Technologies
Watch a Robot Stuff Cash Into a Wallet Just Like You Do
Generalist AI’s Gen-1 model is all about «teaching robots physical common sense.»
In 2026, we’re seeing robots progress by leaps and bounds with markedly improved dexterity, the kind of progress long needed in the quest for truly useful household helpers. Now a new AI model has arrived to power robots through activities, including folding laundry, constructing boxes, fixing other robots and even filling wallets with flimsy paper money.
Earlier this month, California-based company Generalist AI released Gen-1, a new physical AI model that makes robots capable of performing all of these tasks (and more) with success. It’s a big step forward in terms of robots designed for the real world based on intelligence born from the real world, Pete Florence, co-founder and CEO of Generalist AI told me.
In most of the example videos published by the company, Gen-1 is seen running on a pair of robotic arms, but that’s not all it’s built for. «Gen-1 is designed to be the brain of any robot, meaning the same model can run on a humanoid, an industrial arm or other robotic systems,» said Florence.
Already, this has proved to be a breakthrough year for general-purpose humanoid robots, with companies including Boston Dynamics and Honor unveiling cutting-edge bots capable of uncannily humanlike movements. The market for robots is expected to explode, with one estimate from Morgan Stanley predicting growth to a $5 trillion market by 2050. Predictions see robots coming for industry, retail, hospitality and care environments before eventually landing in our homes. To get us there, we need to see further advances in AI.
Training robots to live alongside humans
Over the past few years we’ve seen large language models, such as ChatGPT, Gemini and Claude, evolve at lightning speed. The same hasn’t been true of the physical AI models required to power robots, in large part because of a lack of data to train those models on. Robots — and especially humanoid robots — must learn to navigate a world built for humans just as a human would.
Often this data is collected from robots performing tasks while being teleoperated by humans, but not Gen-1. Instead, the dataset used to train Generalist AI’s models has been assembled by humans completing millions of different tasks using wearable technology.
«We built our own lightweight ‘data hands’ and distributed them globally to learn how people actually interact with objects, with all the subtle force feedback, tactile feel, slips, corrections and recoveries that define human dexterity in the real world,» said Florence. «That kind of data is critical for teaching robots physical common sense, the intuitive understanding and ability to adapt in real time rather than execute rigid instructions.»
Generalist AI has released a series of videos showing the model running on robots repetitively performing a range of different tasks, with the most compelling, perhaps, being a robot drawing cash out of a wallet before reinserting it into the same pocket. This is a fiddly task that many humans fumble over. It’s clearly not easy for the robot, either, given the flimsiness of the paper money and the fabric of the wallet — and yet it completes the task.
Another video shows a robot sorting socks by color, folding them in neat piles and counting the number of pairs using a touchscreen. Other tricky tasks the model can complete include unzipping and filling a pencil case with pens, stacking oranges in a neat pyramid and plugging in an Ethernet cable.
These videos show the breadth of Gen-1’s capabilities, but more impressive is the success rate with which it can complete certain tasks. Generalist AI measured the model’s hit rate against the previous version and found Gen-1 could successfully service a robot vacuum cleaner in 99% of cases (up from 50% for Gen-0), fold boxes in 99% of cases (up from 81% for Gen-0) and package up phones in 99% of cases (up from 62% for Gen-0).
Robots do improv
Most robots are programmed to complete a task in a specific and orderly way. But what happens when a curve ball gets thrown? «The smallest changes in the environment can cause failures,» said Florence.
An important skill robots need, which humans innately possess, is the ability to think on their feet. This is why Gen-1 has been designed with improvisation in mind so it can come up with strategies to complete tasks. Florence gives me an example of a robot using two hands to reposition an awkwardly placed part for an automotive task, even though it has only been trained to use one.
«This kind of creativity has been largely absent from robotics until now,» he said.
Significant work still needs to be done when it comes to beefing up robots’ improv chops, but early progress show glimpses of a positive impact on both reliability and speed, says Florence. «We’re beginning to see real progress and are excited to push the boundaries of embodied intelligence.»
After all, there may come a day when you need a robot in your house that can fix all your other smaller robots.
Technologies
Google races to put Gemini at the center of Android before Apple’s AI reboot
Google is using its latest Android rollout to position Gemini as the AI layer across phones, Chrome, laptops and cars.
Google is using its latest Android rollout to make Gemini less of a chatbot and more of an operating layer across the phone, browser, car and laptop, just weeks before Apple is expected to show its own Gemini-powered Apple Intelligence reboot at WWDC.
Ahead of its Google I/O developer conference next week, the company previewed a number of Android updates, including AI-powered app automation, a smarter version of Chrome on Android, new tools for creators, a redesigned Android Auto experience, and a sweeping set of new security features.
Alphabet is counting on Gemini to help Google compete directly with OpenAI and Anthropic in the market for artificial intelligence models and services, while also serving as the AI backbone across its expansive portfolio of products, including Android. Meanwhile, Gemini is powering part of Apple’s new AI strategy, giving Google a role in the iPhone maker’s reset even as it races to prove its own version of personal AI on the phone is further along.
Sameer Samat, who oversees Google’s Android ecosystem, told CNBC that Google is rebuilding parts of Android around Gemini Intelligence to help users complete everyday tasks more easily.
“We’re transitioning from an operating system to an intelligence system,” he said.
As part of Tuesday’s announcements. Google said Gemini Intelligence will be able to move across apps, understand what’s on the screen and complete tasks that would normally require a user to jump between multiple services. That means Android is moving beyond the traditional assistant model, where users ask a question and get an answer, and acting more like an agent.
For instance, Google says Gemini can pull relevant information from Gmail, build shopping carts and book reservations. Samat gave the example of asking Gemini to look at the guest list for a barbecue, build a menu, add ingredients to an Instacart list and return for approval before checkout.
A big concern surrounding agentic AI involves software taking action on a user’s behalf without permissions. Samat said Gemini will come back to the user before completing a transaction, adding, “the human is always in the loop.”
Four months after announcing its Gemini deal with Google, Apple is under pressure to show a more capable version of Apple Intelligence, which has been a relative laggard on the market. Apple has long framed privacy, hardware integration and control of the user experience as its advantages.
Google’s Android push is designed to show it can bring AI deeper into the device experience while still giving users control over what Gemini can see, where it can act and when it needs confirmation.
The app automation features will roll out in waves, starting with the latest Samsung Galaxy and Google Pixel phones this summer, before expanding across more Android devices, including watches, cars, glasses and laptops later this year.
The company is also redesigning Android Auto around Gemini, turning the car into another major surface for its assistant. Android Auto is in more than 250 million cars, and Google says the new release includes its biggest maps update in a decade and Gemini-powered help with tasks like ordering dinner while driving.
Alphabet’s AI strategy has been embraced by Wall Street, which has pushed the company’s stock price up more than 140% in the past year, compared to Apple’s roughly 40% gain. Investors now want to see how Gemini can become more central to the products people use every day.
WATCH: Alphabet briefly tops Nvidia after report of $200 billion Anthropic cloud deal
Technologies
Waymo recalls 3,800 robotaxis after glitch allowed some vehicles to ‘drive into standing water’
Waymo issued a voluntary recall of about 3,800 of its robotaxis to fix software issues that could allow them to drive into flooded roadways.
Waymo is recalling about 3,800 robotaxis in the U.S. to fix software issues that could allow them to “drive onto a flooded roadway,” according to a letter on the National Highway Traffic Safety Administration’s website.
The voluntary recall is for Waymo vehicles that use the company’s fifth and sixth generation automated driving systems (or ADS), the U.S. auto safety regulator said in the letter posted Tuesday.
Waymo autonomous vehicles in Austin, Texas, were seen on camera driving onto a flooded street and stalling, requiring other drivers to navigate around them. It’s the latest example of a safety-related issue for the Alphabet-owned AV unit that’s rapidly bolstering its fleet of vehicles and entering new U.S. markets.
Waymo has drawn criticism for its vehicles failing to yield to school buses in Austin, and for the performance of its vehicles during widespread power outages in San Francisco in December, when robotaxis halted in traffic, causing gridlock.
The company said in a statement on Tuesday that it’s “identified an area of improvement regarding untraversable flooded lanes specific to higher-speed roadways,” and opted to file a “voluntary software recall” with the NHTSA.
“Waymo provides over half a million trips every week in some of the most challenging driving environments across the U.S., and safety is our primary priority,” the company said.
Waymo added that it’s working on “additional software safeguards” and has put “mitigations” in place, limiting where its robotaxis operate during extreme weather, so that they avoid “areas where flash flooding might occur” in periods of intense rain.
WATCH: Waymo launches new autonomous system in Chinese-made vehicle
Technologies
Qualcomm tumbles 13% as semiconductor stocks retreat from historic AI-fueled surge
Semiconductor equities reversed sharply after a broad AI-driven advance, with Qualcomm suffering its worst day since 2020 amid inflation concerns and rising oil prices.
Semiconductor stocks fell sharply on Tuesday, reversing course after an extensive rally that had expanded the artificial intelligence investment theme well past Nvidia and driven the industry to unprecedented levels.
Qualcomm plunged 13% and was on track for its steepest single-day decline since 2020. Intel shed 8%, while On Semiconductor and Skyworks Solutions each lost more than 6%. The iShares Semiconductor ETF, which benchmarks the overall sector, fell 5%.
The sell-off came after a key gauge of consumer prices came in above forecasts, and as conflict in Iran pushed crude oil higher—prompting investors to shift away from riskier assets.
The preceding advance had widened the AI opportunity set beyond longtime industry leader Nvidia, which for much of the past several years had largely carried the market to new peaks on its own.
Explosive appetite for central processing units, along with the graphics processing units that power large language models, has sent chipmakers to all-time highs.
Market participants are wagering that the shift from AI model training to autonomous agents will lift demand for additional AI hardware. Among the beneficiaries are memory chip producers, which are raising prices as supply remains tight.
Micron Technology slid 6%, and Sandisk cratered 8%. Sandisk’s stock has surged more than six times over since January.
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