Science

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

I think of creativity very broadly, for me it's about solving problems. A lot of people put creativity into the narrow bucket of artistic expression; including film-making, creative writing, music and so on- but there are many who understand that if you look at science and engineering, there are many very interesting problems that require creativity and you see a great outpouring of new ideas.

Co-Founder of Pixar & Pioneer in Computer Graphics

I learned to problem-solve and be self-sufficient at an early age, and that has influenced how I operate my lab. I try to make sure we generate as much of our research, data and activity in house as possible, so that we own what we produce.

Nobel Prize Winner for Gene Targeting in Mice

All ideas and questions might be very interesting, and children has to experience that their questions are equally valued as those coming from a grown up or a Nobel Prize winner.

Neuroscientist; Nobel Prize for discovering brain's positioning system cells

I don't think about myself as a woman in these contexts, I think about myself as a human. I feel like role model for all young people who wants to do science – not only girls.

Neuroscientist; Nobel Prize for discovering brain's positioning system cells

Within each of us is a deep, complex network of capillaries, veins and arteries which extend a distance equivalent to more than 3 times the circumference of the Earth, and because our body has lost its conditioning to nature, our hearts have to pump 20-30 times a minute more than if we regularly exposed our body to cold water.

Extreme athlete known for ice exposure & breathing technique methods

Going around the world thousands of times presents you with the depth, fragility, strength and richness of Earth; and gives you a sense of what 4.5 billion years actually means. I travelled with our Earth as it crossed the Solar System and watched as Winter and Summer swapped- it was like watching the world take one of 4.5 billion breaths.

Canadian Astronaut & International Space Station Commander

Seeing the Earth from space gives you an unfiltered understanding of it. Until you see the Earth from this vantage point, everything you knew about the planet was based on something that someone else had told you – based on their own filtered understanding and bias.

Canadian Astronaut & International Space Station Commander