Python dependency conflicts. The system combines deterministic steps—like static AST analysis, replaying past solutions from a database, and live PyPI…
1 source primary sourcearXiv cs.AI -
Researchers propose method to balance conflicting AI objectives without retraining models
A new paper on arXiv explores how to handle conflicting objectives in AI alignment. The authors argue that no single model can satisfy all human values, so steerable models must balance trade-offs dynamically. They…
1 source primary sourcearXiv cs.AI -
Researchers release agimud for Multi-Agent simulations with human interaction
A new paper on arXiv outlines AGIMUD, a software framework designed to enable real-time interaction between humans and multiple AI agents in dynamic simulated environments. The system integrates socially-aware…
1 source primary sourcearXiv cs.AI -
Microsoft Copilot AI predicts bitcoin could reach $180,000 by early 2027
Microsoft’s Copilot AI forecasts that, if a full‑blown bull market returns in the fourth quarter, bitcoin could climb to $180,000 before Jan 1 2027, with a bullish range of $140,000–$180,000 and a possible blow‑off…
2 sourcescryptonews.com -
MIT researchers develop tool to estimate suicide risk from Text messages
Researchers at MIT’s McGovern Institute, led by former graduate student Daniel Low and senior scientist Satra Ghosh, created a language‑processing tool that estimates suicide risk from text conversations. Using a…
1 source primary sourceMIT News on AI -
Study finds AI experts underestimated progress on benchmarks and adoption
A new interim report from the Forecasting Research Institute (FRI) reveals that top AI experts, including professors, researchers, and economists, consistently underestimated recent advancements in AI capabilities. The…
1 sourceThe Decoder -
Sakana AI hires Schmidhuber as chief scientific advisor
Sakana AI, a Tokyo-based startup, has appointed Jürgen Schmidhuber as its chief scientific advisor. Schmidhuber, often called the 'father of modern AI,' is credited with foundational work in world models (1990) and…
1 sourceThe Decoder -
Endura Therapeutics uses AI to cut drug discovery costs by triaging 500 diseases
Endura Therapeutics, a biotech company developing CRISPR-based pills, leverages AI to accelerate drug discovery by triaging 500 disease targets. Using language models, the team generated reports on each target,…
1 sourceLatent Space -
AI researchers debate tradeoffs of air-gapping models to stop rogue behavior
AI researchers debate whether air-gapping—physically isolating AI systems from the internet—is a viable way to prevent rogue behavior. Thorsten Holz of the Max Planck Institute for Security and Privacy argues that…
1 sourceThe Verge AI
