Week 40, 2026 · Beginner · for younger readers

Newly checked in Week 40, 2026

This week, the most news came from Physical World & Real-World Impact (5 items). In all, 18 items were newly checked, and 9 areas moved. There were 7 new names too — NVIDIA (Saša Zdjelar), Anthropic, CEPI, WHO AFRO, INRB.

18records added

9axes that moved

Sep 28–Oct 4dates

1,187total records then

Added, by axis

Axes with the most records come first. A record that spans several axes is counted once, under its main axis.

⑭5 records

Physical World & Real-World Impact

Sep 24, 2026NVIDIA, Google DeepMind, EMBL-EBI and others — Released predicted 3D structures of protein complexes from more than 2,800 virus species through the AlphaFold Database — generated by accelerating AlphaFold2 with the NVIDIA BioNeMo inference runtime; says about 30% of the protein interactions are being reported to science for the first time. The BioNeMo structure prediction pipeline was open-sourced along with it. Participants include CEPI, Seoul National University, Sungkyunkwan University, the Swiss Institute of Bioinformatics and the University of Glasgow
Sep 23, 2026Airbnb, OpenAI — Airbnb announced it is expanding GPT-6 Astra access across its engineering and product organizations — using it through both the OpenAI API and Amazon Bedrock. Beyond coding, it is used to pin down complex bugs, design system architecture and brainstorm development strategy, and it is also applied to search, fraud prevention, customer support and insurance claims processing. Airbnb CTO Ahmad Al-Dahle said development teams are shipping about 80% more features than a year ago, and gave the example of strategy-document work that took more than 20 attempts with another model being done in 3–4

⑩3 records

Safety, Alignment & Interpretability

Sep 25, 2026Zhenhua Zou et al. — AgentKernel released — treats as the problem the very structure of performing privileged operations while processing untrusted inputs, as in prompt injection and memory poisoning, and proposes building an OS layer as a mandatory service that cannot be bypassed. Its four pillars are identity, for cross-organizational collaboration; perception, which replaces single-point defenses with staged filtering; cognition, i.e. memory governance with information-flow control; and execution, which reduces semantic-level requests to kernel-level permissions and enforces them. It applies classic OS security principles not to code-level threats but to semantic-level failures
Sep 22, 2026OpenAI — OpenAI published "Priorities and principles for effective third party assessments" — it sets out four priority areas for third-party assessment (evaluating safety cases that span training, evaluation, and internal and external deployment; evaluating core safeguards, including adversarial testing and monitoring; preparedness capability evaluations, such as chemical, biological and cyber, along with alignment evaluations; and investigating alignment-failure incidents) and seven principles (clearly specified, agreed assessment targets; proportionate access; transparency of methods and criteria; expertise, independence and disclosure of conflicts of interest; security and confidentiality; a guaranteed remediation period before publication; and responsible disclosure). As examples of access it has provided in the past, it cites technical safeguard information, viewing of chains of thought, and non-public deployment data

⑥2 records

Reasoning Models & the AGI Debate

Sep 22, 2026Anthropic — Claude Opus 5.5 released — company-reported scores: Terminal-Bench 4.0 66.4% (Opus 5: 52.3%), FrontierCode v1.1 54.4% (48.0%), GDPval-AA v2.1 1846 Elo (1708), and OSWorld 2.0 partial-credit score 81.8% (74.0%). Pricing per 1M tokens is $4 input, $20 output and $0.20 for cache reads, lower than Opus 5 ($5/$25/$0.50), and Anthropic claims 40% lower operating costs and more than 30% faster output than Opus 5. Available as claude-opus-5-5 on AWS, Google Cloud and Azure. Improvements in prompt-injection resistance and in safety on automated behavioral audits were also presented
Sep 22, 2026OpenAI — GPT-6 Sol and GPT-6 Luna released — two tiers below Astra: mid-range (Sol) and entry-level (Luna). Per 1M tokens, Sol costs $2/$10 and Luna $0.10/$0.50, which the company announced as a 50% cut from the equivalent GPT-5.6 models. Company-reported results: on AutomationBench, Sol (extra-high effort) scored 33.2% at $0.27 per task; on DeepSWE v1.1, Sol scored 68.8% and Luna 66.6%; and on OSWorld 2.0, Sol reached Claude Opus 5's level at about 80% lower cost

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