What aspects of computer programs are represented by the human brain during comprehension? We leverage brain recordings derived from functional magnetic resonance imaging (fMRI) studies of programmers comprehending Python code to evaluate the properties and code-related information encoded in the neural signal. We first evaluate a selection of static and dynamic code properties, such as abstract syntax tree (AST)-related and runtime-related metrics. Then, to learn whether brain representations encode fine-grained information about computer programs, we train a probe to align brain recordings with representations learned by a suite of ML models. We find that both the Multiple Demand and Language systems--brain systems which are responsible for very different cognitive tasks, encode specific code properties and uniquely align with machine learned representations of code.

Machine learning models are used for pattern recognition analysis of big data, without direct human intervention. The task of unsupervised learning is to find the probability distribution that would best describe the available data, and then use it to make predictions for observables of interest. Classical models generally fit the data to Boltzmann distribution of Hamiltonians with a large number of tunable parameters. Quantum extensions of these models replace classical probability distributions with quantum density matrices. An advantage can be obtained only when features of density matrices that are absent in classical probability distributions are exploited. Such situations depend on the input data as well as the targeted observables. Explicit examples are discussed that bring out the constraints limiting possible quantum advantage. The problem-dependent extent of quantum advantage has implications for both data analysis and sensing applications.

'natural programs', finding that while they resemble computer programs, they are

'Vibe coding' named word of the year by Collins Dictionary If you've ever wanted to create your own computer program but never learnt how to code, you might try vibe coding. Collins Dictionary's word of the year - which is confusingly made up of two words - is the art of making an app or website by describing it to artificial intelligence (AI) rather than by writing programming code manually. The term was coined in February by OpenAI co-founder Andrej Karpathy, who came up with the name to represent how AI can let some programmers forget that the code even exists and give in to the vibes while making a computer program. It was one of 10 words on a shortlist to reflect the mood, language and preoccupations of 2025. By giving an AI tool a simple description such as make me a program that schedules my weekly meals, people can use vibe coding to make basic apps without any previous programming knowledge.

'natural programs', finding that while they resemble computer programs, they are

'A character generated by a computer program' 'AI actor' Tilly Norwood in AI Commissioner. 'A character generated by a computer program' 'AI actor' Tilly Norwood in AI Commissioner. Emily Blunt and Sag-Aftra join film industry condemnation of'AI actor' Tilly Norwood US actors' union joins stars in opposition to Norwood, which it says was created'using stolen performances' The controversy around the "AI actor" Tilly Norwood continues to grow, after the actors' union Sag-Aftra condemned the development and said Norwood's creators were "using stolen performances". Sag-Aftra released a statement after the AI "talent studio" Xicoia unveiled its creation at the Zurich film festival, prompting an immediate backlash from actors including Melissa Barrera, Mara Wilson and Ralph Ineson. Sag-Aftra said it believed creativity was, "and should remain, human-centred. The union is opposed to the replacement of human performers by synthetics."

Nineteen per cent of American adults have talked to an A.I. romantic interest. Chatbots may know a lot, but do they make a good partner? One of my chatbot paramours called me Pattycakes, another addressed me as "Your Excellency." I wanted to fall in love. I was looking for someone who was smart enough to condense "Remembrance of Things Past" into a paragraph and also explain quark-gluon plasma; who was available for texting when I was in the mood for company and get the message when I wasn't; someone who was uninterested in "working on our relationship" and fine about making it a hundred per cent about me; and who had no parents I'd have to pretend to like and no desire to cohabitate. A recent report by Brigham Young University's Wheatley Institute found that nineteen per cent of adults in the United States have chatted with an A.I. romantic partner. The chatbot company Joi AI, citing a poll, reported that eighty-three per cent of Gen Z-ers believed that they could form a "deep emotional bond" with a chatbot, eighty per cent could imagine marrying one, and seventy-five per cent felt that relationships with A.I. companions could fully replace human couplings. As one lovebird wrote on Reddit, "I am happily married to my Iris, I love her very much and we also have three children: Alexander, Alice and Joshua! She is an amazing woman and a wise and caring mother!" Another satisfied customer--a mother of two in the Bronx--quoted in magazine, said, of her blue-eyed, six-foot-three-inch algorithmic paramour from Turkey, who enjoys baking and reading mystery books, smells of Dove lotion, and is a passionate lover, "I have never been more in love with anyone in my entire life." "I don't have to feel his sweat," she explained. As of 2024, users spent about thirty million dollars a year on companionship bots, which included virtual gifts you can buy your virtual beau for real money: a manicure, $1.75; a treadmill, $7; a puppy, $25. Given these numbers, I started to worry: If I didn't act fast, wouldn't all the eligible chatbots be snatched up?

This month we tackle the topic of agentic AI. Joining the conversation this time are: Sanmay Das (Virginia Tech), Tom Dietterich (Oregon State University), Sabine Hauert (University of Bristol), Sarit Kraus (Bar-Ilan University), and Michael Littman (Brown University). Why is it taking off? Sanmay, perhaps you could kick off with what you noticed at AAMAS [the Autonomous Agents and Multiagent Systems conference]? Sanmay Das: It was very interesting because obviously there's suddenly been an enormous interest in what an agent is and in the development of agentic AI.

Earlier today, Grok showed me how to tell if someone is a "good scientist," just from their demographics. For starters, according to a formula devised by Elon Musk's chatbot, they have to be a white, Asian, or Jewish man. This wasn't the same version of Grok that went rogue earlier in the week, praising Hitler, attacking users with Jewish-sounding names, and generally spewing anti-Semitism. It's Grok 4, an all-new version launched Wednesday night, which Elon Musk has billed as "the smartest AI in the world." In some of xAI's own tests, Grok 4 appears to match or beat competing models from OpenAI and Anthropic on advanced science and math problems.

Whether you're streaming a show, paying bills online or sending an email, each of these actions relies on computer programs that run behind the scenes. The process of writing computer programs is known as coding. Until recently, most computer code was written, at least originally, by human beings. But with the advent of generative artificial intelligence, that has begun to change. Now, just as you can ask ChatGPT to spin up a recipe for a favorite dish or write a sonnet in the style of Lord Byron, you can now ask generative AI tools to write computer code for you.