To see what the future might look like it is often helpful to study our history. This is what I will do in this article. I retrace the brief history of computers and artificial intelligence to see what we can expect for the future.
How did we get here?
How rapidly the world has changed becomes clear by how even quite recent computer technology feels ancient to us today. Mobile phones in the ‘90s were big bricks with tiny green displays. Two decades before that the main storage for computers was punch cards.
In a short period computers evolved so quickly and became such an integral part of our daily lives that it is easy to forget how recent this technology is. The first digital computers were only invented about eight decades ago, as the timeline shows.
Since the early days of this history, some computer scientists have strived to make machines as intelligent as humans. The next timeline shows some of the notable artificial intelligence (AI) systems and describes what they were capable of.
The first system I mention is the Theseus. It was built by Claude Shannon in 1950 and was a remote-controlled mouse that was able to find its way out of a labyrinth and could remember its course.1 In seven decades the abilities of artificial intelligence have come a long way.
Language and image recognition capabilities of AI systems are now comparable to those of humans
The language and image recognition capabilities of AI systems have developed very rapidly.
The chart shows how we got here by zooming into the last two decades of AI development. The plotted data stems from a number of tests in which human and AI performance were evaluated in five different domains, from handwriting recognition to language understanding.
Within each of the five domains the initial performance of the AI system is set to -100, and human performance in these tests is used as a baseline that is set to zero. This means that when the model’s performance crosses the zero line is when the AI system scored more points in the relevant test than the humans who did the same test.2
Just 10 years ago, no machine could reliably provide language or image recognition at a human level. But, as the chart shows, AI systems have become steadily more capable and are now beating humans in tests in all these domains.
Outside of these standardized tests the performance of these AIs is mixed. In some real-world cases these systems are still performing much worse than humans. On the other hand, some implementations of such AI systems are already so cheap that they are available on the phone in your pocket: image recognition categorizes your photos and speech recognition transcribes what you dictate.
Language and image recognition capabilities of AI systems have improved rapidly3
From image recognition to image generation
The previous chart showed the rapid advances in the perceptive abilities of artificial intelligence. AI systems have also become much more capable of generating images.
This series of nine images shows the development over the last nine years. None of the people in these images exist; all of them were generated by an AI system.
The series begins with an image from 2014 in the top left, a primitive image of a pixelated face in black and white. As the first image in the second row shows, just three years later AI systems were already able to generate images that were hard to differentiate from a photograph.
In recent years, the capability of AI systems has become much more impressive still. While the early systems focused on generating images of faces, these newer models broadened their capabilities to text-to-image generation based on almost any prompt. The image in the bottom right shows that even the most challenging prompts – such as “A Pomeranian is sitting on the King’s throne wearing a crown. Two tiger soldiers are standing next to the throne” – are turned into photorealistic images within seconds.4
Timeline of images generated by artificial intelligence5
Language recognition and production is developing fast
Just as striking as the advances of image-generating AIs is the rapid development of systems that parse and respond to human language.
Shown in the image are examples from an AI system developed by Google called PaLM. In these six examples, the system was asked to explain six different jokes. I find the explanation in the bottom right particularly remarkable: the AI explains an anti-joke that is specifically meant to confuse the listener.
AIs that produce language have entered our world in many ways over the last few years. Emails get auto-completed, massive amounts of online texts get translated, videos get automatically transcribed, school children use language models to do their homework, reports get auto-generated, and media outlets publish AI-generated journalism.
AI systems are not yet able to produce long, coherent texts. In the future, we will see whether the recent developments will slow down – or even end – or whether we will one day read a bestselling novel written by an AI.
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