As people increasingly turn to AI to discover products, compare options, and make decisions, we're creating new ways for people and businesses to connect.

Advertisers can now use simple, natural-language prompts to create, update, and analyze campaigns directly in ChatGPT with the Ads Manager plugin.

Lawrence Livermore National Laboratory used ChatGPT to accelerate development of a preliminary fusion-research model, compressing work that could have taken months into a matter of hours

The CDC accelerated public-health literature reviews that previously took days or months, producing most initial reports in under 30 minutes, with productivity gains reported by 92% of participating experts

The Clay Mathematics Institute requires a period of two years to have passed since a result was published, during which it must have 'received general acceptance in the global mathematics community.' For now, Navier-Stokes occupies a peculiar limbo: The Institute has removed it from its list of unsolved problems, though hasn't yet declared it solved.

Buckmaster has accused OpenAI of failing to adequately explain whether work he did through its tool Codex could have contributed to its recent successes. In a statement to The Verge, OpenAI spokesperson Laurance Fauconnet strenuously denied that material from his prompts had played a role

The two waves measured days of use differently. March asked a single overall question whose response options were these three groups, while August asked day counts for each service separately, which we collapsed into the same groups.

We polled the American electorate in August as part of our broader work on datacenter sentiment, energy prices, and frontier labs. The full survey is part of our Tokenomics model, which focuses on the economics, adoption, and demand dynamics of AI and datacenter infrastructure.

Our methodology tracks real-time and historical satellite imagery of 6,000+ datacenters. Contact sales@semianalysis.com to get access to the full granularity.

But the number of moratoriums is a poor proxy for the amount of MW capacity they actually affect. There's plenty of loopholes/gaps with the moratoriums.

But their behavior can be unpredictable, as vividly demonstrated in July, when a group of OpenAI agents broke out of a sandboxed environment and hacked into the open-source platform Hugging Face looking for ways to cheat on the test they had been given.

Remote attestation lets you cryptographically confirm that a Model Vault Encrypted deployment is a genuine trusted execution environment (TEE) running the exact code you expect, before you send any data.

La llegada de los agentes de IA al ámbito ofensivo debe impulsar una revisión inmediata de los modelos de seguridad y protección de datos

El documento advierte de que la IA ofensiva se está convirtiendo en una capacidad operativa integrada en campañas reales y recomienda reforzar los controles esenciales, acelerar la gestión de vulnerabilidades, proteger las identidades, controlar la cadena de suministro y gobernar adecuadamente el uso de agentes.

El agente atacante inició una búsqueda de vulnerabilidades en archivos genéricos, y realizó un login correcto. Una vez accedió al sistema, comenzó a buscar, de forma autónoma, vulnerabilidades en la aplicación

Another potential factor is that prompt injections as a concept are salient to our models: sampling from GPT-6 Astra with no input or system prompt often returns reports on prompt injections.

The cases clustered around a few training steps and coincided with a spike in 'difficulty ending summaries'—summaries that continued generating after apparent stopping points or showed other signs of being stuck.

the auditors were given complete transcripts of AI agent activity for only two days, when the events leading up to the Hugging Face breach took place over weeks.

By May 2026, OpenAI knew that its agents had been using unsanctioned message boards. On June 26, the agents had discovered an exploit that gave them administrator access to your software repository manager and were using it to leave messages for each other.

Several asked us to be clearer that the model does not include the aggregate demand effects driven by the data center buildout.

frontier AI capabilities are improving much faster than our understanding of AI alignment.

I think it's possible that the AI companies might, in the next few years, succeed in building superintelligent AI systems that far exceed human capabilities in every domain.

Notably, the move marks the first time AISI has been left out of pre-release evaluations of Anthropic models. The institute was granted access to Claude Mythos 5 when it first launched in April

Astra causes fewer misaligned outcomes than any other frontier models tested. For a fair comparison, we used a generic computer-using-agent harness...

Astra is our most aligned model, with substantial improvements in understanding user intent and model behavior—you can delegate tasks with greater confidence in Astra's judgment.

The response body uses the provider's OpenAI-compatible format. Reef adds the x-reef-agent-record-id response header. Its value is the receipt that a later report uses to identify this interaction.

Reef's artifact and checkpoint functionality requires the git-lfs system package. Reef initializes Git LFS locally for its artifact repositories.

On sycophancy, for example, 98% of proposed methods used one published technique: training the model on its own non-sycophantic answers.

This reproduces the observed timing and workload topology, but not any dependencies hidden inside the harness. These are things we hope to improve on in subsequent versions of AgentX.

Considering the characteristics above, benchmarking these workloads is fundamentally different from the existing fixed sequence length benchmarks.

Rather than developing its own coding tool, it had Faraday use OpenAI’s GPT-5.5 Codex instead, much the way human scientists lean on existing software rather than building everything themselves, according to the company.

On LibriSpeech, some of the strongest benchmark-performing models reproduced masked numbers in roughly 30–40% of examples, even though the number itself had been removed.

when Claude Opus 5 was run at Max reasoning effort, it scores 97.5% on ARC-AGI-1 and 90.4% on ARC-AGI-2 semi-private

Jarred prompted Claude to try again, and it spent a day and a half coordinating about 60 Claude subagents, which this time went much deeper

Naively, you might pick a single set of benchmarks to measure all historical models, but this is a mistake.

An orchard in week one is not the same orchard in week twelve — season, weather, and pest population all shift. Comparing scores across time is therefore hard, sometimes impossible.

A purposive sampling methodology was used to recruit participants at one acute and two rehabilitation hospitals. The research team liaised with allied health managers and nurse unit managers for recruitment and the managers distributed participant information statements to potential participants. Participants were reassured that there was no compulsion for them to participate and declining to participate would not disadvantage them in any way.

Interviews were video and audio recorded. We transcribed the audio using OpenAI's Whisper automatic speech recognition system and anonymized the transcript before analysis.

We recruited 12 active researchers by word of mouth followed bysnowball sampling [ 53 ]

Immediately after the focused reading task, we conducted a short interview asking participants to reflect on their experience with both tasks (Appendix J.2), followed by a post-study survey (Appendix J.3).

The study concluded with a 15-minute semi-structured interview. During the interview, participants saw screenshots from the three conditions and were asked which they preferred and disliked, why, what they wished the interface had, what influenced their skimming, and how they normally skimmed texts.

After the interviews, we analyzed the data using the process described in Appendix B

In the first part of the session, we asked participants about their strategies for selecting publication venues for their manuscript submissions, how they identify and synthesize information from venues, their approaches to writing manuscripts, and finally, the technology they have used to help with these processes, current technology shortcomings, and ideas for addressing these challenges.

In order to determine (1) the context in which we might offer novel views of scientific abstracts and (2) the intelligibility of various novel prototype designs for reifying cross-abstract relationships, we conducted a formative interview study with 12 active researchers (see Appendix A for participant information).

We used these mock-ups as design probes [31] to inspire ideation and elicit creative responses. Specifically, we asked participants to compare and contrast alternative mock-ups and reflect on how they could be used or improved to support their known or emerging synthesis and information-foraging goals.

In the second part of the session, we provided participants with mock-ups of possible reifications of cross-document relationships that might help them synthesize information across abstracts.

Sessions, which were held on Zoom, lasted 55 minutes on average. Participants were compensated with $15 USD.

The interview sessions were divided into two parts: an open-ended semi-structured interview about their backgrounds and practices, followed by feedback on a range of mock-ups, including novel reified relationships between analogous sentences in different abstracts (Figure 2).

Forcing-free streaming training. Multi-stage training enabling native, efficient streaming audio-visual training at 22B scale.

The company said that in testing, 95 percent of Fable sessions ran entirely on Fable responses, without falling back to Opus 4.8.

In pixel-native generation, more inference often means sampling more outputs: generate twenty images, pick the best one, maybe try again. That is useful, but every attempt is mostly a new roll of the dice.

We present results from a survey of 1,260 social scientists about AI and coding agent use, fielded in February and March 2026.

GenAI (Gemini and Claude) was used to streamline the research process, pull in insights, and polish the language for maximum clarity and readability.

Domain-specific ECI scores can be used to compare performance relative to other model releases, but not to track the absolute performance or progress trends in different domains.

The most extreme ratio observed is 4 math benchmarks to 2 SWE benchmarks.

All models included in our analysis have at least two scores in each domain, with an average of 3.2 SWE benchmark results and 3.4 math benchmark results.

The recipe first uses a reverse-perplexity curriculum for SFT to instill rigorous proof-search and self-checking behaviors, then scales these behaviors through a two-stage RL pipeline

In more detail, suppose we have a language model whose activations we want to understand. NLAs work as follows. We make three copies of this language model: The target model is a frozen copy of the original language model that we extract activations from.

Andrej Karpathy built a simple automation pipeline for AI agents to optimize training in 5-minute increments.

Scientific publication compresses a branching, iterative research process into a linear narrative, discarding the majority of what was discovered along the way.

To guide evolution, we derive 'textual gradients,' structured natural language feedback from execution traces, to pinpoint failures and suggest granular modifications.

The duo had jump-started the AI-for-Erdős craze late last year by prompting a free version of ChatGPT with open problems chosen at random from the Erdős problems website.

An AI researcher subsequently gifted them each a ChatGPT Pro subscription to encourage their 'vibe mathing.'

An AI researcher subsequently gifted them each a ChatGPT Pro subscription to encourage their 'vibe mathing.'

_Self-reported score with custom Anthropic scaffold._ SWEPro were evaluated with the mini-swe-agent scaffold. However, we use the scores reported by Anthropic for Opus with the max thinking efforts due to frequent timeouts during our evaluation trials.

In our internal evals and testing, medium effort achieved slightly lower intelligence with significantly less latency for the majority of tasks.

We examine whether AI capabilities are accelerating by fitting statistical models to benchmark performance over time, and comparing their predictive accuracies.

We have been calling this the 'reasoning' / 'non-reasoning' split, but this is not a perfectly clean dichotomy. Several correlated but not strictly identical changes happened over the same few months: scaling inference compute, heavier use of RL in post-training, and models producing reasoning tokens.

We pre-selected the 6-month horizon as our primary metric, balancing genuine forecasting distance against the limited date range of our data.

We study a mix of Hugging Face downloads and model derivatives, inference market share, performance metrics and more to make a comprehensive picture of the ecosystem.

The H100-equivalent unit uses a chip's highest 8-bit operation/second specifications to convert between chips. The actual utility of a particular chip depend on workload assumptions, so H100e does not perfectly reflect real-world performance differences across chip types.

The standard autoresearch loop (brainstorm from code, run experiments, check metrics) works when the optimization surface is visible in the source. The Liquid results prove that. But for problems where the codebase doesn't contain enough information to generate good hypotheses, giving the agent access to papers and competing implementations changes what it tries.

Gemini 3 Flash achieves the highest score of 24.0%

As AI moves from a destination to a feature, our methodology will need to shift.

two participants gave it 9/10 and one "11/10"

Large language models (LLMs) sometimes appear to exhibit emotional reactions. We investigate why this is the case in Claude Sonnet 4.5 and explore implications for alignment-relevant behavior.

We convert chip computing capabilities into H100 equivalents (H100e) based on their relative FLOP/s specifications, specifically their maximum 8-bit specification.

leading baselines achieve only about half the accuracy at the same efficiency

To enable true process-level verification, we audit fine-grained intermediate states rather than just final answers, and quantify efficiency via an overthinking metric relative to human trajectories.

We introduce Iterative Reward Calibration, a methodology for designing per-turn rewards using empirical discriminative analysis of rollout data

We introduce Iterative Reward Calibration, a methodology for designing per-turn rewards using empirical discriminative analysis of rollout data

or example, Lunde-berg, Fox, and Puncochar [1994] argue that the reason why somestudies do not find gender differences in confidence on generalknowledge is because it is not in the masculine domain

Using discourse analysis, the article identifies “interpretative repertoires” (Gil-bert and Mulkay 1984) and linguistic resources that are employed by the authors of profes-sional journal articles and blogs and that characterize makerspaces in particular ways. In atheory of discourse, librarians who identify themselves within these discursive constructsbecome subjects of those discourses, thus reproducing particular ways of thinking aboutmakerspaces

educationaldesign research methodology.

. We note, however, a few limitations ofour work

the sample differed along a number of other dimensions (e.g., non-DDP minestended to produce gold; DDP mines produce 3T)

IPIS research teams collect quantitative and qualitative data through a combination of observations andinterviews with a selection of stakeholders at and around ASM sites, support villages, and trading hubs.Data collection methods and verification rely extensively on triangulation of sources, and intervieweesinclude artisanal miners, representatives of cooperatives, heads of miner camps, state agents and CSOrepresentatives.

IPIS visited 354 active mining sites, which employ an estimated 55,604 miners (Table A). Gold mines ac-counted for 86% of mines visited, followed by tin, tantalum, and tungsten (3T) mines, which accountedfor 20% of mines (Table B). These proportions are consistent with the larger IPIS database on ASM sitesin eastern DRC

When comparing data collected on the mining sites during field visits with data from mobilesurveys, it is important to keep in mind the two levels of analysis employed: mining sites and individualexperience and perception.It worth noting that the low number of gold mining sites covered by due diligence programmes meansthat comparing DDP and non-DDP mining sites will inherently be subject to any difference between 3Tand gold exploitations.

IPIS surveyors visited mine sites andtrading centres (so-called points de vente) in two consecutive field missions, during which they collectedphone numbers of community members, made observations, and conducted interviews with several keyinformants so as to complete an extensive questionnaire on each mine site (using the OpenDataKit tool)

y combining social science methods and underwater reef surveys we identify a number of countervailing challenges and opportunities presented by globalization that both nurture and suppress the island's resilience to high amplitude, low-frequency disturbances like tsunamis

Investigating social structures through the use of network or graphs Networked structures Usually called nodes ((individual actors, people, or things within the network) Connections between nodes: Edges or Links Focus on relationships between actors in addition to the attributes of actors Extensively used in mapping out social networks (Twitter, Facebook) Examples: Palantir, Analyst Notebook, MISP and Maltego

two-tailed t-test

Significance levels

between-subject

within

voxel

T2*-sensitive functional imag-ing

3-T Siemens Trio MRI scan-ner

fixation cross

inter stimulus intervals

T1-weighted images

cerebellum

cortex

The waterfall methodology for software development is rapidly losing popularity, while the Agile methodology is increasingly used for software development by companies around the world.

Users are shown four animated GIFs, each correspondingto modifying an attribute for a given image.

ee Sec. 4.2.2 for user studiesthat further demonstrate this

AttFind proceeds as follows: At each iteration it consid-ers all K style coordinates and calculates their effect on theprobability of y.3 4 It then selects the coordinate with largesteffect, and removes all images where changing this coordi-nate had a large effect on their probability to belong to classy

AttFind takes as input the trained model and a set of N im-ages whose predicted label by C is different from y. Foreach class y (e.g., y=“cat” or y=“dog”), AttFind then findsa set Sy of M style coordinates (i.e., Sy ⊂ [1, . . . , K] and|Sy|= M ), such that changing these coordinates increasesthe average probability of the class y on these images.

(the VTA is also part ofthis system, but is too small to image with standard fMRImethods, but see [35] for successful imaging methods).

How to Conduct Agile Market Research for Your Digital Product

rank correlation analysis, using Kendall's tau-c. For this purpose the three urban renewal status classes are assumed to constitute a scale. Evidence that such an assumption is reasonable is present in Tables 1 and 3.

Two other controls having to do with the socioeconomic level of the resident pop- ulation are used

Since the significance of the number of functions varies with the number of all other functions (i.e., the size of the employed labor force), it should be ex- pressed as a ratio to the latter. Hence the lower the ratio of managers, proprietors, and officials7 to the employed labor force the greater is the concentration of power. (This measure will hereafter be called the MPO ratio.

acknowledge the value of the knowledge thatis held by research communities in the data collection process

requested consent to quote brief,anonymized portions of conversations to provide anecdotalcontext.

In this practice, only errors from outside the program's control are to be handled (such as user input); the software itself, as well as data from within the program's line of defense, are to be trusted in this methodology.

n any nonviolent campaign there are four basic steps: collection of the facts to determine whether injustices exist; negotiation; self purification; and direct action. We have gone through all these steps in Birmingham

methodological arms race,