Researchers built an analogue computer that uses water waves to forecast the chaotic future

Can a computer learn from the past and anticipate what will happen next, like a human? You might not be surprised to hear that some cutting-edge AI models could achieve this feat, but what about a computer that looks a little different – more like a tank of water?

We have built a small proof-of-concept computer that uses running water instead of a traditional logical circuitry processor, and forecasts future events via an approach called “reservoir computing”.

In benchmark tests, our analogue computer did well at remembering input data and forecasting future events – and in some cases it even did better than a high-performance digital computer.

So how does it work?

Throwing stones in the pond

Imagine two kids, Alice and Bob, playing at the edge of a pond. Bob throws big and small stones into water one at a time, seemingly at random.

Big and small stones create water waves of different size. Alice watches the water waves created by the stones and learns to anticipate what the waves will do next – and from that, she can have an idea of which stone Bob will throw next.

Reservoir computers copy the reasoning process taking place in Alice’s brain. They can learn from past inputs to predict the future events.

Although reservoir computers were first proposed using neural networks – computer programs loosely based on the structure of neurons in the brain – they can also be built with simple physical systems.

Reservoir computers are analogue computers. An analogue computer represents data continuously, as opposed to digital computers which represent data as abruptly changing binary “zero” and “one” states.

Representing data in a continuous way enables analogue computers to model certain natural events – ones that occur in a kind of unpredictable sequence called a “chaotic time series” – better than a digital computer.

How to make predictions

To understand how we can use a reservoir computer to make predictions, imagine you have a record of daily rainfall for the past year and a bucket full of water near you. The bucket will be our “computational reservoir”.

We input the daily rainfall record to the bucket by means of stone. For a day of light rain, we throw a small stone; for a day of heavy rain, a big stone. For a day of no rain, we throw no rock.

Each stone creates waves, which then slosh around the bucket and interact with waves created by other stones.

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At the end of this process, the state of the water in the bucket gives us a prediction. If the interactions between waves create large new waves, we can say our reservoir computer predicts heavy rains. But if they are small then we should expect only light rain.

It is also possible that the waves will cancel one another, forming a still water surface. In that case we should not expect any rain.

The reservoir makes a weather forecast because the waves in the bucket and rainfall patterns evolve over time following the same laws of physics.

So do many other natural and socio-economic processes. This means a reservoir computer can also forecast financial markets and even certain kinds of human activity.

Longer-lasting waves

The “bucket of water” reservoir computer has its limits. For one thing, the waves are short-lived. To forecast complex processes such as climate change and population growth, we need a reservoir with more durable waves.

One option is “solitons”. These are self-reinforcing waves that keep their shape and move for long distances.