What role for Britain in the AI revolution? Kanishka Narayan, the UK’s minister for AI and Online Safety, does a great job outlining both the country's vulnerability — no frontier LLMs to call its own — and its strength: more than a century of computing and AI innovation. Speaking to the Financial Times:
I think that the diagnosis has to be that we are not in a terrific position from a strategic leverage point of view. The frontier models are developed either in the United States or slightly behind them by a few months in China. And so Britain does not have companies when it comes to frontier language models, and we don’t have the core chip architecture, the Nvidia chips, as well as the memory and packaging.
So SK Hynix in South Korea, for example, gives them an advantage. TSMC in Taiwan gives them an advantage. ASML in Netherlands gives them an advantage. And so broadly speaking, we have some strengths in that supply chain, but none of those you would point to. Arm does a lot of the chip design, but none of those you’d really point to and say Britain is currently competing sufficiently with the United States and China so that we can have continued access to critical inputs.
And so the nature of the problem is very stark, and I think it’s a serious question for the future of our economic and national security. And so what do you do about it? And there are two ways I think about this. Broadly, what you’re trying to do is have, without the pun, chips on the table so that you can access others as critical inputs.
And you can do that either by having chips on the table in the AI stack, or you can also think about it as a broader international negotiation bundle. We might not just offer AI things, we might offer other things that are important to, say, the United States or to China to be able to secure access. On AI, what we’re trying to do is effectively say we think it’s really critical we build more leverage, and that’s why we are focused on things that give us leverage.
We think our chip companies will, if they succeed, be in a position where it’s very hard to replace them in some cases, and that gives you leverage. We think some of the frontier models that we’re developing outside of language in materials discovery, in new drugs discovery, in world models and vision models, we think those will give us leverage. But those are not overnight things, and they take a little bit of time.
And the third thing is, we have built pretty remarkable state capacity. We have built the AI Security Institute, which is the only lab in the world that gets pre-deployment access to all the core models. And so by understanding the risks, sharing it in a trusted way with core allies across the Five Eyes, we think we’re able to build trust that also gives us leverage in the AI stack as well.
And so my focus across the AI stack, both on hardware, on models, and at the heart of it on governance assurance, on safety, on state capacity, is to try and build things that serve British interests domestically as well as internationally.
The Fall of Amazon’s Mechanical Turk Is an Omen for the AI Agebloomberg.comFor more than two decades, Amazon.com Inc.’s Mechanical Turk offered a similar illusion to its namesake. The 18th century chess-playing “machine” was actually a contraption controlled by a human hidden in a box. Amazon’s groundbreaking digital work platform did this at scale. Its Mechanical Turk was an army of hidden, anonymous workers carrying out a dizzying array of small mundane tasks for money.
