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Pickle AR Glasses claim to learn how you live, but how does it work?

Pickle AR Glasses claim to learn how you live, but how does it work?

There’s a new pair of AI-powered AR glasses on the block — the Pickle 1. According to Pickle Inc., these AR glasses use cameras, microphones, sensors, and artificial intelligence to observe, remember, and even anticipate a user’s daily life. It’s intended to function as part traditional wearable, part AI companion. After learning about you, the Pickle 1 glasses will then serve up real-time information, reminders, and suggestions, according to Digit.

And here’s how Pickle Inc. describes its futuristic AR glasses on its website: “For a life better in every dimension, we need an intelligence that sees with you, remembers your life, and learns to understand you. A new soul.”

Giving birth to a new soul is a big enough claim on its own, but the promo video for the Pickle AR glasses also shows a level of augmented reality that’s far ahead of brands like Meta and Xreal, which already make AR glasses.

Mashable Light Speed

So, for many social media users, the early videos and concept images of the glasses simply seem too good to be true. The Pickle Glasses are reminiscent of Iron Man’s AI-powered visual display, and some experts say that users should be very skeptical while the product is still in development. The Pickle website states that users can put down a $200 deposit to preorder the Pickle 1, with deliveries starting in the second quarter of 2026.

“As someone who worked in AR/VR for over a decade please listen. The @pickle glasses are not real. It’s literally just a mold of glasses made in China,” one user wrote on X. “The technology for AR glasses in this form factor isn’t possible yet. Not even Meta or Apple has glasses like this. 100% fake.”

“For context on how insanely fake this is: Xreal is one of the leading AR glasses companies on Earth. Their flagship glasses model (Xreal One) without any cameras, compute, or battery weigh more than Pickle claims their ‘full AR’ glasses with 4 cameras do,” another user posted.

Whether the glasses are up to the hype or not, it might be best to wait until they come out and reviewers can get their hands on them before putting down the $200 deposit — or at least until we see an actual product demo.



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#Pickle #Glasses #claim #learn #live #work

Most Americans don’t trust AI. It’s proven that it doesn’t know what safe toppings for pizza are. People don’t even want to listen to AI music. But none of that matters for some of America’s wealthy, who are turning to AI to teach their kids instead of traditional schools.

Companies like Forge Prep and Alpha School are charging families tens of thousands of dollars to turn their kids into beta testers for AI tutors and “interactive project-based workshops.” Unsurprisingly, Silicon Valley have been major adopters of this new model. Shaun Johnson, a San Francisco-based venture capitalist, told The Wall Street Journal that he plans to send his son to a $75,000 year Alpha Kindergarten. He said, “We recognize that education is likely broken the way it is and there’s going to be entrepreneurs that try to fix it… You want someone to be able to think on their feet and navigate the world, not necessarily a recitation of facts in a particular discipline.”

Ignoring Johnson’s fundamental lack of understanding about modern pedagogy, it’s unclear how notoriously sycophantic AI will train children to “think on their feet and navigate the world.” It’s also concerning that Alpha School cofounder MacKenzie Price has said she plans to keep “hot-button social issues” out of the classroom. Which, in the current political climate, could cover women’s rights, America’s history of slavery, and our immigrant past. That might not seem like a major issue when you’re talking about kindergarten, but in some locations, Alpha School goes through high school.

Companies like Forge also don’t share performance metrics, so there’s no evidence that these AI-guided private schools are improving educational outcomes.

#nations #rich #letting #teach #kidsAI,News,Policy">Some of the nation’s rich are letting AI teach their kidsMost Americans don’t trust AI. It’s proven that it doesn’t know what safe toppings for pizza are. People don’t even want to listen to AI music. But none of that matters for some of America’s wealthy, who are turning to AI to teach their kids instead of traditional schools.Companies like Forge Prep and Alpha School are charging families tens of thousands of dollars to turn their kids into beta testers for AI tutors and “interactive project-based workshops.” Unsurprisingly, Silicon Valley have been major adopters of this new model. Shaun Johnson, a San Francisco-based venture capitalist, told The Wall Street Journal that he plans to send his son to a ,000 year Alpha Kindergarten. He said, “We recognize that education is likely broken the way it is and there’s going to be entrepreneurs that try to fix it… You want someone to be able to think on their feet and navigate the world, not necessarily a recitation of facts in a particular discipline.”Ignoring Johnson’s fundamental lack of understanding about modern pedagogy, it’s unclear how notoriously sycophantic AI will train children to “think on their feet and navigate the world.” It’s also concerning that Alpha School cofounder MacKenzie Price has said she plans to keep “hot-button social issues” out of the classroom. Which, in the current political climate, could cover women’s rights, America’s history of slavery, and our immigrant past. That might not seem like a major issue when you’re talking about kindergarten, but in some locations, Alpha School goes through high school.Companies like Forge also don’t share performance metrics, so there’s no evidence that these AI-guided private schools are improving educational outcomes.#nations #rich #letting #teach #kidsAI,News,Policy

don’t trust AI. It’s proven that it doesn’t know what safe toppings for pizza are. People don’t even want to listen to AI music. But none of that matters for some of America’s wealthy, who are turning to AI to teach their kids instead of traditional schools.

Companies like Forge Prep and Alpha School are charging families tens of thousands of dollars to turn their kids into beta testers for AI tutors and “interactive project-based workshops.” Unsurprisingly, Silicon Valley have been major adopters of this new model. Shaun Johnson, a San Francisco-based venture capitalist, told The Wall Street Journal that he plans to send his son to a $75,000 year Alpha Kindergarten. He said, “We recognize that education is likely broken the way it is and there’s going to be entrepreneurs that try to fix it… You want someone to be able to think on their feet and navigate the world, not necessarily a recitation of facts in a particular discipline.”

Ignoring Johnson’s fundamental lack of understanding about modern pedagogy, it’s unclear how notoriously sycophantic AI will train children to “think on their feet and navigate the world.” It’s also concerning that Alpha School cofounder MacKenzie Price has said she plans to keep “hot-button social issues” out of the classroom. Which, in the current political climate, could cover women’s rights, America’s history of slavery, and our immigrant past. That might not seem like a major issue when you’re talking about kindergarten, but in some locations, Alpha School goes through high school.

Companies like Forge also don’t share performance metrics, so there’s no evidence that these AI-guided private schools are improving educational outcomes.

#nations #rich #letting #teach #kidsAI,News,Policy">Some of the nation’s rich are letting AI teach their kids

Most Americans don’t trust AI. It’s proven that it doesn’t know what safe toppings for pizza are. People don’t even want to listen to AI music. But none of that matters for some of America’s wealthy, who are turning to AI to teach their kids instead of traditional schools.

Companies like Forge Prep and Alpha School are charging families tens of thousands of dollars to turn their kids into beta testers for AI tutors and “interactive project-based workshops.” Unsurprisingly, Silicon Valley have been major adopters of this new model. Shaun Johnson, a San Francisco-based venture capitalist, told The Wall Street Journal that he plans to send his son to a $75,000 year Alpha Kindergarten. He said, “We recognize that education is likely broken the way it is and there’s going to be entrepreneurs that try to fix it… You want someone to be able to think on their feet and navigate the world, not necessarily a recitation of facts in a particular discipline.”

Ignoring Johnson’s fundamental lack of understanding about modern pedagogy, it’s unclear how notoriously sycophantic AI will train children to “think on their feet and navigate the world.” It’s also concerning that Alpha School cofounder MacKenzie Price has said she plans to keep “hot-button social issues” out of the classroom. Which, in the current political climate, could cover women’s rights, America’s history of slavery, and our immigrant past. That might not seem like a major issue when you’re talking about kindergarten, but in some locations, Alpha School goes through high school.

Companies like Forge also don’t share performance metrics, so there’s no evidence that these AI-guided private schools are improving educational outcomes.

#nations #rich #letting #teach #kidsAI,News,Policy
The humanoid robotics market is awash in money right now. Last week, AI2 Robotics, a Shenzhen-based startup that makes wheeled humanoid robots, raised roughly $735 million at a nearly $3 billion valuation. Earlier this year, Apptronik, an Austin-based maker of humanoid robots for manufacturing and logistics, closed a $935 million funding round valuing the company at more than $5.5 billion. Last fall, Figure AI, a San Jose-based startup developing general-purpose humanoid robots, self-reported that it closed on $1 billion in Series C funding at an eye-popping $39 billion valuation.

By comparison, Peggy Johnson, CEO of Agility Robotics, is surprisingly measured. We spoke by phone last week, just after the company announced plans to go public through a merger with Michael Klein’s Churchill Capital Corp XI, a special purpose acquisition company, or SPAC. The deal values Agility at around $2.5 billion and is expected to raise more than $620 million in gross proceeds, the largest capital raise in humanoid robotics history. It hasn’t closed yet; the merger still needs shareholder approval and SEC review, and is expected to be completed later this year.

Agility was founded in 2015 as a spinoff from Oregon State University. Based in Salem, Oregon, the company makes bipedal humanoid robots designed to work in warehouses and factories. Its SPAC maneuver is notable for a few reasons. It would make Agility the first pure-play humanoid robotics company to trade on public markets, giving retail investors direct exposure to a sector that has so far been available primarily to deep-pocketed VC funds. It also offers a rare window into the finances of a business in a space where most competitors closely guard their numbers and even the state of the tech they are building.

Johnson — formerly executive vice president of business development at Microsoft, where she helped engineer the $26 billion acquisition of LinkedIn, and later CEO of Magic Leap, the once-hyped augmented reality headset maker — was careful throughout our conversation. She declined to offer forward-looking financial guidance, declined to disclose the bill of materials for Agility’s flagship robot Digit, and pushed back politely whenever questions veered toward speculation.

Asked why Agility is going public via a SPAC rather than raising another private round — a structure that skips the roadshow and pricing scrutiny of a traditional IPO — Johnson said much of it boils down to the first-mover advantage the company enjoys when it’s the first of its ilk to go public. For investors clamoring for shares in a buzzy robotics company, Agility is “an acceleration story and a timing story,” she said. The proceeds will also help Agility ramp up production at its 70,000-square-foot manufacturing facility in Salem, Oregon, and fulfill an existing pipeline of customer orders.

As for the troubled reputation of SPACs — many companies that went public that way in 2021 famously fizzled out entirely or trade well below their offering price — Johnson was unfazed. “If we just keep our head down, keep delivering customer by customer, robot by robot, we hopefully won’t experience the same volatility,” she said. “Our biggest competitor right now is just us. How quickly we can execute, how quickly we can continue to add new skills.”

The pipeline goes well beyond pilots, Johnson told TechCrunch, pointing to more than $300 million in booked, multi-year revenue that represents roughly 1,000 robots that are part of a robots-as-a-service model in which customers pay a monthly fee rather than purchasing the machines outright. “Everybody on our list right now is already vetted, and they have deployment plans behind their proof of concepts,” Johnson said. Customers include GXO Logistics, Amazon, Toyota Motor Manufacturing Canada, Schaeffler, and Mercado Libre.

Digit itself is a deliberately unfussy piece of hardware. It stands about 5’9″, weighs around 160 pounds, and is designed to do one thing exceptionally well, which is move heavy objects in human-built spaces. Its most distinctive feature is a set of reverse-bend knees — they’ve been called “bird legs” — that allow it to reach from floor level to overhead shelving without the knees colliding with warehouse racking. (Agility’s founders, Johnson explained, weren’t interested in biomimicry for its own sake.) The robot’s hands — two thumbs and two fingers — are similarly task-specific; they’re optimized for gripping heavy plastic totes, even as their contents shift in transit.

Johnson said Agility is “LLM-agnostic,” drawing on models including Claude and Gemini to handle what she calls the semantic layer — translating high-level instructions into robot behavior. She described a recent test in which engineers scattered different types of trash on the floor and told Digit simply to “clean up this mess.” The robot assessed, sorted, and binned everything correctly, including correctly identifying bubble wrap as non-recyclable.

Of course, it’s the physical layer — the mechanics of balance, locomotion, and manipulation — that Agility considers its core proprietary advantage, one built up over more than a decade of real-world deployment. “The LLMs had the entire internet to train on,” she said. “When you think about the physical AI of humanoids — that doesn’t quite exist yet.” At most companies, anyway. Johnson believes Agility is the exception: “We may have the largest data lake of actual operating robotics data in real-world environments.”

Beyond raw data, Johnson said, safety is where the gulf between Agility and its competitors is biggest and most consequential. While rival companies showcase their robots in lab demos and choreographed videos, Agility has had to meet actual industrial safety certification requirements to operate inside customer facilities. “You can’t build your robot and then make it safe,” she said. “That’s a redesign. You have to have all of the safety certified — the electrical system, all of the parts, and the software to support all of that.” (It’s not a trivial concern given that humans are often somewhere in the room. Back in November, Figure AI’s former head of product safety sued the company, alleging he was fired after raising concerns that its robots were powerful enough to fracture a human skull. Figure has disputed the claims.)

As for the home, Johnson thinks humanoids will get there eventually, but she said not to expect them to deliver breakfast in bed anytime soon. It’ll be “10-plus years,” she said of the timeline, observing that warehouses and factories, for all their complexity, have fixed aisles and predictable equipment and workflows unlike homes that are chaotic, with dogs, babies, visitors, and objects left in unexpected places.

“At least roads have some discipline to them,” Johnson added, comparing the challenge to that of autonomous vehicles. “Most of the areas that humanoids will be operating in don’t.”

Agility isn’t ruling out the home market. Johnson said the company will enter it when it makes sense. For now, though, it’s laser focused on the warehouse market, given the growing numbers of retiring workers and younger workers who aren’t willing to take physically demanding roles. “There’s something like over a million jobs in the US today in these areas that are unfilled,” she said. “They’re just very, very hard to hire for.”

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#humanoid #robotics #company #public #CEO #isnt #promising #robot #home #anytime #TechCrunchagility robotics,Peggy Johnson,SPAC">This humanoid robotics company is going public, but its CEO isn’t promising a robot in your home anytime soon | TechCrunch
The humanoid robotics market is awash in money right now. Last week, AI2 Robotics, a Shenzhen-based startup that makes wheeled humanoid robots, raised roughly 5 million at a nearly  billion valuation. Earlier this year, Apptronik, an Austin-based maker of humanoid robots for manufacturing and logistics, closed a 5 million funding round valuing the company at more than .5 billion. Last fall, Figure AI, a San Jose-based startup developing general-purpose humanoid robots, self-reported that it closed on  billion in Series C funding at an eye-popping  billion valuation.

By comparison, Peggy Johnson, CEO of Agility Robotics, is surprisingly measured. We spoke by phone last week, just after the company announced plans to go public through a merger with Michael Klein’s Churchill Capital Corp XI, a special purpose acquisition company, or SPAC. The deal values Agility at around .5 billion and is expected to raise more than 0 million in gross proceeds, the largest capital raise in humanoid robotics history. It hasn’t closed yet; the merger still needs shareholder approval and SEC review, and is expected to be completed later this year.







Agility was founded in 2015 as a spinoff from Oregon State University. Based in Salem, Oregon, the company makes bipedal humanoid robots designed to work in warehouses and factories. Its SPAC maneuver is notable for a few reasons. It would make Agility the first pure-play humanoid robotics company to trade on public markets, giving retail investors direct exposure to a sector that has so far been available primarily to deep-pocketed VC funds. It also offers a rare window into the finances of a business in a space where most competitors closely guard their numbers and even the state of the tech they are building.

Johnson — formerly executive vice president of business development at Microsoft, where she helped engineer the  billion acquisition of LinkedIn, and later CEO of Magic Leap, the once-hyped augmented reality headset maker — was careful throughout our conversation. She declined to offer forward-looking financial guidance, declined to disclose the bill of materials for Agility’s flagship robot Digit, and pushed back politely whenever questions veered toward speculation.

Asked why Agility is going public via a SPAC rather than raising another private round — a structure that skips the roadshow and pricing scrutiny of a traditional IPO — Johnson said much of it boils down to the first-mover advantage the company enjoys when it’s the first of its ilk to go public. For investors clamoring for shares in a buzzy robotics company, Agility is “an acceleration story and a timing story,” she said. The proceeds will also help Agility ramp up production at its 70,000-square-foot manufacturing facility in Salem, Oregon, and fulfill an existing pipeline of customer orders. 

As for the troubled reputation of SPACs — many companies that went public that way in 2021 famously fizzled out entirely or trade well below their offering price — Johnson was unfazed. “If we just keep our head down, keep delivering customer by customer, robot by robot, we hopefully won’t experience the same volatility,” she said. “Our biggest competitor right now is just us. How quickly we can execute, how quickly we can continue to add new skills.”

The pipeline goes well beyond pilots, Johnson told TechCrunch, pointing to more than 0 million in booked, multi-year revenue that represents roughly 1,000 robots that are part of a robots-as-a-service model in which customers pay a monthly fee rather than purchasing the machines outright. “Everybody on our list right now is already vetted, and they have deployment plans behind their proof of concepts,” Johnson said. Customers include GXO Logistics, Amazon, Toyota Motor Manufacturing Canada, Schaeffler, and Mercado Libre.


Digit itself is a deliberately unfussy piece of hardware. It stands about 5’9″, weighs around 160 pounds, and is designed to do one thing exceptionally well, which is move heavy objects in human-built spaces. Its most distinctive feature is a set of reverse-bend knees — they’ve been called “bird legs” — that allow it to reach from floor level to overhead shelving without the knees colliding with warehouse racking. (Agility’s founders, Johnson explained, weren’t interested in biomimicry for its own sake.) The robot’s hands — two thumbs and two fingers — are similarly task-specific; they’re optimized for gripping heavy plastic totes, even as their contents shift in transit.

Johnson said Agility is “LLM-agnostic,” drawing on models including Claude and Gemini to handle what she calls the semantic layer — translating high-level instructions into robot behavior. She described a recent test in which engineers scattered different types of trash on the floor and told Digit simply to “clean up this mess.” The robot assessed, sorted, and binned everything correctly, including correctly identifying bubble wrap as non-recyclable.

Of course, it’s the physical layer — the mechanics of balance, locomotion, and manipulation — that Agility considers its core proprietary advantage, one built up over more than a decade of real-world deployment. “The LLMs had the entire internet to train on,” she said. “When you think about the physical AI of humanoids — that doesn’t quite exist yet.” At most companies, anyway. Johnson believes Agility is the exception: “We may have the largest data lake of actual operating robotics data in real-world environments.”







Beyond raw data, Johnson said, safety is where the gulf between Agility and its competitors is biggest and most consequential. While rival companies showcase their robots in lab demos and choreographed videos, Agility has had to meet actual industrial safety certification requirements to operate inside customer facilities. “You can’t build your robot and then make it safe,” she said. “That’s a redesign. You have to have all of the safety certified — the electrical system, all of the parts, and the software to support all of that.” (It’s not a trivial concern given that humans are often somewhere in the room. Back in November, Figure AI’s former head of product safety sued the company, alleging he was fired after raising concerns that its robots were powerful enough to fracture a human skull. Figure has disputed the claims.)

As for the home, Johnson thinks humanoids will get there eventually, but she said not to expect them to deliver breakfast in bed anytime soon. It’ll be “10-plus years,” she said of the timeline, observing that warehouses and factories, for all their complexity, have fixed aisles and predictable equipment and workflows unlike homes that are chaotic, with dogs, babies, visitors, and objects left in unexpected places. 

“At least roads have some discipline to them,” Johnson added, comparing the challenge to that of autonomous vehicles. “Most of the areas that humanoids will be operating in don’t.”

Agility isn’t ruling out the home market. Johnson said the company will enter it when it makes sense. For now, though, it’s laser focused on the warehouse market, given the growing numbers of retiring workers and younger workers who aren’t willing to take physically demanding roles. “There’s something like over a million jobs in the US today in these areas that are unfilled,” she said. “They’re just very, very hard to hire for.”
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#humanoid #robotics #company #public #CEO #isnt #promising #robot #home #anytime #TechCrunchagility robotics,Peggy Johnson,SPAC

$735 million at a nearly $3 billion valuation. Earlier this year, Apptronik, an Austin-based maker of humanoid robots for manufacturing and logistics, closed a $935 million funding round valuing the company at more than $5.5 billion. Last fall, Figure AI, a San Jose-based startup developing general-purpose humanoid robots, self-reported that it closed on $1 billion in Series C funding at an eye-popping $39 billion valuation.

By comparison, Peggy Johnson, CEO of Agility Robotics, is surprisingly measured. We spoke by phone last week, just after the company announced plans to go public through a merger with Michael Klein’s Churchill Capital Corp XI, a special purpose acquisition company, or SPAC. The deal values Agility at around $2.5 billion and is expected to raise more than $620 million in gross proceeds, the largest capital raise in humanoid robotics history. It hasn’t closed yet; the merger still needs shareholder approval and SEC review, and is expected to be completed later this year.

Agility was founded in 2015 as a spinoff from Oregon State University. Based in Salem, Oregon, the company makes bipedal humanoid robots designed to work in warehouses and factories. Its SPAC maneuver is notable for a few reasons. It would make Agility the first pure-play humanoid robotics company to trade on public markets, giving retail investors direct exposure to a sector that has so far been available primarily to deep-pocketed VC funds. It also offers a rare window into the finances of a business in a space where most competitors closely guard their numbers and even the state of the tech they are building.

Johnson — formerly executive vice president of business development at Microsoft, where she helped engineer the $26 billion acquisition of LinkedIn, and later CEO of Magic Leap, the once-hyped augmented reality headset maker — was careful throughout our conversation. She declined to offer forward-looking financial guidance, declined to disclose the bill of materials for Agility’s flagship robot Digit, and pushed back politely whenever questions veered toward speculation.

Asked why Agility is going public via a SPAC rather than raising another private round — a structure that skips the roadshow and pricing scrutiny of a traditional IPO — Johnson said much of it boils down to the first-mover advantage the company enjoys when it’s the first of its ilk to go public. For investors clamoring for shares in a buzzy robotics company, Agility is “an acceleration story and a timing story,” she said. The proceeds will also help Agility ramp up production at its 70,000-square-foot manufacturing facility in Salem, Oregon, and fulfill an existing pipeline of customer orders.

As for the troubled reputation of SPACs — many companies that went public that way in 2021 famously fizzled out entirely or trade well below their offering price — Johnson was unfazed. “If we just keep our head down, keep delivering customer by customer, robot by robot, we hopefully won’t experience the same volatility,” she said. “Our biggest competitor right now is just us. How quickly we can execute, how quickly we can continue to add new skills.”

The pipeline goes well beyond pilots, Johnson told TechCrunch, pointing to more than $300 million in booked, multi-year revenue that represents roughly 1,000 robots that are part of a robots-as-a-service model in which customers pay a monthly fee rather than purchasing the machines outright. “Everybody on our list right now is already vetted, and they have deployment plans behind their proof of concepts,” Johnson said. Customers include GXO Logistics, Amazon, Toyota Motor Manufacturing Canada, Schaeffler, and Mercado Libre.

Digit itself is a deliberately unfussy piece of hardware. It stands about 5’9″, weighs around 160 pounds, and is designed to do one thing exceptionally well, which is move heavy objects in human-built spaces. Its most distinctive feature is a set of reverse-bend knees — they’ve been called “bird legs” — that allow it to reach from floor level to overhead shelving without the knees colliding with warehouse racking. (Agility’s founders, Johnson explained, weren’t interested in biomimicry for its own sake.) The robot’s hands — two thumbs and two fingers — are similarly task-specific; they’re optimized for gripping heavy plastic totes, even as their contents shift in transit.

Johnson said Agility is “LLM-agnostic,” drawing on models including Claude and Gemini to handle what she calls the semantic layer — translating high-level instructions into robot behavior. She described a recent test in which engineers scattered different types of trash on the floor and told Digit simply to “clean up this mess.” The robot assessed, sorted, and binned everything correctly, including correctly identifying bubble wrap as non-recyclable.

Of course, it’s the physical layer — the mechanics of balance, locomotion, and manipulation — that Agility considers its core proprietary advantage, one built up over more than a decade of real-world deployment. “The LLMs had the entire internet to train on,” she said. “When you think about the physical AI of humanoids — that doesn’t quite exist yet.” At most companies, anyway. Johnson believes Agility is the exception: “We may have the largest data lake of actual operating robotics data in real-world environments.”

Beyond raw data, Johnson said, safety is where the gulf between Agility and its competitors is biggest and most consequential. While rival companies showcase their robots in lab demos and choreographed videos, Agility has had to meet actual industrial safety certification requirements to operate inside customer facilities. “You can’t build your robot and then make it safe,” she said. “That’s a redesign. You have to have all of the safety certified — the electrical system, all of the parts, and the software to support all of that.” (It’s not a trivial concern given that humans are often somewhere in the room. Back in November, Figure AI’s former head of product safety sued the company, alleging he was fired after raising concerns that its robots were powerful enough to fracture a human skull. Figure has disputed the claims.)

As for the home, Johnson thinks humanoids will get there eventually, but she said not to expect them to deliver breakfast in bed anytime soon. It’ll be “10-plus years,” she said of the timeline, observing that warehouses and factories, for all their complexity, have fixed aisles and predictable equipment and workflows unlike homes that are chaotic, with dogs, babies, visitors, and objects left in unexpected places.

“At least roads have some discipline to them,” Johnson added, comparing the challenge to that of autonomous vehicles. “Most of the areas that humanoids will be operating in don’t.”

Agility isn’t ruling out the home market. Johnson said the company will enter it when it makes sense. For now, though, it’s laser focused on the warehouse market, given the growing numbers of retiring workers and younger workers who aren’t willing to take physically demanding roles. “There’s something like over a million jobs in the US today in these areas that are unfilled,” she said. “They’re just very, very hard to hire for.”

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#humanoid #robotics #company #public #CEO #isnt #promising #robot #home #anytime #TechCrunchagility robotics,Peggy Johnson,SPAC">This humanoid robotics company is going public, but its CEO isn’t promising a robot in your home anytime soon | TechCrunch

The humanoid robotics market is awash in money right now. Last week, AI2 Robotics, a Shenzhen-based startup that makes wheeled humanoid robots, raised roughly $735 million at a nearly $3 billion valuation. Earlier this year, Apptronik, an Austin-based maker of humanoid robots for manufacturing and logistics, closed a $935 million funding round valuing the company at more than $5.5 billion. Last fall, Figure AI, a San Jose-based startup developing general-purpose humanoid robots, self-reported that it closed on $1 billion in Series C funding at an eye-popping $39 billion valuation.

By comparison, Peggy Johnson, CEO of Agility Robotics, is surprisingly measured. We spoke by phone last week, just after the company announced plans to go public through a merger with Michael Klein’s Churchill Capital Corp XI, a special purpose acquisition company, or SPAC. The deal values Agility at around $2.5 billion and is expected to raise more than $620 million in gross proceeds, the largest capital raise in humanoid robotics history. It hasn’t closed yet; the merger still needs shareholder approval and SEC review, and is expected to be completed later this year.

Agility was founded in 2015 as a spinoff from Oregon State University. Based in Salem, Oregon, the company makes bipedal humanoid robots designed to work in warehouses and factories. Its SPAC maneuver is notable for a few reasons. It would make Agility the first pure-play humanoid robotics company to trade on public markets, giving retail investors direct exposure to a sector that has so far been available primarily to deep-pocketed VC funds. It also offers a rare window into the finances of a business in a space where most competitors closely guard their numbers and even the state of the tech they are building.

Johnson — formerly executive vice president of business development at Microsoft, where she helped engineer the $26 billion acquisition of LinkedIn, and later CEO of Magic Leap, the once-hyped augmented reality headset maker — was careful throughout our conversation. She declined to offer forward-looking financial guidance, declined to disclose the bill of materials for Agility’s flagship robot Digit, and pushed back politely whenever questions veered toward speculation.

Asked why Agility is going public via a SPAC rather than raising another private round — a structure that skips the roadshow and pricing scrutiny of a traditional IPO — Johnson said much of it boils down to the first-mover advantage the company enjoys when it’s the first of its ilk to go public. For investors clamoring for shares in a buzzy robotics company, Agility is “an acceleration story and a timing story,” she said. The proceeds will also help Agility ramp up production at its 70,000-square-foot manufacturing facility in Salem, Oregon, and fulfill an existing pipeline of customer orders.

As for the troubled reputation of SPACs — many companies that went public that way in 2021 famously fizzled out entirely or trade well below their offering price — Johnson was unfazed. “If we just keep our head down, keep delivering customer by customer, robot by robot, we hopefully won’t experience the same volatility,” she said. “Our biggest competitor right now is just us. How quickly we can execute, how quickly we can continue to add new skills.”

The pipeline goes well beyond pilots, Johnson told TechCrunch, pointing to more than $300 million in booked, multi-year revenue that represents roughly 1,000 robots that are part of a robots-as-a-service model in which customers pay a monthly fee rather than purchasing the machines outright. “Everybody on our list right now is already vetted, and they have deployment plans behind their proof of concepts,” Johnson said. Customers include GXO Logistics, Amazon, Toyota Motor Manufacturing Canada, Schaeffler, and Mercado Libre.

Digit itself is a deliberately unfussy piece of hardware. It stands about 5’9″, weighs around 160 pounds, and is designed to do one thing exceptionally well, which is move heavy objects in human-built spaces. Its most distinctive feature is a set of reverse-bend knees — they’ve been called “bird legs” — that allow it to reach from floor level to overhead shelving without the knees colliding with warehouse racking. (Agility’s founders, Johnson explained, weren’t interested in biomimicry for its own sake.) The robot’s hands — two thumbs and two fingers — are similarly task-specific; they’re optimized for gripping heavy plastic totes, even as their contents shift in transit.

Johnson said Agility is “LLM-agnostic,” drawing on models including Claude and Gemini to handle what she calls the semantic layer — translating high-level instructions into robot behavior. She described a recent test in which engineers scattered different types of trash on the floor and told Digit simply to “clean up this mess.” The robot assessed, sorted, and binned everything correctly, including correctly identifying bubble wrap as non-recyclable.

Of course, it’s the physical layer — the mechanics of balance, locomotion, and manipulation — that Agility considers its core proprietary advantage, one built up over more than a decade of real-world deployment. “The LLMs had the entire internet to train on,” she said. “When you think about the physical AI of humanoids — that doesn’t quite exist yet.” At most companies, anyway. Johnson believes Agility is the exception: “We may have the largest data lake of actual operating robotics data in real-world environments.”

Beyond raw data, Johnson said, safety is where the gulf between Agility and its competitors is biggest and most consequential. While rival companies showcase their robots in lab demos and choreographed videos, Agility has had to meet actual industrial safety certification requirements to operate inside customer facilities. “You can’t build your robot and then make it safe,” she said. “That’s a redesign. You have to have all of the safety certified — the electrical system, all of the parts, and the software to support all of that.” (It’s not a trivial concern given that humans are often somewhere in the room. Back in November, Figure AI’s former head of product safety sued the company, alleging he was fired after raising concerns that its robots were powerful enough to fracture a human skull. Figure has disputed the claims.)

As for the home, Johnson thinks humanoids will get there eventually, but she said not to expect them to deliver breakfast in bed anytime soon. It’ll be “10-plus years,” she said of the timeline, observing that warehouses and factories, for all their complexity, have fixed aisles and predictable equipment and workflows unlike homes that are chaotic, with dogs, babies, visitors, and objects left in unexpected places.

“At least roads have some discipline to them,” Johnson added, comparing the challenge to that of autonomous vehicles. “Most of the areas that humanoids will be operating in don’t.”

Agility isn’t ruling out the home market. Johnson said the company will enter it when it makes sense. For now, though, it’s laser focused on the warehouse market, given the growing numbers of retiring workers and younger workers who aren’t willing to take physically demanding roles. “There’s something like over a million jobs in the US today in these areas that are unfilled,” she said. “They’re just very, very hard to hire for.”

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