They are here: The rise and rise of AI robots
You can spot them blinking away, triggering awe and curiosity. They enable check-ins at some airline counters at airports, roll across hotel reception areas offering welcome drinks, serve orders at restaurants. They are manning duties in warehouses, factories and logistics hubs. They are deployed at bars, aid doctors in surgery and first responders to triage. They are not yet ubiquitous, but there is no doubt that robots are here.
The buzz is visible in headlines streaming live. Masayoshi Son is making a $1.3-trillion bet under Project Crystal Land alongside TSMC for building robots and AI hubs. Tesla is all set, finally, to unveil its Robotaxi in Austin, Texas. Nvidia and Foxconn are in talks to deploy humanoid robots at the Houston AI server plant. Amazon deploys AI-enabled robot Vulcan at its warehouses and plans to deploy delivery robots as part of a plan to automate $200 billion in logistics costs. A Chinese outfit has unveiled the first robotic hand combining tactile perception with complete motion capabilities. Hexagon launched Aeon, a humanoid designed for industry for autonomy, automated measurement systems and perception—and what's more, it can produce digital twins.
Indian entities, too, are chasing productivity to expand the use of robotics for an array of businesses. Reliance-backed Addverb is launching humanoid robots to eliminate '3D jobs', ones that are dull, dirty and dangerous. Bengaluru-based Invento is developing Mitra robots for retail, hospitality and senior care. Kochi-based Asimov Robotics develops robots for high-risk settings. Hyderabad-based Svaya Robotics specialises in industrial robots for collaborative tasks in manufacturing and logistics. Bengaluru start-up Genobotics is the developer of Bandicoot robot which automates sewer cleaning. Kody from Ahmedabad is developing robots for surveillance, office services and industry.
The term robot owes its etymology to the Czech word robota, which means forced labour, and was introduced in Czech author Karel Capek's 1921 science fiction play Rossum's Universal Robots. Robots made their cinematic debut in 1927 in Metropolis, a movie about a polarised society in a divided futuristic city. Popular passions, though, surfaced with the 2007 blockbuster Transformers about alien robots produced by toymakers Hasbro and Takara Tomy and Schwarzenegger starrer Terminator. A century after Capek's coinage, a combination of factors has spurred the creeping robot evolution to a tipping point. The blend of knowledge and technology has propelled investments.
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Hindustan Times
an hour ago
- Hindustan Times
Is this year the beginning of the end of smartphones?
Last month, a curious partnership in the Valley made me wonder on the future of smart devices and the way we access our digital universe. In a rather whimsical blog post, OpenAI announced the acquisition of Jony Ive's studio startup io for $6.5 billion. 'We have the opportunity to completely reimagine what it means to use a computer,' said Altman, adding that despite unprecedented capability and new technologies like AI, the digital experience is being shaped by traditional products and interfaces. A new technology like AI, he explained, requires a complete rethink of tools through which we interact with the digital universe. The first smartphone came into being in the early 1993, when IBM's Simon added email and fax to a phone's capability. (Representative photo) This acquisition would've become yet another corporate announcement, except for the timing of it. In the last couple of years, there's a feeling across Silicon Valley that smartphone as a device to interact with the digital world is not enough. New technologies like AR/VR, robotics and now AI need new products to explore them with. The new generation is approaching the digital world as an extension of themselves, through speech and not swiping or typing. As technology becomes more intuitive, we need new devices to reflect this change – more immersive and aural, devices that augment the real world and not take you away from it. Tech companies are putting their heads together to develop devices that are more immersive or approach digital through other senses like aural or even neural. Legacy companies like Meta, Apple and Google and startups like Neuralink are experimenting with smart glasses, wearables, iOT devices, smartwatches, neural computers and even spatial computers (like VisionPro) where digital media is integrated with our real-life experience. So far, none of these devices have worked, but it does feel like we're at a cusp of dramatic change. A senior vice president in Apple even acknowledged that in 10 years, iPhones could go the way of iPods - become irrelevant and retro. It's time for this change, I would say. After all, our way of interacting with digital spaces – through laptops, desktops and smart devices - has been the same for more than 30 years now. The first smartphone came into being in the early 1993, when IBM's Simon added email and fax to a phone's capability. In 1990s that there was a constant feeling of experimentation as the handheld phones and PDAs that could access the internet were being played with through product design. Companies across the world from USA to Japan wanted to integrate access to internet with a phone. The mid 2000s brought smartphones like Blackberry with QWERTY keyboards, which quickly made tapping and emailing the done thing to do. This changed dramatically when finger-operative touchscreen technology came out into the market. Within a couple of years in 2006, LG had used it to launch a touchscreen smartphone. And then Apple made it the new normal when it launched iPhones in 2007. Also Read: Do gaming smartphones really make sense in 2025? Though there have been amazing advances in the smartphone including camera capabilities, chip design and biometrics, the device design itself hasn't changed the way we interact with the digital world. There's a screen we swipe, touch and pinch. We check out social media, upload our photos on cloud and chat and email on the go. This staleness in the design was clear in Apple's recently concluded annual developer conference, WWDC 2025. The new iPhone 17 will be more or less the same as iPhone 16 with a few tiny tweaks. Jony Ive, whose company OpenAI acquired, was formerly Apple's chief design officer and led design teams for Apple's iconic products – the iPhone, the iPod and even the Macbook Pro – before leaving the company in 2019. This new project that he's working on, has got him (and us) excited. According to him, this time now, 2025, reminds him of three decades ago when he emigrated to Silicon Valley to design products that would interact with the Internet. 'I have a growing sense that everything I have learned over the last 30 years has led me to this moment,' he said in the acquisition announcement. The Wall Street Journal reported that Open AI is considering options that want to move consumers beyond screens into a unique combination of listening devices and cameras. 'Surely there's something beyond legacy products,' says Ive, adding that they've already built a prototype and are currently working on more AI-first devices. I know what you're thinking and frankly, I'm thinking the same. Smartphones are our lifelines. We do everything on these devices – from chatting to watching shorts and videos, to making payments on the go. We're multi-screen beasts today, our fingers constantly swiping or typing and ridden with RSI, our eyes fatigued. Also Read: AI needs to be open and inclusive like India Stack But the world is also changing in ways that make me think maybe we will use devices without screens as the enablers. Voice interaction has caught on. The way we fish for information is going from a typed search to a prompt we ask. There is an increasing unease about phone-addiction and screen time. We're all looking for a way out. Something that allows us to be digitally connected without exhausting us. Devices that are more intuitive, more immersive, aural and neural that become extensions of us so we can interact with digital spaces without choosing them over real life. All this signals to an experimentative market which is ready for something new. I can't wait to find out what replaces my screens in the near future. What about you?
Indian Express
2 hours ago
- Indian Express
How is Tesla expected to remotely control its robotaxis, and what are its limitations?
Tesla is expected to tiptoe into its long-awaited robotaxi service in Austin, Texas, as soon as Sunday with about 10 of its Model Y SUVs that will operate within strict limits. CEO Elon Musk has said the company is being 'super paranoid' about safety and that humans will remotely monitor the fleet. Remote access and control – known in the industry as 'teleoperation' – is used in varying degrees by the handful of robotaxi startups operating around the globe. The technology has clear advantages and important limitations. Here are some details of how it works: Teleoperation is the control of machines by humans in a different location, usually over a wireless network. It is used to train robots to operate autonomously, monitor their autonomous activity, and take over when required. The global robotaxi industry is still in test mode, as companies deploy the vehicles in limited geographic areas and continually adjust the artificial intelligence software that controls them. Teleoperation is often used to intervene when a vehicle is unsure of what to do. Alphabet's Waymo, for example, has a team of human 'fleet response' agents who respond to questions from the Waymo Driver – its bot. 'Much like phone-a-friend, when the Waymo vehicle encounters a particular situation on the road, the autonomous driver can reach out to a human fleet response agent for additional information,' Waymo said in a blog post last year. Former Waymo CEO John Krafcik told Reuters, 'the cars aren't being actively monitored,' adding that the software is 'the ultimate decision-maker.' A Waymo video shows a car asking a remote operator whether a street with emergency response vehicles is open to traffic. When the human says yes, the vehicle proceeds. In contrast, other companies, such as Baidu's Apollo Go in China, have used fully remote backup drivers who can step in to virtually drive the vehicles. Baidu declined to comment. Driving vehicles remotely on public roads has a major potential problem: it relies on cellular data connections that can drop or operate with a lag, disconnecting the vehicle from the remote driver in dangerous situations. Philip Koopman, a Carnegie Mellon University engineering professor and autonomous-vehicle safety expert, said that approach could work for a small test deployment of 10 vehicles, such as Tesla's initial effort in Austin, but he called teleoperation 'inherently unreliable technology.' 'Eventually you will lose connection at exactly the worst time,' he said. 'If they've done their homework, this won't ever happen for 10 cars. With a million cars, it's going to happen every day.' Former Waymo CEO Krafcik agreed, adding that the time delay in cell signal makes remote driving 'very risky.' On the other hand, relying on the vehicle to reach out for help and allowing the vehicle to be the decision-maker are risky as well, Koopman said, as it does not guarantee the vehicle will make the right decision. Waymo declined to comment on the limitations of its approach. Koopman also noted there are limits to how many vehicles one person can safely monitor. A group of Democratic Texas lawmakers asked Tesla on Wednesday to delay its robotaxi launch until September, when a new autonomous-driving law is scheduled to take effect. The Austin-area lawmakers said in a letter that delaying the launch 'is in the best interest of both public safety and building public trust in Tesla's operations.' Musk for years has promised, without delivering, that its Full Self-Driving (Supervised) advanced driver assistance software would graduate to completely self-driving and control robotaxis. This year, he said Tesla would roll out a paid service in Austin underpinned by an 'unsupervised' version of the software. 'Teslas will be in the wild, with no one in them, in June, in Austin,' Musk told analysts and investors in January. In May, he told CNBC that the robotaxi would only operate in parts of Austin that are safe for it, would avoid difficult intersections, and would use humans to monitor the vehicles. What those teleoperators will do is not clear. For years inside Tesla, company executives have expected to use teleoperators who could take over in case of trouble, said one person familiar with the matter. For instance, if a robotaxi were stuck in a crowded pedestrian area and confused about what to do next, a human teleoperator could take over and guide it, the source said. Tesla advertised for teleoperation positions, saying the company needs the ability to 'access and control' autonomous vehicles and humanoid robots remotely. Such employees can 'remotely perform complex and intricate tasks,' it said in the advertisements. Tesla did not respond to a request for comment. 'We are being super paranoid about safety, so the date could shift,' Musk said in a post on X last week while providing a tentative launch date of June 22.
Indian Express
2 hours ago
- Indian Express
Can AI quicken the pace of math discovery?
Artificial intelligence can write a poem in the style of Walt Whitman, provide dating advice and suggest the best way to cook an artichoke. But when it comes to mathematics, large language models like OpenAI's immensely popular ChatGPT have sometimes stumbled over basic problems. Some see this as an inherent limitation of the technology, especially when it comes to complex reasoning. A new initiative from the Defense Advanced Research Projects Agency seeks to account for that shortfall by enlisting researchers in finding ways to conduct high-level mathematics research with an AI 'co-author.' The goal of the new grant-making program, Exponentiating Mathematics, is to speed up the pace of progress in pure (as opposed to applied) math — and, in doing so, to turn AI into a superlative mathematician. 'Mathematics is this great test bed for what is right now the key pain point for AI systems,' said Patrick Shafto, a Rutgers University mathematician and computer scientist who now serves as a program manager in DARPA's information innovation office, known as I20. 'So if we overcome that, potentially, it would unleash much more powerful AI.' He added, 'There's huge potential benefit to the community of mathematicians and to society at large.' Shafto spoke from his office at DARPA's headquarters, an anonymous building in northern Virginia whose facade of bluish glass gives little indication that it houses one of the most unusual agencies in the federal government. Inside the building's airy lobby, visitors surrender their cellphones. Near a bank of chairs, a glass display shows a prosthetic arm that can be controlled by the wearer's brain signals. 'By improving mathematics, we're also understanding how AI works better,' said Alondra Nelson, who served as a top science adviser in President Joe Biden's administration and is a faculty member at the Institute for Advanced Study in Princeton, New Jersey. 'So I think it's kind of a virtuous cycle of understanding.' She suggested that, down the road, math-adept AI could enhance cryptography and aid in space exploration. Started after World War II to compete with the Soviet Union in the space race, DARPA is most famous for fostering the research that led to the creation of ARPANET, the precursor to the internet we use today. At the agency's small gift store, which is not accessible to the public, one can buy replicas of a cocktail napkin on which someone sketched out the rudimentary state of computer networks in 1969. DARPA later funded the research that gave rise to drones and Apple's digital assistant, Siri. But it is also responsible for the development of Agent Orange, the potent defoliant used to devastating effect during the Vietnam War. 'I'm sure this isn't 100% innocent,' Andrew Granville, a mathematician at the University of Montreal, said of DARPA's math initiative, although he emphasized that he was only speculating about eventual outcomes. DARPA is, after all, part of the Pentagon, even if it has traditionally operated with enviable independence. The U.S. military is rapidly incorporating AI into its operations, with the aim of not losing out to China and its People's Liberation Army or to Russia, which has been testing out new technologies on the battlefield in Ukraine. At the same time, Granville praised the endeavor, which comes as the Trump administration is cutting funding for scientific research. 'We are in disastrous times for U.S. science,' Granville said. 'I'm very pleased that DARPA is able to funnel money to academia.' A surfer and skateboarder in his free time, Shafto, 49, sat in a sparse conference room one recent afternoon, imagining a future when AI would be as good at solving multistep problems as it is at trying to glean meaning from huge troves of texts, which it does through the use of probability theory. Despite the unseasonably raw weather, Shafto seemed dressed for the beach in a blue-and-white Hawaiian-style shirt, white flannel trousers and sandals, with a trilby hat on the table before him. His vibe was, on the whole, decidedly closer to that of Santa Cruz than of Capitol Hill, largely in keeping with DARPA's traditional disregard for the capital's slow, bureaucratic pace. (The agency sets priorities and funds outside scientists but does not do research on its own; academics like Shafto spend an average of four years as program managers.) 'There are great mathematicians who work on age-old problems,' Shafto said. 'That's not the kind of thing that I'm particularly interested in.' Instead, he wanted the discipline to move more quickly by using AI to save time. 'Problems in mathematics take decades or centuries, sometimes, to solve,' he said in a recent presentation at DARPA's headquarters on the Exponentiating Mathematics project, which is accepting applications through mid-July. He then shared a slide showing that, in terms of the number of papers published, math had stagnated during the last century while life and technical sciences had exploded. In case the point wasn't clear, the slide's heading drove it home: 'Math is sloooowwww. …' The kind of pure math Shafto wants to accelerate tends to be 'sloooowwww' because it is not seeking numerical solutions to concrete problems, the way applied mathematics does. Instead, pure math is the heady domain of visionary theoreticians who make audacious observations about how the world works, which are promptly scrutinized (and sometimes torn apart) by their peers. 'Proof is king,' Granville said. Math proofs consist of multiple building blocks called lemmas, minor theorems employed to prove bigger ones. Whether each Jenga tower of lemmas can maintain integrity in the face of intense scrutiny is precisely what makes pure math such a 'long and laborious process,' acknowledged Bryna R. Kra, a mathematician at Northwestern University. 'All of math builds on previous math, so you can't really prove new things if you don't understand how to prove the old things,' she said. 'To be a research mathematician, the current practice is that you go through every step, you prove every single detail.' Lean, a software-based proof assistant, can speed up the process, but Granville said it was 'annoying, because it has its own protocols and language,' requiring programming expertise. 'We need to have a much better way of communication,' he added. Could artificial intelligence save the day? That's the hope, according to Shafto. An AI model that could reliably check proofs would save enormous amounts of time, freeing mathematicians to be more creative. 'The constancy of math coincides with the fact that we practice math more or less the same: still people standing at a chalkboard,' Shafto said. 'It's hard not to draw the correlation and say, 'Well, you know, maybe if we had better tools, that would change progress.'' AI would benefit, too, Shafto and others believe. Large language models like ChatGPT can scour the digitized storehouses of human knowledge to produce a half-convincing college essay on the Russian Revolution. But thinking through the many intricate steps of a mathematical problem remains elusive. 'I think we'll learn a lot about what the capabilities of various AI protocols are from how well we can get them to generate material that's of interest,' said Jordan S. Ellenberg, a mathematician at the University of Wisconsin-Madison who is part of a team applying for an Exponentiating Mathematics grant. 'We have no intuition yet about which problems are going to be hard and which problems are easy. We need to learn that.' One of the more disconcerting truths about artificial intelligence is that we do not entirely understand how it works. 'This lack of understanding is essentially unprecedented in the history of technology,' Dario Amodei, CEO of the artificial intelligence company Anthropic, wrote in a recent essay. Ellenberg somewhat downplayed that assertion, pointing out that electricity was widely used before its properties were fully understood. Then again, with some AI experts worrying that artificial intelligence could destroy the world, any clarity into its operations tends to be welcome. Nelson, the former White House adviser, acknowledged 'legitimate' concerns about the rapid pace at which artificial intelligence is being integrated into seemingly every sector of society. All the more reason, she argued, to have DARPA on the case. 'There's a much higher benchmark that needs to be reached than whether or not your chatbot is hallucinating if you ask it a question about Shakespeare,' she said. 'The stakes are much higher.'
