Across the technology industry, artificial intelligence (AI) has boomed over the last year. Lensa went viral creating artistic avatar artwork generated from real-life photos. The OpenAI chatbot ChatGPT garnered praise as a revolutionary leap in generative AI with the ability to provide answers to complex questions in natural language text. Such innovations have ignited an outpouring of investments even as the tech sector continues to experience major losses in stock value along with massive job cuts. And there is no indication the development of these AI-powered capabilities will slow down from their record pace.

Biologists inspired by digital art generators like DALL-E decide to build artificial intelligence human proteins that can fight cancer, flu, and Covid. DALL-E works by processing the text descriptions through several layers of neural networks, which are sets of algorithms that are designed to mimic the way the human brain works. These neural networks analyze the text and extract a representation of the image that is described. This representation is then used to generate the new image, which is done by passing it through a decoder network. The decoder network then generates a new image that corresponds to the text description. One of the key features of DALL-E is its ability to generate images that are not present in the training dataset.

A mental health service that allows people to receive encouraging words of support and advice from others tested AI-generated responses without first notifying the recipients. Rob Morris, founder of the free mental health service Koko, outlined in a series of Twitter posts how the firm tested using a chatbot to help provide mental health support to about 4000 people. The chatbots were powered by GPT-3, a publicly available AI built by San Francisco-based company OpenAI.

On a recent afternoon Jonas Thiel, a socioeconomics major at a college in northern Germany, spent more than an hour chatting online with some of the left-wing political philosophers he had been studying. These were not the actual philosophers but virtual recreations, brought to conversation, if not quite life, by sophisticated chatbots on a website called Character.AI. Mr. Thiel's favorite was a bot that imitated Karl Kautsky, a Czech-Austrian socialist who died before World War Two. When Mr. Thiel asked Kautsky's digital avatar to provide some advice for modern-day socialists struggling to rebuild the worker's movement in Germany, Kautsky-bot suggested that they launch a newspaper. "They can use it not only as a means of spreading socialist propaganda, which is in short supply in Germany for the time being, but also to organize working class people," the bot said. Kautsky-bot went on to argue that the working classes would eventually "come to their senses" and embrace a modern-day Marxist revolution.

The use of artificial intelligence in medicine is growing rapidly.Credit: ktsimage/Getty Each day, around 350 people in the United States die from lung cancer. Many of those deaths could be prevented by screening with low-dose computed tomography (CT) scans. But scanning millions of people would produce millions of images, and there aren't enough radiologists to do the work. Even if there were, specialists regularly disagree about whether images show cancer or not. The 2017 Kaggle Data Science Bowl set out to test whether machine-learning algorithms could fill the gap.

Japan has been developing robots to care for older people for over two decades, with public and private investment accelerating markedly in the 2010s. By 2018, the national government alone had spent well in excess of $300 million funding research and development for such devices. At first glance, the reason for racing to roboticize care may seem obvious. Almost any news article, presentation, or academic paper on the subject is prefaced by an array of anxiety-inducing facts and figures about Japan's aging population: birth rates are below replacement levels, the population has started to shrink, and though in 2000 there were about four working-age adults for every person over 65, by 2050 the two groups will be near parity. The number of older people requiring care is increasing rapidly, as is the cost of caring for them.

Artificial intelligence has promised much, but there has been something holding it back from being used successfully by billions of people: a frustrating struggle for humans and machines to understand one another in natural language. This is now changing, thanks to the arrival of large language models powered by transformer architectures, one of the most important AI breakthroughs in the past 20 years. This story is from the WIRED World in 2023, our annual trends briefing. Read more stories from the series here--or download or order a copy of the magazine. Transformers are neural networks designed to model sequential data and generate a prediction of what should come next in a series.

What will RLHF-based PaLM apps be able to accomplish? With the model's expanding scale, performance across all activities keeps becoming better, creating more opportunities. Up to 540 billion parameters can be used with PaLM. Comparatively, GPT-3 only has about 175. The first open source ChatGPT equivalent appears to have appeared.

Various research groups have been teasing the idea of an AI doctor for the better half of the past decade. In late December, computer scientists from Google and DeepMind put forth their version of an AI clinician that can diagnose a patient's medical conditions based on their symptoms, using a large language model called PaLM. Per a preprint paper published by the group, their model scored 67.6 percent on a benchmark test containing questions from the US Medical License Exam, which they claim surpassed previous state-of-the-art software by 17 percent. One version of it performed at a similar level to human clinicians. But, there are plenty of caveats that come with this algorithm, and others like it.

This is Bloomberg Opinion Today, an updated Bayeux Tapestry of Bloomberg Opinion's opinions. Apple Inc. recently added audiobook narration to the growing list of occupations where algorithms are poised to replace humans alongside graphic designers, college essayists and limerick writers. Luckily, the fine art of newslettering remains (ahem) far beyond the capabilities of even the most sophisticated artificial intelligence software. Still, hope is at hand for those not fortunate enough to toil in the newsletter mines but still seeking gainful employment that won't disappear as robots take control.