×
Aiper’s Scuba V3 Pool Robot Brings AI Vision Underwater

Aiper’s Scuba V3 Pool Robot Brings AI Vision Underwater

The app also includes access to two scheduled operational modes for those who would like to leave the robot in the pool, including a calendar-based mode with three frequency levels—90 minutes x 2, 60 minutes x 3, or 45 minutes x 4. The other mode is a bit of a letdown: The so-called AI Navium mode sounds like it uses the AI camera to periodically survey the pool over the course of a week and perform a routine cleaning only when required—but in reality, this mode merely performs a quick analysis of your previous runs and then uses AI to create a schedule for the next few days, based on how you’ve used the robot in the past.

Hungry for Gunk

Video: Chris Null

The Scuba V3 made fairly quick work of debris in my pool during test runs, rarely needing more than a couple of hours to scoop up all visible detritus on the pool floor while also scrubbing the walls and waterline. The AI camera system does seem to work as advertised, even locating small pebbles I tossed into the pool and dutifully routing itself to collect them. With organic debris, the pool looked fully clean after each run (ending between 170 and 190 minutes each time), and with synthetic debris, the Scuba V3 achieved a 96 percent cleanliness rating, with just a few test leaves remaining in some difficult corners. That’s especially good performance given that three hours is not a lot of operating time. And note there’s no way to adjust the running time outside of the scheduled modes; on-demand modes always run the battery until it’s nearly dead. Fortunately, Aiper does seem to make the most of this time, formally specifying a maximum coverage area of a significant 1,600 square feet.

I unfortunately didn’t have much success with the AI schedule mode. After running the analyzer, the app suggested a baffling five-day schedule comprising two floor runs, two floor-plus-waterline runs, and a final floor run. It then ignored the schedule and promptly ran a three-hour floor run, which drained the battery completely. I tried again the next day, and the robot missed its schedule, then ran randomly late in the night. I wasn’t a big fan of leave-it-in-the-pool scheduling before testing the Scuba V3, and this showing didn’t improve that opinion.

Video: Chris Null

When finished with a run, the Scuba climbs to the waterline and sends a push notification to the app, alerting you that it’s ready to be collected and cleaned. Note that you only have 10 minutes to reach it: The Scuba can’t float, so it has to use the last of its juice to run a motor to tread water and hold itself in place. After that 10 minutes is up, the spent Scuba sinks to the floor of the pool and must be retrieved with a pool and hook. My best advice is to set a 175-minute timer each time you launch a run to remind you to watch for the completion notification.

Cleanup can be somewhat involved. The filter basket design features a large lid that makes it easy to access the inner filter, and hosing down both of these filters clean is straightforward. The removable mesh on the interior basket is another story, though. While it’s very effective at capturing dirt and other very fine debris, it’s quite difficult to clean, and if you don’t remove it from the basket, lots of debris gets caught between the mesh and the basket itself. Removing and replacing the mesh is difficult, especially when it’s wet, so I usually just left it in place and cleaned it the best I could after each run, accepting that it would never be perfect. I expect most users will do the same.

Source link
#Aipers #Scuba #Pool #Robot #Brings #Vision #Underwater

On May 4, 2026, the U.S. Securities and Exchange Commission filed an amended complaint to add the Elon Musk Revocable Trust dated July 22, 2003 (the “Revocable Trust”) as a defendant to this action. The amended complaint alleges that the defendants failed to timely file a beneficial ownership report with the Commission after the Revocable Trust acquired beneficial ownership of more than five percent of the outstanding shares of Twitter, Inc. common stock, in violation of the beneficial ownership reporting requirements under the Securities Exchange Act of 1934 (“Exchange Act”).

The SEC simultaneously moved for entry of a consent final judgment as to the Revocable Trust. Without admitting or denying the allegations of the complaint as to the Revocable Trust, the Revocable Trust consented to entry of a final judgment, subject to court approval, that would permanently enjoin it from violating Section 13(d) of the Exchange Act and Rule 13d-1 thereunder and order it to pay a civil penalty of $1.5 million.

As explained in the consent motion, if the court enters the proposed final judgment as to the Revocable Trust as proposed by the Revocable Trust and the SEC, the SEC will file a stipulated dismissal of Elon Musk in his personal capacity, which will resolve this case in its entirety.

#Elon #Musk #settle #feds #Twitter #lawsuit #pocket #changeElon Musk,Law,News,Policy,Tech,Twitter – X">Elon Musk will settle the feds’ Twitter lawsuit with pocket changeOn May 4, 2026, the U.S. Securities and Exchange Commission filed an amended complaint to add the Elon Musk Revocable Trust dated July 22, 2003 (the “Revocable Trust”) as a defendant to this action. The amended complaint alleges that the defendants failed to timely file a beneficial ownership report with the Commission after the Revocable Trust acquired beneficial ownership of more than five percent of the outstanding shares of Twitter, Inc. common stock, in violation of the beneficial ownership reporting requirements under the Securities Exchange Act of 1934 (“Exchange Act”).The SEC simultaneously moved for entry of a consent final judgment as to the Revocable Trust. Without admitting or denying the allegations of the complaint as to the Revocable Trust, the Revocable Trust consented to entry of a final judgment, subject to court approval, that would permanently enjoin it from violating Section 13(d) of the Exchange Act and Rule 13d-1 thereunder and order it to pay a civil penalty of .5 million.As explained in the consent motion, if the court enters the proposed final judgment as to the Revocable Trust as proposed by the Revocable Trust and the SEC, the SEC will file a stipulated dismissal of Elon Musk in his personal capacity, which will resolve this case in its entirety.#Elon #Musk #settle #feds #Twitter #lawsuit #pocket #changeElon Musk,Law,News,Policy,Tech,Twitter – X


Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures.

This marks a shift from earlier days, when the release of new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.

For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found.

For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed.

Image AI models now drive app growth, beating chatbot upgrades | TechCrunch
Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures.

This marks a shift from earlier days, when the release of new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.







For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found.

For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed.

Image Credits:Appfigures

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out.

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	


Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

Among the three, only ChatGPT turned the increased attention into actual dollars. 







OpenAI’s 4o image-generation model led to an estimated  million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said.

Image Credits:Appfigures

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern. 

While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai
Image Credits:Appfigures

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out.

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

Techcrunch event

San Francisco, CA | October 13-15, 2026

Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only $181,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

Among the three, only ChatGPT turned the increased attention into actual dollars.

OpenAI’s 4o image-generation model led to an estimated $70 million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said.

Image Credits:Appfigures

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern.

While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.

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

#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai">Image AI models now drive app growth, beating chatbot upgrades | TechCrunch
Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures.

This marks a shift from earlier days, when the release of new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.







For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found.

For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed.

Image Credits:Appfigures

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out.

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	


Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

Among the three, only ChatGPT turned the increased attention into actual dollars. 







OpenAI’s 4o image-generation model led to an estimated  million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said.

Image Credits:Appfigures

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern. 

While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai

new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.

For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found.

For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed.

Image AI models now drive app growth, beating chatbot upgrades | TechCrunch
Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures.

This marks a shift from earlier days, when the release of new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.







For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found.

For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed.

Image Credits:Appfigures

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out.

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	


Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

Among the three, only ChatGPT turned the increased attention into actual dollars. 







OpenAI’s 4o image-generation model led to an estimated  million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said.

Image Credits:Appfigures

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern. 

While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai
Image Credits:Appfigures

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out.

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

Techcrunch event

San Francisco, CA | October 13-15, 2026

Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only $181,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

Among the three, only ChatGPT turned the increased attention into actual dollars.

OpenAI’s 4o image-generation model led to an estimated $70 million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said.

Image Credits:Appfigures

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern.

While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.

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

#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai">Image AI models now drive app growth, beating chatbot upgrades | TechCrunch


Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures.

This marks a shift from earlier days, when the release of new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.

For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found.

For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed.

Image AI models now drive app growth, beating chatbot upgrades | TechCrunch
Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures.

This marks a shift from earlier days, when the release of new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.







For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found.

For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed.

Image Credits:Appfigures

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out.

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	


Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

Among the three, only ChatGPT turned the increased attention into actual dollars. 







OpenAI’s 4o image-generation model led to an estimated  million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said.

Image Credits:Appfigures

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern. 

While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai
Image Credits:Appfigures

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out.

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

Techcrunch event

San Francisco, CA | October 13-15, 2026

Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only $181,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

Among the three, only ChatGPT turned the increased attention into actual dollars.

OpenAI’s 4o image-generation model led to an estimated $70 million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said.

Image Credits:Appfigures

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern.

While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.

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

#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai

Post Comment