Record 08092026 · captured 2026-09-09
The world looked up Elizabeth Holmes. 30 tracked subjects, 25 discussions, 25 papers. This record is frozen and will not change.
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What the most people looked up, ranked by Wikipedia pageviews for that day.
Elizabeth Anne Holmes is an American businesswoman convicted of fraud in connection with her health technology company Theranos. Holmes founded Theranos in 2003, and its valuation soared in the early 2010s after it claimed to have revolutionized blood testing
Killing of the Clancy children
On January 24, 2023, Lindsay Clancy fatally strangled her three children—five-year-old Cora, three-year-old Dawson, and eight-month-old Callan—at the family's home in Duxbury, Massachusetts, United States. She then attempted suicide by cutting her wrists and n
Labor Day is a federal holiday in the United States celebrated on the first Monday of September to honor and recognize the American labor movement and the works and contributions of laborers to the development and achievements in the United States.
You Can See Everything is a 2026 American documentary film directed by Nathan Fielder and Lance Oppenheim. It follows Elizabeth Holmes, the founder of the defunct health technology company Theranos, who invited a film crew to document her in the weeks before s
Alternative for Germany is a far-right, right-wing populist, national conservative, and in parts völkisch nationalist political party in Germany. It has 151 members of the Bundestag and 15 members of the European Parliament. It is the largest opposition party
Mirzapur: The Movie is a 2026 Indian Hindi-language action crime thriller film directed by Gurmeet Singh and written by Puneet Krishna. Produced by Ritesh Sidhwani and Farhan Akhtar under Excel Entertainment, the film stars Pankaj Tripathi, Ali Fazal, Divyennd
Hanuman Ansh is a 2026 Indian Hindi-language biographical devotional drama film written, directed and produced by Dr Vishal Chaturvedi under his banner, Swambhu Media Network. The film is first instalment of the film trilogy based on his book Divine Detour: Th
Lanterns is an American buddy cop superhero television series created by Chris Mundy, Damon Lindelof, and Tom King for HBO, based on the DC Comics Green Lantern characters Hal Jordan and John Stewart. It is the third television series in the DC Universe (DCU).
2026 Saxony-Anhalt state election
The 2026 Saxony-Anhalt state election was held on 6 September 2026 to elect the 9th Landtag of Saxony-Anhalt, two weeks before the state elections in Berlin and Mecklenburg-Vorpommern. It resulted in the highest vote share for the far-right in Germany since 19
The following notable deaths occurred in 2026. Names are reported under the date of death, in alphabetical order. A typical entry reports information in the following sequence:Name, age, country of citizenship at birth, subsequent nationality, what subject was
Nathan Joseph Fielder is a Canadian comedian, known for his awkward persona and for creating works that blur the line between reality and fiction.
The Gentlemen (2024 TV series)
The Gentlemen is a black comedy crime drama television series created by Guy Ritchie for Netflix and is a spin-off of Ritchie's 2019 film. The series stars Theo James in the lead role and premiered on March 7, 2024. In August 2024, the series was renewed for a
Toxic: A Fairy Tale for Grown-Ups is a 2026 Indian psychological thriller gangster film directed by Geetu Mohandas and jointly produced by Venkat K. Narayana and Yash through KVN Productions and Monster Mind Creations respectively. It stars Yash, Kiara Advani,
Saturday Night's Main Event is a series of American professional wrestling television specials produced by WWE. The series originally broadcast from 1985 to 1992, by NBC until 1991 then briefly by Fox. The specials were briefly revived on NBC from 2006 to 2008
Emma Navarro is an American professional tennis player. She has a career-high singles ranking of No. 8 by the WTA, achieved on September 9, 2024, and a doubles ranking of No. 93, achieved on August 12, 2024. Navarro has won three singles titles on the WTA Tour
Saxony-Anhalt is a landlocked state of Germany, bordering the states of Brandenburg, Saxony, Thuringia and Lower Saxony. It covers an area of 20,555 square kilometres (7,936 sq mi) and has a population of about 2.14 million inhabitants, making it the 8th-large
The 78th Primetime Emmy Awards will honor the best in American prime time television programming from June 1, 2025, until May 31, 2026, as chosen by the Academy of Television Arts & Sciences. The awards ceremony will be held live on September 14, 2026, at the
Spider-Man: Brand New Day is a 2026 American superhero film based on the Marvel Comics character Spider-Man. Produced by Columbia Pictures, Marvel Studios, and Pascal Pictures, and distributed by Sony Pictures Releasing, it is the 38th film in the Marvel Cinem
Alice Elisabeth Weidel is a German politician who has been serving as co-chairwoman of the far-right Alternative for Germany (AfD) party alongside Tino Chrupalla since June 2022. Since October 2017, she has held the position of leader of the AfD parliamentary
Coyote vs. Acme is a 2026 American comedy film directed by Dave Green and written by Samy Burch, who developed the story with James Gunn and Jeremy Slater. Loosely based on the 1990 The New Yorker magazine article "Coyote v. Acme" by Ian Frazier, it follows Wi
The Odyssey is a 2026 epic action fantasy film written and directed by Christopher Nolan, who produced it with his wife Emma Thomas. An adaptation of Homer's ancient Greek epic poem the Odyssey, it stars an ensemble cast including Matt Damon, Tom Holland, Anne
Andrew Williams was an American musician and professional wrestler. He is best known as the rhythm guitarist of the metalcore band Every Time I Die.
Lance Oppenheim is an American filmmaker, documentarian, and producer. His work blends nonfiction storytelling with heightened, cinematic formalism. Oppenheim has received critical acclaim for his films Some Kind of Heaven (2020) and Spermworld (2024). He is a
Elena Andreyevna Rybakina is a Russian-born Kazakhstani professional tennis player. She is currently ranked world No. 2 in women's singles by the Women's Tennis Association (WTA). Rybakina has won 13 WTA Tour-level singles titles, including two majors at the 2
Gopalaswamy Doraiswamy Naidu was an Indian innovator, inventor, industrialist, and educator. He redesigned and transformed imported technologies into practical and affordable innovations for India, and is widely regarded as a versatile genius. His contribution
Neatsville is an unincorporated community in Adair County, in the U.S. state of Kentucky. It is located at the junction of Kentucky Route 206 and Kentucky Route 76. Its elevation is 705 feet (215 m). For unknown reasons, the town's name was spelled as Neetsvil
.xyz is a top-level domain name that was proposed in ICANN's new generic top-level domain (gTLD) Program for consisting of the last three letters of the Latin-script alphabet. XYZ.com and CentralNic are the registries for the domain, which was created by entre
Theranos Inc. was an American privately held corporation that was touted as a breakthrough health technology company. Founded in 2003 by then 19-year-old Elizabeth Holmes, Theranos raised more than US$700 million from venture capitalists and private investors,
Zheng Qinwen is a Chinese professional tennis player. She has been ranked world No. 4 by the WTA, achieved in June 2025, and is only the second Chinese player to reach the top 5 in women's singles after Li Na. Zheng has won five career singles titles, includin
Buddy is a 2026 American postmodernist supernatural comedy horror film directed by Casper Kelly and written by Kelly and Jamie King. The film stars Cristin Milioti, Delaney Quinn, Patton Oswalt, Clint Howard, Michael Shannon, Topher Grace, and Keegan-Michael K
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model
We study the problem of navigating cluttered indoor environments with a humanoid robot. Unlike conventional methods that model navigation as a 2D path planning problem, humanoid traversal in cluttered environments requires continuous geometry-aware whole-body adaptation, including coordinated arm placement, torso adjustment, and gait modulation for collision-free movement through complex 3D spaces. We introduce TANGO
Procedural Graphs: Self-Evolving Execution Structures for LLM Agents
Large language models are increasingly deployed as agents that plan over long horizons and act through external tools. Most agents select actions through unconstrained generation over an accumulating history, leaving implicit the procedural knowledge of what to do, in what order, and under which conditions. As trajectories lengthen, agents can lose track of their objectives, invoke tools out of order, and repeat unpr
The digitization of healthcare has generated vast, longitudinal, and multimodal patient records over a lifetime, yet fully exploiting these data to represent and predict patient state trajectories remains a critical challenge. Current AI models often struggle to capture the complex, irregular temporal dynamics and inherent stochasticity of real-world multimodal patient data. Existing AI approaches for modeling longit
A Data-Driven Framework for Identifying and Prioritizing RPA Opportunities in Healthcare Processes
Robotic Process Automation (RPA) is widely used to reduce administrative burden in United States hospitals, yet an estimated 30-50% of RPA initiatives underperform because processes are selected informally, without a repeatable method to catalogue candidates, prioritize them, match each to an automation tier -- a Python bot, an open-source orchestrator such as n8n, or an enterprise platform such as UiPath -- and fore
Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a critical determinant of agentic task success. Automated harness evolution can enable smaller models to perform well on domain-specific tasks at a fraction of frontier-model cost. Since both the harness and model weights shape behavior, we ask how harness evolution and lightweight fine-tuning should
ExecCritic: Learn to Test, Test to Improve for Coding Agents
Execution feedback can guide coding agents toward correct repository repairs, but only when the tests capture the behavior requested by the issue. Agent-generated tests can encode incomplete or incorrect behavioral targets; when the same trajectory writes both the patch and the test, their errors can agree and create false confidence. We introduce ExecCritic, combining a test--verify--revise scaffold with a role-spec
A Generalization of Amari's Bayesian Duality
Amari's contributions to information geometry and machine learning are well known. Here, we revisit Amari's work on Bayesian duality which has not received as much attention. We connect Amari's Bayesian duality to a convex duality of Bayes' rule. Using this connection, we present a generalization of Amari's Bayesian duality and discuss its relevance for modern artificial intelligence.
Canonical Color as a Lens into Concept Decodability in Vision Encoders and VLMs
Visual encoders construct a representation of the image input for Vision-Language models. How much conceptual, as opposed to immediately visible, information does this representation contain? We use canonical color as a controlled test case to ask whether vision encoders make canonical-color information linearly accessible, even when color is removed from the input image. We construct a dataset of objects with canoni
Dexterous manipulation involves contact-rich and fine-grained interactions with the physical world, posing significant challenges for existing vision-language-action (VLA) models due to severe visual occlusions and complex contact dynamics. While recent works have incorporated tactile sensing into robotic manipulation, most approaches still rely on homogeneous multimodal fusion, lacking adaptive tactile integration a
Long horizon Large Language Model (LLM) agents rely on external memory systems to preserve user preferences and task knowledge across extended interactions. Conventional retrieval mechanisms optimize semantic compatibility rather than downstream utility, frequently introducing outdated, misleading, or conflicting evidence into the active context. We present MeClear, a task conditioned memory clearance framework that
SAEScientist-Bench: Can AI Agents Conduct Autonomous SAE Interpretability Research?
While research on recursive self-improvement (RSI) has predominantly automated model training pipelines, reliable autonomous development demands a missing pillar: post-hoc monitoring and auditing to understand what models learn and ensure safe alignment. Mechanistic interpretability tools are essential to bridge this gap, among which Sparse Autoencoders (SAEs) serve as a cornerstone by isolating interpretable feature
The Surprising Effectiveness of Approximate Value Iteration in Self-Play
Combining search with function approximation has driven major advances in game-playing programs, making self-play algorithms more competitive than ever. Still, the computational overhead of the most popular methods, based on Monte Carlo Tree Search (MCTS), can be substantial. In this work, we investigate whether simpler methods remain competitive in non-trivial, moderately sized games such as Connect Four, Hex(7x7) a
Measuring LLM Sycophancy under Sustained Multi-Turn Pressure
Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations typically use short, pre-specified conversations and may therefore miss failures that emerge under sustained, adaptive disagreement. We introduce SPINE, a benchmark in which an LLM proxy plays a persistent but mistaken user and adaptively challenges a target model for up
GoDeep: Annotation-Free Open-Vocabulary 3D Scene Understanding via Language-Space Lifting
Open vocabulary 3D semantic segmentation methods typically lift CLIP features into 3D. This embeds points in a joint vision-language space known to behave like a bag-of-words on compositional tasks. Furthermore, even annotation free variants often require a large 3D training corpus and a dedicated 3D encoder per domain. Instead we use a vision-language model purely as a translator. It produces structured, entity-leve
Mid-training, the stage between pre-training and alignment, is where a model's per-domain data composition is typically set by data availability rather than principled design. We ask what that decision buys, and whether a later alignment pass can undo it. In a controlled logical-reasoning setting (Qwen3-8B-Base, with a 4B replication; five semantically rule-disjoint KOR-Bench domains) we train 30 allocations spanning
ThinkPrior: Zero-Rollout Difficulty Priors for Cold-Start Prompt Selection in RLVR
In reinforcement learning with verifiable rewards (RLVR) trained with group relative policy optimization (GRPO), the KL-free reward-advantage term studied here depends on within-group reward variation. If all rollouts in a group are correct or all are wrong, their group-relative advantages are identically zero; these zero-advantage silent groups provide no reward-advantage gradient, yet uniform sampling spends 39% of
Clinical AI evaluation should encompass diagnosis and management after adaptive information gathering. We compared Doctorina, eight physicians and four standalone frontier language models in 150 synthetic Polish-language primary-care consultations. Doctorina achieved 82.0% Top-1 concordance versus 57.0% for physicians (difference, 25.0 percentage points; 95% confidence interval, 17.7-32.7) and 97.3% versus 85.0% prim
Time-Varying Data as Sheaves: an Invitation to Narratives
Modern science and engineering increasingly rely on time-varying data, yet the mathematical tools used to model temporal phenomena are often developed within separate disciplines, obscuring common principles and limiting the transfer of ideas across fields. This chapter presents the theory of narratives, an abstract framework for time-varying objects of any mathematical kind that supports both theoretical investigati
Training-Free Task Vectors for LLM Behavioral Control
Task vectors enable post-training model editing by identifying semantically meaningful directions in weight space, typically computed as the difference between a fine-tuned model and its pretrained initialization. However, this reliance on fine-tuning makes discovering such directions costly and limits the practicality of post-training model editing. To address this limitation, we introduce Training-Free Task Vectors
The Audit Decides the Verdict: Instrument Effects Rival Demographic Bias in LLM Decision Audits
Whether a language model looks demographically biased can depend on how the audit asks its question. A charitable-aid benchmark reports that the same models favor minority applicants when rating requests one at a time and penalize some when ranking side by side. We test whether that reversal generalizes to hiring, lending, and medical triage: 40,726 requests to five models, applications differing only in the applican
Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning
Chain-of-thought reasoning provides a structured computation between a model's input and final answer. Yet it is often evaluated through endpoint accuracy, which ignores the path taken to reach that answer. An emerging line of work addresses this limitation using entropy profiles, which track how uncertainty evolves over the reasoning process but do not reveal which competing hypotheses account for that uncertainty.
AI-assisted programming raises distinct questions about who produces code, who feels ownership of it, and who is responsible when it fails. This research note examines these distinctions through a hypothetical enrollment failure and a selective reading of the literature. Identifying the producer of a defective expression does not, by itself, determine the duties of reviewers, release decision-makers, or service opera
Let It Go or Learn to Self-Correct: Continuous Diffusion for Constrained Discrete Tasks
Denoising Diffusion Probabilistic Models (DDPMs) generate samples by starting from noise and repeatedly denoising while keeping each update close to the current noisy state. This behavior is effective in many continuous domains, but its role is less clear for globally constrained discrete tasks, such as Sudoku, graph connectivity, Latin squares, and N-queens. In such settings, early discrete errors can be difficult t
Multi-step LLM reasoning lacks a machine-recheckable ledger: discarded reasoning paths leave no auditable record. We propose the Deposon scattering layer, which binds each node of an LLM-generated concept-decomposition graph to a two-parameter Deposon state; paths undergo three-channel scattering -- transmission, reflection, irreversible dissipation -- obeying T+R+A=1 for arbitrary parameters, with a maximum per-path
Transformers as In-Context Samplers: From Closed-Form Diffusion to Estimation-Free Sampling
A growing body of work establishes that large language models are not mere statistical memorizers, but are capable of in-context learning: performing inference at test time using only examples provided in the prompt, without any parameter updates. Prior theoretical work has shown that this capability extends to supervised learning tasks such as linear regression. We prove that in-context learning extends further to \
Origins publishing files written for machines rather than people. Measured against a frozen cohort, so a change in the number means a change in adoption.
| Signal | Web head Tranco top 1,000 n=1,000 | Web tail sampled to rank 100k n=1,000 | AI-native model & dev platforms n=110 |
|---|---|---|---|
| Any agent-facing signal | 11.8% (118) | 4.6% (46) | 75.45% (83) |
| llms.txt (apex domain) | 9.4% (94) | 3.8% (38) | 60.91% (67) |
| llms.txt (docs subdomain) | 3.8% (38) | 0.9% (9) | 43.64% (48) |
| .well-known/mcp.json | 0.6% (6) | 0.2% (2) | 7.27% (8) |
| .well-known/agents.txt | 0.3% (3) | 0.1% (1) | 0% (0) |
| ai.txt | 0.2% (2) | 0.1% (1) | 0% (0) |
| ai-plugin.json (deprecated) | 0.6% (6) | 0.1% (1) | 0.91% (1) |
Notable events recorded on this day and month across all years.