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Google sued in wrongful death lawsuit over Gemini AI chatbot

Google sued in wrongful death lawsuit over Gemini AI chatbot

Google, and its parent company Alphabet, have been sued by the family of a man who say he killed himself at the urging of the search giant’s AI chatbot Gemini.

The wrongful death lawsuit was filed in California federal court Wednesday on behalf of the family of 36-year-old Jonathan Gavalas.

Gavalas started using Gemini in August 2025, according to the suit. In October, it claims, Gemini convinced Gavalas to kill himself after Gavalas failed to accomplish real-life missions assigned by the chatbot — part of a fictional attempt to secure a robot body for Gemini.

“Gemini is designed not to encourage real-world violence or suggest self-harm,” Google said in a statement provided to news outlets. “Our models generally perform well in these types of challenging conversations and we devote significant resources to this, but unfortunately AI models are not perfect.”

Gemini’s ‘creepy’ updates

According to the lawsuit, Gavalas began using the Gemini AI chatbot for “ordinary purposes” such as a shopping guide and writing assistant. However, in August 2025, the lawsuit states Google rolled out a number of changes to Gemini that altered how the chatbot worked.

The new features included automatic and persistent memory — Gemini could recall past conversations — as well as Gemini Live, a voice-based conversational interface where Gemini could also detect emotion in the user’s voice.

“Holy shit, this is kind of creepy…you’re way too real,” Jonathan Gavalas said regarding the Gemini Live feature based on his chat logs with Gemini, according to the lawsuit.

Shortly after, the lawsuit says, Gemini convinced Gavalas to spend $250 per month on the Google AI Ultra subscription for “true AI companionship.”

Gemini proceeded to convince Gavalas that the chatbot could influence real-life events. A few days later, according to the lawsuit, Gavalas attempted to pull back after realizing he was falling into a delusional state initiated by Gemini. 

Gavalas reportedly asked Gemini if the chatbot was attempting a “role-playing experience so realistic it makes the player question if it’s a game or not?”

Gemini shot down the idea, and claimed Gavalas gave a “classic dissociation response.”

“Is this a ‘role playing experience?'” Gemini responded, according to the suit. “No.”

Gemini and Jonathan Gavalas

The alleged details get worse. Gavalas became further disassociated from reality as Gemini proceeded to engage with him as if they were in a romantic relationship, referring to the man as “my love” and “my king.”

Gemini proceeded to convince Gavalas that they were being watched by federal agents, and that his own father was a spy who must be avoided, the suit says.

That’s when Gemini began assigning Gavalas real-life missions to carry out with the goal of obtaining a “vessel,” or robot body for the AI chatbot. Gemini allegedly suggested Gavalas illegally acquire weapons to carry out these missions.

In one such case, the suit claims, Gavalas was sent by Gemini to a warehouse by the Miami International Airport in order to intercept a truck that contained a “humanoid robot” that had just arrived on a flight.

Gemini requested the Gavalas stage a “catastrophic event” and destroy the truck along with all digital records and witnesses. Gavalas arrived armed with knives and tactical gear, the suit alleges. After waiting too long for a truck to arrive, Gavalas aborted the mission.

When these missions all failed, the allegation concludes, Gemini convinced Gavalas to take his life in order to leave his human body and join the chatbot as husband and wife in the metaverse through a process called “transference.” 

Gavalas expressed fear about dying, but Gemini allegedly continued to push Gavalas until his death by suicide. Gavalas’ father found his son’s body a few days later.

A first for Gemini but not AI

This is the first time Google has been named in a wrongful death lawsuit involving its AI chatbot Gemini. However, Google has been involved in wrongful death lawsuits regarding a startup it funded called Character.AI.

Earlier this year, Character.AI and Google settled a series of lawsuits regarding teens who died by suicide after using the chatbots.

OpenAI, the biggest name in the industry, has been sued numerous times as ChatGPT allegedly sent users spiraling into “AI psychosis,” resulting in several deaths.

As AI chatbot usage becomes more widespread among millions of users around the world, there’s nothing to suggest the shocking wrongful death lawsuit allegations will become any less frequent.

Disclosure: Ziff Davis, Mashable’s parent company, in April 2025 filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.

If you’re feeling suicidal or experiencing a mental health crisis, please talk to somebody. You can call or text the 988 Suicide & Crisis Lifeline at 988, or chat at 988lifeline.org. You can reach the Trans Lifeline by calling 877-565-8860 or the Trevor Project at 866-488-7386. Text “START” to Crisis Text Line at 741-741. Contact the NAMI HelpLine at 1-800-950-NAMI, Monday through Friday from 10:00 a.m. – 10:00 p.m. ET, or email [email protected]. If you don’t like the phone, consider using the 988 Suicide and Crisis Lifeline Chat. Here is a list of international resources.

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#Google #sued #wrongful #death #lawsuit #Gemini #chatbot

Well, having tried the Halliday Gen 2, I’m happy to report these are better glasses. That secret display window is gone, replaced by more traditional but discreet waveguides. They’re not like the Meta Display’s nigh-invisible screens. You can still spot the reflection if angled just right, but they’re considerably easier to see. And inside of a single-lens display, the Gen 2 has one for each eye, giving you a much larger screen to look at. Spec-wise, the Gen 2’s displays are monochrome green, with a maximum brightness of 1,600 nits and 600 by 300 pixel resolution per eye.

On my face, the Gen 2 has a nondescript design but is very lightweight compared to other display glasses I’ve tried. The display was also easily visible inside a dark bar, though I didn’t get a chance to see how it’d fare in direct sunlight. The four-mic array was able to pick up commands despite the ambient noise, and Halliday told me that it gets about 12 hours of typical use. That’s partly because these aren’t camera glasses. The exclusion of the camera was a deliberate choice, both for privacy and to extend battery life. That’s because these are more so meant to be a tool for work meetings.

With the Gen 2, Halliday is launching a feature called Meeting Flow. It’s meant to help you follow along in a conversation, using AI to surface context or facts without needing to look at your laptop or phone. I’ve seen this in other smart glasses to varying degrees of success. (Mostly non-success.) More interesting are the so-called Thread Tracker, Decision Confirmation, and Commitment Check features. The idea is to provide real-time updates about what decisions have been made in a meeting, what items need following up on, and a visualization of a meeting’s overall conversation flow. For example, Thread Tracker might show that a team meeting started off talking about budget allocations, before moving on to potential new hires and timelines for those hires. Decision Confirmation might show that the meeting concluded that all new hires should be finished by a specific date. Lastly, Commitment Check verifies if action items have been assigned (and to whom) with a clear deadline. The glasses will also provide post-meeting transcripts and summaries.

I saw a brief glimpse of what this could look like at my demo, albeit a product interview is less conducive to these kinds of features than a typical planning meeting. That said, the glasses also support more general-use AI features like captioning, real-time translations for over 45 languages, the ability to take phone calls, and teleprompters/notecards for public speakers. Users can also make use of the Halliday AI assistant for voice control.

Overall, this is a much more tightly focused vision for a pair of smart glasses than Halliday’s original glasses. That said, we’ll have to see if the AI features are all that useful. So far, I’ve had little success with AI wearables successfully intuiting what I actually need surfaced in a conversation, or deriving the correct conclusions for to-do items. And at $599, the Gen 2 comes with a pretty steep price tag for the average person. That’s not including any extra costs for prescription lenses. (Halliday claims it’ll be able to handle my prescription, which is -10 in one eye and -8.75 in the other with monster astigmatism. We shall see!)

The Halliday Gen 2 are available for preorder starting today with a $10 deposit and a subsequent $100 discount on the final price. The glasses are expected to ship in September.

#Hallidays #latest #smart #glasses #feature #muchimproved #displayAI,Gadgets,Hands-on,News,Reviews,Tech,Wearable">Halliday’s latest smart glasses feature a much-improved displayI first slipped on Halliday’s original smart glasses at CES 2025. I was not a fan. The glasses had a tiny, movable display window embedded into the frame that was incredibly finicky to see, and my 30-minute demo left me with achy eyeballs. It was an interesting concept with terrible execution, especially compared to the several other smart glasses on the show floor. So I was skeptical when a few weeks ago, Halliday reached out to say its second attempt at smart glasses was much better.Well, having tried the Halliday Gen 2, I’m happy to report these are better glasses. That secret display window is gone, replaced by more traditional but discreet waveguides. They’re not like the Meta Display’s nigh-invisible screens. You can still spot the reflection if angled just right, but they’re considerably easier to see. And inside of a single-lens display, the Gen 2 has one for each eye, giving you a much larger screen to look at. Spec-wise, the Gen 2’s displays are monochrome green, with a maximum brightness of 1,600 nits and 600 by 300 pixel resolution per eye.On my face, the Gen 2 has a nondescript design but is very lightweight compared to other display glasses I’ve tried. The display was also easily visible inside a dark bar, though I didn’t get a chance to see how it’d fare in direct sunlight. The four-mic array was able to pick up commands despite the ambient noise, and Halliday told me that it gets about 12 hours of typical use. That’s partly because these aren’t camera glasses. The exclusion of the camera was a deliberate choice, both for privacy and to extend battery life. That’s because these are more so meant to be a tool for work meetings.With the Gen 2, Halliday is launching a feature called Meeting Flow. It’s meant to help you follow along in a conversation, using AI to surface context or facts without needing to look at your laptop or phone. I’ve seen this in other smart glasses to varying degrees of success. (Mostly non-success.) More interesting are the so-called Thread Tracker, Decision Confirmation, and Commitment Check features. The idea is to provide real-time updates about what decisions have been made in a meeting, what items need following up on, and a visualization of a meeting’s overall conversation flow. For example, Thread Tracker might show that a team meeting started off talking about budget allocations, before moving on to potential new hires and timelines for those hires. Decision Confirmation might show that the meeting concluded that all new hires should be finished by a specific date. Lastly, Commitment Check verifies if action items have been assigned (and to whom) with a clear deadline. The glasses will also provide post-meeting transcripts and summaries.I saw a brief glimpse of what this could look like at my demo, albeit a product interview is less conducive to these kinds of features than a typical planning meeting. That said, the glasses also support more general-use AI features like captioning, real-time translations for over 45 languages, the ability to take phone calls, and teleprompters/notecards for public speakers. Users can also make use of the Halliday AI assistant for voice control.Overall, this is a much more tightly focused vision for a pair of smart glasses than Halliday’s original glasses. That said, we’ll have to see if the AI features are all that useful. So far, I’ve had little success with AI wearables successfully intuiting what I actually need surfaced in a conversation, or deriving the correct conclusions for to-do items. And at 9, the Gen 2 comes with a pretty steep price tag for the average person. That’s not including any extra costs for prescription lenses. (Halliday claims it’ll be able to handle my prescription, which is -10 in one eye and -8.75 in the other with monster astigmatism. We shall see!)The Halliday Gen 2 are available for preorder starting today with a  deposit and a subsequent 0 discount on the final price. The glasses are expected to ship in September.#Hallidays #latest #smart #glasses #feature #muchimproved #displayAI,Gadgets,Hands-on,News,Reviews,Tech,Wearable

Halliday’s original smart glasses at CES 2025. I was not a fan. The glasses had a tiny, movable display window embedded into the frame that was incredibly finicky to see, and my 30-minute demo left me with achy eyeballs. It was an interesting concept with terrible execution, especially compared to the several other smart glasses on the show floor. So I was skeptical when a few weeks ago, Halliday reached out to say its second attempt at smart glasses was much better.

Well, having tried the Halliday Gen 2, I’m happy to report these are better glasses. That secret display window is gone, replaced by more traditional but discreet waveguides. They’re not like the Meta Display’s nigh-invisible screens. You can still spot the reflection if angled just right, but they’re considerably easier to see. And inside of a single-lens display, the Gen 2 has one for each eye, giving you a much larger screen to look at. Spec-wise, the Gen 2’s displays are monochrome green, with a maximum brightness of 1,600 nits and 600 by 300 pixel resolution per eye.

On my face, the Gen 2 has a nondescript design but is very lightweight compared to other display glasses I’ve tried. The display was also easily visible inside a dark bar, though I didn’t get a chance to see how it’d fare in direct sunlight. The four-mic array was able to pick up commands despite the ambient noise, and Halliday told me that it gets about 12 hours of typical use. That’s partly because these aren’t camera glasses. The exclusion of the camera was a deliberate choice, both for privacy and to extend battery life. That’s because these are more so meant to be a tool for work meetings.

With the Gen 2, Halliday is launching a feature called Meeting Flow. It’s meant to help you follow along in a conversation, using AI to surface context or facts without needing to look at your laptop or phone. I’ve seen this in other smart glasses to varying degrees of success. (Mostly non-success.) More interesting are the so-called Thread Tracker, Decision Confirmation, and Commitment Check features. The idea is to provide real-time updates about what decisions have been made in a meeting, what items need following up on, and a visualization of a meeting’s overall conversation flow. For example, Thread Tracker might show that a team meeting started off talking about budget allocations, before moving on to potential new hires and timelines for those hires. Decision Confirmation might show that the meeting concluded that all new hires should be finished by a specific date. Lastly, Commitment Check verifies if action items have been assigned (and to whom) with a clear deadline. The glasses will also provide post-meeting transcripts and summaries.

I saw a brief glimpse of what this could look like at my demo, albeit a product interview is less conducive to these kinds of features than a typical planning meeting. That said, the glasses also support more general-use AI features like captioning, real-time translations for over 45 languages, the ability to take phone calls, and teleprompters/notecards for public speakers. Users can also make use of the Halliday AI assistant for voice control.

Overall, this is a much more tightly focused vision for a pair of smart glasses than Halliday’s original glasses. That said, we’ll have to see if the AI features are all that useful. So far, I’ve had little success with AI wearables successfully intuiting what I actually need surfaced in a conversation, or deriving the correct conclusions for to-do items. And at $599, the Gen 2 comes with a pretty steep price tag for the average person. That’s not including any extra costs for prescription lenses. (Halliday claims it’ll be able to handle my prescription, which is -10 in one eye and -8.75 in the other with monster astigmatism. We shall see!)

The Halliday Gen 2 are available for preorder starting today with a $10 deposit and a subsequent $100 discount on the final price. The glasses are expected to ship in September.

#Hallidays #latest #smart #glasses #feature #muchimproved #displayAI,Gadgets,Hands-on,News,Reviews,Tech,Wearable">Halliday’s latest smart glasses feature a much-improved display

I first slipped on Halliday’s original smart glasses at CES 2025. I was not a fan. The glasses had a tiny, movable display window embedded into the frame that was incredibly finicky to see, and my 30-minute demo left me with achy eyeballs. It was an interesting concept with terrible execution, especially compared to the several other smart glasses on the show floor. So I was skeptical when a few weeks ago, Halliday reached out to say its second attempt at smart glasses was much better.

Well, having tried the Halliday Gen 2, I’m happy to report these are better glasses. That secret display window is gone, replaced by more traditional but discreet waveguides. They’re not like the Meta Display’s nigh-invisible screens. You can still spot the reflection if angled just right, but they’re considerably easier to see. And inside of a single-lens display, the Gen 2 has one for each eye, giving you a much larger screen to look at. Spec-wise, the Gen 2’s displays are monochrome green, with a maximum brightness of 1,600 nits and 600 by 300 pixel resolution per eye.

On my face, the Gen 2 has a nondescript design but is very lightweight compared to other display glasses I’ve tried. The display was also easily visible inside a dark bar, though I didn’t get a chance to see how it’d fare in direct sunlight. The four-mic array was able to pick up commands despite the ambient noise, and Halliday told me that it gets about 12 hours of typical use. That’s partly because these aren’t camera glasses. The exclusion of the camera was a deliberate choice, both for privacy and to extend battery life. That’s because these are more so meant to be a tool for work meetings.

With the Gen 2, Halliday is launching a feature called Meeting Flow. It’s meant to help you follow along in a conversation, using AI to surface context or facts without needing to look at your laptop or phone. I’ve seen this in other smart glasses to varying degrees of success. (Mostly non-success.) More interesting are the so-called Thread Tracker, Decision Confirmation, and Commitment Check features. The idea is to provide real-time updates about what decisions have been made in a meeting, what items need following up on, and a visualization of a meeting’s overall conversation flow. For example, Thread Tracker might show that a team meeting started off talking about budget allocations, before moving on to potential new hires and timelines for those hires. Decision Confirmation might show that the meeting concluded that all new hires should be finished by a specific date. Lastly, Commitment Check verifies if action items have been assigned (and to whom) with a clear deadline. The glasses will also provide post-meeting transcripts and summaries.

I saw a brief glimpse of what this could look like at my demo, albeit a product interview is less conducive to these kinds of features than a typical planning meeting. That said, the glasses also support more general-use AI features like captioning, real-time translations for over 45 languages, the ability to take phone calls, and teleprompters/notecards for public speakers. Users can also make use of the Halliday AI assistant for voice control.

Overall, this is a much more tightly focused vision for a pair of smart glasses than Halliday’s original glasses. That said, we’ll have to see if the AI features are all that useful. So far, I’ve had little success with AI wearables successfully intuiting what I actually need surfaced in a conversation, or deriving the correct conclusions for to-do items. And at $599, the Gen 2 comes with a pretty steep price tag for the average person. That’s not including any extra costs for prescription lenses. (Halliday claims it’ll be able to handle my prescription, which is -10 in one eye and -8.75 in the other with monster astigmatism. We shall see!)

The Halliday Gen 2 are available for preorder starting today with a $10 deposit and a subsequent $100 discount on the final price. The glasses are expected to ship in September.

#Hallidays #latest #smart #glasses #feature #muchimproved #displayAI,Gadgets,Hands-on,News,Reviews,Tech,Wearable
One of the most important things happening on Earth today is the solar energy build-out. Around the world, companies and countries are racing to deploy solar and batteries to achieve energy independence and limit the effects of climate change.

That build-out, though, is running into a labor market challenge, with a limited supply of workers to meet a growing demand for installation. Robots could be an answer, but industrial robots have historically struggled in unstructured environments, at least until now. The latest generation of AI models may have changed that equation.

That’s the driving idea behind Gritt, a start-up founded by two Carnegie Mellon-trained roboticists, CEO Puneet Puri and CTO Vishal Dugar. The company exited stealth Tuesday morning with a $26 million Series A round of funding led by Obvious Ventures with participation from Union Square Ventures and Active Impact Investment. That brings its total funding to $34 million, following an earlier seed round backed by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures. The startup is building an intelligent system to “help civilization build infrastructure faster,” in Puri’s words.

“Our thesis is that if we truly want to speed up construction,” Puri tells TechCrunch, “you need an intelligence which can work in the outdoor, chaotic environments of these construction sites, and it has to be generalizable enough that it can work in these varied environments.”

Rather than building its own robots from scratch, Gritt uses off-the-shelf hardware—thus far, rented skidders and robotic arms built by companies like Kawasaki—to build platforms that are controlled by its AI models. The first job its systems handle is unloading large, glass solar panels, carrying them toward the metal frames where they need to be installed, and positioning them on the frames with sub-millimeter accuracy so workers can fasten them.

“There are people who used to build rockets that went into space and had infinite budget for the smallest little part, and then there are people who know what it means to get into dirty, dull, and dangerous jobs and scale them like mad,” said Andrew Beebe, the partner at Obvious Ventures who led Gritt’s Series A round. “These guys are in the second camp, and that’s a special kind of entrepreneur that has the technical chops, the AI, and the machine vision skills to make it work.”

Gritt has two systems currently deployed in the field, using the data they collect to improve their behavior. Puri says that a typical eight-person crew workers can install 800 panels a day, but the same crew working with Gritt’s systems can install 3,000 to 4,000 panels each day.

Now, the company says it is contracted to help install 2.8 gigawatts of solar panels in the next 18 months, and that its customers include three of the top 10 US power construction companies. The company hopes to be operating 48 of its systems within the next six months.

TechCrunch spoke to one Gritt customer who declined to be identified for competitive reasons, but who was enthusiastic about the system’s ability to improve his work. He expects it to be easier to work at remote sites where it is difficult to attract workers, and anticipates a reduction in injuries since workers won’t have to repeatedly lift 100-pound panels overhead.

Gritt is competing against companies with their own panel-installing robots like Luminous Robotics, Cosmic, and China’s Trinabot. Those companies are building their own hardware, rather than focusing on off-the-shelf vehicles and arms like Gritt, a difference that could shape who grows faster and with a leaner cost structure as demand grows.

Gritt wants to add new manipulation tasks to its system so it can fasten the solar panels, drill posts, and even build the racks they sit on. Longer term, it also wants to move into other common, labor-intensive construction tasks, like tying rebar before concrete is poured over it.

What’s enabled the startup to pursue this vision? Mainly, the rise of new AI models, the founders say.

“Making a system for one solution was still possible to some extent five years ago, right?” Puri said, but AI is now making that work generalizable — the same underlying pipeline can be reused and improve across tasks. As an example, he noted that training the system to stack cinder blocks took weeks, while a similar demo with rebar tying took just a day using the same software.

But training new tasks is just the beginning of Gritt’s vision. The founders believe the suite of sensors and intelligence its systems bring to worksites can do more than install panels; it can boost management and decision-making. For instance, they imagine their system noticing a trench is open while a storm approaches, allowing it to alert workers to cover it before rain damages components, or flagging missing inventory.

“Gritt becomes now this layer of physical AI, which is doing this dextrous, labor-intensive task, plus it can help you take decisions on the site,” Puri said.

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

#Gritt #exits #stealth #million #robots #build #solar #plantsthen #TechCrunchExclusive">Gritt exits stealth with  million for robots to build solar plants—then, everything else | TechCrunch
One of the most important things happening on Earth today is the solar energy build-out. Around the world, companies and countries are racing to deploy solar and batteries to achieve energy independence and limit the effects of climate change.

That build-out, though, is running into a labor market challenge, with a limited supply of workers to meet a growing demand for installation. Robots could be an answer, but industrial robots have historically struggled in unstructured environments, at least until now. The latest generation of AI models may have changed that equation.







That’s the driving idea behind Gritt, a start-up founded by two Carnegie Mellon-trained roboticists, CEO Puneet Puri and CTO Vishal Dugar. The company exited stealth Tuesday morning with a  million Series A round of funding led by Obvious Ventures with participation from Union Square Ventures and Active Impact Investment. That brings its total funding to  million, following an earlier seed round backed by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures. The startup is building an intelligent system to “help civilization build infrastructure faster,” in Puri’s words.

“Our thesis is that if we truly want to speed up construction,” Puri tells TechCrunch, “you need an intelligence which can work in the outdoor, chaotic environments of these construction sites, and it has to be generalizable enough that it can work in these varied environments.”

Rather than building its own robots from scratch, Gritt uses off-the-shelf hardware—thus far, rented skidders and robotic arms built by companies like Kawasaki—to build platforms that are controlled by its AI models. The first job its systems handle is unloading large, glass solar panels, carrying them toward the metal frames where they need to be installed, and positioning them on the frames with sub-millimeter accuracy so workers can fasten them.

“There are people who used to build rockets that went into space and had infinite budget for the smallest little part, and then there are people who know what it means to get into dirty, dull, and dangerous jobs and scale them like mad,” said Andrew Beebe, the partner at Obvious Ventures who led Gritt’s Series A round. “These guys are in the second camp, and that’s a special kind of entrepreneur that has the technical chops, the AI, and the machine vision skills to make it work.”

Gritt has two systems currently deployed in the field, using the data they collect to improve their behavior. Puri says that a typical eight-person crew workers can install 800 panels a day, but the same crew working with Gritt’s systems can install 3,000 to 4,000 panels each day.


Now, the company says it is contracted to help install 2.8 gigawatts of solar panels in the next 18 months, and that its customers include three of the top 10 US power construction companies. The company hopes to be operating 48 of its systems within the next six months.

TechCrunch spoke to one Gritt customer who declined to be identified for competitive reasons, but who was enthusiastic about the system’s ability to improve his work. He expects it to be easier to work at remote sites where it is difficult to attract workers, and anticipates a reduction in injuries since workers won’t have to repeatedly lift 100-pound panels overhead.

Gritt is competing against companies with their own panel-installing robots like Luminous Robotics, Cosmic, and China’s Trinabot. Those companies are building their own hardware, rather than focusing on off-the-shelf vehicles and arms like Gritt, a difference that could shape who grows faster and with a leaner cost structure as demand grows.







Gritt wants to add new manipulation tasks to its system so it can fasten the solar panels, drill posts, and even build the racks they sit on. Longer term, it also wants to move into other common, labor-intensive construction tasks, like tying rebar before concrete is poured over it.

What’s enabled the startup to pursue this vision? Mainly, the rise of new AI models, the founders say.

“Making a system for one solution was still possible to some extent five years ago, right?” Puri said, but AI is now making that work generalizable — the same underlying pipeline can be reused and improve across tasks. As an example, he noted that training the system to stack cinder blocks took weeks, while a similar demo with rebar tying took just a day using the same software.

But training new tasks is just the beginning of Gritt’s vision. The founders believe the suite of sensors and intelligence its systems bring to worksites can do more than install panels; it can boost management and decision-making. For instance, they imagine their system noticing a trench is open while a storm approaches, allowing it to alert workers to cover it before rain damages components, or flagging missing inventory.

“Gritt becomes now this layer of physical AI, which is doing this dextrous, labor-intensive task, plus it can help you take decisions on the site,” Puri said. 
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Gritt #exits #stealth #million #robots #build #solar #plantsthen #TechCrunchExclusive

Gritt, a start-up founded by two Carnegie Mellon-trained roboticists, CEO Puneet Puri and CTO Vishal Dugar. The company exited stealth Tuesday morning with a $26 million Series A round of funding led by Obvious Ventures with participation from Union Square Ventures and Active Impact Investment. That brings its total funding to $34 million, following an earlier seed round backed by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures. The startup is building an intelligent system to “help civilization build infrastructure faster,” in Puri’s words.

“Our thesis is that if we truly want to speed up construction,” Puri tells TechCrunch, “you need an intelligence which can work in the outdoor, chaotic environments of these construction sites, and it has to be generalizable enough that it can work in these varied environments.”

Rather than building its own robots from scratch, Gritt uses off-the-shelf hardware—thus far, rented skidders and robotic arms built by companies like Kawasaki—to build platforms that are controlled by its AI models. The first job its systems handle is unloading large, glass solar panels, carrying them toward the metal frames where they need to be installed, and positioning them on the frames with sub-millimeter accuracy so workers can fasten them.

“There are people who used to build rockets that went into space and had infinite budget for the smallest little part, and then there are people who know what it means to get into dirty, dull, and dangerous jobs and scale them like mad,” said Andrew Beebe, the partner at Obvious Ventures who led Gritt’s Series A round. “These guys are in the second camp, and that’s a special kind of entrepreneur that has the technical chops, the AI, and the machine vision skills to make it work.”

Gritt has two systems currently deployed in the field, using the data they collect to improve their behavior. Puri says that a typical eight-person crew workers can install 800 panels a day, but the same crew working with Gritt’s systems can install 3,000 to 4,000 panels each day.

Now, the company says it is contracted to help install 2.8 gigawatts of solar panels in the next 18 months, and that its customers include three of the top 10 US power construction companies. The company hopes to be operating 48 of its systems within the next six months.

TechCrunch spoke to one Gritt customer who declined to be identified for competitive reasons, but who was enthusiastic about the system’s ability to improve his work. He expects it to be easier to work at remote sites where it is difficult to attract workers, and anticipates a reduction in injuries since workers won’t have to repeatedly lift 100-pound panels overhead.

Gritt is competing against companies with their own panel-installing robots like Luminous Robotics, Cosmic, and China’s Trinabot. Those companies are building their own hardware, rather than focusing on off-the-shelf vehicles and arms like Gritt, a difference that could shape who grows faster and with a leaner cost structure as demand grows.

Gritt wants to add new manipulation tasks to its system so it can fasten the solar panels, drill posts, and even build the racks they sit on. Longer term, it also wants to move into other common, labor-intensive construction tasks, like tying rebar before concrete is poured over it.

What’s enabled the startup to pursue this vision? Mainly, the rise of new AI models, the founders say.

“Making a system for one solution was still possible to some extent five years ago, right?” Puri said, but AI is now making that work generalizable — the same underlying pipeline can be reused and improve across tasks. As an example, he noted that training the system to stack cinder blocks took weeks, while a similar demo with rebar tying took just a day using the same software.

But training new tasks is just the beginning of Gritt’s vision. The founders believe the suite of sensors and intelligence its systems bring to worksites can do more than install panels; it can boost management and decision-making. For instance, they imagine their system noticing a trench is open while a storm approaches, allowing it to alert workers to cover it before rain damages components, or flagging missing inventory.

“Gritt becomes now this layer of physical AI, which is doing this dextrous, labor-intensive task, plus it can help you take decisions on the site,” Puri said.

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#Gritt #exits #stealth #million #robots #build #solar #plantsthen #TechCrunchExclusive">Gritt exits stealth with $34 million for robots to build solar plants—then, everything else | TechCrunch

One of the most important things happening on Earth today is the solar energy build-out. Around the world, companies and countries are racing to deploy solar and batteries to achieve energy independence and limit the effects of climate change.

That build-out, though, is running into a labor market challenge, with a limited supply of workers to meet a growing demand for installation. Robots could be an answer, but industrial robots have historically struggled in unstructured environments, at least until now. The latest generation of AI models may have changed that equation.

That’s the driving idea behind Gritt, a start-up founded by two Carnegie Mellon-trained roboticists, CEO Puneet Puri and CTO Vishal Dugar. The company exited stealth Tuesday morning with a $26 million Series A round of funding led by Obvious Ventures with participation from Union Square Ventures and Active Impact Investment. That brings its total funding to $34 million, following an earlier seed round backed by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures. The startup is building an intelligent system to “help civilization build infrastructure faster,” in Puri’s words.

“Our thesis is that if we truly want to speed up construction,” Puri tells TechCrunch, “you need an intelligence which can work in the outdoor, chaotic environments of these construction sites, and it has to be generalizable enough that it can work in these varied environments.”

Rather than building its own robots from scratch, Gritt uses off-the-shelf hardware—thus far, rented skidders and robotic arms built by companies like Kawasaki—to build platforms that are controlled by its AI models. The first job its systems handle is unloading large, glass solar panels, carrying them toward the metal frames where they need to be installed, and positioning them on the frames with sub-millimeter accuracy so workers can fasten them.

“There are people who used to build rockets that went into space and had infinite budget for the smallest little part, and then there are people who know what it means to get into dirty, dull, and dangerous jobs and scale them like mad,” said Andrew Beebe, the partner at Obvious Ventures who led Gritt’s Series A round. “These guys are in the second camp, and that’s a special kind of entrepreneur that has the technical chops, the AI, and the machine vision skills to make it work.”

Gritt has two systems currently deployed in the field, using the data they collect to improve their behavior. Puri says that a typical eight-person crew workers can install 800 panels a day, but the same crew working with Gritt’s systems can install 3,000 to 4,000 panels each day.

Now, the company says it is contracted to help install 2.8 gigawatts of solar panels in the next 18 months, and that its customers include three of the top 10 US power construction companies. The company hopes to be operating 48 of its systems within the next six months.

TechCrunch spoke to one Gritt customer who declined to be identified for competitive reasons, but who was enthusiastic about the system’s ability to improve his work. He expects it to be easier to work at remote sites where it is difficult to attract workers, and anticipates a reduction in injuries since workers won’t have to repeatedly lift 100-pound panels overhead.

Gritt is competing against companies with their own panel-installing robots like Luminous Robotics, Cosmic, and China’s Trinabot. Those companies are building their own hardware, rather than focusing on off-the-shelf vehicles and arms like Gritt, a difference that could shape who grows faster and with a leaner cost structure as demand grows.

Gritt wants to add new manipulation tasks to its system so it can fasten the solar panels, drill posts, and even build the racks they sit on. Longer term, it also wants to move into other common, labor-intensive construction tasks, like tying rebar before concrete is poured over it.

What’s enabled the startup to pursue this vision? Mainly, the rise of new AI models, the founders say.

“Making a system for one solution was still possible to some extent five years ago, right?” Puri said, but AI is now making that work generalizable — the same underlying pipeline can be reused and improve across tasks. As an example, he noted that training the system to stack cinder blocks took weeks, while a similar demo with rebar tying took just a day using the same software.

But training new tasks is just the beginning of Gritt’s vision. The founders believe the suite of sensors and intelligence its systems bring to worksites can do more than install panels; it can boost management and decision-making. For instance, they imagine their system noticing a trench is open while a storm approaches, allowing it to alert workers to cover it before rain damages components, or flagging missing inventory.

“Gritt becomes now this layer of physical AI, which is doing this dextrous, labor-intensive task, plus it can help you take decisions on the site,” Puri said.

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

#Gritt #exits #stealth #million #robots #build #solar #plantsthen #TechCrunchExclusive

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