Skip to main content

A Brief Guide to Artificial Intelligence - James Stone ***(*)

Some brief guides miss the point and in reality go on for rather a long time, but this one very much does what it says on the tin. Readable in an hour, it gives us the basics of what modern artificial intelligence is and how it works. To achieve such brevity, James Stone has cut away much of the support mechanism of popular science - so we get very little background and historical context, limited storytelling and not much about applications. Instead, the focus is laser-sharp on delivering the basics of how neural networks work, where modern AI is successful and where it has a long way to go.

Broadly, Stone identifies two areas where AI triumphs - image recognition and playing games. If I'm honest, perhaps he is a little generous on the first of these - as he points out himself, tiny elements undetectable to the human eye can be sufficient to totally change what an image is recognised to be, and most of the techniques (he takes us through different types of machine learning) require a very large amount of training material where (again as Stone acknowledges) humans can often learn to recognise something with just a handful of examples. The AI technology is on firmer ground with its game playing - in chess, go, backgammon and a range of computer games, AI is now unbeatable, and teaching humans new approaches. What perhaps Stone doesn't emphasise enough is how much this demonstrates that AI's real success is in non-real world applications where the rules are clear and relatively simple, even if they haven't been specified to the system. In the real world, things are often more messy, again something that is acknowledged in, for example, being far less optimistic about self-driving cars than is often the case.

Stone gives us a good simple introduction to neural networks, back propagation, four different kinds of machine learning (from semi-supervised to reinforcement) and the dangers of overfitting, making it clear that even current AI is doing significantly more than curve fitting. The book (probably sensibly) brushes aside fears about AI might take over the world and displace humans as somewhat far fetched at the moment.

My only real disappointment was at the end of the book, where Stone tells us true AI is likely to emerge relatively soon, given it took just millions of years for flying to develop in the natural world, but just 66 to get from the Wright brothers to the Moon landing, citing acceleration of advancement that could be experimental. There are two problems with this. One is that the proper modern comparison with the Wright brothers is not space travel but commercial flights. These did indeed get much faster. The Wright brothers had an airspeed in the tens of miles per hour. Within 73 years, passengers could fly at 1,350 mph. But Concorde has now been withdrawn for nearly 20 years - instead of speeding up, we fly at less than half the speed. Even if you do take the leap from Wright brothers to Apollo - yes, that only took 66 years. But in over 50 years since we have done nothing comparable in space, let alone gone further and faster. Just because there was acceleration in the past does not mean it will continue.

I give the guide four stars for its solid, approachable and extremely brief introduction to the modern field, but three stars for lacking context and effective narrative. While approachable and doing the job admirably, it's not outstandingly particularly to read without that contextual material. Even so, for the right purpose it's an excellent little book.

Paperback:  
Kindle:  
Using these links earns us commission at no cost to you
Review by Brian Clegg

Comments

Popular posts from this blog

Who Invented the Computer? – Ian Watson

Ian Watson is the author of  The Universal Machine  and featured in a recent  Four Way Interview . Saturday June 23 2012 was the centenary of the birth of Alan Turing, the troubled genius who invented the modern computer. Why though do so few people recognize his name and his great achievements? In 1936 English mathematician Alan Turing, published a paper,  On Computable Numbers, with an application to the Entscheidungsproblem . This became the foundation of computing. In it Turing presented a theoretical machine that could solve any problem that could be described by instructions encoded on a paper tape. A Turing Machine could calculate square roots, whilst another might solve Sudoku puzzles. Turing demonstrated you could construct a single  Universal Machine  that could simulate any Turing Machine. One machine solving any problem for which a program could be written – sound familiar? He’d invented the computer. Then,  computers  were peop...

The Star Book – Peter Grego ****

This attractive landscape format book combines an excellent introduction to the stars and basic astronomy with a set of star maps, plus in depth looks at some of the stars featured, with a  bonus section on the solar system. Amazon says it’s a hardback, but in fact it’s a paperback with a rather ingenious cover – you can’t tell from the photo, but the words ‘The Star Book’ are punched through as a series of holes that show the white paper of the next page beneath. Like many astronomy/space books, the cover lacks shelf appeal because it is mostly black, but at least there is some original thought here. Unlike many books in this format which tend to concentrate on the pictures, there is a good deal of excellent text by Peter Grego, so there was no feeling that you were only getting the star maps and star ‘biographies’, something these days much more suited to an iPad or smartphone app. Instead, the opening 30 or so pages give a very good introduction that would be valuable to ...

Ignorance: How it drives science – Stuart Firestein *****

This is a delightful little book that really gets you thinking. I stress the ‘little’ part not as a negative, but as a good thing. There is nothing worse than fat, bloated popular science books where the author feels they have to get 120,000 words to be taken seriously. This is the sort of book that can be read in a couple of hours – but you will get so much more out of it than one of those tedious doorstops. The premise underlying the book is in once sense extremely simple, yet is fundamental to an understanding of what science is and what scientists do. And it is an understanding that is totally at odds with the typical way science is portrayed both in university lectures and popular science books. As Stuart Firestein points out, what is important is not the facts, but rather the area of ignorance. The interesting part and the fundamental heart of science is not about what we know, but about what we don’t know and where we want to look next. Take this lovely quote: ‘Working ...