It's nearly two years since OpenAI released ChatGPT on an unsuspecting world, and the world, closely followed by the stock market, lost its mind. All over the place, people were wringing their hands wondering: What This Will Mean For [enter occupation, industry, business, institution]. Within academia, for example, humanities professors agonised about how they would henceforth be able to grade essays if students were using ChatGPT or similar technology to help write them. The answer, of course, is to come up with better ways of grading, because students will use these tools for the simple reason that it would be idiotic not to – just as it would be daft to do budgeting without spreadsheets. But universities are slow-moving beasts and even as I write, there are committees in many ivory towers solemnly trying to formulate "policies on AI use".

More than 7,000 languages are currently spoken on this planet and Meta seemingly wants to understand them all. Six months ago, the company launched its ambitious No Language Left Behind (NLLB) project, training AI to translate seamlessly between numerous languages without having to go through English first. On Wednesday, the company announced its first big success, dubbed NLLB-200. It's an AI model that can speak in 200 tongues, including a number of less-widely spoken languages from across Asia and Africa, like Lao and Kamba. According to a Wednesday blog post from the company, NLLB-200 can translate 55 African languages with "high-quality results."

Google's DeepMind AI team has collaborated with physicists from the Swiss Plasma Center at EPFL in Ecublens, Switzerland to develop an AI method to control the plasmas inside a nuclear fusion reactor. The study, published in the scientific journal Nature, furthers nuclear fusion research and could help quicken the arrival of a cheaper, clean, unlimited source of energy. DeepMind has now built a neural network using deep reinforcement learning that is able to manipulate the magnetic coils which are essential to confine the soup of plasma at a temperature that is hundreds of millions of degrees Celsius, even hotter than the sun's core. "This AI algorithm, the reinforcement learning, chose to use the TCV coils in a completely different way, which still more or less generates the same magnetic field. So it was still creating the same plasma as we had expected, but it just used the magnetic cores in a completely different way because it had complete freedom to explore the whole operational space. So people were looking at these experimental results about how the coil currents evolve and they were pretty surprised," said EPFL scientist Federico Felici.

Speech recognition is an important cog in Big Tech's AI machinery. But, despite its ubiquity, speech recognition is still a work in progress. Today, Facebook is heralding a major breakthrough in the way it trains these systems to learn new languages. The company says it has developed a method of building speech recognition tools that don't require transcribed data. The time consuming task involves humans listening to and transcribing hours of audio, a monotonous process that has to be repeated for each language. Whereas Facebook's "unsupervised" system learns purely from speech audio and unpaired text to give it a better sense of what human communication sounds like.

In 2016, Alphabet's DeepMind came out with AlphaGo, an AI which consistently beat the best human Go players. One year later, the subsidiary went on to refine its work, creating AlphaGo Zero. Where its predecessor learned to play Go by observing amateur and professional matches, AlphaGo Zero mastered the ancient game by simply playing against itself. DeepMind then created AlphaZero, which could play Go, chess and shogi with a single algorithm. What tied all those AIs together is that they knew the rules of the games they had to master going into their training.

Alexander Fleming left a petri dish of bacteria out while he went on a two-week holiday. On his return, he found that the dish had been contaminated by a fungus that produced an antibacterial substance. He named it penicillin, and it has since saved millions of lives. Even in the modern world, drug discovery still essentially relies on chance. Pharmaceutical companies often screen thousands of compounds trying to find one with the desired effect.

IBM has developed a new AI model which predicts the onset of Alzheimer's better than standard clinical tests. The AI is designed to be non-invasive and uses a short language sample from a verbal cognitive test given to a patient. Using this sample, the AI model is able to predict the onset of Alzheimer's with around 71 percent accuracy. For comparison, standard clinical tests are correct approximately 59 percent of the time and take much longer to diagnose. Current tests analyse the descriptive abilities of people as they age for potential warning signs.

A new AI system developed by researchers from Google and the University of California could prevent deaths caused by incorrect prescriptions. While quite rare, prescriptions that are incorrect – or react badly to a patient's existing medications – can result in hospitalisation or even death. In a blog post today, Alvin Rajkomar MD, Research Scientist and Eyal Oren PhD, Product Manager, Google AI, set out their work on using AI for medical predictions. The AI is able to predict which conditions a patient is being treated for based on certain parameters. "For example, if a doctor prescribed ceftriaxone and doxycycline for a patient with an elevated temperature, fever and cough, the model could identify these as signals that the patient was being treated for pneumonia," the researchers wrote.

A new "text-generating system" created by the brains behind Massachusetts Institute of Technology may be the beginning of the end for all human editing jobs. The system, announced in a press release Wednesday, is able to rummage through the millions of Wikipedia pages, sniff around for outdated data, and replace it with the most recent information available on the internet in a "human-like" style -- thus making the need for real, hot-blooded editors basically obsolete.

Companies that aim to transform how we recycle, make websites more accessible for people who are Deaf, and give the public a greater say in how their towns change have joined a Microsoft programme that uses AI to tackle challenges in society. The latest AI for Good cohort, based in London, contains 12 start-ups from across Britain who will be given access to Microsoft technology, resources and expertise that will help them develop and launch their products and solutions. The programme is run by Microsoft and the Social Tech Trust. It is open to entrepreneurs from the UK who are developing a solution that focuses on one of four areas – AI for Earth, AI for Accessibility, AI for Humanitarian Action and AI for Cultural Heritage. By helping grow innovative ideas into established companies, Microsoft and the Social Tech Trust hope to create a more sustainable and accessible world.