 So obviously, we live in the information age, and everyone knows that a great deal of our energy resources and the power that we generate has got to go into maintaining computations. And this also includes data storage. Of course, data storage and computations always go hand in hand. And there is some staggering statistics that I've read about recently. For example, companies like Google, if you think in terms of their energy expenditure, are comparable to the whole of the airline industry. So the heat they generate simply because they have to store large memories. In fact, the US government spends 3% of their energy on exactly the same problem, on data storage. And this has severe environmental implications simply because every time you compute, you heat up and you generate heat in the atmosphere. And as you've seen from the other talks, this is of course a big problem. The question I'll be asking is, is there anything we can do to make the number crunching more efficient in terms of energy expenditure? So this is a huge problem. There's a multitude of problems. One of them is, what are the physical limitations to that? What are the laws of physics telling us about how low we can go in terms of energy expenditure? On the other hand, I think the question that we are asking within this session is, if we manage to reduce our energy expenditure based on our understanding of physics, what kind of impact would that have on our environment? And this would be, of course, extremely helpful to us as well. Now we have the latest evidence from the experiments in the laboratory that nature is much more effective at information processing. Photosynthesis is one famous example where there is a nanowire whose quantum efficiency is almost 100 percent, certainly bigger than anything we can do artificially in our labs. The other interesting example is the DNA, where you can think of the base pairing inside the DNA as a basic computational step, in which case this replication is 10,000 times more effective in terms of energy expenditure than the best computer that we have. And this is really interesting. So the question is, can we learn anything from this? The basic issue why computers heat up when they calculate is because they are irreversible. When you do something and when you have to undo it, it generates a lot of friction and this friction manifests itself as heat. So irreversibility here is the key issue. The way to make it reversible, and this is my two slides on quantum mechanics, that's all you're going to hear about it, is that quantum mechanics is unusual in the sense that all quantum processes are fully reversible and that's because all particles are really like waves. And I think the next slide will illustrate to you, if you think of a computational step as taking one of the two alternatives, like in this slide, then a quantum system can actually go down both of these lanes simultaneously and it's this that makes the whole thing efficient in terms of energy expenditure. Classically, you'd have to make a choice. You'd have to go left or right, which actually results in expanding heat. So that's the key issue. So the issue that we'll be asking and addressing within my session is, how can we learn from the natural systems, like the photosynthesis, like the DNA, and make our own energy processing more effective? And there is even more examples on this which are birds that use quantum mechanical systems to actually navigate properly. This is a genuine quantum mechanical process and it's the only paper I've got in the Daily Mail, by the way, coming out of my research, which is also interesting. The key message ultimately is that even a little bit of saving in terms of reversibility could give us a huge benefit and that seems to be the route that nature is taking. Most of the natural processes are actually classical, but in the bottleneck where it matters, they become quantum mechanical. It's a hybrid quantum and classical system, which is really what this picture is meant to illustrate. And in fact, even a little bit of efficiency could really make the difference between life and death in natural systems. We have these bacteria that live only on a few photon diet a day. And the question is, how do they do it? How quantum mechanical is that? Is it quantum mechanical, really? As Ian said earlier, I run a consortium with a bunch of eggheads addressing these and similar issues and what I'll be asking in my session is exactly here. How can we learn from nature to do more efficient computation? Thank you.