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SK Hynix filed to raise up to 45.45 trillion won (~$29.4B) via a Nasdaq ADR listing

A gameplay clip is not merely pixels. It is pixels plus choices.

South Korea’s Ministry of Climate, Energy and Environment said it was working to secure 6.3 gigawatts of electricity and 650,000 tons of water for the southwestern chip plants, along with an additional 8 gigawatts of power to support the new AI data centers

The government’s goal is to double South Korea’s production of dynamic random-access memory (DRAM) within five years.

Jonathan Rinderknecht was facing arson charges for setting a fire on New Year’s Day in 2025, which became one of the deadliest wildfires in LA history.

a directional estimate of roughly 82 hours/week of security-team capacity unlocked.

HP’s channel ecosystem is a major platform opportunity with more than 80% of its business flowing through partners, and 100,000+ partners using the Partner Portal globally.

One engineer used OpenAI models to move through 122 pull requests across 43 projects in a matter of weeks.

Rubicon Water Says FY26 Revenue Expected To Be A$60 Million-A$62 Million

Vietnam Q2 GDP grows 8.39% y/y - statistics office

[Analyze on Supercharts](https://www.tradingview.com/chart/?symbol=NASDAQ%3AANTHROPIC)

A locally set model can be fine-tuned to our needs, and cannot be taken away. Businesses can use them for proprietary and sensitive data.

30 tokens per second is not bad, well within typical frontier model API range.

A common 8-bit quantization saves half the space at almost no cost to quality. Going further down the road, models are smaller (and potentially - faster), but at the cost of quality

Then, we segment sentences within each aspect into grammarpreserving chunks (see prompt used in Appendix D.2). This results in grammatically coherent chunks that are the basis of structure patterns. After identifying chunk boundaries, we again prompt an LLM to generate labels for chunks in a human-in-the-loop approach: starting from an initial set of labels for chunk roles, when a new label is generated, a researcher from the research team examines the new label and merges it with existing labels if appropriate, controlling for the total number of labels.

After obtaining an expanded set of high-level chunk labels, we assign them to each of the sentence chunks by using LLMs in a multiclass classification few-shot learning task, with the initial labels and assignment as examples (see prompt used in Appendix D.3).

We process this data in a three-stage pipeline (Figure 6). In the first stage, Sentence Segmentation and Categorization, abstracts are split into individual sentences using the NLTK package, and each sentence is classified into one of the five pre-defined aspects as listed in Section 4.1.1. Classification is performed by prompting an LLM (see prompt used in Appendix D.1) with the sentence and its full abstract.

We conducted a qualitative analysis of user study transcripts and survey responses using a Grounded Theory approach [8]. First, the lead researcher collected a list of participants' behaviors, approaches, reflections on their experience, and feedback about the interface. The researcher then systematically coded this data, revisiting the data multiples times and refining the codes to ensure consistency and coherence. Through this process, high-level themes were identified and organized using affinity diagramming. Once the thematic structure was finalized, the researcher gathered supporting evidence for each theme and synthesized the findings, which were reviewed by the research team to ensure agreement on the results.

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 analyzed the interview data using thematic analysis [1]. First, two members of the research team independently coded four (25% of collected data) randomly chosen participant data to generate low-level codes. The inter-coder reliability between the coders was 0.88 using Krippendorff's alpha [37]. The two coders then met together to cross-check, resolve coding conflicts, and consolidate the codes into a codebook across two sessions. Using the codebook, the two coders analyzed six randomly selected participant data each. The research team then met, discussed the analysis outcomes, and finalized themes over three sessions.

Activity log data, which revealed how participants actually used the interface, echoed the above findings. According to the log data, participants spent most of their reading time (66.31%) with vertical alignment on the second element in structure pairs, followed by alignment on the first element (29.19%), and left-justified alignment (5.13%). Highlighting usage showed a similar preference: 91.13% of time with all chunks highlighted, 8.25% with partial highlighting, and minimal time (0.63%) without highlights.

In this section, we present findings on how AbstractExplorer supports comparative close reading at scale by integrating quantitative survey responses and log data with qualitative analysis of transcripts and open-ended responses. The qualitative analysis process is described in detail in Appendix H.

Throughout the two tasks, we also collected detailed interaction logs including counts of user-defined aspects created, duration of highlighting usage, and time allocation across the three possible alignment options.

Using a two-tailed Mann-Whitney U Test, we found that participants who reported their lowest perceived cognitive load when all three features were enabled had significantly lower NFC than participants who reported their lowest cognitive load level when skimming with no features enabled—in the baseline interface (p=0.03).

Both gaze data and the semi-structured interviews revealed that lower NFC participants were more willing to be guided by the three features and took advantage of them consciously.

To compute a participant's NFC score, we averaged their response to the six questions, each ranging from 1 to 7, after reversing the appropriate questions.

For simplicity of analysis, we denote participants with NFC scores above the overall participants' median NFC of 5.42 (IQR = 0.583) as higher NFC, and lower NFC otherwise.

The raw NASA-TLX score is the sum of all 6 NASA-TLX questions after reversing the appropriate questions.

We collected 80 sentences from our abstracts dataset labeled by our system as "Methodology/Contribution." Participants viewed the same 80 sentences in each condition—often with a different subset of sentences initially visible due to ordering changes—but only had two minutes to look at them in each condition.

To contrast participants' gaze patterns in each condition, we used a Tobii Pro Spark eye-tracker placed below the desktop monitor used by all subjects; Tobii Pro Lab software recorded each participant's gaze over time in each condition.

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

With datasets like LOCUS we’re going to make the strange half-seen rules and laws that govern much of civic, local life be made accessible to AI systems, which may eventually allow them to better adapt themselves to hyperlocal purposes.

The 2025 [Stack Overflow developer survey](https://survey.stackoverflow.co/2025) put 84% of developers on AI tools, with 46% saying they do not trust the output, up sharply from 31% the year before.

An AWS engineering team described an 18-month rearchitecture, originally scoped for 30 engineers, was completed by 6 people in 76 days.

LinkedIn replaced its associate product manager track with a 'Product Builder' program that trains generalists across product, design, and engineering.

Robot Park and other global sites collect real-world data from Apollo 2 robots in logistics and manufacturing, training the embodied-AI models crucial for Apollo 3's performance and scalability.

The technique worked on a wide range of AI browsers, including ChatGPT Atlas, Comet, Fellou, Genspark, Sigma, and the Claude Chrome plugin.

The malicious site in the proof-of-concept exploit presents the browser with an instruction to win a game by solving a puzzle. The puzzle, however, rewards incorrect answers, such as 2 + 2 = 5.

After that, an attacker has free rein to invoke all kinds of destructive actions, such as extracting code from a private repository or extracting credentials from the built-in password manager.

The lighter treatment carried roughly a 60% success rate for his presentation. The aggressive one brought that number to around 85%.

He had an aggressive, fast-growing form of non-Hodgkin’s lymphoma — a rare diagnosis affecting roughly one in 420,000 people, caused by a random genetic mutation with no connection to lifestyle, diet, or stress.

He had been doing the annual bloodwork for four consecutive years, following the protocols of longevity researchers like Peter Attia and Rhonda Patrick.

TabFM is trained entirely on hundreds of millions of synthetic datasets.

Tabular data constitutes the backbone of enterprise data infrastructure and powers a significant fraction of critical predictive machine learning applications.

The proposal is to treat data generation as a data scientist agent loop with creation, analysis, and meta-optimization...

It provides substantially improved cost efficiency at medium effort; its higher-effort performance can match Opus 4.8 on some tasks.

It’s a substantial improvement over its predecessor, Sonnet 4.6, on important aspects of agentic performance like reasoning, tool use, coding, and knowledge work:

Our safety assessments found that Sonnet 5 shows an overall lower rate of undesirable behaviors than Sonnet 4.6, and is generally safer to use in agentic contexts.

Sonnet 5 narrows the gap: its performance is close to that of Opus 4.8, but at lower prices.

Claude Sonnet 5 is built to be the most agentic Sonnet model yet. It can make plans, use tools like browsers and terminals, and run autonomously at a level that, just a few months ago, required larger and more expensive models.

In the right geographic location, with the right system design, you don't need any refrigeration equipment. You can just put big radiator coils outside and use the air temperature for all your cooling. It's incredibly efficient.

Async agents are moving into everyday work. For an agent to be trustworthy and useful inside an organization, it needs real enterprise data: CRM records, repositories, inboxes, knowledge bases.

The number of model parameters $N$ needed to fit a dataset of size $D$ also scales as a power law.

Classic scaling laws assume effectively _unlimited unique data_, no repetition, and no multi-epoch training.

Anthropic said operators affiliated with Alibaba and its AI lab carried out 28.8 million exchanges with its models using roughly 25,000 fraudulent accounts between April 22 and June 5.

AI napędzi polską gospodarkę, ale są też koszty. Grubo ponad ćwierć miliona osób może stracić pracę

Epicenter separates app-owned data from user-owned Markdown. App output belongs under apps/<name>/; folders you own stay ordinary Markdown.

Ile czasu przeciętny Polak spędzi w internecie? Dane z raportu

Codex weekly active users in Korea have grown nearly 800% since February 1, 2026.

More than 5 million people now use Codex every week for technical and non-technical workflows and roles.

This represents one of OpenAI’s largest enterprise deployments to date.

the estimated value of the average session rose by 27% between October and April

the share of sessions spent fixing broken code fell by nearly half, from 33% to 19%

each prompt the user sends sets off a chain of around 10 actions taken by Claude on average

people make about 70% of the planning decisions but only 20% of the execution decisions

Claude Code users now spend an average of 20 hours per week using the tool.

we introduce a framework for studying interactive agentic coding based on a privacy-preserving analysis of ~400,000 Claude Code sessions from between October 2025 and April 2026.

In typical novice sessions, each prompt sets off about five Claude actions and roughly 600 words of output, while expert sessions set off action chains more than twice as long (12 actions) carrying five times the output (3,200 words)

each prompt the user sends sets off a chain of around 10 actions taken by Claude on average

people make about 70% of the planning decisions but only 20% of the execution decisions

we introduce a framework for studying interactive agentic coding based on a privacy-preserving analysis of ~400,000 Claude Code sessions from between October 2025 and April 2026.

53 million square feet of data centers have been constructed over the past 20 years

the number of active opposition groups more than doubled to 833 across 49 states

$130 billion in data center projects blocked by protests so far this year

A public dataset is not encountered in the same way by every actor. For one community, it may be a tool for language preservation, research or local innovation. For a large company, it may become one more input into a product that returns little value to the people represented in the data.

In testing with an RTX 5090, DiffusionGemma spits out around 700 tokens per second. With a single Nvidia H100 AI accelerator, DiffusionGemma can produce 1,000+ tokens per second.

In testing with an RTX 5090, DiffusionGemma spits out around 700 tokens per second. With a single Nvidia H100 AI accelerator, DiffusionGemma can produce 1,000+ tokens per second.

The move makes it the third company to file for what could be a trillion-dollar IPO this year.

The IPOs could value each of these companies at over $1 trillion despite all of them being unprofitable and having roughly 80 percent to 90 percent lower sales than nearly every existing trillion-dollar public company.

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

Google will pay SpaceX $920M per month for compute

NASA, which has a nearly $4 billion contract with SpaceX to use Starship as a Moon lander, still isn't ready to commit to a test mission with the vehicle scheduled for late 2027.

SpaceX assessed the total market for that business as $22.7 trillion, compared to $2.4 trillion for AI infrastructure and just under $2 trillion for the company's space efforts.

Both exercises find SpaceX significantly less valuable than the nearly $1.8 trillion assessment proffered by the company's bankers. Morningstar assigns a value of about $825 billion, while Damodaran suggests the company is worth $1.2 trillion.

The $75 billion stock offering is reportedly deeply over-subscribed, with some institutional investors ponying up for $10 billion blocks of Elon Musk's empire.

A newly disclosed letter shows the warnings went unheeded: US Central Command now confirms it has received “multiple threat reports concerning adversary exploitation of commercial location data to target or surveil US personnel in theater”—the first official acknowledgment that the data-broker economy is being used to hunt American forces in the Middle East.The targeting was first reported by Reuters, which obtained the Centcom letter. But the confirmation lands atop a record that is longer and more damning than the single document suggests.

Published Time: 2026-06-07T00:00:00Z

Composer 2.5 is exceptionally intelligent & up to 10x more efficient than similarly capable models.

Pulled the trigger today & switched 100% of Lindy traffic to DeepSeek v4, churning from Anthropic models. Saves us millions of $ & we're actually seeing an _increase_ in performance on many core use cases.

Read by 150k+ founders & operators.

switched 100% of Lindy traffic to DeepSeek v4

Composer 2.5 is exceptionally intelligent & up to 10x more efficient than similarly capable models.

$84 vs $954 across the same 100 tasks, or ~11x cheaper.

while token usage continues to grow exponentially.

Read by 150k+ founders & operators.

agents often lack a dependable way to access the databases containing the information they need.

FrontierCode produces 81% less misclassification errors than other leading benchmarks.

Kimi K2.6, the best-performing open-source model, achieves just 3.8% on Diamond, 16% on Main and 37% on Extended.

Claude Opus 4.8, achieves a score of only 13.4%. Other models score significantly lower: GPT-5.5 receives 6.3%, Gemini 3.1 Pro 4.7%, and others even less.

We achieve an 81% lower false positive rate compared to SWE-Bench Pro.

20+ world-class open-source developers built realistic, diverse, and challenging coding tasks from the repos they maintain, spending more than 40 hours per task.

Before rolling out the enhancements and features, Apple was adamant about its privacy-centric approach to AI. 'We believe privacy in AI is non-negotiable,' Apple Senior Vice President Craig Federighi said during the stream

Tracking token costs is a trillions-of-rows-a-month data problem. You can't just stick that into whatever spreadsheet or even basic tool.

Each person on the team gets their own slice of the brain, scoped by login. When you query, you only see what you're allowed to see — never another person's notes, never another team's data. We fuzz-tested this across every way you can read the brain (search, list, lookup, multi-source reads) and got zero leaks.

Children cannot meaningfully consent to data collection, and parents often don't fully understand the extent of what's being collected. AI toys gather voice recordings, conversation transcripts, usage patterns (when, how long, and what topics), emotional tone analysis, behavioral data (what makes the child engage or disengage), and derived insights into development, interests, and emotional states.

By offloading analytics execution to CXL-based computational memory like the MX1, intermediate data can be processed closer to where it resides, reducing memory bottlenecks and unnecessary data transfers.

Scale-out analytics frameworks such as Spark, Databricks, and Snowflake rely on clusters composed of many servers to handle memory-intensive ETL workloads, which leads to high infrastructure cost and inefficiencies from data movement and memory pressure.

The external script identifies links to other workbooks in the stolen data, exfiltrates the discovered workbooks, and continues across all workbooks it can find

A single indirect prompt injection attack triggered by a single benign user query can trigger all of the following effects at once: Exfiltration of many workbooks from across the victim's account

OpenAI选择砍掉视频应用，把算力集中到GPT-5.5的Agent架构和Codex代码工具上

Ilya Sutskever的SSI获20亿美元融资押注新范式，Yann LeCun离职Meta创办AMI Labs，融资10.3亿美元，估值35亿。

20亿参数对比同体量自回归模型、千亿参数LLaDA2.0，连续路线的scaling曲线健康有效。

ELF用Flow Matching完成生成，仅32个采样步生成质量就超过离散模型1024步结果

训练数据约450亿token，仅为主流方法的十分之一。

KPMG and UT Austin's research helps clarify what that human should be doing

KPMG becomes a preferred consultant for deploying Claude and Anthropic's agents into those portfolio companies

Anthropic raises $65B in Series H funding at $965B post-money valuation

Building an AI agent to help clients adjust to changing tax regulations used to take weeks and required teams to switch between multiple tools and chat windows

every one of KPMG's 276,000+ employees globally will gain access to Claude

KPMG—one of the world's largest professional services firms for audit, tax, legal, and advisory services across 138 countries and territories

Currently, the US only fully manufactures about 10 percent of the chips it requires

Tech giants collectively plan to spend $750 billion on AI infrastructure this year, with "a significant portion" of that expected to "go towards chips for data centers"

Four years ago, five years ago, Nvidia was spending about 10, 15 billion dollars a year in Taiwan. Now we're spending 100, going to 150 billion dollars in Taiwan each year.

Nvidia will invest $150 billion a year to make Taiwan an AI "epicenter."

Adoption differences extend beyond discipline and career stage. We classify researcher names according to gender and find that those with typically male names have adopted coding agents at more than twice the rate of respondents with typically female names.

Claude Code is the most common coding agent tool reported, with 86% of users reporting Claude Code use (31% report using Codex, the next most common tool).

On a 1 to 10 scale, 88% of respondents were above a 5, and half were at 8 or above. Figure 6 shows that these ratings vary strongly with AI use. The left side of the plot shows researchers that use AI for more types of tasks are more optimistic.

Coding agent users are starting projects at a pace of around a quarter of a paper more and posting around a half of a working paper more than non agent users. In percentage terms, coding agent users look around 10% (empirical projects started) to 75% (working papers posted) more productive than others in their discipline and career stage.

There are sharp disparities in use of coding agents. Twice as many researchers with typically male names use coding agents as those with female names. Researchers at top universities are 40% more likely than others to use coding agents.

The vast majority of respondents (81%) have tried using AI chatbots in research, particularly for writing code and editing prose. But only 20% have adopted coding agents—tools like Claude Code that autonomously write and execute analysis code—into their work.

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

The time from business to production workflow drops from months to days.

McKinsey predicts that by 2030, three-quarters of current jobs will require redesign, upskilling, or redeployment

Although 85% of organizations say they want to be agentic within the next three years, 76% say their current operations and infrastructure can't support that change.

the unemployment rate for recent college graduates rose to 5.6%, while the underemployment rate (the share of graduates working in jobs that typically do not require a college degree) reached 42.5%, its highest level since the covid pandemic

workers aged 22 to 25 in the most AI-exposed occupations experienced a 16% relative decline in employment after the spread of generative AI

the unemployment rate for recent college graduates rose to 5.6%, while the underemployment rate (the share of graduates working in jobs that typically do not require a college degree) reached 42.5%

workers aged 22 to 25 in the most AI-exposed occupations experienced a 16% relative decline in employment after the spread of generative AI

Vibe drafts the deliverable using the Canvas tool, from a one-page brief to a report, an RFP response, or a board deck

Sessions can run in parallel, can persist while your machine is off, and can be triggered from third-party apps, such as Slack (coming in June)

Mistral Vibe extension for VS Code; the coding agent working across your whole project, inside your IDE.

Team, $24.99/user/month: a shared workspace with admin controls and more storage.

Pro, $14.99/month: complex tasks, deeper reasoning, and all-day coding.

Over the last 20 years the fastest-growing occupation in the US was manicurists and pedicurists. But following close behind? Compliance Officers.

annual employment growth for coders has slowed significantly—by about 3%—since the introduction of ChatGPT

16% decline in entry-level jobs in AI-exposed occupations

a little over 40% of workers but adoption varies by sectors

US Census data showing that only one in five companies are using AI in any business function.

Crete practitioners prepare tens of thousands of tax returns each season which requires working through millions of underlying documents.

Over the past six months, OpenAI forward deployed engineers and researchers along with Thrive Holdings' engineers collaborated to build Tax AI

One senior accountant who spent 180 hours on tax prep last year spent only 15 hours on it this year.

Rental properties took about six weeks and substantial engineering oversight to reach 90% precision and recall

At launch, only a quarter of returns were at 75% correct field completion, but within six weeks, 86% hit that mark.

Even today, colonialism assumes new forms. It no longer dominates only bodies, but appropriates data, transforming personal lives into exploitable information.

In practical terms, in the age of AI and robotics, ensuring that the economy favors human dignity means adopting certain criteria for firm action. First, transparency and accountability: when data and algorithms influence credit distribution, personnel selection or access to services and opportunities, it is necessary that decisions be understandable, contestable and subject to oversight, so that individuals are not reduced to mere profiles. Second, inclusion and access: the benefits of innovation must be paired with investments in skills, infrastructure and essential services to ensure that technology does not widen the gap between those who have and those who have not. Finally, measures to ensure equity: taxation, social protection and industrial policies must correct the imbalances created by the concentration of wealth and power. Indeed, these criteria do not constitute a curb on innovation; instead they make it civilized and humane.

Moreover, ownership of data cannot be left solely in private hands but must be appropriately regulated. Data is the product of many contributors and should not be treated as something to be sold off or entrusted to a select few. It is necessary to think creatively in order to manage data as a common or shared good, in a spirit of participation, as Saint John Paul II already suggested regarding collective goods. [128]

It claims 8 million global users and 100 trillion tokens processed per month

after raising $40 million in Series A funding in June 2025

it landed at about $1.3 billion post-money

Claude Opus 4.7 has been used to patch over 2,100 vulnerabilities

on average, a high- or critical-severity bug found by Mythos Preview takes two weeks to patch

90.6% (1,587) have proved to be valid true positives, and 62.4% (1,094) were confirmed as either high- or critical-severity

Mythos Preview has found what it estimates are 6,202 high- or critical-severity vulnerabilities in these projects (out of 23,019 in total)

their rate of bug-finding has increased by more than a factor of ten

we and our approximately 50 partners have used Claude Mythos Preview to find more than ten thousand high- or critical-severity vulnerabilities

Claude Opus 4.7 has been used to patch over 2,100 vulnerabilities

on average, a high- or critical-severity bug found by Mythos Preview takes two weeks to patch

90.6% (1,587) have proved to be valid true positives, and 62.4% (1,094) were confirmed as either high- or critical-severity

Mythos Preview has found what it estimates are 6,202 high- or critical-severity vulnerabilities in these projects (out of 23,019 in total)

their rate of bug-finding has increased by more than a factor of ten

we and our approximately 50 partners have used Claude Mythos Preview to find more than ten thousand high- or critical-severity vulnerabilities

V4-Flash by default for cheap iteration; /pro lifts a single turn to V4-Pro

Node ≥ 22 on macOS / Linux / Windows

In long sessions the bill typically lands at ~1/3 of comparable generic tooling.

$0.07 /Mtok in · $0.014 /Mtok cached

long sessions hold 90%+ cache hit and input-token cost collapses to ~1/5

Perceptual BD-rates are based on human ratings from a large-scale subjective study

search over millions of model configurations to jointly optimize over perceptual quality and on-device runtime

Based on large-scale subjective user studies

faster than most top ML-based codecs run on a V100 GPU

on an iPhone 17 Pro Max, it encodes 12MP images as fast as 230ms, and decodes them in 150ms

error analysis identifies data-layer defects (e.g., incorrect query composition and ORM runtime violations) as the leading root causes.

the best data filter may be **no filter**, with projections suggesting the crossover for internet-scale pools lands around **1e30 FLOPs**

Another secondary summary gives Humanity’s Last Exam: 64.7% vs 53.1%, possibly under different setup/effort/tool conditions.

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 SWE overperformance has been consistent across most generations, and remains in recent models.

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.

Opus 4.6 and 4.7 both have Math-ECIs within 1 point of their general ECI, compared to larger gaps for earlier models.

On average Claude models have an SWE-ECI 2.7 points higher than their general ECI, and a Math-ECI 1.8 points lower.

We don't train on your data by default on our Team and Enterprise Plans.

We intend to publish our thinking and decision-making as we do

The first of these will be released publicly later this year

In sub-Saharan Africa and India, we are creating AI-powered apps that support foundational literacy and numeracy programs