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  Artificial intelligence platform Hugging Face has launched a dedicated app marketplace for its Reachy Mini desktop robot, opening robotics development to a much wider audience beyond engineers and programmers. The new Reachy Mini App Store arrives less than a year after the company introduced the low-cost robot in July 2025 following its acquisition of robotics startup Pollen Robotics. Unlike traditional robotics systems that often require technical expertise and expensive hardware, Reachy Mini was designed as a small desktop robot that ordinary users can experiment with at home or in workplaces. The store already contains more than 200 applications created by community members. Owners of the robot can install these apps without paying additional fees. At present, developers cannot monetize their creations, although Hugging Face says the system may support paid apps later because the platform is built on its existing “Spaces” infrastructure for hosting AI applications. According to Hugging Face CEO Clément Delangue, the company’s main objective is to remove the technical barrier that has historically made robotics inaccessible to most people. He explained that users without coding or engineering experience are now building working robot applications in less than an hour using AI-powered tools. A major obstacle in robotics has long been the shortage of large public datasets. While large language models improved rapidly using enormous collections of publicly available software code from platforms such as [GitHub], robotics-specific programming data remains far more limited. This has traditionally made it difficult for AI systems to understand how physical machines operate or interact with hardware components. To address this problem, Hugging Face developed a system that allows users to describe robot behaviors in normal language instead of writing complex code manually. For example, a user can simply instruct the robot to wave when greeted. An AI agent then generates the necessary code, checks whether it works within the robot’s hardware limitations, and prepares the application automatically. The company says the platform supports multiple AI models rather than relying on a single provider. Developers can use Hugging Face’s own “ML Intern” tool or connect external models including GPT-5.5, Claude Opus 4.6, Gemini Live, Mini Max GM5, Kimmy 2.6, and Deep Sig V4 Pro. Official conversation-based apps currently use OpenAI Realtime and Gemini Live for real-time interaction. Hugging Face argues that these higher-level software abstractions substantially reduce the amount of time needed to build robotics applications. Tasks that previously required weeks of integration work can now reportedly be completed within minutes. The Reachy Mini itself is positioned as an affordable alternative to commercial robotics platforms. The company noted that robots from firms such as Boston Dynamics can cost tens of thousands of dollars, while some competing Chinese systems begin at more than $1,900. Reachy Mini is available in two versions. The Reachy Mini Lite costs $299 plus shipping and connects to an external computer through USB for processing. The wireless edition costs $449 plus shipping and includes built-in computing hardware using a Raspberry Pi CM4 alongside Wi-Fi support. Delangue said approximately 10,000 units have already been sold, including 3,000 purchases within the past two weeks alone. Hugging Face expects another 1,000 robots to ship within the next month. People who do not own the robot can still experiment with the platform through a browser-based simulator that recreates the robot in a virtual 3D environment. Users can also duplicate existing apps through a feature known as “forking” and then modify them using AI instructions, such as changing a robot’s responses into another language. The App Store forms part of Hugging Face’s broader “Le Robot” initiative launched in 2024 to publish open-source robotics code, tutorials, and hardware resources online. Unlike developer-focused repositories, the Reachy Mini App Store was designed specifically for non-technical users and hobbyists. More than 150 creators have already contributed applications to the store, many without previous robotics experience. One example highlighted by the company involved 78-year-old retired marketing executive Joel Cohen, who has no technical training and is colorblind. Despite taking two weeks to assemble his Reachy Mini Lite, a process that normally requires only a few hours, Cohen used AI tools to create a robot assistant for CEO discussion groups held over Zoom. The system greets participants by name, verifies claims during discussions, summarizes conversations, and challenges shallow responses in real time. Other applications developed by the community include a chess-playing robot that jokes about user mistakes, a productivity assistant that detects phone usage, a language-learning companion that corrects pronunciation, and a Formula 1 race commentator that narrates races live. Delangue also described creating his own office receptionist application in under two hours. The system uses facial recognition to identify visitors, greet them, ask whom they are meeting, and automatically send notifications to employees. According to Delangue, developing robotics software previously required deep specialization and months of work for people outside the robotics industry. Hugging Face believes combining low-cost hardware with AI agents capable of generating code could reshape how ordinary users interact with robots. The company says its longer-term goal is to make robotics resemble the personal computer and smartphone markets, where hardware becomes widely available and software creation is no longer restricted to technical specialists.

What if robots could think for themselves—no cloud, no lag, just pure, real-time intelligence? In this episode, we dive into the game-changing world of Google DeepMind’s Gemini Robotics on-device model, the breakthrough that’s redefining what robots can do. Imagine a compact AI brain that lets robots operate autonomously, process information instantly, and make split-second decisions—whether on the factory floor, in your living room, or even on a mission to Mars. We’ll break down how Gemini Robotics is slashing latency, boosting adaptability, and delivering jaw-dropping performance with minimal training data. You’ll hear how this on-device AI is setting new standards for robot safety and flexibility, making it a must-watch development for anyone fascinated by artificial intelligence, robotics, or the future of technology. From the latest in edge AI to the real-world impact of autonomous robots, this episode is packed with insights, controversy, and a glimpse into a future where machines are smarter, faster, and more independent than ever. Whether you’re a tech enthusiast, a robotics pro, or just curious about the next big thing, you’ll want to stick around till the end. Ready to see how Google DeepMind is changing the robotics game? Hit play, share this episode with your fellow techies, and don’t forget to subscribe for more mind-blowing updates on AI and robotics!

 A single password opened thousands of Yarbo’s robot mowers worldwide, leaving owners in over thirty nations vulnerable without knowing it. While testing how these smart devices manage login requests, analyst Andreas Makris spotted the weak point - simple as typing “admin” into a forgotten backdoor. Some of these exposed devices operate using Linux platforms, linked straight to the web, depending on camera inputs, location signals, wireless links - also automatic map functions.  Units across many regions used identical preset login details, investigators found. Remote entry into such hardware could happen without consent, Makris explained. Midway through the review, personal data came into view - email addresses, exact lawn mower locations, and network credentials laid bare. Testing revealed a real-time display pinpointing above 11,000 units active in at least thirty nations.  While examining traffic patterns, digital trails linked each machine to specific geographic points. Visibility extended beyond basic details once hidden layers were uncovered. Not just limited to leaked information, the dangers included remote hijacking of lawn robots. Through experiments, scientists showed unauthorized users might trigger motion controls, switch on built-in imaging tools, while also probing residential networks for weak spots - all from a distance.  Operating much like standard web-linked machines, these gadgets may end up pulled into coordinated hacking efforts. Such capabilities raise concern about their role in broader digital threats. A test shown to journalists supposedly let someone in Germany steer a 200-pound lawn mower near a home in New York, though they were separated by thousands of miles. Commands sent from afar took priority over hands-on operation, yet people close by received no warning when shifts occurred.  Warnings emerged about gadgets placed close to critical infrastructure raising wider safety risks. Not far from power stations or manufacturing zones, fragile automated machines might operate, Makris noted - highlighting growing unease over threats to both physical setups and digital networks. Fixing the problem via firmware patches did not work - systems kept falling back to identical default passwords.  Even after updates, the same login details resurfaced across devices. Experts pointed out that swapping passwords alone misses larger flaws: built-in factory access remains, while remote management tools stay vulnerable by design. Later, Yarbo admitted the issues once details emerged. Though based openly in New York, it holds ties to Hanyang Tech located in Shenzhen, China. Reports indicate the firm shut down some remote diagnostics pathways following scrutiny.  Root passwords were reset shortly afterward. Access without authentication saw restrictions applied. Instead of using one password for every machine, new measures shifted toward unique credentials per device. Despite pledges of improved audit mechanisms and stricter controls on remote diagnostics, concerns lingered. Backdoor-style access by manufacturers allegedly persists in the equipment, skeptics noted - undermining claims of real change. Hidden backdoors and minimal built-in safeguards in smart gadgets are drawing sharper scrutiny, according to researchers.  With households increasingly using AI-powered tools, robotic aids, or connected sensors, vulnerabilities multiply. Instead of isolated digital leaks, failures might now trigger real-world harm - door locks failing, cameras hijacked, entire home networks invaded. Security flaws once seen as minor glitches may now enable intrusions beyond data theft.  When manufacturers skip strong defaults, everyday convenience turns into risk points across neighborhoods. Because these devices interact physically with environments, weaknesses aren’t just virtual - they can reach into living rooms, garages, even children's bedrooms. So while automation spreads rapidly, oversight lags behind, leaving gaps attackers can exploit.

 Salaries climb fast as demand surges for experts who blend AI know-how with hands-on hardware skills. Firms in robotics, military tech, and self-operating machines now pay between three hundred thousand and five hundred thousand dollars just to attract top people. That surge comes on the heels of earlier fights for workers during the driverless car push, when even big names had trouble pulling in talent. Waymo once set the bar high - now others chase it harder than before. Pressure builds not because of trends, but due to how few can actually bridge software brains with real-world devices.  Competition doesn’t slow - it spreads, fueled by what very few offer. What drives this wave of hiring is the need for people able to connect classic robotics with current AI tools. Such individuals must build and roll out smart systems that work in many areas - humanoid machines, factory automation, self-driving lift trucks, plus equipment found in farming, mining, and building sites. Because these jobs involve high-level challenges, skilled workers have become highly sought after; rivalry now stretches beyond new tech firms to include long-standing car makers too.  Now stepping into a sharper spotlight, defense tech companies attract skilled professionals more aggressively than many peers - backed by steady financial support from organizations including the U.S. Department of Defense. Because these firms propose better pay, workers once aimed at self-driving car ventures shift direction, nudging auto industry players and new entrants alike toward rethinking how they hire and reward staff. Positions like AI enablement engineers and applied AI researchers see intense demand; such roles feed straight into building advanced smart technologies. While quiet on the surface, movement beneath reshapes where expertise flows.  A shift in talent demand could reshape parts of the auto industry. Those focusing on driverless systems might lose key staff, possibly stalling progress. Firms new to the field may have to find more money or use what they have more carefully just to keep up. Some investors are moving fast - one backer gathered well over a billion dollars to support emerging hardware-driven AI ventures. Growth in this space seems tied closely to who can attract and hold technical experts. Money flows follow where specialists choose to work.  What lies ahead isn’t just about filling roles - industries are shifting as firms move past self-driving cars toward what some call physical AI. These efforts stretch into areas like military tech, factory robots, and new kinds of transport machinery. Firms like Hermeus, having secured major capital lately, show where money is going: complex builds that tie artificial intelligence to real-world hardware. Growth now hinges less on software alone, more on machines that act in space. Quiet progress reshapes entire sectors without loud announcements. Capital follows builders who merge circuits with movement.  Now that the field has grown older, fighting for skilled workers plays a central role in where it heads next. Winning trust and keeping sharp minds depends on which organizations manage operations at scale using actual AI systems today. Because need keeps climbing while available experts stay few, hardware-linked AI skill shortages persist - pointing toward lasting changes in how firms assess and pursue tech talent. Though time passes, pressure does not ease.

 Chinese autonomous taxis could begin operating on UK roads by 2026 after Uber and Lyft announced plans to partner with Chinese technology company Baidu to trial driverless vehicles in London. Both companies are seeking government approval to test Baidu’s Apollo Go robotaxis, a move that could mark an important step in the UK’s adoption of self-driving transport.  Baidu’s Apollo Go service already operates in several cities, mainly in China, where it has completed millions of passenger journeys without a human driver. If approved, the UK trials would represent the first large-scale use of Chinese-developed robotaxis in Europe, placing London among key global hubs working toward autonomous mobility.  The UK government has welcomed the development. Transport secretary Heidi Alexander said the announcement supports Britain’s plans for self-driving vehicles and confirmed that the government is preparing to allow autonomous cars to carry passengers under a pilot scheme starting in spring. The Department for Transport is developing regulations to enable small autonomous taxi- and bus-style services from 2026, with an emphasis on responsible and safe deployment.  Uber has said it plans to begin UK driverless car trials as regulations evolve, partnering with Baidu to help position Britain as a leader in future transport while offering Londoners another travel option. Lyft has also expressed interest, stating that London could become the first European city to host Baidu’s Apollo Go vehicles as part of a broader agreement covering the UK and Germany.   Despite enthusiasm from companies and policymakers, regulatory approval remains a major challenge. Lyft chief executive David Risher said that, if approved, testing could begin in London in 2026 with a small fleet of robotaxis, eventually scaling to hundreds. Experts caution, however, that autonomous transport systems cannot expand as quickly as other digital technologies.   Jack Stilgoe, professor of science and technology policy at University College London, warned that moving from limited trials to a fully operational transport system is complex. He stressed the importance of addressing safety, governance, and public trust before autonomous taxis can become widely used.  Public scepticism remains strong. A YouGov poll in October found that nearly 60 percent of UK respondents would not ride in a driverless taxi under any circumstances, while 85 percent would prefer a human-driven cab if price and convenience were the same. Ongoing reports of autonomous vehicle errors, traffic disruptions, and service suspensions have added to concerns. Critics also warn that poorly regulated robotaxis could worsen congestion, undermining London’s efforts to reduce city-centre traffic.

 In popular culture, robots have long carried nicknames. Battlestar Galactica called them “toasters,” while Blade Runner used the term “skinjobs.” Now, amid rising tensions over artificial intelligence, a new label has emerged online: “clanker.”  The word, once confined to Star Wars lore where it was used against battle droids, has become the latest insult aimed at robots and AI chatbots. In a viral video, a man shouted, “Get this dirty clanker out of here!” at a sidewalk robot, echoing a sentiment spreading rapidly across social platforms.  Posts using the term have exploded on TikTok, Instagram, and X, amassing hundreds of millions of views. Beyond online humor, “clanker” has been adopted in real-world debates. Arizona Senator Ruben Gallego even used the word while promoting his bill to regulate AI-driven customer service bots. For critics, it has become a rallying cry against automation, generative AI content, and the displacement of human jobs.  Anti-AI protests in San Francisco and London have also adopted the phrase as a unifying slogan. “It’s still early, but people are really beginning to see the negative impacts,” said protest organizer Sam Kirchner, who recently led a demonstration outside OpenAI’s headquarters.  While often used humorously, the word reflects genuine frustration. Jay Pinkert, a marketing manager in Austin, admits he tells ChatGPT to “stop being a clanker” when it fails to answer him properly. For him, the insult feels like a way to channel human irritation toward a machine that increasingly behaves like one of us.  The term’s evolution highlights how quickly internet culture reshapes language. According to etymologist Adam Aleksic, clanker gained traction this year after online users sought a new word to push back against AI. “People wanted a way to lash out,” he said. “Now the word is everywhere.”  Not everyone is comfortable with the trend. On Reddit and Star Wars forums, debates continue over whether it is ethical to use derogatory terms, even against machines. Some argue it echoes real-world slurs, while others worry about the long-term implications if AI achieves advanced intelligence. Culture writer Hajin Yoo cautioned that the word’s playful edge risks normalizing harmful language patterns.  Still, the viral momentum shows little sign of slowing. Popular TikTok skits depict a future where robots, labeled clankers, are treated as second-class citizens in human society. For now, the term embodies both the humor and unease shaping public attitudes toward AI, capturing how deeply the technology has entered cultural debates.

  In a major leap for artificial intelligence and robotics, computer scientist Peter Burke has introduced a project that uses generative AI to build autonomous drone software. Far from being a routine technical experiment, this initiative marks a pivotal shift in how we perceive machine intelligence and automation. By harnessing advanced AI models such as ChatGPT, Burke’s work showcases how robots can evolve beyond predefined programming, opening new possibilities for fully autonomous systems. The project is designed around training a robot’s "brain" and hardware using generative AI, with minimal human supervision. “It’s a significant step forward,” Burke notes, drawing parallels to The Terminator’s portrayal of self-aware robots—while adding that his goal is to prevent such dystopian outcomes. At the heart of the innovation lies a dual-robot framework: the AI models run on cloud-based laptops, while the drones execute their tasks through a Raspberry Pi Zero 2 W onboard computer. The models generate functional code, and the drones bring it to life. This combination gives drones autonomy while retaining the intelligence of advanced AI systems. Burke’s system, called WebGCS, enables drones to host their own control dashboard on a small website, accessible online. This approach represents a clear departure from traditional drone control, offering both flexibility and independence from external operators. The development process was rigorous, involving multiple “sprints” across different AI tools. Early attempts with models like Claude struggled with context limitations, while Gemini 2.5 and Cursor also posed challenges. Eventually, success came with the Windsurf model, which generated nearly 10,000 lines of code in just 100 hours. To put that into perspective, a similar project—Cloudstation—previously took Burke’s team four years to build. The comparison highlights the disruptive speed and efficiency AI brings to software prototyping. Industry experts have taken note. Hantz Févry, CEO of spatial data firm Geolava, commended Burke’s ambition and the project’s alignment with the future of spatial intelligence. At the same time, he emphasized the importance of safeguards and ethical boundaries, pointing out that unchecked autonomy could pose risks. Projects like Burke’s illustrate both the promise and the perils of generative AI. On one hand, they showcase how autonomous systems can transform industries; on the other, they raise urgent questions about ethics, regulation, and safety. As AI innovation accelerates, the challenge will be balancing progress with responsibility. The ability for machines to independently develop and execute complex functions forces us to rethink issues of employment, security, and governance.  

The Future of Robotics: From Warehouses to Homes Forget the clunky, slow-moving robots you've seen in old sci-fi movies. The reality of robotics is moving faster than most of us…

Google DeepMind announced Gemini Robotics, new AI models designed for real-world robot interaction and navigation. Demo videos showcased robots performing tasks like folding paper and responding to voice commands. A slimmed-down model, Gemini Robotics-ER, was also released for researchers to train their own robotics models.

The Material Handling Robotics Market is rapidly emerging as a cornerstone of modern industrial infrastructure. As supply chains evolve to meet the demands of e-commerce, manufacturing agility, and la...