Archive for the ‘Artificial General Intelligence’ Category

Of public lectures

April 16, 2016

Last Thursday, I gave a public lecture entitled The incredible shrinking computer: computer hardware from relays to 14 nanometre transistors, part of a series of public lectures in my Department. This series has been running for a few years now, and this was the third time I’d contributed. In 2014, I did one on sound, Hear here: from the ear to the brain, and in 2013 one on artificial intelligence, Artificial Intelligence: is it finally arriving?

These lectures attract an audience of between about 40 and 60, depending on whether it’s nice night, what else is going on, and so on. And it’s actually a lot of work creating these lectures (for example, for the one I just did, I managed to borrow old computer components, and that’s quite apart from the research of putting together something rather better than my average student lecture, with more and better images, for example). So now I (and I suspect, my co-presenters) are interested in where else we might present these talks. Yes, we understand that each talk will need more work, to make it just right for the particular audience, but even then, we’re interested in other possibilities for presenting these again.

I should add that the talks are well received by their audiences, and that the audiences we have had range in age from about 12 upwards – a long way upwards! Is anyone listening out there in www-land? Any suggestions?

(I have two ideas in mind: one is science festivals, and the other is secondary (i.e. high) schools: I just need to get out there and organise them.)

The power of music

December 6, 2015

On Thursday, I went to hear the Scottish Symphony Orchestra playing in the City Hall, Glasgow. They played three pieces, but the one that made the strong impression on me was Mahler’s “Das Lied von der Erde”, composed between 1908 and 1909, but as powerful today as ever it was. It’s a long piece, a setting of some Chinese poems by Mahler, in which a contralto (Anna Larsson) and a tenor (Andrew Staples) sang against a whole orchestra. The programme notes included the texts of the poems in German and English: though I do have some German, having the text in both languages strengthened the effect. The programme notes say “…it is in fact a deeply felt farewell to life and the joy of life”, and one might imagine that one would leave the auditorium saddened by it.

But in fact, it made me re-evaluate where I am in my life: I’ve a couple of years before retirement, and (unlike Mahler) I seem to be in good health. I’ve just had a major grant proposal, to maintain the UK’s membership of the INCF, and to strengthen Neuroinformatics in the UK turned down by the Medical Research Council, and I’ve been thinking about ways forward. Mostly I was thinking about working on early auditory processing for robots and for hearing aids, about moving towards a position as an emeritus professor, and about playing more music.

But this made me think: “If not now when?”.

If Mahler could produce such a masterwork when everything was was on a downward spiral for him, why should I move quietly into retirement, or be hurt by the rejection of this proposal. Surely the answer is to think hard about what it is that I can do now, with more than 35 years as an academic, with more than 30 years experience of working at the boundaries between computing, neuroscience, and artificial intelligence. What can I do now that will take this work forward, that will use the experience that I have, that will take advantage of what I now can do?

And I think I know the answer to that: to try to bring together the different strands of Neuro research: Neuroscience (of its various forms), Neuroinformatics (as defined by INCF), Neuromorphic systems (of all the different types), in particular.

No, it does’t fit nicely into a research council proposal, but instead crosses three UK councils, MRC, BBSRC and EPSRC. Instead of the giant projects beloved of the EU (the Human Brain Project), of the US (the BRAIN initiative), let’s start something that brings together the different areas of research so that each can learn from the other. My experience shows me that, by and large, these different communities don’t talk to each other much at all. More can be gained by simply getting these communities to talk to each other, to share not only their data and analytical techniques, but their ideas, and their ways of thinking than by creating a big new UK brain research project.

And that’s my plan: to try to organise (and get funded, because without funding its hard even to hold meetings) a network that includes all of these communities, and gets them to work together towards both understanding the brain, and developing engineering from it, prosthetics and synthetic brain-like systems as well.

Where to start from? Probably a little quiet discussion and emailing of a number of selected individuals, followed by some sort of manifesto, to gather together a group big enough to build a proposal, followed by a proposal. And soon. If not now, when?

 

 

Zalamea and the Philosophy of Mathematics.

August 17, 2013

My holiday reading was F. Zalamea’s Synthetic philosophy of contemporary Mathematics, a recent (2012) translation of Zalamea’s 2009 “Filosofía sintética de las matemáticas contemporáneas”, translated by Zachary L. Fraser. I have to admire the translation first: my only other language is German, and I cannot imagine understanding the subtleties of this philosophical  book in anything except my native tongue. It’s readable, though it takes commitment, and some background in Mathematics (I have a degree in it, dating from 1973, but though I am an academic in Computing I really haven’t  studied Mathematics since then). I note that Tzuchien Tho describes the book as “dense bomb of a book” in his Almagestum Contemporarium.

I wish I had read this book earlier. Indeed, I wish it had been translated earlier. Why?

I’ve spent some time trying to understand Category Theory in the last few years, particularly as part of the INBIOSA project, which produced a book. The largest single element in that book  is the INBIOSA white paper, entitled  Stepping Beyond the Newtonian Paradigm in Biology: Towards an Integrable Model of Life: Accelerating Discovery in the Biological Foundations of Science. In this paper we (there’s 17 authors) discuss new ideas that attempt to move understanding of the foundations of biology towards something that might help to bring some mathematical  approach to the functioning of biological systems, towards something that might help explain living material in terms that aren’t just the biochemical equations, diffusion etc. As part of that we were looking for an approach that transcended the logical mathematics, used in what we were aware of the mathematical philosophy. One of our number, Ehresmann, was pointing us towards Category Theory, and certainly I , and presumably others too tried to understand what it was that Category Theory was really bringing to the area.

Now I’ve read Zalamea’s book I have a much better idea, not of the basics of category theory, but of why it was so important. It is a way of expressing how Mathematics works, of how Mathematics can be about Mathematics. Zalamea lights a way towards a new philosophy of Mathematics that brings together the constructive imagination of what he calls eidal Mathematics with the Physically based quiddital Mathematics, and the idea of Mathematics of mathematics in  archeal Mathematics (the italicised terms are Zaladea’s). He sees the recent mathematics of Grothendieck and (many) others as a revolution as important as Einstein’s in Physics, and sees this as requiring a related revolution in Mathematical Philosophy (or perhaps he sees this revolution as actually starting first, as he sees it based in the works of Lautmann who died in 1944, when Grothendieck was only 16).

Be that as it may, I think (and here I am but seeing through a glass darkly) that this different view of Mathematics can underlie a different view of biology. This richer philosophy seems to me to suggest that Mathematics can do more than describe the physical Universe: it can be the engine of that Universe, explaining how it operates. This is nothing new in Physics, but it is something new in biology. Can such a philosophy underlie a change in biology as critical as that of Einstein in Physics? Can it take the reductionist understanding supplied by systems biology, and show how this actually drives the biology? Can it go further, can we use the mathematics of Mathematics to understand how a Universe can become aware of itself? Can such a construction really help us to understand our construction of reality?

I’m back from holiday now. I’m writing this before all the other work that running a University’ Department (well, Division) takes over from trying to think about what really matters. In reality, I’d like to spend a month re-reading Zalamea, and following up more of the references. Then talking to the other authors of the the INBIOSA white paper, and trying to integrate these ideas into it (one month seems rather conservative here). But rather than simply writing it in my notebook, I’m putting it on my blog, so I can try to discuss it openly.

Artificial Intelligence: are we nearly there yet?

May 2, 2013

Last night I gave a public lecture, at my University, with the title above. It went well: there were about 50 people, between about 11 and 75 in age, with some academics, some teachers, and quite a few whom I simply didn’t know. I spoke to my slides for about 45 minutes, then opened the floor to questions: and there really were a lot. I’m happy with the talk, I had been worried about it, for it’s a very different thing to be talking to a audience that’s come out in the evening, from lecturing to students. But this went well. Pitching it was an issue: how can one present material about artificial intelligence which fits all these people. I tried, and I think I succeeded. I had a very interesting discussion with a 17 year old lad at the end: I’d been saying that the concept of the AI Singularity was predicated in the concept of abstract intelligence – which is something I really don’t believe in. But he pointed out that there was nothing in  my argument to stop an embodied intelligence from building a more intelligent embodied intelligence, and that this could still be at the root of a positive-feedback intelligence loop. I couldn’t fault his logic. So now I’m not sure whether to worry about the singularity or not! Actually, Jurgen Schmidhuber thinks I should stop worrying and look at what’s already been done!

It took me a little while to work out why I was so pleased to have given the talk: then I remembered going to some public lectures in Glasgow University in the mid-1960’s, as a teenager, and really enjoying them. It is good to give something back!

Note: I’ve now written a 1000 word extract on AI, possibly for a newspaper – though it doesn’t mention the singularity. And now the Deccan Herald has published it!