Month: June 2026

Babbage: making money through game AI

A game of noughts and crosses
Image by Clker-Free-Vector-Images from Pixabay

Victorian Innovator, Charles Babbage, had big ideas. He intended to build the first ever general purpose computer, despite living in the age of steam and cogs. But he needed money to do it, and he didn’t have any. He was also notorious for alienating those who invested money in his schemes. He needed a new source of income. Perhaps he could do it through games?

He came up with the idea of building a less ‘serious’ money making machine that would capture the imagination and part people with their money as a curiositiy. His big idea was to design a machine that could play Noughts and Crosses (called at the time Tit-Tat-To) and so also create the first AI game playing machine.

He had previously used game playing (and specifically Chess) as a theoretical demonstration of his argument that machines, such as his proposed Analytical Engine, would be able to do things that were thought at the time to need human reasoning. He even did a mini-survey asking “the opinions of persons in every class of life and of all ages” to find out if people believed that playing games of skill needed human reasoning (the answer was overwhelmingly, yes!) He therefore set about analysing games, and specifically Noughts and Crosses as the simplest such game of skill that he knew.

Having seen that the number of states of the game (possible positions) of Noughts and Crosses was well within the scope of what his proposed machines could handle, he started to think more seriously about actually building one. His reasoning was that by exhibiting it and charging people to play against it, he would raise enough money to fund the completion of the Analytical Engine. After all, he thought, if it could even beat the parents at a child’s game, then any parent would want to take their child to see it.

He even thought about fun, decorative automata details such as:

“I imagined that the machine might consist of the figures of two children playing against each other, accompanied by a lamb and a cock. That the child who won the game might clap his hands whilst the cock was crowing, after which, that the child who was beaten might cry and wring his hands whilst the lamb began bleating.”

He worked out the design of the machine in general terms, determining different mechanisms that could be used and noting that they it would be far simpler than the Analytical Engine itself. A specific issue he worked on was how the machine should make a choice when two equally good options were possible as he didn’t want the machine to be predictable. He came up with the solution that it could keep a record of how many times it had won so far and use that number to make the choice between moves, so use a simple version of pseudo-randomness. An even number of wins so far meant do option 1 and an add number eant do option 2. If there were three options it would take the remainder when dividing by three. He thought that this would be opaque enough that noone watching it play would work out how it was deciding where to go. He noted that this engineering design nicely illustrated definitions of chance given by philosophers

“Chance is but the expression of man’s ignorance.” – Laplace

and poets

“All chance, design ill understood.” – Pope

Sadly, before building it, when doing his equivalent of working on the business case, he discovered others had tried making money from machines. Both a machine that made Latin verse, and another that talked had failed to make money. Combined with the time it would take him to build it, he therefore gave up on the whole money-making idea. 

Perhaps if he had just had more faith in people’s interest in games (over Latin!) it would have been a success and he might have raised the money to successfully build the first computer 100 years before it eventually happened. Now, of course, the computer games industry is worth billions! (The Latin verse industry is not so strong, though of course Generative AIs are now writing poems, in living languages like English, to people’s delight, if not yet making money from doing so!)

Now, what might I build to fund my research? Donations welcome!

Paul Curzon, Queen Mary University of London

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William Kamkwamba: The boy who harnessed the wind

William’s wind turbine made from local wood, scrap metal and a destroyed bicycle by CS4FN

[SPOILER ALERT]

“The boy who harnessed the wind” is a new musical from the Royal Shakespeare Company that tells the inspiring story of teenage innovator William Kamkwamba, based on his autobiography of the same name. As a young teenager he helped save his African village from famine by working out how to build a windmill to generate electricity from scrap, that might ultimately pump water to irrigate the crops.

William grew up in the village of Wimbe in Malawi, at a time when magic was still present in people’s lives and few had electricity or running water. Drought killed, and disease was rife. He, however, was obsessed with gadgets and working out how they worked. He was especially intrigued by the dynamo on a bike and how rather than just using electricity, it created it. It generated electricity that could be used to power other things.

Unfortunately, his family were too poor to pay the fees so he was forced to leave his village school aged only 14. He was left having to learn what he could from the books he could get hold of and his own tinkering.

A famine followed with crops failing and there being too little grain produced to feed the village to last through the winter. However, he had an idea, having read a book about western wind power. There was plenty of wind in Malawi, so if he could build a windmill connected to a dynamo, the power it generated could drive a water pump to irrigate crops, allowing a second planting even in the dry season.

With no one to teach him he had to work out the science himself from books, and overcome the engineering problems on his own. Also, all he had to make it from was scrap metal, local wood and broken gadgets. To make things even harder for a long time few in the village believed he was anything but a mad dreamer, mocking him rather than helping. His family also needed him to help work on the farm just to survive in the short term.

However, he was determined he could make his idea work if only he could solve the problems using scrap parts. The book and musical (and linked film) tell the story of his village’s struggle with famine and his struggle to be believed.

Ultimately, he made a wind turbine, that powered a radio, proving to everyone that the idea could work. He then used it to power other devices around their home. The story spread, leading to international fame, leading to him giving a TED talk, having his schooling paid for him and going to university in the US. With grants he gained he trained others in his village to build windmills and fix water pumps and he built a solar powered water pump for his village.

Sometimes what local communities need is simple not complex technology that meets their real needs, and empowerment for people with ideas of how to solve them. William Kamkwamba has since set up a foundation “Moving Windmills” to support innovation and the building of infrastructure in Malawi, so to do just that.

Paul Curzon, Queen Mary University of London

“The boy who harnessed the wind” is playing at Soho Place London until 18 July 2026

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Emotional glasses

Image by Km Nazrul Islam from Pixabay

It’s fun to add emoticons to messages, and they help ensure people understand our feelings. They are helping some people understand feelings face-to-face too, with a bit of help from an Artificial Intelligence.

Reading faces

We take it for granted that we can look at someone’s face and tell whether they are happy or sad, angry or surprised. Autistic children, however, often struggle to understand people’s expressions. When anxious we also all tend to avoid eye contact. Some autistic children do that all the time. They are then even less likely to see the clues in people’s faces, and so start to understand emotions. This can make it harder to make friends.

From robots to glasses

Many hi-tech ways have been tried to help autistic children learn about emotions. One, for example, involves letting them play with robot ‘friends’ as some find the cartoon-like expressions on a robot face more comfortable and easier to follow. A different approach is based on wearable technology. Researchers at Stanford University have created a program for autistic children that works out a person’s expression and displays an emoticon of it in a pair of smart glasses.

An AI reading faces for you

A camera in the glasses records what the wearer sees and the Artificial Intelligence (AI) program detects any faces. This kind of technology is also used in smartphones to detect faces in your photo collection. It uses ‘machine learning’: the program learns what a face is by being shown lots of images, some with and some without faces. The program uses all that data to work out the patterns in an image that mean there is a face. It then uses that pattern to spot new faces.

In a similar way it can be trained on faces with different expressions. A training set of faces are used that are labelled with the emotion in that image. This allows the program to spot what pattern in a face makes a happy face, what makes a sad face, and so on. Having recognised an expression, the glasses finally act as a screen and show an emoticon, such as a smiley, corresponding to that expression. Superimposing digital images on the real world like this is called augmented reality. It makes looking at faces like a game and means that the child can use the emoticon to understand what the person in front of them is feeling. It also means they can start to learn for themselves – almost like the AI! The AI is labelling the faces for them, just as people had done for it. With the glasses, autistic children can be sure what each face is actually saying rather than having to guess. Eventually they might then form their own rules and so do it on their own.

Making a difference

The Stanford system was trialled with autistic children in their own homes. They used the system for several months and their parents found it made a clear difference. By the end many of the children were engaging much more with their family including making a lot more eye contact.

Emoticons are making a real difference to their lives.

Paul Curzon, Queen Mary University of London

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