Today, we publish a Transformative AI Strategy for Europe. Over the last few months, we’ve rallied researchers and engaged with governments to develop a plan for protecting the prosperity, sovereignty, and security of Europeans in a time of rapid AI progress. @MonikaSchnitzer and I are honored to have convened an all-star team of thinkers and researchers contributing ambitious near-term objectives to make Europe relevant again, including: — Creating a Member State Alliance for Supply Chain Security (@anton_d_leicht et al) — Making European institutions ready to act in a transformative AI world (Conor McGlynn et al) — Securing Europe's share of global AI compute, in a ‘European Way’ that benefits local communities (@philip_fox_ et al) — Ensuring resilience to AI crises (@ben_s_bucknall et al) — Making Europe the global leader in assurance technology — And more objectives around security of supply and leverage (@milorignell et al), economic strength (@FraukeStehr et al), and safety/security (@NoemiDreksler et al) Our all-star senior expert council of Europe’s best and brightest (and non-European friends) reviewed drafts, provided strategic advice, and made suggestions for how to make the strategy more useful: @Ph_Aghion @Christophkw @bakkermichiel @ischinger @vestager @aleks_madry @FuestClemens Marta Kwiatkowska @LeoVaradkar @antonosika @DAcemogluMIT @Yoshua_Bengio It’s never been more clear: AI is real, and Europe needs to act. We’ve had all the warning shots and wake-up calls we need. Now the question is ‘what must be done?’ This strategy is our answer.

We’re excited to see Dario and Sam commit to “embedded evaluators who have employee-like access to verify safety practices and report incidents.” [...] “whose role is to verify adherence to safety practices and commitments, report incidents, and help assess the alignment of not just completed AI models but training pipelines and processes.” We’ve long advocated for third-party evaluators to have deep access. Risks from internal deployment and scheming cannot be appropriately assessed without direct insight into the training pipelines and internal deployment practices. Apollo is looking forward to working on Embedded Evaluations with all Frontier AI developers. 1/3

We’re doubling down on our control and monitoring research. We have recently successfully red-teamed Anthropic’s auto-mode and will run more such campaigns in the future with multiple labs. We will also continue to make better monitors ourselves and improve the research frontier for the blue team. There are many low hanging fruits to pick for monitoring and not a lot of time. Our main blocker is having more hands on deck. Come join us! RS (Control): AI Red Team Engineer: AI Security & Control Researcher: Every role is open in both offices, London and San Francisco. We provide visa sponsorship. Our monitoring agenda: Auto-mode red-teaming: All open roles:

🚨 MATS Winter 2027 applications are now open. Fully-funded, 12-week fellowship for aspiring & established AI alignment, interpretability, security, governance researchers & field-builders 📍 Berkeley/London 📅 Jan 19–Apr 10 💰 $6.4k/mo + $8k - 16k/mo compute Apply by Sep 6 ↓

We can finally talk about it: We found a way to extract hidden reasoning of frontier models using a vulnerability in the APIs of every frontier AI company. We verified that our reasoning token count matches billed API thinking tokens 1:1 for most of the prompts we queried.

RL assumes that LLMs explore well during training. What if they choose not to? In our new ICML paper with @GoogleDeepMind, we train LLMs that strategically resist RL capability elicitation by under-exploring. We study this threat model, called exploration hacking.