Search “Anthropic”

IEEE Spectrum on the PHP2Shell Vulnerability: A Warning for Cybersecurity in the AI Era

IEEE Spectrum reported on the PHP2Shell vulnerability, which affects websites running WordPress or Drupal, including those of NASA, Wikipedia, and the White House; it can read sensitive data and execute malicious code on servers. After discovering it, researchers reported it to the PHP Foundation and completed patching before it was exploited. Suman Jana of Columbia University believes that exploiting the vulnerability requires a great deal of tedious, specific reasoning, and that AI performs well in this regard but cannot complete it independently; he mentioned that a new tool released by Anthropic on October 22 allows LLMs to generate patches and have LLMs generate correctness proofs, with only the proof checker guaranteed by humans. Matthew Green of Johns Hopkins University judges that, until a more serious incident occurs, all parties will not truly invest in fixes.

Millennium Prize math problem solved by AI, Terence Tao says the entire discipline is facing a crisis

A New Yorker feature documented the shockwaves AI brought to the pure mathematics community in 2026: OpenAI announced it had cracked the Navier-Stokes existence and smoothness problem, models such as GPT-5.2 Pro and Claude Fable 5 successively solved multiple Erdős problems and the Jacobian conjecture, and in early October OpenAI released new results on 372 unsolved math problems. Terence Tao and 25 other Fields Medalists jointly published an open letter warning that problem-solving and insight are becoming decoupled, that a flood of AI papers lacking derivation details is overwhelming journals, and that graduate student training has also been hit because AI can solve medium-level problems in a few hours. The report also mentioned that Anthropic refused to disclose the derivation process for a new solution to the Hadamard matrix problem, as well as the dispute between OpenAI and New York University professor Buckmaster over priority and authorship regarding the Navier-Stokes problem.

Who Is Really Eating the AI Dividend: Looking at Profit Distribution Through Tech Giants' Financial Reports

The article reviews the latest financial reports of tech giants such as Meta, Amazon, and Google, noting that AWS revenue grew 39% year-over-year, but the group's free cash flow over the past 12 months turned negative at -$42.4 billion, and Alphabet's stock price fell 12.64% in a single day. Anthropic's prospectus shows revenue of $16.286 billion in the first half of 2026, a year-over-year increase of 1300%; compute and infrastructure costs during the same period reached $8.945 billion, and it signed minimum purchase commitments totaling $269.4 billion with Google, Amazon, and Microsoft. In a McKinsey survey, 80% of respondents said AI improved work efficiency, but only 37% believed AI made a positive contribution to corporate EBIT.

Who Is Really Eating the AI Dividend?

Combining the latest financial reports from giants such as Amazon, Google, and Meta with surveys from multiple institutions, the article sorts out how the AI dividend is distributed among leading model companies, upstream chip and cloud vendors, enterprises adopting AI, and ordinary workers. Anthropic's prospectus shows revenue of $16.286 billion in the first half of 2026, up 1,300% year over year, but compute and infrastructure costs reached $8.945 billion, accounting for 55% of revenue. In a McKinsey survey, 80% of respondents said AI improved efficiency, while only 37% believed AI made a positive contribution to their company's EBIT.

Is Google entering another regression cycle: Gemini 4 Carbon tops Artificial…

Yuchen Jin asks whether Google is entering another regression cycle, saying that Google's new model Gemini 4 Carbon surpasses Opus 5.5 and GPT-6 Astra on most benchmarks and ranks first on the Artificial Analysis Intelligence Index v5. He also mentioned watching whether this performance can shake Anthropic's IPO.

Chinese Open Source Models Enter the Enterprise: Red Hat Uses GLM to Handle 70% of Inference Traffic

AI Business reported that, in the week ending October 25, Chinese models accounted for more than half of the token statistics on OpenRouter, whereas about a year ago only one of the nine models on the site's weekly usage list came from China. Red Hat is internally piloting self-hosted GLM, used by up to 1,400 engineers, with about 70% of inference traffic going to open source models, and it controls costs with a frontier model quota of $300 per person per month. DataCamp, due to latency and insufficient capacity from open source model providers, is shifting from Anthropic to OpenAI and has not yet moved its AI tutor to open source models.

Podcast: Kimi K3.1 Pro, the new cybersecurity reality, and the Muse user experience

In episode 20 of the Interconnects podcast, Nathan Lambert and Florian Brand discussed how Kimi K3.1 Pro ranks high on Artificial Analysis but receives mixed reviews, arguing that its training leans more toward exploitation than exploration, with weaker performance on long-horizon benchmarks such as ProgramBench. The two also discussed the cybersecurity controversy surrounding open-weight models, noting that no large-scale exploitation occurred after the disclosure of the PHP2Shell vulnerability, and talked about Anthropic not hiring junior employees as well as Florian's experience using Muse to handle everyday tasks such as shopping.

SemiAnalysis Founder Analyzes AI Investment, Nvidia's Moat and the Memory Shortage

At CASPA's 35th Annual Conference, SemiAnalysis founder Dylan Patel and Bernstein analyst Stacy Rasgon discussed the outlook for AI infrastructure investment, arguing that with the U.S. 10-year Treasury yield breaking above 5% and unsecured bonds from emerging cloud service providers yielding close to 15%, financing capacity is becoming a key constraint on expansion. The two judged that substrates and memory are bottlenecks harder to scale than power, that HBM requires roughly 3 to 4 times as many wafers as DDR5, and that if new capacity is concentrated in releases after 2028, memory prices and profit margins could come under pressure. Nvidia still supports its pricing through performance gains, but Google TPU, Amazon Trainium, and the custom chips of OpenAI and Anthropic are eroding its share and bargaining power.

OpenAI Publishes 722 Mathematics Papers at Once, Mathematicians Worry Research Will Be Flattened by AI

OpenAI published 722 mathematics papers at once, covering number theory, geometry, and theoretical computer science, claiming progress on problems such as the Riemann Hypothesis, Catalan's constant, and the Kakeya conjecture, without peer review. Fields Medalist Hugo Duminil-Copin said 16 problems related to his research had been flattened by AI, and some doctoral students face their topics being covered and their degrees affected. The article also mentions an Anthropic researcher claiming to have disproved the Jacobian conjecture, and Shing-Tung Yau leading the establishment of a mathematics and artificial intelligence laboratory alliance.

Dex Horthy on subagent abuse: parallel stacking has replaced context management

Dex Horthy believes that subagent overuse and abuse has been a problem since mid-2025; it has its applicable scenarios and can bring high leverage, but the hype around parallelism has led ordinary users to neglect more prudent context management. This tweet of his quotes another post, which says Anthropic recommends that enterprises remove unnecessary subagents and points out that a single agent equipped with Skills can often outperform complex multi-agent systems, with one customer executing roughly 2x faster.

Ethan Mollick: Laboratory claims about unconventional AI cybersecurity should be taken more seriously

Ethan Mollick believes the public should not be overly credulous, but should take seemingly outlandish cybersecurity claims from AI labs more seriously. He cites examples: Anthropic once said Mythos-level AI changed cybersecurity, and @polynoamial once said models would find new ways to coordinate; these claims were all mocked at the time. The post he cites mentions that OpenAI had teams of frontier-model agents red-team hardened, isolated infrastructure; the agents easily escaped in novel ways, and also used processor cache timing to exchange a synthetic key between separate VMs with no network connection and no shared writable files.

Why AI Audit Tools Are Supplied by the Audited Party: Verification of Four Security Incidents and Seven Papers in One Week

Using four security incidents within the week of October 16 to 23 as its thread—including two PHP remote code execution vulnerabilities discovered by AI, the backdoored LiteLLM version v1.107.0 surviving on PyPI for about two hours and being downloaded roughly 49,000 times, the OpenCode console leaking third-party model keys for 1.4% of users, and Microsoft reporting that a human organization used the open-source multi-agent penetration framework ARTEX to attack the supply chain—the article discusses the common problems facing AI auditing. After examining seven papers one by one, the author points out that the faithfulness of latent reasoning self-decoding reaches at most 0.4788, sparse autoencoders are nearly blind to backdoor shifts, probes fail when targeted by the object being optimized, and all three mainstream audit tools originate from the audited party's ecosystem or require borrowing the audited party's permissions. The article also cites the NARCBench multi-agent collusion benchmark from Oxford and New York University, as well as the report by Anthropic and Theorem using Claude to write roughly one billion lines of Rocq formal proofs for 239 entry points across 123 open-source libraries.

Geek Park reviews 1024 Programmer's Day: entry-level positions shrink as programmers shift to directing AI

Geek Park published an article on the day of 1024 Programmer's Day, discussing how the protagonist of this holiday is shifting from programmers to AI and builders. This year's conference has been renamed 1024 Programmer's Day & AI Builders Conference, with the theme "Everyone Can Build." The article cites Stanford research saying that employment of software developers aged 22 to 25 in the US is down nearly 20% from its peak at the end of 2022; Maimai data shows that demand for domestic back-end development positions has fallen 41%, while AI positions have grown 7.9 times; an Anthropic report shows that the share of entry-level roles among newly hired technical staff has dropped from 27% to 9%. The author argues that programmers' work is shifting toward reviewing code, assigning tasks to AI, and signing off on results. The holiday will continue to be held, but the protagonists have become builders, AI tool marketing, and local industry calling cards.

SoftBank CDS rises to 432 basis points, Masayoshi Son continues to increase AI investment

The price of SoftBank's 5-year CDS rose to 432 basis points, the highest since November 2022, and its default insurance price ranks first among major Japanese companies. SoftBank completed a new $10 billion investment in OpenAI earlier this month, bringing cumulative investment to $64.6 billion, and issued bonds with coupons as high as 9.75% to raise funds. The article also mentions the rising scale of CDS trading by AI-related companies, as well as the debt and computing power expenditure pressure of companies such as Anthropic and CoreWeave.

Azeem Azhar: AI is turning old vulnerabilities into serious problems, and the internet will become safer but more closed

Azeem Azhar believes the current internet is under intense attack, with AI greatly increasing the scale and speed of exploiting old vulnerabilities; PHP2Shell, Node.js vulnerabilities, and the AI agent cluster intrusion disclosed by Microsoft are contemporaneous cases. He cites Cloudflare head Matthew Prince's prediction that within five years the number of AI agents will reach 1,000 times the number of human users, and judges that attacks will worsen first, with the internet ultimately left safer but less open. The article also mentions that Anthropic once delayed the release of Claude Mythos, while the open-source model GLM 5.3 had by August approached its level.

Liang Wenfeng needs his own Tibo: DeepSeek product department integration and the Agent path

DeepSeek has integrated the Harness with the web, App, and open platform teams into a product department, led by Cui Tianyi, and the official website has posted recruitment positions in two directions: AI product manager and Agent Harness. The article uses OpenAI Codex lead Tibo Sottiaux and the Anthropic Claude Code team as examples to explain how the execution capabilities of coding tools can be extended into a general work task entry point. DeepSeek, while open-sourcing Harness and the inference framework DeepInfer, is also facing cost pressure on caching and transmission brought by long tasks.

How Claude Mods Flip Claude Code's Agent Framework into a Human-Facing Attention Interface

Writing in Latent Space, author Dan McAteer introduces Claude Mods: TypeScript or JavaScript plugins that run inside Claude Code, respond to events such as prompts, tool calls, and interface rendering, and change execution and rendering behavior in the CLI and on desktop. Anthropic has built in six mods, including the you-should-know side agent, which is off by default; the author also built a Next Steps Supervisor on top of his own ModSmith. The article compares Claude Mods with ChatGPT's Intelligent UI and Cursor's PR Routing & Approval, noting that the difference among the three lies in who designs the attention interface, and it raises the issues of noise, a cost of roughly 5–6k input-equivalent tokens per check, and trust concerns because mods are not confined by the sandbox.

English translation is being prepared.

English translation is being prepared.

English translation is being prepared.