Search: “olympics”

22 stories

DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

CategoryAll Ransomware 77 Malware 64 Threat actor 51 Exploit / PoC 38 Vulnerability 35 Phishing & fraud 30 Data breach 22 Policy & legal 19 Industry 16 Research 5 Advisory 4 AI tools & infra 1

SeverityAll critical 149 high 110 medium 46 low 55 info 2

Smart search ranks by meaning as well as keywords (one row per story, last 45 days).

Network Abuses Leveraging High-Profile Events: Suspicious Domain Registrations and Other Scams

Unit 42 found scammers surge deceptive domain registrations around major events like the 2024 Paris Olympics to run phishing and counterfeit merchandise scams.

Unit 42 analyzed newly registered domains (over 200,000 detected daily from zone files, WHOIS, and passive DNS) containing event-specific keywords, using the 2024 Paris Summer Olympics as a case study. Threat actors register lookalike domains to sell counterfeit merchandise, push fraudulent services, and run phishing, as previously seen with COVID-19-themed and fake ChatGPT tool scams. The article recommends monitoring domain registrations, DNS and URL traffic trends, textual patterns, and verdict change requests to catch event-themed abuse early.

Palo Alto Unit 42Aug 17, 12:46 UTC · Aug 17, 2026Phishing & fraud in the wild

A misalignment of AI in mathematics

Fields Medalists including Terence Tao warn AI benchmark-chasing in mathematics is misaligned with scientific goals and threatens research culture.

Twenty-five Fields Medal-winning mathematicians, including Terence Tao, Peter Scholze, and Manjul Bhargava, published an essay arguing that AI companies' push to solve mathematical problems as benchmarks is severely misaligned with the goal of conceptual understanding. They warn that rushed AI solutions create attribution and plagiarism risks and bypass the human process of integrating results into the mathematical canon. The authors frame the issue as a broader alignment problem facing scientific and creative professions and call for urgent action by AI developers and society.

Hacker News · AISep 11, 17:45 UTC · 5d agoAI safety & security 2 sources HN 59↑ · 153 comments

An Open Recipe for IMO Gold: Training Nemotron for Olympiad Mathematics

Open post-training pipeline turns Nemotron 3 Ultra checkpoints into an IMO 2026 gold-medal system, scoring 30/42 without formal provers or external tools.

Starting from Nemotron 3 Ultra, researchers trained two specialist checkpoints using supervised fine-tuning and reinforcement learning for natural-language olympiad proof generation. Three checkpoints power an iterative generate-verify-refine search plus a separate high-compute selection stage, operating entirely in natural language with no formal prover, external tools, or internet access. The system scored 30 of 42 points at IMO 2026, reaching the gold-medal threshold. The release includes the post-trained checkpoints, training data, training and inference code, submitted solutions, and Nemotron-IMO-Bench with 200 novel olympiad-level problems.

Hugging Face daily papersSep 8, 20:00 UTC · 8d agoModel release

TLD Tracker: Exploring Newly Released Top

Unit 42 tracked 19 newly released top-level domains and found large-scale phishing, unwanted program distribution, and cybersquatting tied to TLD launch dates.

Researchers analyzed 19 new generic TLDs, including .zip, .bot, .ing, and .meme, released or approaching general availability over roughly 18 months. Data from passive DNS, registry zone files, newly registered domain feeds, and the Tranco top-1M list showed phishing campaigns, potentially unwanted program distribution, and domain squatting on these TLDs. Abuse correlated with each TLD's rollout phases, indicating attackers monitor general availability dates to register and weaponize domains. The IANA root database now lists over 1,000 generic TLDs.

Palo Alto Unit 42Aug 17, 12:47 UTC · Aug 17, 2026Research

On the Navier–Stokes Millennium Prize Problem

OpenAI announced an AI-generated solution to the Navier-Stokes Millennium Prize Problem, including a writeup and a formal Lean proof.

OpenAI shared what it describes as an AI-generated solution to the Navier-Stokes Millennium Prize Problem, one of the Clay Mathematics Institute's seven Millennium Prize Problems concerning fluid dynamics. The announcement includes a writeup and a machine-checkable formal proof in the Lean theorem prover. Details on the model, methodology and independent verification were not provided in the announcement text.

OpenAI NewsSep 8, 10:00 UTC · 8d agoAI research

On the Navier–Stokes Millennium Prize Problem

OpenAI says an unreleased model produced a claimed solution to the Navier-Stokes existence and smoothness problem, disputed by an NYU mathematician.

OpenAI used an unreleased model to produce a claimed solution to the Navier-Stokes existence and smoothness problem, one of the seven Millennium Prize Problems carrying a $1,000,000 prize since May 24, 2000. The result is contested: NYU mathematics professor Tristan Buckmaster accused collaborators of skulduggery and rushed out his own competing results with mathematician Levent Alpoge, who works at Anthropic. The dispute is documented in a published PDF describing the competing claims.

Simon WillisonSep 8, 23:39 UTC · 8d agoAI research

Unsolved Problem by Fields Medalist Breached by Two High School Students

Two high school students used Claude Opus 5 and GPT-5.6 Sol to help solve an open Lorentzian polynomials problem, posting a 75-page arXiv proof.

Aayush Bathija and Prince Rohatgi of Oak Park High School, mentored by UCLA postdoc Daniel Soskin, published the 75-page paper 'Bounded Ratios for Lorentzian Polynomials' (arXiv 2609.05341), solving an open problem in Fields Medalist June Huh's Lorentzian polynomial theory. The main structural theorem extends bounded coefficient-ratio characterization from quadratic to arbitrary-degree polynomials via discrete convexity conditions. The students used Claude Opus 5 and GPT-5.6 Sol for exploration and proof ideas but independently verified all arguments; the result follows an open letter from 25 Fields Medalists voicing concerns about AI's impact on mathematical rigor.

Hacker News · securitySep 14, 12:23 UTC · 2d agoAI research HN 22↑ · 19 comments

Caltech Mathathon – first hackathon ever devoted to research level mathematics

Caltech will host the first research-level mathematics hackathon on October 30, giving 100 teams frontier AI models to attack open conjectures.

The Caltech Mathathon runs October 30 to November 1, assembling about 100 teams that will receive frontier models and over $2 million in AI credits to work on open mathematical problems. Teams will defend their results before leading mathematicians, with prize rounds before and after community verification of the results. The announcement cites recent AI-driven math results, including the disproof of Erdos's 80-year-old planar unit-distance conjecture, the first explicit non-sofic group, and a claimed complex structure on the six-sphere (unverified).

Hacker News · securitySep 7, 09:26 UTC · 9d agoAI industry HN 264↑ · 92 comments1

Leading mathematicians fear AI is making their field dumber, and warn the rest of us is next

Twenty-five Fields Medal winners, including Terence Tao, warn AI companies' benchmark-driven approach to mathematics is misaligned with the discipline's purpose of understanding.

In a joint statement, 25 Fields Medal winners including Terence Tao, Peter Scholze, and Maryna Viazovska warn that AI systems solving major open problems at machine speed undermine conceptual understanding and raise severe attribution and plagiarism questions. The statement lands amid a controversy accusing OpenAI of training math models to beat researchers to a rumored partial solution of a Millennium Prize Problem. The signatories describe a general threat to intellectual work across professions and call for urgent action by mathematicians, AI companies, and society, while not seeking a ban.

The DecoderSep 12, 08:28 UTC · 4d agoAI industry1

OpenAI just wants to win

OpenAI says roughly 10,000 agents and tens of millions in compute solved the Navier-Stokes Millennium Prize problem in 88 hours, amid controversy.

OpenAI claims an advanced unreleased model, run with about 10,000 agents and tens of millions of dollars of compute for 88 hours, produced a solution to the Navier-Stokes problem, one of seven $1 million Millennium Prize problems set by the Clay Mathematics Institute in 2000. NYU professor Tristan Buckmaster, who was pursuing the problem with Anthropic researcher Levent Alpöge, accused OpenAI of racing his team and of possibly benefiting from his Codex prompts; OpenAI categorically denied both. OpenAI researcher Sébastien Bubeck acknowledged offering Buckmaster compute and authorship arrangements, which Buckmaster characterized as a bribe, while many mathematicians expressed unease at OpenAI's competitive conduct.

The Verge · AISep 12, 11:00 UTC · 4d agoAI industry 2 sources1

Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach

Researchers introduce GRAF, a greedy framework for crowdsourcing contest self-selection, and LLMScore, an LLM-driven method that auto-designs its scoring algorithm.

The paper studies self-selection in Tullock contests (SSTC), where workers choose contests and then compete within them. GRAF is a greedy polynomial-time framework that orders workers by a score vector with zero worker regret and platform optimality guarantees in special cases. LLMScore is an LLM-driven evolutionary framework that produces human-readable, inspectable scoring code, jointly optimizing platform utility and worker satisfaction. Across 1,000 synthetic instances in four settings, GRAF with LLMScore achieves high-quality, often near-optimal outcomes with low worker regret, transferring from small training instances to larger, structurally different settings.

arXiv cs.AI / cs.LG / cs.CLSep 7, 16:51 UTC · 9d agoAI research1

Measuring Language Transfer in Robot Policies: Adding Greek to a Cosmos3 Vision-Language-Action Policy

Researchers added Greek to the Cosmos3 vision-language-action policy using only machine-rephrased instructions, finding bilingual training reaches roughly two fifths of English performance.

The paper studies localizing the open Cosmos3 vision-language-action robot policy to Greek without architectural changes, using machine-rephrased instructions only. Bilingual training yields a consistent 6.7-7.1 point margin over controls on a 90-task, three-seed evaluation suite, while Greek-only training gains at most 2.7 points. Several common evaluation instruments, including color-histogram metrics and single-goal benchmarks, produced false conclusions, and results were dominated by seed variation. The authors recommend building guaranteed-null baselines and replicating low-resource-language results across seeds.

Hugging Face daily papersSep 6, 20:00 UTC · 10d agoAI research

ChatGPT Ads expands across Europe

OpenAI is expanding ChatGPT Ads to 31 European markets, letting advertisers reach users as they explore, compare, and decide.

OpenAI announced that ChatGPT Ads is expanding to 31 European markets. The move extends OpenAI's advertising monetization, allowing advertisers to reach users during exploration, comparison of options, and purchase decisions. The announcement has no direct security relevance and carries no risk beyond competitive AI industry impact.

OpenAI NewsAug 18, 22:00 UTC · 29d agoAI industry

A milestone in expanding access to AI

OpenAI announced ChatGPT Ads reached a $1 billion annualized revenue run rate and expanded availability globally to fund free and affordable AI access.

OpenAI stated that ChatGPT Ads, its advertising product, has reached $1 billion in annualized revenue run rate. The company framed this as a milestone that expands global availability of the ads product and supports broader access to AI through free and lower-cost options. No technical, model, or security details were included in the announcement.

OpenAI NewsAug 31, 04:00 UTC · 17d agoAI industry

The Open ASR Leaderboard Adds Its First Global South Language

Hugging Face's Open ASR Leaderboard added its first Global South language, expanding speech-recognition benchmark coverage.

The Hugging Face Open ASR Leaderboard, a community benchmark tracker for automatic speech recognition models, added its first Global South language. This expands evaluation coverage beyond the high-resource languages the leaderboard previously tracked. No further details were available in the announcement text.

Hugging Face BlogAug 28, 00:00 UTC · 20d agoAI research

The Pelican comparison grid for Astra is pretty interesting

Simon Willison's pelican SVG comparison shows GPT-6 Astra producing markedly better images than GPT-5.6 Sol, Terra, and Luna across reasoning levels.

Willison generated pelicans-riding-bicycles SVGs with newly accessed GPT-6 Astra at low through max reasoning levels and rendered them in a comparison grid against GPT-5.6 Sol, Terra, and Luna. Astra's outputs were markedly more coherent, while even the best GPT-5.6-Sol images remained largely abstract shapes. Astra does not support a reasoning=none setting, so all comparisons involved reasoning-enabled runs.

Simon WillisonSep 4, 23:59 UTC · 12d agoAI research

Quoting Jakub Pachocki

OpenAI chief scientist Jakub Pachocki argues powerful aligned AI is needed for defense against AI dangers while warning against reckless racing.

Quoted by Simon Willison, OpenAI's Jakub Pachocki says the need to build defensive systems against dangers posed by other AI is the strongest argument for continuing to train much smarter models quickly. He frames powerful, aligned AI as central to securing infrastructure, protecting against rogue agents in real time, and OpenAI's deployment efforts, while cautioning that racing forward at all costs is absurd given the stakes.

Simon WillisonSep 7, 22:26 UTC · 9d agoAI safety & security

[AINews] OpenAI reports Navier-Stokes singularity find in 88 hours using Astra-next, roughly 10,000 agents and 130B tokens (>$40M), a contender for second ever Millennium Prize awarded

OpenAI-linked accounts claim roughly 10,000 AI agents produced a Navier-Stokes singularity result in 88 hours, pending mathematical verification.

OpenAI-affiliated accounts claim a system of roughly 10,000 agents, trained over about a year with multi-agent reinforcement learning, produced a finite-time singularity result related to the Navier-Stokes Millennium Problem. The claimed 88-hour runtime and 130B-token cost circulate only via social posts, and no preprint, theorem statement, or proof artifact is available. Acceptance by the mathematics community is unresolved, so the claim's epistemic status remains unknown. The roundup also notes Cognition's $48B and Mistral's $24B fundraises, GPT Image 2.5, and Meta's Muse agent relaunch.

Latent SpaceSep 9, 05:04 UTC · 8d agoAI research1

Drama swirls around OpenAI’s legendary mathematical milestone

OpenAI claims an internal AI model solved the 90-year-old Navier-Stokes problem, sparking a priority dispute with mathematician Tristan Buckmaster.

OpenAI announced a solution to the Navier-Stokes problem, one of the $1 million Millennium Prize Problems, using an internal AI model it says outperforms the newly released GPT-6 Astra alongside 10,000 concurrent agents. NYU professor Tristan Buckmaster, who with Anthropic researcher Levent Alpöge published related findings a day earlier, questioned whether OpenAI accessed drafts from his Codex sessions. OpenAI says no specific user data was accessed, though it cannot rule out that de-identified usage data helped improve its models.

The Verge · AISep 8, 20:53 UTC · 8d agoAI industry1

LLM-Based Social Engineering Scams

OpenAI disrupted a Cambodia-based ChatGPT-powered scam network running romance, crypto-investment, gambling, and fake law-enforcement fraud campaigns.

OpenAI disrupted a social engineering network operating from Cambodia that used ChatGPT to run multiple scam types simultaneously. Operators built trust with fake dating personas before pitching fraudulent cryptocurrency and spot gold investments, posed as gambling platforms offering fake bonuses, or impersonated law enforcement agencies demanding fine payments. The network also generated images of forged documents including passports, legal notices, stock-purchase confirmations, and gambling platform interfaces.

Schneier on SecurityAug 27, 09:57 UTC · 20d agoAI safety & security in the wild

OpenAI’s sly mathematical breakthrough sends a chill through academia

OpenAI claims an unreleased model solved the Navier-Stokes Millennium Prize problem in 88 hours using ~10,000 agents, sparking academic scooping controversy.

OpenAI announced that one of its unreleased internal models took 88 hours, running a swarm of roughly 10,000 AI agents, to produce a solution to the Navier-Stokes Millennium Prize problem, a $1 million Clay Mathematics Institute challenge unsolved by humans for nearly 90 years. The announcement triggered allegations from NYU professor Tristan Buckmaster that OpenAI scooped his joint work with Anthropic researcher Levent Alpoge and questioned whether OpenAI accessed his Codex sessions; OpenAI denies using specific user data but concedes de-identified data influence cannot be ruled out. Critics say the rushed, reportedly million-dollar effort violates academic norms around trust and openness, potentially chilling collaboration in mathematics.

The Verge · AISep 9, 21:16 UTC · 7d agoAI industry2

MUSE: Benchmarking Large Vision-Language Models on Multi-Modal Understanding in Situated Education

Introduces MUSE, a twelve-task benchmark evaluating vision-language models on artistic image understanding in situated educational, Southeast Asian contexts.

MUSE is a benchmark assessing large vision-language models on artistic image understanding across twelve tasks spanning visual perception, semantic and affective interpretation, cultural understanding, and compositional reasoning. It decouples image annotation from question generation for controllable difficulty and curates images centering Singaporean and Southeast Asian multicultural contexts alongside Western art. Evaluations of open-source and proprietary models found substantial disparities, especially in affective interpretation and compositional reasoning.

arXiv cs.AI / cs.LG / cs.CLSep 16, 17:26 UTC · 12h agoAI research