TRENDING
Introducing Apple Intelligence, the personal intelligence system that puts powerful generative models at the core of iPhone, iPad, and Mac
June 10, 2024
Updates to the Home experience elevate entertainment and bring more convenience
June 10, 2024
Apple Vision Pro arrives in new countries and regions beginning June 28
June 10, 2024
Apple expands developer support and resources
June 7, 2024
This AI Was Not Our AI Dream.
June 7, 2024
Anthropic’s Claude 3 Opus and tool use are generally available on Vertex AI
June 4, 2024
Of Nuggets And Tenders. To Know Or Not To Know, Is Not The Question. How To Become, Is.
May 25, 2024
From The Heart of Stockholm To Welcoming City Of Seven Hills
May 24, 2024
Stockholm Sounds: From ABBA’s Waterloo to Taylor’s Eras Tour
May 24, 2024
GoSwifties, Beneath And Beyond Celebrity, A Delayed Prelude.
May 21, 2024
Integrate with all of the leading AI models, from open-source to closed-source, including OpenAI, Anthropic, Google PaLM, Cohere, and more.
Integrate your enterprise data into the fold of these models, providing the base for long-term strategic differentiation.
In Partnership
Integrating AI technologies responsibly across industries by developing robust regulatory frameworks through resilient governance and regulation, and advancing technical standards for safe and advanced AI systems.
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Artificial Intelligence promises to catalyse one of the most profound transformations in history.
Our team comprises engineers, leaders, scientists, ethicists, and various other experts dedicated to developing the next generation of AI systems with safety and responsibility at the forefront.
By tackling some of the most challenging scientific and engineering problems of our era, we aim to create groundbreaking technologies that can advance and enhance the lives of billions of people.
Let us know your requirements, thoughts or feedback. Book a demo and discussion with us to get started.
London,
United Kingdom
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Build AI
Discover and understand how large language models work internally — the foundation of ensuring safety and positive outcomes. We work to understand and develop ways to keep future advancements in AI helpful, honest, and harmless.
Inspired by the universality of scaling in statistical physics, we develop scaling laws to help us do systematic, empirically-driven research. We search for simple relations among data, compute, parameters, and performance of large-scale networks. Then we leverage these relations to train networks more efficiently and predictably, and to evaluate our own progress. We’re also investigating what scaling laws for the safety of AI systems might look like, and this will inform our future research.
We believe critically evaluating the potential societal impacts of our work is a key pillar of research. Our approach centers on building tools and measurements to evaluate and understand the capabilities, limitations, and potential for societal impact of our AI systems.