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GPT-5.6

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Headlines · 7

  1. lieflat less ai tone v2 expands its evaluation corpus

    The author released version 2 of the open-source lieflat less ai tone skill on GitHub, expanding the testing methodology and corpora. The first round used 629 articles, while the second used 270 topic-, fact- and length-matched pairs totaling about 5.2 million Chinese characters. According to the author, the evaluation combined 90 scripted indicators, about 430,000 semantic judgments by Jev, and human review of metaphor appropriateness, identifying Europeanized antithesis, dense parallelism and mismatched metaphors as prominent AI-like traits.

    即刻 · AI探索站 · 🔥 0
  2. Study identifies six linguistic patterns that make AI text harder to read

    Researchers from New York University and the University of Texas at Austin analyzed text from 14 language models, including 120 conversations, 45 coding sessions and 980 essays, and compared it with human writing. They identified six recurring constructions that the models overused: unusual word combinations, widely separated related sentence elements, shortened references with dropped connectors, stacked nouns, nouns converted into verbs, and animate verbs applied to inanimate subjects. Llama and the Olmo base model were closest to human text. In a proof-of-concept experiment, a smaller model trained with a penalty for longer answers favored shorter phrasing under certain conditions.

    The Decoder · 🔥 0
  3. Qwen 3.8 Flash Next Used for a Privacy-Sensitive Academic Workflow

    A Reddit user reports using Qwen 3.8 Flash Next locally through OpenCode with a vLLM backend to manage an MSc dissertation workflow involving student records, supervisors, projects, examiners and grades. The sandboxed system ingested differently formatted CSV exports, built a relational database and generated a project booklet while keeping sensitive records on local disk. The user says the model performed this specific task as well as a frontier cloud model and ran faster than Codex, but this is an unverified personal assessment rather than a general benchmark.

    r/LocalLLaMA · 🔥 0
  4. A Developer’s Guide to Pruning Codex Skills for Stronger Models

    In a Juejin commentary, the author argues that GPT-5.6, K3 and Claude Fable5 can handle many basic development steps that older Skills packages explicitly encoded. Using Codex as the main example, the author recommends retaining only Skills that add scripts, templates, specialist knowledge, personal preferences or reusable checks, while placing routine project rules in AGENTS.md and mechanical safeguards in Hooks, CI, linters or tests.

    掘金 · 人工智能 · 🔥 0
  5. OpenAI API adds 12-hour prompt-cache option; cache writes cost 2.5x

    OpenAI's API will offer a 12-hour cache-retention option, announced by Tibo, who leads ChatGPT and Codex, according to a 智东西 report. The option applies to GPT-5.6 and later models and sits alongside the default 30-minute retention; choosing 12 hours raises cache-write pricing from 1.25x to 2.5x the uncached input token price while cache-read pricing is unchanged. Tibo also said cache retention for logged-in Codex and Work users would be permanent, but 智东西 notes that no formal announcement had been published and that the implementation and billing treatment remain unclear. OpenAI's API documentation states the 12-hour setting defines the minimum lifetime for cache-read billing eligibility and does not guarantee cache reuse or lower latency, the report said.

    智东西 · 🔥 0
  6. OpenAI details Third Moment Research running 10,000 agents for 36+ hours

    OpenAI published a case study saying startup Third Moment Research uses Codex along with GPT-6 Astra, GPT-6 Sol and GPT-6.1 Sol to run 10,000 agents at once on investigations lasting 36 to 48 hours. It says Codex with GPT-5.6 found a quantitative backtesting bottleneck and cut a year-long order-level US equity backtest from roughly 3 hours to roughly 3 to 5 minutes, while an outer harness decides whether to retry, terminate or escalate unfinished tasks to humans. A 36Kr report adds figures not stated in OpenAI's post, including about 1 trillion tokens per day and a 97% reduction in backtest time.

    OpenAI · 🔥 0
  7. Atlassian and OpenAI Expand Enterprise AI Partnership

    Atlassian and OpenAI are expanding their partnership, with OpenAI frontier models powering agents across Atlassian’s platform and Rovo. The agreement also expands Atlassian’s access to models including GPT-6 Astra and the GPT-5.6 series, while connecting ChatGPT and Codex to Atlassian work data through plugins and the Teamwork Graph.

    OpenAI · 🔥 0

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