AI

A model that's really strong at mathematical reasoning is likely to be strong at coding. And a model that's excellent at both math and code is often very good at analysing the nuts and bolts of legal reasoning as well. The third and deepest reason this matters is the ability to bridge different levels of abstraction. All of these domains involve multiple layers of abstraction, and the ability to move fluidly between those layers is likely to be extremely commercially valuable.

At Axiom we've raised $64 million—we're a small startup—and we recently won the Putnam competition. We scored 90 out of 120, which would have placed us above all ~4,000 human contestants last year and at the level of a Putnam Fellow, meaning top five in the world. If you tried to achieve that purely through informal methods—where hallucination is a persistent risk—getting to the same level of consistent correctness would likely require a lot more resources.

We see math as code and code as math. The real magic, and the key transition, comes from combining AI, programming languages, and mathematics—bringing all three pillars together. What we envision is humans using informal reasoning and intuition as a powerful guide, with formal systems then verifying those ideas. That interplay across layers is, I think, the real magic of combining multiple levels of abstraction.

Think about a rabbit sitting in a field. If that rabbit saw a hawk circling above and decided to wait for the back-propagation step before responding, it would be dead. It has been eliminated from the gene pool. The better you model the world, and the faster you can act on that model, the more likely your genes are to survive.

The brain is definitely not doing computation in the purest sense. We are not crunching numbers in binary ones and zeros in our heads. When people ask me how our system compares to an NVIDIA GPU in terms of FLOPS, I tell them they're asking the wrong question. A more important question is: what are your inputs, what output do you want, and how intelligently can the system get from one to the other?

I think intelligence is best understood as an entity that has the ability to improve a metric through repeated exposure over time. By that definition, machine learning algorithms are learning systems — they get better with more data and more exposures. A dog is a learning system. A cat is a learning system — you teach it a trick, reward it a few times, and it just does it from there on. And humans, of course, are the ultimate example of a learning system.

Instead of worrying about powerful artificial intelligences in the future, we should be concerned about the lack of intelligence in the Oval Office today!

World Chess Champion & Political Activist Against Russian Authoritarianism

We cannot think about technology in confrontational terms. There is no race against the machines, there is no fight, no war. We have to end this long, historical confrontational narrative.

World Chess Champion & Political Activist Against Russian Authoritarianism

We're living in a world of increasing, exponentially growing computational power. Technology is always on, always available, and we're now moving into the quantum computing era – these exponential technologies are enabling artificial intelligence, robotics, 3D printing, synthetic biology, augmented reality, blockchain and allowing these technologies to converge, creating new business models.

Founder of X Prize Foundation & Singularity University

At some point, if this kind of technological progress continues, it would seem that our descendants will become entirely digital: uploads or artificial intellects implemented on computers.

Philosopher & Director of Future of Humanity Institute at Oxford

Among future technologies that may pose significant existential risks I would rank machine super intelligence at or near the top.

Philosopher & Director of Future of Humanity Institute at Oxford

We therefore see the drone exhibiting through software signs of the moral-affective function of 'guilt' when engaging in each mission.

Roboticist & Pioneer of Ethical Autonomous Systems and Robot Ethics

After each strike the drone would be updated with information about the actual destruction caused. If it did more damage than expected, then it could use this information to restrict its choice of weapon in future engagements.

Roboticist & Pioneer of Ethical Autonomous Systems and Robot Ethics

We cannot think about technology in confrontational terms. There is no race against the machines, there is no fight, no war. We have to end this long, historical confrontational narrative.

World Chess Champion & Political Activist Against Russian Authoritarianism

Playing chess, I learned the dramatic effect combining humans and machines. Humans have intuition, can recognise patterns and positions, and machines have brute-force of calculation and memory. By bringing these capabilities together in other walks of life, we can achieve incredible results.

World Chess Champion & Political Activist Against Russian Authoritarianism

Most people run around like biological robots, as if we are an algorithm not a being. We become the predictable outcomes of the conditioned reflexes of our nerves, constantly triggered by people in reaction to circumstances.

Wellness Entrepreneur & Author Promoting Mind-Body Medicine and Spirituality