Watch A Cybertruck Dangle In Mid-Air Thanks To Tesla Repair Glue
This stunt followed a legitimate concern of Jerry's around Tesla's structural repair method. Months earlier, the same truck suffered what looked like a catastrophic failure when its tow hitch ripped clean out of the rear casting during a stress test that pushed far beyond its rated 1,100-pound tongue weight. Instead of getting totaled, the truck was repaired using Tesla's published repair procedure: sectioning out the broken gigacasting and gluing in a replacement section using a structural adhesive called Fusor 2098.
After curing, this specific repair adhesive has a tensile strength of 3,190 pounds per square inch (psi). A two-and-a-half-inch patch of the same blue glue used in that repair bore the entire weight of the Cybertruck. You read that right — glued, cured, then hoisted skyward. Whether you see that as genius or terrifying probably depends on how much time you've spent in collision shops. Either way, it's an impressive demonstration.
Read more: 2025 Cadillac Escalade IQ Is All About Big Numbers
Cool Stunt, But What This Means For Modern Car Repair
The idea of glue holding your car together feels a little unsettling — like duct tape on a spaceship. But in today's auto engineering, it's not just common, but in many cases, it's the smarter, stronger choice. The adhesive used in the Cybertruck repair is a two-part epoxy classified as a Crash Durable Structural Adhesive. It's not Tesla-exclusive, either — all OEMs use similar stuff for high-strength bonding across differing substrates.
Why not just weld it? Well, adhesives in some applications distribute loads more evenly, preserve material integrity, and protect against corrosion between joints. Plus, when paired with mechanical fasteners like rivets — which Tesla also specifies for this repair — the resulting bond can outperform welds in peel and impact strength.
But there's a flip side: if your ride needs this kind of fix, it better be done exactly by the book. Adhesives can be uber-strong, but that doesn't mean it can, or should, be used in lieu of OEM repair procedures. Tesla mandates that only certified shops use specified adhesives, parts, and procedures. No aftermarket shortcuts, no recycled structures, and absolutely no expired glue. Every step — from grinding off etch-coat, to rivet type and spacing, to adhesive bead thickness — all laid out in the repair manuals.
Here's where things get murky, though. If you're in a wreck, your insurance policy promises to return your car to its "pre-loss condition." But what does that even mean when you're gluing in structural chunks that were once a monolithic piece? Is a sectioned-then-epoxied casting still "as it was"? Tesla says yes — the repair is OEM-approved. Technically speaking, it should meet or exceed original specs — but that's assuming the job's done right. Honestly, we'd love to see JerryRigEverything run that hitch test again on the repaired Cybertruck. If the glue job really is stronger than stock, that truck should out-muscle its factory self.
Want more like this? Join the Jalopnik newsletter to get the latest auto news sent straight to your inbox...
Read the original article on Jalopnik.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Android Authority
24 minutes ago
- Android Authority
5 productivity apps I swear by, and one of them unlocks the rest
Joe Maring / Android Authority Productivity apps are the bane of the app world. On one end of the spectrum are the total nerds who could shame a cyborg with their organizing skills, and on the other are those who dump everything into Google Keep just to have everything in one place. I live somewhere in the middle. I'm not pedantic enough to run the most complex Notion server and flex about it on Reddit, nor am I a simpleton who relies solely on a notes app. I use a bunch of apps every day to improve my productivity. They're all varied in kind and now form a solid part of a puzzle. If one piece is out of place, my workflow wouldn't break, but it would definitely distract me, or make me want to pull my hair out, depending on how severe the disruption is. Do you think AI chatbots improve your productivity? 0 votes Absolutely NaN % Somewhat NaN % Not really NaN % Here they are: Enpass + Ente Auth Karandeep Singh / Android Authority Every time I set up a new phone, these two are the first apps I install. My password manager of choice, Enpass, is the stepping stone — I wouldn't be able to log into any other app without it. So, it's the first thing that goes in. I started using it many years ago and have stuck with it ever since. While I'm on a lifetime grandfathered plan and it hasn't given me any trouble so far, the real reason I've stayed is that it carries my entire life's worth of passwords and important files in my pocket, always. Whenever someone needs a document, I just fire up Enpass and hand it over with all the sass that a password manager can afford. And of course, I need a 2FA code manager too, right? I've already gone on record about why I absolutely love Ente Auth and how convenient it's made my life with encrypted backups. But I'll say it again: I love it for making my life so damn convenient. This pair is something I genuinely can't live without. Nothing on my phones or laptops would work without these, and I use them at least 15 times a day — more often than I say the word 'Android' every day. TickTick Dhruv Bhutani / Android Authority Okay, I admit it, I've raved about this app too before. But it deserves all the praise and more! TickTick is by far the best task management app available for Android (and otherwise). It gets so many things right, is packed with features, and doesn't even ask you to pay for most of it. I sincerely can't plan my day without some of its reminder tools like subtasks, granular repeat reminder controls, and habit tracking. It's the app that's been logging my reading streak for years, too. It has more features than I use, but I think that's how nerd-centric apps should be. Not every feature is for everyone; you should be able to use what suits you and ignore the rest. That's exactly how I've set up TickTick to work for me, like no other app could. Notion Dhruv Bhutani / Android Authority Ah, the crown jewel of productivity apps that every enthusiast wants to flex about. What I like about Notion is its ability to be as complex or straightforward as you want it to be. Mine isn't too complicated, but it still meets my varied needs. For instance, it has my reading list, complete with the book's current reading status, the month I finished a book, what form it was in, the author, and the month I finished it in. I've even ditched MS Word for Notion for all my personal writing — essays, short stories, poetry, you name it. Its text formatting is just enough for me: three font styles and some basic markdown options. That's it. I'm not spending time adjusting fonts or tweaking margins anymore like in Word. I just open it and let my momentary creative spark shine on paper without formatting dimming it down. Google Keep Kaitlyn Cimino / Android Authority I know I said Google Keep was a simpleton's app, but sometimes that's exactly what you need. While Notion is for more complex tasks and granular control, Keep is the warehouse where raw material sits before it goes through processing and turns into usable data. My thoughts, random info dumps, things I need to remember, it all goes here. You also can't discount its ability to share notes with literally anyone who has a Google account. And when I do share notes with people (say, with my mum), I know it won't overwhelm them like a Notion clip with a bunch of text, toggles, and indecipherable icons. What I still despise about Keep, though, is that all the new formatting options still aren't cross-platform, when we're more than halfway through 2025. ChatGPT Kaitlyn Cimino / Android Authority Okay, I can already feel the side-eyes for this one. But I can't deny that ChatGPT has actually helped me become more productive and cut down on mundane tasks a lot. Take research, for instance. When I'm looking into something personal like a specific kind of diet, I'll feed it YouTube videos, forum threads, and articles that I find relevant, and ask it to combine all the dense information into something easier to parse. Then I'll ask it to generate a Notion-style doc, and boom, it's ready in seconds. No formatting needed. ChatGPT is that second brain, the one I bounce ideas off of, the one that helps me look at things from another angle. For writers, an editor is someone who gives you a different perspective that one fails to see while writing. For me, ChatGPT is that second brain, the one I bounce ideas off of, the one that helps me look at things from another angle, and helps me zero in on a direction. That would otherwise require a brainstorming session with a bunch of people. And we all know how hard it is to align timing and get people even on Google Meet, let alone in the same room. I could've added more mainstream apps to this list, but come on, Gmail and Calendar are part of everyone's productivity suite at this point. Most people wouldn't even call them productivity apps anymore. For me, anything that furthers my cause of staying productive while I fight tooth and nail with procrastination (jk, that battle will now happen tomorrow) earns a spot. These are the apps that help me sail through my work and personal day as if I'm a professional surfer. What's on your list of productivity apps? Comment below. Follow
TechCrunch
24 minutes ago
- TechCrunch
Inside OpenAI's quest to make AI do anything for you
Shortly after Hunter Lightman joined OpenAI as a researcher in 2022, he watched his colleagues launch ChatGPT, one of the fastest-growing products ever. Meanwhile, Lightman quietly worked on a team teaching OpenAI's models to solve high school math competitions. Today that team, known as MathGen, is considered instrumental to OpenAI's industry-leading effort to create AI reasoning models: the core technology behind AI agents that can do tasks on a computer like a human would. 'We were trying to make the models better at mathematical reasoning, which at the time they weren't very good at,' Lightman told TechCrunch, describing MathGen's early work. OpenAI's models are far from perfect today — the company's latest AI systems still hallucinate and its agents struggle with complex tasks. But its state-of-the-art models have improved significantly on mathematical reasoning. One of OpenAI's models recently won a gold medal at the International Math Olympiad, a math competition for the world's brightest high school students. OpenAI believes these reasoning capabilities will translate to other subjects, and ultimately power general-purpose agents that the company has always dreamed of building. ChatGPT was a happy accident — a lowkey research preview turned viral consumer business — but OpenAI's agents are the product of a years-long, deliberate effort within the company. 'Eventually, you'll just ask the computer for what you need and it'll do all of these tasks for you,' said OpenAI CEO Sam Altman at the company's first developer conference in 2023. 'These capabilities are often talked about in the AI field as agents. The upsides of this are going to be tremendous.' Techcrunch event Tech and VC heavyweights join the Disrupt 2025 agenda Netflix, ElevenLabs, Wayve, Sequoia Capital — just a few of the heavy hitters joining the Disrupt 2025 agenda. They're here to deliver the insights that fuel startup growth and sharpen your edge. Don't miss the 20th anniversary of TechCrunch Disrupt, and a chance to learn from the top voices in tech — grab your ticket now and save up to $675 before prices rise. Tech and VC heavyweights join the Disrupt 2025 agenda Netflix, ElevenLabs, Wayve, Sequoia Capital — just a few of the heavy hitters joining the Disrupt 2025 agenda. They're here to deliver the insights that fuel startup growth and sharpen your edge. Don't miss the 20th anniversary of TechCrunch Disrupt, and a chance to learn from the top voices in tech — grab your ticket now and save up to $675 before prices rise. San Francisco | REGISTER NOW OpenAI CEO Sam Altman speaks during the OpenAI DevDay event on November 06, 2023 in San Francisco, California.(Photo by) Image Credits:Justin Sullivan / Getty Images Whether agents will meet Altman's vision remains to be seen, but OpenAI shocked the world with the release of its first AI reasoning model, o1, in the fall of 2024. Less than a year later, the 21 foundational researchers behind that breakthrough are the most highly sought-after talent in Silicon Valley. Mark Zuckerberg recruited five of the o1 researchers to work on Meta's new superintelligence-focused unit, offering some compensation packages north of $100 million. One of them, Shengjia Zhao, was recently named chief scientist of Meta Superintelligence Labs. The reinforcement learning renaissance The rise of OpenAI's reasoning models and agents are tied to a machine learning training technique known as reinforcement learning (RL). RL provides feedback to an AI model on whether its choices were correct or not in simulated environments. RL has been used for decades. For instance, in 2016, about a year after OpenAI was founded in 2015, an AI system created by Google DeepMind using RL, AlphaGo, gained global attention after beating a world champion in the board game, Go. South Korean professional Go player Lee Se-Dol (R) prepares for his fourth match against Google's artificial intelligence program, AlphaGo, during the Google DeepMind Challenge Match on March 13, 2016 in Seoul, South Korea. Lee Se-dol played a five-game match against a computer program developed by a Google, AlphaGo. (Photo by Google via Getty Images) Around that time, one of OpenAI's first employees, Andrej Karpathy, began pondering how to leverage RL to create an AI agent that could use a computer. But it would take years for OpenAI to develop the necessary models and training techniques. By 2018, OpenAI pioneered its first large language model in the GPT series, pretrained on massive amounts of internet data and a large clusters of GPUs. GPT models excelled at text processing, eventually leading to ChatGPT, but struggled with basic math. It took until 2023 for OpenAI to achieve a breakthrough, initially dubbed 'Q*' and then 'Strawberry,' by combining LLMs, RL, and a technique called test-time computation. The latter gave the models extra time and computing power to plan and work through problems, verifying its steps, before providing an answer. This allowed OpenAI to introduce a new approach called 'chain-of-thought' (CoT), which improved AI's performance on math questions the models hadn't seen before. 'I could see the model starting to reason,' said El Kishky. 'It would notice mistakes and backtrack, it would get frustrated. It really felt like reading the thoughts of a person.' Though individually these techniques weren't novel, OpenAI uniquely combined them to create Strawberry, which directly led to the development of o1. OpenAI quickly identified that the planning and fact checking abilities of AI reasoning models could be useful to power AI agents. 'We had solved a problem that I had been banging my head against for a couple of years,' said Lightman. 'It was one of the most exciting moments of my research career.' Scaling reasoning With AI reasoning models, OpenAI determined it had two new axes that would allow it to improve AI models: using more computational power during the post-training of AI models, and giving AI models more time and processing power while answering a question. 'OpenAI, as a company, thinks a lot about not just the way things are, but the way things are going to scale,' said Lightman. Shortly after the 2023 Strawberry breakthrough, OpenAI spun up an 'Agents' team led by OpenAI researcher Daniel Selsam to make further progress on this new paradigm, two sources told TechCrunch. Although the team was called 'Agents,' OpenAI didn't initially differentiate between reasoning models and agents as we think of them today. The company just wanted to make AI systems capable of completing complex tasks. Eventually, the work of Selsam's Agents team became part of a larger project to develop the o1 reasoning model, with leaders including OpenAI co-founder Ilya Sutskever, chief research officer Mark Chen, and chief scientist Jakub Pachocki. Ilya Sutskever, Russian Israeli-Canadian computer scientist and co-founder and Chief Scientist of OpenAI, speaks at Tel Aviv University in Tel Aviv on June 5, 2023. (Photo by JACK GUEZ / AFP) Image Credits:Getty Images OpenAI would have to divert precious resources — mainly talent and GPUs — to create o1. Throughout OpenAI's history, researchers have had to negotiate with company leaders to obtain resources; demonstrating breakthroughs was a surefire way to secure them. 'One of the core components of OpenAI is that everything in research is bottom up,' said Lightman. 'When we showed the evidence [for o1], the company was like, 'This makes sense, let's push on it.'' Some former employees say that the startup's mission to develop AGI was the key factor in achieving breakthroughs around AI reasoning models. By focusing on developing the smartest-possible AI models, rather than products, OpenAI was able to prioritize o1 above other efforts. That type of large investment in ideas wasn't always possible at competing AI labs. The decision to try new training methods proved prescient. By late 2024, several leading AI labs started seeing diminishing returns on models created through traditional pretraining scaling. Today, much of the AI field's momentum comes from advances in reasoning models. What does it mean for an AI to 'reason?' In many ways, the goal of AI research is to recreate human intelligence with computers. Since the launch of o1, ChatGPT's UX has been filled with more human-sounding features such as 'thinking' and 'reasoning.' When asked whether OpenAI's models were truly reasoning, El Kishky hedged, saying he thinks about the concept in terms of computer science. 'We're teaching the model how to efficiently expend compute to get an answer. So if you define it that way, yes, it is reasoning,' said El Kishky. Lightman takes the approach of focusing on the model's results and not as much on the means or their relation to human brains. The OpenAI logo on screen at their developer day stage. (Credit: Devin Coldeway) Image Credits:Devin Coldewey 'If the model is doing hard things, then it is doing whatever necessary approximation of reasoning it needs in order to do that,' said Lightman. 'We can call it reasoning, because it looks like these reasoning traces, but it's all just a proxy for trying to make AI tools that are really powerful and useful to a lot of people.' OpenAI's researchers note people may disagree with their nomenclature or definitions of reasoning — and surely, critics have emerged — but they argue it's less important than the capabilities of their models. Other AI researchers tend to agree. Nathan Lambert, an AI researcher with the non-profit AI2, compares AI reasoning modes to airplanes in a blog post. Both, he says, are manmade systems inspired by nature — human reasoning and bird flight, respectively — but they operate through entirely different mechanisms. That doesn't make them any less useful, or any less capable of achieving similar outcomes. A group of AI researchers from OpenAI, Anthropic, and Google DeepMind agreed in a recent position paper that AI reasoning models are not well understood today, and more research is needed. It may be too early to confidently claim what exactly is going on inside them. The next frontier: AI agents for subjective tasks The AI agents on the market today work best for well-defined, verifiable domains such as coding. OpenAI's Codex agent aims to help software engineers offload simple coding tasks. Meanwhile, Anthropic's models have become particularly popular in AI coding tools like Cursor and Claude Code — these are some of the first AI agents that people are willing to pay up for. However, general purpose AI agents like OpenAI's ChatGPT Agent and Perplexity's Comet struggle with many of the complex, subjective tasks people want to automate. When trying to use these tools for online shopping or finding a long-term parking spot, I've found the agents take longer than I'd like and make silly mistakes. Agents are, of course, early systems that will undoubtedly improve. But researchers must first figure out how to better train the underlying models to complete tasks that are more subjective. AI applications (Photo by Jonathan Raa/NurPhoto via Getty Images) 'Like many problems in machine learning, it's a data problem,' said Lightman, when asked about the limitations of agents on subjective tasks. 'Some of the research I'm really excited about right now is figuring out how to train on less verifiable tasks. We have some leads on how to do these things.' Noam Brown, an OpenAI researcher who helped create the IMO model and o1, told TechCrunch that OpenAI has new general-purpose RL techniques which allow them to teach AI models skills that aren't easily verified. This was how the company built the model which achieved a gold medal at IMO, he said. OpenAI's IMO model was a newer AI system that spawns multiple agents, which then simultaneously explore several ideas, and then choose the best possible answer. These types of AI models are becoming more popular; Google and xAI have recently released state-of-the-art models using this technique. 'I think these models will become more capable at math, and I think they'll get more capable in other reasoning areas as well,' said Brown. 'The progress has been incredibly fast. I don't see any reason to think it will slow down.' These techniques may help OpenAI's models become more performant, gains that could show up in the company's upcoming GPT-5 model. OpenAI hopes to assert its dominance over competitors with the launch of GPT-5, ideally offering the best AI model to power agents for developers and consumers. But the company also wants to make its products simpler to use. El Kishky says OpenAI wants to develop AI agents that intuitively understand what users want, without requiring them to select specific settings. He says OpenAI aims to build AI systems that understand when to call up certain tools, and how long to reason for. These ideas paint a picture of an ultimate version of ChatGPT: an agent that can do anything on the internet for you, and understand how you want it to be done. That's a much different product than what ChatGPT is today, but the company's research is squarely headed in this direction. While OpenAI undoubtedly led the AI industry a few years ago, the company now faces a tranche of worthy opponents. The question is no longer just whether OpenAI can deliver its agentic future, but can the company do so before Google, Anthropic, xAI, or Meta beat them to it?
CNN
25 minutes ago
- CNN
I spent a weekend testing this $3,500 robot pool cleaner. Is it worth the investment?
Robot pool cleaners are essentially the aquatic equivalent of robot vacuums. At least, that's the conclusion I've come to after spending an entire weekend testing the Beatbot AquaSense 2 Ultra. As a Southern California resident who's spent a chunk of her summers in pools, the idea of a cordless robotic pool cleaner sounds appealing. Pool maintenance and cleaning, after all, is far from inexpensive. According to Aqua Masters Inc., a local pool cleaning service here in Los Angeles, California, pool cleaning 'can cost anywhere from $75 to $150 per month' on average, but the actual cost varies depending on the size and shape of your pool. So, if this type of cleaning product can somehow offset that, surely it's a worthy investment for pool cleaners. The Beatbot AquaSense 2 Ultra is an impressively capable product, scaling pool walls and skimming water surfaces with ease like some kind of pool-cleaning martial arts master. Unfortunately, much like robot vacuums, the question of whether it's a satisfactory replacement for weekly or monthly human intervention is up for debate, especially with that high upfront cost. Beatbot AquaSense 2 Ultra Robotic Pool Cleaner This premium robot pool cleaner will give your pool a thorough, comprehensive cleaning, even clearing the surface of floating debris. It's also effortless to use and comes with many features. However, it's still a splurge at $3,550, so it's not for everyone. It's easy to set up, very intuitive to use and packed with smart features I haven't tested many cordless robotic pool cleaners, but I have gone through my share of robot vacuums. Among the many things I don't like about them is the fussy initial setup. Luckily for me, that isn't the case with the Beatbot AquaSense 2 Ultra. One of the best things about this pool cleaner is that despite its features, such as app support and smart appliance functionalities (including ability to park itself), it's unbelievably effortless to assemble and set up. You simply attach the side brushes, install the cleaning agent, charge the device and connect it to the app. That's it. Connecting the Beatbot AquaSense 2 Ultra to the Beatbot app is also snag-free, and the app itself is intuitive to use and feature-rich, a testament to how well the product was programmed. As someone who had to return a brand-new robot vacuum after spending a week unsuccessfully connecting and setting it up on the app, the experience of setting this one up did a lot to heal that trauma. It has a battery life long enough to last a whole day of cleaning Before talking about battery life, I want to first say that charging the Beatbot AquaSense 2 Ultra takes a long time. During my weekend of testing, it took under three hours to go from 50% to full, which means charging it could be a whole day affair. It's worth noting that Beatbot says it should only take about four and a half hours to fully charge. Either way, it's hardly a cause for concern since you only really need to clean your pool once a week unless there are special circumstances. What's more, this cordless robotic pool cleaner can practically last an entire day's cleaning. It has several different cleaning modes, and if you choose the full cleaning option, which includes floor, wall, waterline and surface cleaning plus water clarification, the whole thing can take up to 10 hours. And that's exactly how long the Beatbot AquaSense 2 Ultra is rated for. If you're worried whether it lives up to that rating, I spent an entire Sunday watching this cordless robot pool cleaner do a full deep clean of a medium-sized pool, and trust me, its battery will likely outlast yours. The app gives you several control options The Beatbot app is thoughtfully designed for an uncomplicated user experience. It's not only easy to set up and connect to the robot pool cleaner but also free of any bugs or other issues, at least during my two days of use. Of course, that doesn't necessarily mean bugs and problems won't arise during long-term use, but I also think, considering my bad initial experiences with some robot vacuum apps, Beatbot should be given credit for designing an app that won't make you want to pull out your hair at setup. The app also provides a comprehensive level of control, from letting you select the different cleaning modes to having a remote control function for manual control. That four-way remote control button on the app is just as intuitive to use, even though it may take a bit of practice on your end if you want to perform more precise maneuvers. It's not a perfect app, and there are some missing features that I feel are crucial to the experience, such as real-time clean mapping and being able to call the robot back while it's underwater. However, these missing bits have a lot more to do with the fact that Bluetooth and radio waves simply do not work well underwater, so you can hardly blame Beatbot for excluding them. Its cleaning function is comprehensive There are robot pool cleaners that skim the water surface, and there are those that don't. The Beatbot AquaSense 2 Ultra belongs to the former, skimming your pool's water surface, ideally to rid it of all floating debris. But it goes above and beyond, as it's also a very capable wall scaler, which allows it to scrub the walls and rid the waterline of debris and scum for a full, deep, comprehensive clean. That doesn't mean you have to wait 10 hours for it to do its thing every single time, as there are several different cleaning modes to choose from based on your current need or the amount of time you have. If you do want a full cleaning that comes close to what a human can do, it offers that option for you. It takes a long time to clean a medium-sized pool It takes my aunt's pool guy about an hour every week to clean her large pool, removing floating debris, testing and adjusting water chemistry, cleaning the filter, and brushing the water line if there's algae and scum. Meanwhile, it took the Beatbot AquaSense 2 Ultra more than six hours to do a full clean of the medium-sized, irregularly shaped pool I tested it in. To be clear, this isn't exactly a fair comparison. First of all, most of the wall and floor cleaning in my aunt's pool is performed by a pool vacuum she purchased years ago, which turns on automatically for four hours each day to keep those areas pristine. That's 28 hours of cleaning time every week — almost triple the amount of time it will take for the Beatbot AquaSense 2 Ultra to do a full sweep for a similarly sized pool. Second, robot cleaners are a set-it-and-forget-it kind of appliance, so you can do other things like run errands, do some work or socialize while it's doing its thing. However, it's also fair to say that robot appliances do require some level of supervision in case they get stuck or encounter an error. Sure, the app notifies you of any errors; however, the fact that the Beatbot AquaSense 2 Ultra doesn't offer real-time reporting on what it's doing and how much progress it's made makes supervision far more crucial. My advice? Do a bit of both. Go about your day, but check in once in a while to ensure things are running swimmingly. It constantly spits out small debris Sadly, the Beatbot AquaSense 2 Ultra still has a ways to go in terms of handling small debris. The way its suctioning is designed makes it regularly spit out debris that should already be stored away in its debris canister. And while it does manage to suction about 75% of the debris floating on the surface and at the waterline, it also just pushes most of the lighter stuff around. The fact that it regurgitates and pushes feels very counterproductive, especially since its literal function is to clean. It's like having a vacuum cleaner that doesn't suck up everything, so you end up picking up certain things by hand. It also spits stuff out every time it backs up. It's really too bad. If the Beatbot AquaSense 2 Ultra had a more effective and powerful suction system, it would significantly reduce its cleaning time. Where's the debris detection? The features I was most excited to test on the Beatbot AquaSense 2 Ultra were its intelligent obstacle detection and self-extrication, which, in a perfect world, are supposed to help it navigate around obstacles and extricate itself when it somehow gets stuck. Unfortunately, in my real-world tests, it didn't do so well. I purposely left another pool cleaner's leader hose attached to the filtration system during testing to see if the Beatbot AquaSense 2 Ultra managed to avoid it. It somehow not only didn't detect it, despite its camera and sensors, but also didn't learn from its first few run-ins, even though it's supposed to be using an AI-powered camera. I expected the robot pool cleaner to at least note that point on the map so it could avoid it next time, but it just proceeded as if it hadn't encountered that obstacle before. During cleaning, it also missed a largish leaf that sat in the same spot at the bottom of the pool. It had difficulty navigating the stairs area too. I can understand not being able to clean the shallow parts properly, but not being able to back out of it to find the deeper area that's quite literally a foot away is disappointing. I'm sure that with software updates, these features will improve, but considering all the advanced features it's supposed to have, it's disappointing it doesn't have these basics already mastered. Water surface, floor, walls, waterline Water surface, floor, walls, waterline Water surface, floor, walls, waterline Dual connectivity: 5G/2.4G WiFi + Bluetooth Dual connectivity: 5G/2.4G WiFi + Bluetooth Dual connectivity: 5G/2.4G WiFi + Bluetooth Yes Yes Yes Yes Yes No 5,500 gallons per hour 5,500 gallons per hour 8,500 gallons per hour 4.0L / 3.7L (dual-filter basket) 3.7L / 3.5L (dual-filter basket) Not specified Up to 10 hours Up to 11 hours Up to 3 hours The Beatbot AquaSense 2 Ultra is a highly capable cordless robot pool cleaner that skims water surfaces, scrubs floors, scales walls and clarifies the water for a total, thorough clean. It's also effortless to set up, easy to use, long-lasting and feature-rich. If its suctioning, obstacle detection and avoidance performances were any better during testing, it would knock it out of the park as a pool-cleaning service replacement. But the unfortunate truth is that, during my testing, it regularly regurgitated chunks of the floating foliage it already sucked in, and it could not for the life of it detect and remember that there was a large obstacle in one area of the pool wall. Those get in the way of more time-efficient cleaning. The obstacle detection and avoidance might improve with software updates, but the suctioning I'm not so sure. There's also the fact that cordless robot pool cleaners cannot function without human intervention. Unlike floor robot vacuums, they can't leave their charging base on schedule and make their way to your pool on their own. You still have to do that part yourself, as well as empty the basket, rinse the appliance and put it back in the base. I mention this because that's a big factor to consider if you're hoping to purchase a robot pool cleaner to offset your monthly pool cleaning service. Is that something you can comfortably add to your already busy schedule without regretting it later? More importantly, is a $3,550 model worth it in the long run? Because that's how much the Beatbot AquaSense 2 Ultra goes for unless it's on sale. If you have lots of money to spare and some time to devote to it, this is among the best premium pool cleaners money can buy. Otherwise, there are more affordable options (even from Beatbot itself). How often should you clean a pool? How often should you clean a pool? Most pool cleaning services recommend a weekly clean, especially when the pool is regularly used or open for use. If you close a pool — say, for the winter — then weekly cleaning may not be necessary, as a pool cover can minimize the amount of dust and debris that falls in. Can you leave a robotic pool cleaner in a pool overnight? Can you leave a robotic pool cleaner in a pool overnight? It's not recommended to leave a robot pool cleaner in a pool overnight. The water and pool chemicals can degrade its parts over time, and the longer you leave it in there unnecessarily, the faster those parts will degrade. For the same reason, it's good practice to rinse out your robot pool cleaner with fresh water after every use. How long does a robotic pool cleaner last? How long does a robotic pool cleaner last? Most robot pool cleaners are rated with a lifespan of five to seven years. However, higher-end models can last up to 10 years. CNN Underscored thoroughly tests the products in our testing guides and provides full transparency about how we test them. We have a skilled team of writers and editors with many years of testing experience who ensure each article is carefully edited and products are properly vetted. We talk to top experts when relevant to make certain we are testing each product accurately, recommending only the best products and considering the pros and cons of each item. Testing writer Michelle Rae Uy has extensively tested and reviewed kitchen appliances for years, covering home and kitchen products for various publications before joining CNN Underscored. She wrote many of our top-performing product reviews, such as the best portable air conditioners, best space heaters and best humidifiers.
