Amazon Science: latest AI & code stories | Accept All

Skip to content

Accept All すべて承認 /

Amazon Science

25 stories

Amazon ScienceResearchDeveloping provably correct Rust code with Verus How the Verus "program verifier", which automatically checks code against a mathematical specification of its functionality, helps increase security assurance in software projects.

Amazon ScienceResearchWhen LLM judges agree, should we believe them? Discounting the opinions of LLM judges with highly correlated outputs ensures that panels of judges reflect a true diversity of perspectives.

Amazon ScienceResearchSOP-Bench: A new benchmark for evaluating AI agents on real business procedures Extendable framework enables testing agents on the full set of capabilities required to successfully complete a procedure, not isolated proxy tasks.

Amazon ScienceResearchA decade of mathematical certainty: Reflections on the Automated Reasoning Group Ten years after we founded the Automated Reasoning Group, mathematical logic has moved from academic research into production services that secure millions of customer workloads — demonstrating that systems can be provab

Amazon ScienceResearchAWS Trainium Frontier competition: Co-design models and kernels on purpose-built AI chips A competition with a finalist ceremony during NeurIPS 2026, challenging researchers to train language models from scratch on Trainium, exploring what optimal architectures look like when the hardware changes.

34 Amazon Research Awards Build on Trainium recipients announced

Amazon ScienceResearch34 Amazon Research Awards Build on Trainium recipients announced Amazon announces 34 recipients of the Build on Trainium program, a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Respo

Amazon ScienceResearchHow controllers from industrial machinery can coordinate multitask machine learning Instead of compromising among parameter updates dictated by different training objectives, ControlG allocates computational capacity to objectives sequentially and dynamically.

Amazon ScienceResearchA new benchmark for evaluating patient-facing health AI agents PatientAgentBench generates a synthetic patient health record, a realistic clinical vignette, and a patient agent that converses with the AI system under evaluation, to capture what a patient-facing agent actually has to

Amazon ScienceResearchAmazon is investing in the Lean Focused Research Organization As AI agents take on higher-stakes decisions, Lean programming language makes it possible to mathematically prove they will behave safely.

Amazon ScienceResearchAmazon and University of Michigan give robots a sense of touch HydroShear, a new physics-based simulator, teaches robots how to use their sense of touch to perform complex manipulation tasks, in a way that transfers seamlessly to the real world.

Amazon ScienceResearchCapturing token IDs during agentic interactions for better reinforcement learning A new Rust proxy called Turnstile sits between the model backend and the agent harness to capture information lost in mere text transcripts.

How Amazon tracks carbon intensity across its operations

Amazon ScienceResearchHow Amazon tracks carbon intensity across its operations Amazon is developing precise, sector-specific approaches to measuring decarbonization progress — starting with emissions per unit shipped.

Amazon ScienceResearchThe fuel of the future is already here: Why TRISO matters Millimeter-scale particles of nuclear-reactor fuel are encased in four layers of different materials that act as a “miniature containment system”.

Amazon ScienceResearchEC2’s formally verified “isolation engine” provides mathematical assurance of virtual-machine isolation Splitting the “separation kernel” off from the rest of the Nitro security system and using only a subset of the Rust programming language to code it enabled its formal verification.

Graviton5’s improved design increases speed and energy efficiency — beyond Moore’s law

Amazon ScienceResearchGraviton5’s improved design increases speed and energy efficiency — beyond Moore’s law A new chiplet architecture, custom die-to-die connectivity, and support for DDR5-8800 memory and the latest PCIe gen6 interconnects improve performance by 25% for general-purpose and agentic AI workloads.

Amazon ScienceResearchReal-world grounding in agentic AI Four approaches can dramatically improve the performance and trustworthiness of AI agents in operational environments.

Amazon ScienceResearchBridging intent and execution in agentic systems The harnesses that mediate between models and tools in agentic systems are becoming their own performance bottleneck, but a few simple design principles can fix what ails them.

Amazon ScienceResearchGround truth is a process, not a dataset Automatically fact-checking long, AI-generated research reports poses new challenges — including benchmarking.

Amazon ScienceResearchHow flat is replacing fat in AWS data center networks “Quasi-random” network topologies and new passive optical components called ShuffleBoxes make more-efficient flat networks as practical as traditional “fat-tree” networks.

Amazon Research Awards recipients announced

Amazon ScienceResearchAmazon Research Awards recipients announced Awardees represent more than 49 universities in 11 countries. Recipients have access to Amazon public datasets, along with AWS AI/ML services and tools.

Amazon ScienceResearchDiverse reasoning traces teach LLMs to make better decisions How to train language models to generate diverse, accurate reasoning paths using tokens that control distinct reasoning strategies.

Amazon ScienceResearchMaking LLMs faster without sacrificing accuracy A new scaling law that relates particular architectural choices to loss helps identify models that improve throughput by up to 47% with no loss of accuracy.

Amazon ScienceResearchPromptimus: Improving already good LLM prompts with zero manual engineering By focusing on specific failure points and suggesting targeted solutions, a new automated prompt-engineering framework improves prompt performance without compromising existing functionality.

Amazon ScienceResearchNavigating uncertainty in Amazon's middle-mile network Amazon engineers and scientists have created new tools to optimize delivery networks under uncertainty — and keep them adapting without missing a beat.

On the calendar

予定 · Conferences and launch events, this week's stories from each corner of the industry, and what its press is covering — in English

On view

This week, from that corner the newest stories from the corner of the industry you picked

The wire their own posts, translated

How code moves in 2026 from the industry's own reports

Sources

Fetched every three hours, linked to the original

About

Accept All is a magazine, a radar and a diary about artificial intelligence and the craft of code — read from Tokyo, for people who build.

The name is the button. Code is written by agents now and reviewed by a human thumb that hovers over Accept all a hundred times a day; the whole question of this decade is what, exactly, you just accepted. So we read the diff. A magazine, because every week one model, one tool or one idea is worth reading about slowly. A radar, because we count what the labs, the Valley, GitHub and the chip makers are talking about — releases, agents, open weights, compute, funding, rules — and show it as it moves. A diary, because a seal is set each day in that day's colour, and the days add up.

We read the research labs' own posts, the American and European tech press, the Japanese and Chinese developer sites and the newsletters people actually forward, and bring it together in English and Japanese. Everything here links back to the people who wrote it; the images belong to their authors.

Accept All will keep changing. New sources, new signals, new ways of looking — a little better each week, never finished. If something here made you open a terminal, that is enough.

Thank you for reading. ありがとうございます。