Science

DMT forces you to confront the fact that we know almost nothing about the true nature of reality. Whatever image you have of what's real or possible is obliterated in an instant. You're faced with a world that isn't just strange, but so utterly incomprehensible that it transcends imagination. It's a place that shouldn't exist within our consensus reality, yet there it is—undeniable.

Music can help us heal and achieve therapeutic outcomes by tapping into various neurochemical circuits that influence mood and behaviour. Ours was the first lab to show that listening to music releases the brain's natural pain relievers—opioids. Relaxing music can modulate prolactin, a soothing, tranquilizing hormone. Music also releases dopamine which helps us to focus and motivates us to stay on task.

Neuroscientist & author of "This Is Your Brain on Music

The brain, if nothing else, is a giant pattern detector. It looks for order in chaos. And those patterns matter: they can mean the difference between life and death. Music taps into that same machinery because it's so highly structured. When your brain says, I thought this path would lead here, but it actually took me somewhere new — you experience pleasure.

Neuroscientist & author of "This Is Your Brain on Music

The brain can be thought of as a blank slate, yet it comes with certain built-in constraints and proclivities. Every culture recognizes the octave, because it's grounded in physics, a simple 2:1 frequency ratio. Every culture also uses the perfect fifth, 3:2. And every culture divides the octave into a discrete set of steps for their scale, usually between five and eight.

Neuroscientist & author of "This Is Your Brain on Music

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.

At Colossal, we are not going to work in humans or non-human primates because we felt like we're already going to have an uphill battle with transparency and education, and we don't want people to be like, if a hair-loss treatment comes out of Colossal, 'are they selling a gene from a woolly mammoth?'

We try to make decisions through a kind of committee-based approach around what species we're going to bring back, where we're going to invest our dollars, and what fits our core ethos. If it's not going to be beneficial to humans, if we can't do it at arm's length from humans, and if we can't do it in a way that's good for animals, then we just don't touch it.

I think that we must move to a model where we value nature differently and work by integrating with nature. And that's one of the things I'm very, very excited about—leveraging synthetic biology. Because if we can create excitement, wonder, and solutions to problems like loss of biodiversity, then I think that not only can we inspire the next generation, but we can give them hope.

My entry into this space came in 2019 when I read a paper by Demis Hassabis of DeepMind advocating for machine learning and AI researchers to go back to their roots in neuroscience. I took that literally — I went back to the neuroscience department at my alma mater, the University of Melbourne, and asked what was exciting them.

You cannot expend more energy than you can consume. That's a fundamental law of physics. If you do, you starve, you die, and you remove yourself from the gene pool. Biological systems have therefore been under enormous selective pressure to develop highly efficient intelligence.

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.

By definition, existential risks are those which- by definition- could terminate the species, or permanently limit the long term potential of our civilisation. Martin Rees, the distinguished scientist, said that the difference between killing 90% of humanity, and 100% of humanity is not 10%. The difference is huge. By killing 100% of humanity, you are also killing all future generations.

Co-Founder of Skype & Estonian Entrepreneur & Technologist

There's an interesting over-representation of physicists within the existentialist community. Physicists, especially astronomers and cosmologists have had a glimpse of how vast the universe is, and the potential value of it, versus our planet.

Co-Founder of Skype & Estonian Entrepreneur & Technologist