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Saturday14 items

  1. English text is being prepared.Research
    AI score66

    Anthropic Report: AI Agents' Work Hours Reach 6 Times That of Humans, Share of Junior Tech Job Openings Falls to 9%

    Anthropic released a report stating that by August 2026, the working hours of interactive AI agents deployed by employees had reached 6 times that of human employees, and in March, the company-wide total agent work hours exceeded human work hours for the first time. The report shows that the share of junior employees in the technology department fell from 21% in early 2025 to 14%, the share of junior tech job openings fell from 27% to 9%, and engineers using coding agents averaged 5 times as many code commits as they did 6 months earlier. The report also says its revenue per employee is 2 to 4 times that of Meta and Google during their high-growth periods, but Epoch AI cautions that the related estimates carry uncertainty.

    #Industry news#Agents#English text is being prepared.

  5. Anthropic ResearchFirst-partyResearch
    AI score75

    Anthropic Research: How AI Is Changing Its Internal Hiring and Ways of Working

    Anthropic has released an internal research report analyzing AI's impact on the company's hiring and work organization, based on data including hiring, AI usage, output metrics, employee surveys, calendars, and recruiting records, as well as interviews with 17 employees. The report says the share of junior employees in technical departments fell from 21% in early 2025 to 14%, and the share of junior technical roles in hiring dropped from 27% to 9%; by August, interactive AI Agents were working six times as many hours as employees, and per-engineer code commits reached five times the level of six months earlier. Human attention has become the bottleneck on Agent output, employees are shifting toward meta-work of building monitoring and orchestration Agents, and hiring now places more value on autonomy and judgment.

    Same story · 6 reports

    #English text is being prepared.#Agents#English text is being prepared.

  6. Anthropic ResearchFirst-partyResearch
    AI score58

    Anthropic study: the gap between the public's and its own employees' expectations for AI

    Anthropic released a study based on an August 2026 survey comparing the AI expectations of U.S. adults and Anthropic employees: 91% of employees believe AI will be able to make Nobel Prize-level discoveries by 2030, compared with 39% of U.S. adults. On average, employees expect AI to be able to do 75% of their current work by 2030, compared with 28% for employed Americans; according to the study's economic model, the median U.S. adult's response corresponds to 5.4% GDP growth in 2030, while the median employee's corresponds to 17.1%. The two groups differ markedly on the share of their own jobs that will be replaced by AI, but both believe that the more replacement there is, the higher the unemployment rate.

    Same story · 4 reports

    #Papers/Research#Industry news#Anthropic

  8. Rohan PaulResearch
    AI score58

    Claude Mythos 5 designs elliptic curve quantum circuits with 17x fewer gates

    In Anthropic's STEM Fellows Program, Harvard physics researcher Andi Gu had Claude Mythos 5 design quantum circuits, surpassing human design records on most of 8 tasks. In one elliptic curve quantum circuit, 17x fewer gates were traded for 12% more qubits; Claude wrote the circuit designs as code, which an evaluator scored and iteratively revised, and it also proved new identities and verified them with formal proofs, making a classical mathematical shortcut work on quantum hardware for the first time.

    Quoted postAnthropic · @AnthropicAI

    New from our STEM Fellows Program: Designing more efficient quantum circuits with Claude. Given plain-language instructions, Claude Mythos 5 designed quantum circuits that improve on the best published ones, sometimes by an order of magnitude or more. More efficient circuits reduce the resources needed by quantum algorithms, which could bring quantum computing applications in chemistry and materials science within reach sooner. Read more: https://t.co/QCvoJLDmBo

    Same story · 4 reports

    #Papers/Research#Reasoning#Anthropic

  11. AnthropicResearch
    AI score56

    Anthropic STEM Fellows Program: Claude Mythos 5 Designs More Efficient Quantum Circuits

    Anthropic's STEM Fellows program has announced a result: Claude Mythos 5, when given natural language instructions, designed quantum circuits that outperform the best published solutions, with improvements of an order of magnitude or more in some cases. More efficient circuits can reduce the resources required for quantum algorithms, potentially enabling quantum computing applications in chemistry and materials science to land sooner.

    Same story · 4 reports

    #Papers/Research#Reasoning#Anthropic

  12. Anthropic ResearchFirst-partyResearch
    AI score73

    Anthropic has Claude autonomously design quantum circuits, with some results outperforming published approaches

    Anthropic gave Claude plain-language specifications for eight quantum circuits along with an automated evaluator; in a closed loop with essentially no human intervention, Claude repeatedly submitted designs and improved them based on scores, finding solutions that use fewer qubits and gates than the best published circuits, with some improvements reaching an order of magnitude. The elliptic-curve modular inversion design came from a single 53-hour continuous run, in which Claude derived a reversible divsteps implementation that requires no storage of branch information and formally verified it with Lean; another effort reduced the gate count of the most expensive Reed-Solomon decoding step in DQI to about 1/12 of Google's previous construction. Anthropic also noted that Claude was initially conservative and tended to stick with known methods, which had to be mitigated by requiring parallel exploration of multiple approaches and occasionally prompting it to broaden its search.

    Same story · 4 reports

    #Papers/Research#Reasoning#Anthropic

Friday31 items

  1. Unite.AIResearch
    AI score63

    Imperial College London paper: search-augmented LLMs often cite web pages they never opened

    Three authors from Imperial College London have published the paper "Retrieved but Not Read: Understanding Why Search-Augmented LLMs Fail to Use Available Evidence," examining why search-augmented LLMs frequently cite web pages they never actually open. The study tested GPT-5.6 Luna and six open-weight configurations including GLM-5.3-Flash, gpt-oss-120b, gpt-oss-20b, gemma-4-31b, and qwen3-8b using 225 facts that changed after February 16, 2026, finding that models often answer based solely on search snippets without opening the source pages; under the same set of search results, the proportion of cases where no page was opened ranged from 2.6% to 76%, and when Luna used its built-in search, 53.6% of turns relied only on snippets. When answering from snippets alone, outdated answers accounted for 6.4% and misleading citations for 6.4%, whereas when pages were opened and cited, these fell to 1.3% and 2.3% respectively; placing the correct page directly into the prompt significantly reduced errors, but some models still favored old information even when shown the new facts.

    #Papers/Research#RAG#Evaluations / benchmarks

  4. 36Kr · AIResearch
    AI score76

    DeepMind AlphaProof Nexus appears in《Science》: autonomously solves 9 Erdős problems

    Google DeepMind's automated mathematical proof system AlphaProof Nexus appeared in the October 8 issue of《Science》, autonomously solving 9 of 353 open Erdős problems, two of which had remained open since 1970. The system uses Gemini 3.1 Pro to draft proofs in Lean, with a compiler verifying line by line and feeding back iterations; the reasoning cost per problem is several hundred dollars. The paper's ablation results show that a simplified system that removes complex structures such as the sub-agent tournament and retains only the large model plus Lean feedback can also solve these 9 problems, though the hardest few are more expensive.

    #Papers/Research#Reasoning#DeepMind