Releases

Meta made a $14.3 billion strategic investment for a 49% non-voting minority stake in Scale AI, valuing the independent company at over $29 billion and expanding the commercial partnership.

Founder and CEO Alexandr Wang left day-to-day management to join Meta’s AI efforts while remaining a Scale director; Chief Strategy Officer Jason Droege became interim CEO.

Scale formalized a data-engine offering for robotics and embodied AI, covering multimodal collection, annotation, and real-world model improvement.

The U.S. Defense Innovation Unit selected Scale to lead Project Thunderforge with Anduril and Microsoft, integrating AI agents into operational military planning.

Scale entered a five-year partnership with Qatar’s Ministry of Communications and Information Technology to deploy AI applications, analytics, automation, and workforce programs across government.

Scale published MASK as part of its safety research program for testing whether models knowingly state beliefs inconsistent with their internal representations.

Scale released FORTRESS to evaluate frontier-model safeguards against dual-use national-security and public-safety risks.

Scale and the Center for AI Safety published Humanity’s Last Exam, assembled from nearly 1,000 contributors across more than 500 institutions in 50 countries.

Scale added richer model comparison, failure analysis, cross-sectional reporting, and automated error-discovery capabilities to its frontier evaluation framework.

Scale released Defense Llama, a Llama 3-based model fine-tuned for controlled U.S. national-security use cases inside Scale Donovan.

Scale and the Center for AI Safety launched an international effort to create a broad expert-written benchmark for frontier AI systems.

Scale and research collaborators introduced EnigmaEval, a multimodal reasoning benchmark built from novel puzzle-competition problems.

Scale released MultiChallenge to measure model performance on realistic multi-turn conversation problems involving memory, instruction retention, editing, and self-consistency.

Scale made its model-evaluation platform generally available for model developers, enterprises, and public-sector organizations.

Scale launched expert-evaluated leaderboards for coding, instruction following, mathematics, and multilinguality using private, contamination-resistant prompt sets.

Scale closed a $1 billion primary-and-secondary financing led by Accel at a $13.8 billion valuation.

Scale expanded its generative-AI platform and services into custom agentic applications connected to enterprise data, controls, and workflows.

Scale launched its Safety, Evaluations, and Alignment Lab to build standardized frontier-model benchmarks, evaluation products, and red-team methods.

OpenAI named Scale a preferred partner for enterprise fine-tuning of GPT-3.5, combining Scale’s data engine with OpenAI models.

Scale provided evaluation infrastructure for the White House-supported Generative Red Team Challenge at DEF CON 31, testing frontier models with thousands of participants.

Scale introduced an expert-driven testing and evaluation platform for measuring frontier-model capability, safety, bias, and robustness.

Scale launched EGP as a model-agnostic enterprise platform for deploying secure generative-AI applications with proprietary data, fine-tuning, evaluation, and red teaming.

Scale launched Donovan, a secure decision-support platform using large language models, retrieval, and mission data for government and defense users.

Scale deployed Donovan for the U.S. Army XVIII Airborne Corps, describing it as the first large-language-model platform deployed on a classified network for the Corps.

Scale partnered with Anthropic to help enterprises customize and deploy generative-AI applications powered by Claude.