Stanford University

2026-11-02

MODELS · 1 SOURCE · WIRED AI

When to use — and when to avoid — AI chatbots for web search

Modern AI chatbots like Claude, ChatGPT, and Gemini combine traditional web searching with knowledge from their training data to synthesize answers; this can be convenient for common or complex queries but risks errors, source-selection issues, and timing lags for obscure or high‑stakes searches. Research from Stanford and UC San Diego highlights that LLMs extract information well when they find accurate sources but can present confident answers even when sources are missing or misinterpreted.

4.0

2026-10-16

RESEARCH · 1 SOURCE · MIT Technology Review AI

Stanford PhD student Samuel King used generative AI to propose virus genetic blueprints

MIT Technology Review published an interview with Samuel King about his 2025 project in which he used a generative AI model to propose genetic blueprints for microscopic viruses. The work produced preliminary designs but did not create living organisms, and the interview covers King's recognition as an Innovator Under 35 and the scientific and biosecurity implications.

7.0

2026-10-09

RESEARCH · 1 SOURCE · MIT Technology Review AI

Roundtable: Samuel King on using generative AI to propose viral genomes

MIT Technology Review is hosting a subscriber-only roundtable (Oct 16) in which James O'Donnell interviews Stanford PhD student Samuel King about his 2025 work using a generative AI model to propose genetic blueprints for microscopic viruses; King says this is not yet AI-generated life but could be a step toward it.

7.0

2026-10-05

OTHER · 1 SOURCE · MIT Technology Review AI

Many people dislike AI — yet AI use keeps climbing

Multiple polls and reports show growing public unease about AI — Pew, Stanford, Gallup and NBC among them — even as usage soars (Sensor Tower reports ChatGPT reached 1 billion monthly users and Google DeepMind’s Gemini about 950 million). The article argues the apparent contradiction reflects people’s resentment of companies pushing AI widely and rapidly, not necessarily the underlying technology, and notes increasing regulatory activity (dozens of US state bills) and new open-source alternatives.

5.0

2026-10-02

STARTUPS · 1 SOURCE · WIRED AI

Trillium Labs launches nonprofit to publish open research on post-training, RSI and agents

Nathan Lambert and Tom Zick have launched Trillium Labs, a nonprofit that will conduct and publish experiments on high-risk AI areas—including post-training fine-tuning, recursive self-improvement (RSI), agents, and reinforcement learning—to enable outside scrutiny and replication. The lab has initial funding from Schmidt Sciences and Halcyon Futures, aims to raise $40–100 million total, and plans to spend $30 million on training over the next 18 months.

6.0

2026-10-01

RESEARCH · 1 SOURCE · The Decoder

Ataraxos (CMU/NYU/Stanford/MIT) defeats top Stratego player Pim Niemeijer

Researchers from Carnegie Mellon, NYU, Stanford and MIT published a Nature paper introducing Ataraxos, an AI that the authors say is, to their knowledge, the first to reach superhuman performance in Stratego; in an official 20-game match it beat Pim Niemeijer 15–1–4. The system trains purely by self-play, uses a belief network and a regularization schedule to maintain strategic diversity, and—according to the paper—was trained in about a week on 16 Nvidia H100 GPUs (plus four days on four GPUs for the belief network) with an estimated compute cost under $8,000 (2025 prices).

8.0

2026-09-30

RESEARCH · 1 SOURCE · MIT News AI

Ataraxos AI from MIT-led team achieves superhuman performance in Stratego

Researchers from MIT, Carnegie Mellon, NYU and Stanford developed Ataraxos, an AI trained with self-play and efficient algorithms that defeated top-ranked human Stratego players by a large margin and outperformed prior models while requiring far less compute; the work is reported in Nature. The system also generalizes to other imperfect-information strategic games and could inform decision-making in real-world hidden-information problems.

8.0

2026-09-30

MODELS · 1 SOURCE · Google

Google Translate pairs Gemini models with human linguists to improve conversational translations

Google says it is pairing its latest Gemini models with human linguistic experts on the Google Translate team to prioritize conversational meaning over literal phrasing and to better support under-represented, data-scarce languages; the article profiles three team members (Janneke, Isaac, Harsh) and notes Translate now supports nearly 250 languages.

4.0

2026-09-23

RESEARCH · 2 SOURCES · TechCrunch AI · The Verge AI

OpenAI forms advisory group on mathematics and AI, hosted at Institute for Advanced Study

OpenAI announced an independent Advisory Group on Mathematics and Artificial Intelligence hosted at the Institute for Advanced Study in Princeton to give mathematicians input on the company’s math-focused research. OpenAI said the same internal model recently resolved the Navier–Stokes Millennium Prize problem and more than 100 other open problems; the group will assess significance and coordinate releases but won’t have authority over OpenAI’s research pacing.

8.0

2026-09-20

STARTUPS · 1 SOURCE · TechCrunch AI

ScrollEd debuts AI-powered app that turns textbooks into short-form feeds at TechCrunch Disrupt

ScrollEd, a Palo Alto startup founded by Utsav Gupta and Rebecca Neff, has built an app that converts text files (including PDFs and textbooks) into a TikTok/Reels-like vertical feed using AI-generated video, audio, text, and quizzes. The company, which is bootstrapped and offers a freemium model plus a paid ScrollEd Pro and institutional licenses with analytics, is launching its consumer product at TechCrunch Disrupt and plans pilots with schools and corporate training programs.

4.0

2026-09-18

RESEARCH · 1 SOURCE · WIRED AI

Experts argue AI-enabled bioweapons risk is real but not an imminent existential threat

The article surveys recent concerns—including an Anthropic report flagging efforts to use Claude for biological misuse and research showing AI-designed viral genomes—but presents several scientists who say that while AI can accelerate access to biological information, major technical, material, and human checks still make AI-driven creation and deployment of novel bioweapons unlikely today. It also notes calls from some AI leaders for regulations on synthetic DNA and frontier capabilities.

6.0