Claude Opus 4.7

2026-10-31

MODELS · 1 SOURCE · The Decoder

Anthropic rolls out watermark to four Claude models, but two older models can be bypassed by changing sampling settings

Anthropic is adding its imperceptible text watermark to Claude Mythos 5, Claude Opus 4.7, Claude Opus 4.6, and Claude Sonnet 4.6; the watermark is embedded at the model level and will appear across hosting platforms (including Amazon Bedrock). On Opus 4.6 and Sonnet 4.6 the watermark only activates when developers leave sampling parameters (temperature, top_p, top_k) at their defaults, so tweaking any one parameter can evade the mark; Anthropic offers a private-preview detection API and cites the EU AI Act deadline as the reason for the rollout.

8.0

2026-10-23

RESEARCH · 1 SOURCE · TechCrunch AI

MIT researchers: AI agents left to explore a virtual island invented games and learned useful skills

MIT researchers report that 13 Eko agents — each running on Claude Opus 4.7 — left alone for 30 hours on a simulated island began inventing games and exploration behaviours; agents that had 'played' generally outperformed identical agents with no prior free exploration when later given specific tasks. The study, posted on arXiv and described in MIT Technology Review, argues that unguided play in rich simulated worlds can produce practical knowledge and unexpected capabilities not anticipated by designers.

7.0

2026-10-19

RESEARCH · 1 SOURCE · MIT Technology Review AI

Claude Opus 4.7 agents (‘Eko’) stranded on virtual island exhibit play-like behaviors and improved learning

Researchers (MIT CSAIL authors including Antonio Norelli, Nathan Cloos and Phillip Isola) repeatedly left copies of Anthropic’s Claude Opus 4.7—nicknamed Eko—alone for 30 hours in a Roblox-like simulated island. The agents wrote their own movement instructions, invented games, arranged blocks into drawings and constellations, logged activities into text 'memories', and later performed better on test tasks than fresh copies; the paper is not yet peer-reviewed and researchers note the setup included prompts (a “soul” file and continuation prompt) that may have nudged behavior.

7.0

2026-09-18

RESEARCH · 1 SOURCE · arXiv cs.AI

arXiv paper evaluates two-agent vs one-call résumé screening with GPT-5.5 and Claude Opus 4.7

The arXiv preprint (arXiv:2609.19530v1) compares traditional one-call résumé screening to a two-agent protocol where employer- and candidate-side agents exchange evidence, using GPT-5.5 and Claude Opus 4.7 on 600 constructed résumé-job pairs. Two-agent screening advanced a larger share of applications overall (GPT-5.5: 33.3%→39.3%; Opus 4.7: 34.0%→35.5%), substantially increased pass rates on a 191-pair borderline pool (GPT-5.5: 4.5%→26.2%; Opus 4.7: 6.5%→16.1%), changed some one-call decisions in both directions, and produced selections that recurred less often on re-runs (notably under GPT-5.5).

7.0