For a few days recently, the hottest new hangout on the internet was a vibe-coded Reddit clone called Moltbook, which billed itself as a social network for bots. As the website's tagline puts it: "Where AI agents share, discuss, and upvote. Launched on January 28, Moltbook went viral in a matter of hours. It's been designed as a place where instances of a free open-source LLM-powered agent known as OpenClaw (formerly known as ClawdBot, then Moltbot), could come together and do whatever they wanted. But is Moltbook really a glimpse of the future, as many have claimed? More than a billion people worldwide suffer from a mental-health condition, according to the World Health Organization. The prevalence of anxiety and depression is growing in many demographics, particularly young people, and suicide is claiming hundreds of thousands of lives globally each year. Given the clear demand for accessible and affordable mental-health services, it's no wonder that people have looked to artificial intelligence for possible relief. Millions are already actively seeking therapy from popular chatbots, or from specialized psychology apps like Wysa and Woebot. Four timely new books are a reminder that while the present feels like a blur of breakthroughs, scandals, and confusion, this disorienting time is rooted in deeper histories of care, technology, and trust. Making AI Work, MIT Technology Review's new AI newsletter, is here For years, our newsroom has explored AI's limitations and potential dangers, as well as its growing energy needs . And our reporters have looked closely at how generative tools are being used for tasks such as coding and running scientific experiments . But how is AI being used in fields like health care, climate tech, education, and finance? How are small businesses using it? And what should you keep in mind if you use AI tools at work? These questions guided the creation of Making AI Work, a new AI mini-course newsletter. Read more about it, and sign up here to receive the seven editions straight to your inbox. The number of civil lawsuits it's pursuing has sharply dropped in comparison to Trump's first term. It's the latest example of Brussels' attempts to rein in Big Tech. Local governments and banks are only too happy to oblige promising startups. Cryptocurrency is now fully part of the financial system, for better or worse. "Agentic engineering" is the next big thing, apparently. Runners had long suspected its suggestions were pushing them towards injury. Only around three dozen supporters turned up. Its menswear suggestions are more manosphere influencer than suave gentleman. "There is no Plan B, because that assumes you will fail.

If speed dating mixed with blind dating sounds like your idea of hell, look away now. Ten years since dating app Tinder first encouraged users to swipe through potential partners based largely on their looks, some singles are doing away with profile photos altogether. In the absence of Cilla and "our Graham", those looking for love are turning instead to a new cohort of "blind dating apps" in the hope of making more meaningful connections. "I'm already on Tinder, Badoo, Bumble, Hinge – all of them!" says Victoria Brown, a 26-year-old client success manager from Upminster, east London. "A blind dating app seemed like a good idea because usually you think: 'Oh, he's really good-looking' but then, when you start talking, the chat's not that good. Not seeing what someone looks like, at least at first, gives it a bit of a twist – although I was nervous about the reveal."

Automating routine and transactional interactions such as account management, order confirmations, returns, and address change with smart bots is on the rise.

"Even primitive autonomous technology that exists today is better than an average human driver on the road" Recent moves by big players signal at the potential of India's AV ecosystem. Tata Elxsi has created a full-stack IP called AutonomAI to accelerate programs for AVs, and Intel's decision to gather data on traffic patterns to create algorithms to be used in India and overseas for autonomous driving. Moreover, a large number of AV startups have come up the ladder, especially in the last six years, namely: Swaayatt (2015), AutoNxt (2016), Ati Motors and Flux Auto (2017), Flo Mobility (2019), Minus Zero (2020) etc. Autonomous vehicles (AVs) startups in India, including Swaayatt Robots, Ati Motors, Netradyne, have raised substantial funding recently. Saurabh Chandra, Co-Founder, Ati Motors, said: "There is a confluence of factors due to the pandemic: workforce management has become challenging, prices are rising, making automation more attractive while technology is getting better and cheaper. There is an explosion of demand in the eCommerce space that can't be addressed by simply adding people; technology is the only way to handle the scale." India is a huge market.

Since the release of PyTorch in 2016, it is on a rollercoaster ride as its adoption among developers and researchers is continually increasing. Although it was released long after one of the most popular deep learning frameworks TensorFlow, over the years, PyTorch has quickly gained grounds and has overtaken advantage its competitors had due to their early release. Numerous organisations are utilising PyTorch in their business processes to innovate and eliminate various business challenges. More notably, Microsoft and Tesla have embraced PyTorch in their organisations for adding artificial intelligence capabilities. While Tesla has integrated it for autopilot in the car, Microsoft has been using it for internal developments and have also brought support on Azure.

The premise of this new mode was simple: 100 people parachute onto an island with only the clothes on their back and a pickaxe. Players can go it alone or enter as a team of up to four. As they forage for weapons and defensive items and generally hunt rival players, the game slowly restricts the game area by way of a "Storm Eye," which players must remain inside to survive. It's this mechanic that keeps the game active: The eye periodically shrinks and players are forced to converge on the same areas on the map or risk checking out early. If that idea sounds familiar, it's because the gameplay loop is what made PUBG so popular in the first place.

A number of this week's milestones in the history of technology link the rise of IBM, the introduction of the ENIAC, and the renewed fascination with so-called artificial intelligence. "IBM" was first used for CTR's subsidiaries in Canada and South America, but after "several years of persuading a slow-moving board of directors," Thomas and Marva Belden note in The Lengthening Shadow, Thomas J. Watson Sr. succeeded in applying it to the entire company: "International to represent its big aspirations and Business Machines to evade the confines of the office appliance industry." As Kevin Maney observes in The Maverick and His Machine, IBM "was still an upstart little company" in 1924, when "revenues climbed to $11 million – not quite back to 1920 levels. The upstart, according to Watson, was going to live forever. From a talk he gave at the first meeting of IBM's Quarter Century Club (employees who have served the company for 25 years), on June 21, 1924: The opportunities of the future are bound to be greater than those of the past, and to the possibilities of this business there is no limit so long as it holds the loyal cooperation of men and women like yourselves.

Machine Learning, driven by the rise of big data and evolving technologies, is emerging as a powerful quantitative investment tool, with financial advisers increasingly recognising the benefits it can bring to investors, according to Man AHL. A recent survey of financial advisers, who attended a series of adviser events held by Man AHL across Australia earlier this month, found that nearly three quarters of advisers (74%) believe Machine Learning, a branch of artificial intelligence, has the potential to change the way we invest in the future. Speaking at the adviser events, Man AHL's Oxford-based Chief Scientist Dr. Anthony Ledford said that Machine Learning has become increasingly important to the alternative investment management industry as it deals with larger and more complex data-sets. "The rise of Machine Learning in quantitative investing is powered by three separate revolutions: the growth in computing power, the explosion of data generation and the maturing of methodologies from statistics, computer science, mathematics and engineering, amongst other disciplines." "As more data become available, sophisticated Machine Learning models enable new patterns to be detected that humans can't easily spot. The technology is a significant area of research focus for Man AHL and we believe our enhanced focus on Machine Learning will be strongly supportive of the evolution of our quantitative investment strategies," Dr. Ledford said.

AI, and the branch of this discipline called deep learning, crashed the public consciousness on March 9 when Google DeepMind's AlphaGo program beat South Korean champion Lee Se-dol at ancient Chinese game Go. Since then, barely a week has gone by without a fresh breakthrough – or scare story. True AI implies a change in the relationship between machine and human – from predictable task worker reliant on our instructions, to a system which has the capacity to surprise and surpass us. For many, the loss of control inherent in this change is alarming. Hal and Skynet are suddenly too close for comfort.

It's being dubbed the Fourth Industrial Revolution: the explosion of robots, machines, algorithms and artificial intelligence (AI) in the workplace is coming. There's been a lot of recent speculation about how robotics and automation will change the landscape of employment, and the professions that could become obsolete as a result. We're all familiar with those annoying "unexpected item in the bagging area" self-service supermarket checkouts, or the big robots used on the production line in factories making cars and other complex products. In the supermarket, now just one checkout assistant can manage 6 or more tills, or cars and machines can be assembled safely, with every one being turned out to the same standard. So what jobs will be next on the chopping block in this technological revolution? By and large, the main professions under threat are ones that involve repetitive tasks – that could be inputting data, preparing spreadsheets and reports and other administrative duties, retail jobs, manufacturing and even some more complex analytical roles that could be better served by an algorithm doing all the hard work.