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Drones and Robots are Becoming Common Food Deliverers - DTNS 5333

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This episode of Daily Tech News focuses on the rapid expansion of autonomous delivery systems for food, highlighting a major partnership between Uber and Zipline to introduce drone deliveries for Uber Eats later in 2026. Building on Zipline's existing success in delivering medical supplies and groceries for Walmart and Chipotle, this new initiative aims to complete meal deliveries within five to ten minutes, significantly faster than traditional drivers. While ground-based sidewalk robots from Serve Robotics are being deployed in dense urban areas like Alexandria, Virginia, and Los Angeles, drones are better suited for suburban and rural routes where they can cover longer distances without the congestion that slows down truck traffic. The hosts discuss how these technologies will likely complement each other, with robots handling last-mile deliveries in city centers and drones operating in more open spaces to maximize efficiency. Beyond food delivery, the show covers significant developments in data infrastructure and artificial intelligence ethics. OpenAI has signed a massive deal to build a 10-gigawatt data center in Ohio with SoftBank's SB Energy, a project that includes a natural gas plant for power generation and features Nvidia as an exclusive chip supplier with financial guarantees on the facility's value. Simultaneously, Anthropic has introduced a new text watermarking system for its Claude AI model to clarify content provenance; however, this system is designed not as a detection tool but as a signal that the text was processed by their system, meaning it does not prove the text was generated by AI and can be difficult for third parties to detect without specific keys. This approach has sparked debate regarding how such watermarks might subtly alter user-written text during processing, raising concerns among authors about maintaining their original wording. The program also features an in-depth look at a groundbreaking medical innovation combining sniffer dogs with machine learning to detect cancer from breath samples. A startup called Dognosis is training beagles, Labradors, and Dutch Shepherds to identify volatile organic compounds associated with over 20 types of cancer, while sensors track the dogs' movements, brain activity, and breathing patterns to create a robust diagnostic output. Early trials have shown a 90% sensitivity for early-stage cancers, leading to large-scale phase three trials involving thousands of participants. The hosts express excitement about this technology, noting that it treats the dogs as collaborators rather than just tools, and emphasizes how machine learning can enhance human capabilities by analyzing vast amounts of behavioral data that would be impossible for humans to process manually. In lighter news, the episode touches on various industry updates including Stripe acquiring OpenRouter, Apple adjusting its app tracking transparency rules in Europe, and LG partnering with Nvidia for humanoid robots. The Wall Street Journal reports that Sony has not yet set a release date for the PlayStation 6, potentially waiting until component costs stabilize, while financial analysis suggests that many new data centers are relying on natural gas rather than renewable energy sources. The show concludes with a listener insight about Pringles using supercomputers to optimize their chip shape decades ago, reminding listeners that technology has long been used to solve everyday problems, from snack food manufacturing to fighting cancer and delivering meals efficiently.
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[music] This is the daily tech news for Monday, August 17th, 2026. We tell you what you need to know, give you some important context, and help each other understand. >> Today, Dr. Nikki follows up on the combo of AI and dogs to fight cancer. And drones and robots expand your food delivery options. >> AI dogs and robots, what's not to love? I'm Tom Merritt. >> And I'm Rob Dunwood. Let's start with what you need to know with that big story. So, yeah, Uber is partnering with Zipline. Uh you may recall, longtime listeners of DTNS may recall that Zipline uh kind of made its name delivering medical supplies in Rwanda. Uh they have operations throughout the world now, uh including in the United States. So, Uber is going to partner with Zipline to begin drone delivery of meals for Uber Eats this year. If you were worried that Zipline was going to do a drone delivery of people, it's Uber Eatats. It's Uber Eats going to be delivering food. Uh the partnership will start in Zipline's existing US markets. That includes Pidge, Arkansas, and Dallas Fort Worth later this year, uh before expanding to a few dozen more cities. Zipline currently delivers for Walmart. That's probably why Pidge Arkansas is on there. Uh and also for Chipotle, uh in the US. So, they're adding Uber Eatats to the roster. Uber says it hopes deliveries should be able to be completed in 5 to 10 minutes. Now, I assume that's 5 to 10 minutes from the time the meal is completed. Uh but but still much faster than the 15 minutes maybe the driver would take to get there. Uber says it has a goal of reaching 1 million drone deliveries a day by the end of 2029. Much more ambitious than what we've seen with others. Uber has also previously partnered with Fly Trex. Still has a partnership with Fly Trex. Fly also working with Walmart. Uh so Walmart uh on the forefront of this. Door Dash and Wing recently partnered and expanded their delivery service to include the Atlanta metro area. And meanwhile on the ground, former Uber company Serve Robotics has signed up GrubHub to use its Sidewalk Robots to deliver food in Alexandria, Virginia, Chicago, and Los Angeles. Serve Robotics already delivers for Uber Eats as well as Door Dash. Uh Rob, we are we are getting to the point where these are in the thousands, you know, and Uber wants to make it millions uh a day, adding a few more uh delivery areas here and there. I I see these robots around Los Angeles. How about you? >> Um so where I'm at in the Midwest, we don't see them that regularly, but when I visited large cities that have them, um I'm kind of like, oh, that that's why these will work. these areas that are very very densely populated, particularly for the robots that are on ground that are delivering stuff. I can see it because it's like somebody's got to walk or ride a bike to do the delivery. A robot could just as effectively do that, maybe in some cases more effectively do it. So, um I think that this is just going to be the way of the future. And then we go back to the the drones actually flying through the air to deliver you stuff. the the the LA it's not even really the last miles like that last you know 1500 feet that last you know 2500 feet or however far they've got to go from their base station is where all the time takes with delivery models I remember being at a swim party in a very very large uh complex and there's just multiple UPS trucks uh multiple Amazon delivery trucks there's just multiple trucks just driving through the neighborhood for for literally hours at a time and it's just because they gota you this was on this truck, that was on that truck. But if they could have that stuff all delivered individually via a groundbased robot or a drone, it would save them a lot of time, a lot of manpower, uh, as far as these things, you know, you know, being done by things that are not manpowered. They're, you know, powered by batteries and they fly through the arrow roll on the ground. >> Yeah. Uh, this is a low margin business uh because it only works if it reduces the cost for the clients, but it is reducing the cost of these deliveries. It's speeding them up. You know, Uber Eats saying it wants to do five to 10 minutes uh from the time that pizza's cooked or that burrito is made. Uh and they're complimentary. I actually didn't think about this till you were talking right now. Yeah. You see the sidewalk robots in denser areas. In fact, I don't even have them yet in my area of Los Angeles. They're more in the in the more dense parts uh of Los Angeles. But the tag on the drones has been uh well these only work in the more open areas in the in in like rural areas where where you need to fly farther than a sidewalk robot could could materially speed up and make a delivery. So I think if you got drones on the edges, you know, your suburban and rural areas and you got sidewalk robots in the dense city centers, suddenly you you've got some decent coverage going on. >> Yeah. And the uh the the thing with the the the groundbased delivery robots from Serve looks like they're just trying to be it doesn't matter if it's Uber Eats. It doesn't matter if it's whomever whoever has stuff that wants to be delivered. We're your company. It looks like that's kind of where they're building out. They they want to be the company that you go to when you've got stuff that needs to be delivered on the ground via a robot. That's just it seems like they're setting up their infrastructure to be that kind of player. >> Yeah. Sidewalk Robots as a service or SOS I will say. I'll just coin that. [laughter] >> Uh well, yeah, I I I think uh I think we're still I'm very curious if they can get to a million deliveries a day uh by 2029, but you know, we might be a couple years out from this being common in major cities, maybe even in Columbus. You know, like you're you're big enough that that this should come there. >> Yeah, I'd love to see them here. Um but it it it'll depend on uh how far out in the suburbs they get. I can see it downtown. Maybe it'll get here to the suburbs in sometime. >> I mean, it's not even in the suburbs here [laughter] in LA either. >> DTNS is made possible by you, the listener, thanks to Dale McKay, Matt Zaglin, Jeff Wilks, and Todd Cero. >> Yeah. And we got a couple of new uh patrons, Chris and Charles, as well as a raise from a different Chris. Uh, love all the Chris's uh this week and the Charles's. And uh returning patron surfer no vowels. SRFR. Welcome back, Surfer. Good to have you. There's more we need to know today. Let's get to the briefs. Open AAI signed a 10 gawatt data center deal in Pike County in southern Ohio with Soft Bank's SB Energy, which could become one of the largest AI hubs. The US government will build a natural gas plant at the site to sell energy to the data center. The center will be closed looped and air cooled. Nvidia is providing a guarantee on the buildings in exchange for becoming the exclusive chip supplier is also buying a stake in SB Energy. Nvidia will only have to pay for the buildings if no one ever leases the data center and the building is sold. Even then would only have to pay the difference between the sale price and it guaranteed amount. >> And there's even a clause in there that says if they end up having to pay something, Open AAI will pay them back. they'll indemnify them, which I'm like, well, if OpenAI is so insolvent that they can't do this lease, uh, I don't imagine you're going to get your money, Nvidia. But, uh, yeah, this is a much safer way to do it to say like, hey, we we'll back the we'll make sure it's it's basically like a bridge loan. We'll make sure that it's worth building this building because once it gets built, it's probably going to be worth 1.5 billion, which is what Nvidia is guaranteeing here. Plus, Nvidia also gets to sell uh, a bunch of chips here. I think the more important thing is closed loop and air cooled. That is very good, especially at a data center this size. I think it's going to be 4.25 gigawatty gigawatts off the bat, but with a goal of eventually building out 10 gawatt capacity. So, you want that to not be using your water and it won't. However, I don't like natural gas uh as the energy uh which is becoming more common for these things. >> Yeah. It's like they're, you know, they're trying to make them as clean energy as they can, but if you're using natural gas, if you're using, you know, if you're using anything other than wind electricity, they're not they're not completely clean. So, it would be nice if they could get to that point, but uh this is a big data center and from Nvidia standpoint, it's like, you know what, we'll back them. We're going to make the money back. This is almost like being like a land man or something. I've been watching Land Man lately. just watching how it's like so we really don't we we never lose we never lose the buddies like we'll buy the stuff if it doesn't work out we'll just sell it to somebody else uh and that's kind of what they're doing here like we'll cover it if it doesn't work out it'll get sold it'll probably get sold for more than we than we need to cover it for so so we're good at the end >> yeah they're literally LAN man because it you know data center is just a big local area network right [laughter] >> uh yeah no I I think that's it's smart on Nvidia Uh it certainly is causing a lot of nashing of teeth, the amount of debt these companies are going in to build this stuff. Uh but I think that nashing of teeth is mostly around the people investing in the companies building it because the buildings themselves will be used for something. I I I feel pretty confident about that. Uh and Nvidia feels pretty confident about that. Anthropic has published a layman's explanation of its text watermarking uh which makes it clear what's going on. It's something that I was hoping they would do and I'm glad they did it. Anthropic makes the point in their explanation that the watermark provides a signal that the content was processed by Claude. It does not prove that the text was generated by Claude and should not be used to detect LLM generated text. This is a concern I saw a lot in our chats and emails and such. Uh, Anthropic is saying if you put your own handwritten text through here for for for processing to like bold stuff, this watermark will not show that you didn't write it. Likewise, if there's no detectable watermark, that doesn't mean that the text was not generated. Uh, there are ways to get rid of this watermark, but it's fairly durable. Dclaude uh.org or wrote a very good explanation about how the text watermarking works, including some fun sliders that'll let you see how editing the text will affect the watermark. Basically, a full rewrite will get rid of the watermark. But the key to the watermarking is that it is tilting the probability of word choice. Uh it's basically looking at each word that's about to be detected and it then creates a list of green and red words. Uh, the red words are less likely to be picked. The green words are more likely. Red words can still be picked. So, it's not determinative. It's not going to fully change the text. And it's a different list every time. So, if you are the keyholder, you'll be able to look and see how that text was generated and whether the watermark is there. But teachers and independent detectors will not be able to use this to detect AI composition unless they have the key. And Enthropic says we're the only ones that will have the key. So we will run a watermark detection tool for people to use. Uh but without the key, this is not something you can easily just look at the text or even scan the text and figure out what the watermark is because it's not always the same word choice that's being tilted. Uh, and they they re-emphasize a watermark is not an AI detector. It means the text was processed by Claude, not written by Claude. Uh, but Rob, I'm a little disappointed with this because it works kind of the way Synth IDU does for Google, which has the chance of changing your writing even if you tell it not to because it's using the watermark. >> There's that. And you actually explained this. You you're pretty dead on last week. You know, you had you had a good idea of how this is going to work. The interesting thing to me is that because this is not an indication that it was AI. It's just this is an indication that we may have or may not have actually done something to your code as it comes through us. That is that is kind of interesting. So I'm just thinking it's like so did so is this AI? It could be could not be. Uh did you guys modify it? Maybe maybe we didn't. It's like you know who knows except for anthropic. So it's kind of funny to me in that sense. >> But uh it is interesting. They're saying that it won't be easily detectable. I wonder how easily detectable it will be. I because I hear people saying challenge accepted. I will try to figure out we will try to figure out how this works. So >> and synth ID by by Google is a good test case of that. Uh which it has proved not to be that easily detected. >> Not easy at all. Not easy at [clears throat] all. So, um, so students who were going to use AI to write the term paper, they have they have let their shoulders down and they've taken a side that they're not going to get caught by the teacher. You still shouldn't be doing it, though. Students, you still shouldn't be doing it. >> There are other ways to detect it uh that they could fall subject to. Anthropic's just saying don't use this. There are other tools to do it. Don't use ours uh to do it. that and and our watermarking is not going to make it easier for those third parties necessarily because it is if if you look into the explanations it is really interesting how it is a it is a very difficult pattern that it's putting in there that that wouldn't be obvious to detect. Um and like you like I said there were two ways to doing it. I was hoping it would be in invisible characters because yes those are easier to strip but it won't uh affect my actual text. Uh and it sounds like it won't. On the other hand, if you're a coder and you're like, "Wait, is it going to change my code?" No. Uh, it actually is not very robust when it's generating code at watermarking because it has restrictions of like we don't want to change code. It's also not very good at at at short versions of text. The longer the text you're putting in, the better of a chance you have to get a good watermark out of it. >> Yeah. and and you kind of alluded to this earlier, but as an author, you can't be terribly happy about this because if you're using it to not write your content, but just let's go in here and clean up some stuff. We're going to have, you know, hanging part of the, you know, help me do what AI is good at doing. It now maybe changes what you've written. So, you've got to there there's got to be a way for you to actually stop that. It's like, no, I want the what I've written to be what I've written. I don't want any words changed regardless of what you're doing on the back end to help me correct it. So, I hope that there's going to be like an undo button or something that they have for for folks like yourself that are authors that are writing that do they want the absolute words that they've written down on the paper to be the words that come out for somebody to see. >> Well, like the writing we do for Daily Tech News Show as well, not just for my books, right? Like I I don't need to change up what I wrote. I pick these words very carefully. Uh so yeah, I G Gruber at Daring Fireball was was going off about this. He's very upset that this is what Enthropic is doing. uh he's very upset that this is how Google does it as well. I have not in using these tools to do like formatting and bolding and and fixing commas and stuff found that they end up changing the text all that often. So I think it may be a little bit of an overreaction. Uh but the the possibility is there and I don't like it either. I'm with them that far. Well folks uh we do live streams on YouTube. Uh if you want to watch us on Thursdays, we record DTNS live. You can catch that live. Uh and we do live streams of reading your emails and and doing office hours. We have a tech tournament. Uh that it's the tech tournament of storage devices that is coming up. Uh you can catch all those by becoming a subscriber at youtube.com/daily tech news show. Let's check out some quick headlines that are going to make you look smart because you know these. Payment company Stripe has agreed to buy Open Router, a company that routes request across more than 400 large language models. Open router has called itself Stripe for AI. I probably would have called it Zapier for AI, but since they own Stripe or Stripe owns them now, I guess it makes sense, >> I guess. Yeah, it Zepier also works, but this is more about the like you only have to pay once, you know, makes it easy easy to pay and then you choose the model. Uh, and Stripe was must have liked that they called it that because they bought the company. Apple has agreed to change its app tracking transparency system. That's the one that says like, "Hey, this company would like to have your data. Would you like to give it to them?" Uh, they are changing it to meet requirements from regulators in Germany. Apple requests for your content to provide data to third parties will now, at least in Germany and the United and the European Union, remove possibly discouraging symbols and warnings, make prompts neutral in content wording and layout, and allow third parties to explain why they are requesting access to your personal data. Uh, the idea is to bring these more in line with the third party data disclosures that Apple does for its own apps. Germany is saying you are favoring your own apps by not by having stricter rules on this for third parties. LG signed an agreement with Nvidia to use Nvidia's Jetson Thor processor Isaac Groot Foundation model and Halo safety system in bipedal humanoid robots to arrive in Q1. >> I bet we get to meet that at CES, don't you? >> I cannot wait. Bite Dance and the Motion Picture Association have signed an agreement to strengthen copyright safeguards on Bite Dance's video and image generation models, which means Bite Dance uh can now uh sell their stuff to to Hollywood companies, which they probably weren't going to be able to do without this. >> Alibaba launched a beta version of a music generation model that can create a complete song from a line of text. The model is called Happy Shrimp 1.0 and >> line of storevalds. [laughter] Line of storevalds announced Yeah. Yeah. Uh the release of Linux kernel version 7.2 complaining about the new normal of generated code adding more volume to a release than he would prefer in the final week. Uh he was like there were this was a bigger final week than I would like but that's the new normal because everybody's generating so much code. Uh the new kernel will support the Zename level controller big esports thing. uh handles caches across many core chips and makes it possible to run Linux on an Apple M3. >> The Wall Street Journal reports that Sony CEO says that the company has not fixed a date for the release of the Sony PlayStation 6. And my gut tells me they don't want to release a date until they absolutely have to in hopes that the prices will come down. I thought the digital trends article and this was really interesting because uh yes the price of the components keeps going up and they want to figure that out but also they pointed out that all these AI tools that are driving up the price of the components are also being used by Sony's developers to make the PlayStation 6 better. And so they may be like, "Well, while we wait to figure out the price of the components, maybe we can actually have a better PlayStation 6, you know, if we if we give these developers a few more few more minutes to work on >> better and less expensive." Yay for both. >> I I would like that. Uh the Financial Times analyzed power commitments for 60 of the largest planned data centers in the US and found about 75% of them are building natural gas facilities. So it's not just the OpenAI one. Uh the rest are from renewable sources or from nuclear facilities. Uh if they are all built with the current power sources, when fully operational, this would contribute 7% of the US power sector's carbon dioxide emissions. Reviews for the new HP Omnibook X laptop are out with praise for the keyboard, trackpad, and OLED screen. The HP Omnibook X starts at $1,400, but is currently on sale at a discount. >> All right, those are the essentials for today. Let's dive a little deeper. >> An Indian startup called Diagnosis is looking to combine sniffer dogs with machine learning to detect cancer from a single breath. So, we had to get Dr. Nikki to look into it for us. >> Yeah. Last Friday, Jason and Jen talked about the company that is combining machine learning and dogs to try to help detect and perhaps treat cancer. Uh so, of course, we had to get Dr. Nikki to look into this. Thank you, Dr. Nikki, for joining us. And here I am excited to smell I don't know [laughter] >> sniff out the truth. >> Sniff out the truth on this story. Thank you. >> Yes. So, okay, let's get right to it. How do they plan on doing this? >> Okay. I saw this headline and I was like, I don't know, Tom. This seems pretty far-fetched. [laughter] >> Throw me a bone and explain it to her. >> It's actually really cool. So, how it works, the patient breathes into like a cotton mask. They then ship this mask off to the Dognosis facility, uh, which is the name of the company, is not another bad pun. And they have trained beagles, Labradors, and Dutch shepherds that sniff this sample. Pretty straightforward so far. Um, and here's where the quote unquote artificial intelligence comes in. It's more machine learning, but as the dogs are sniffing, there's multiple sensors in this little uh workstation that they have that collect data on video tracking of the dog's movement, their breathing frequency, their body language, and their brain activity. And they combine all of this into kind of translatable, robust data that will give you a yes or a no on the diagnosis. And the founder says that this method targets over 20 types of cancer, including breast, lung, oral, and cervical. and it looks like it has a promising future. So, I'm actually really excited about this. >> That is crazy. I mean, I've actually heard about dogs ability to to smell indicators of cancer. Two things about this uh intrigued me, which is why I brought it to your attention. One was, of course, the machine learning aspect of it, but also I'm glad you explained this to me. I was imagining when they said people breathed into a mask that like the mask was a little balloon of their breath. It just leaves the compounds on the mask. So that >> I honestly thought they like breathe into the dog. [laughter] >> Hey buddy, how are you doing? Uh, all right. So, let's let's let's go further back, though. How does how does your breath contain anything the dog can smell to indicate that it's cancer? How does that work? >> Yeah. Um, so diseases like cancer, and this works for other diseases. I think they're just focusing on cancer, but they can cause subtle changes in your body's physiology, which then causes the volatile organic compounds or VOCC's that your body emits to change. So, your smell will change. Whether humans can detect it, probably not. But dogs have a really, really strong sense of smell, as we know, and it's powerful enough to notice these subtle changes. And you can specifically train dogs who are good at this to detect specific VOCC odor profiles, including 20 different kinds of cancer. >> Wow. And and I know uh there are other diseases that are detectable. I think I remember something about even COVID uh being detectable by smell and some >> Yeah, apparently there's about 40 kinds of diseases that you can train dogs for. >> All right, so let's talk about how do they get the dogs [laughter] to do this? How do they measure the dogs? I guess that's the really interesting thing for me is like well sure you could train the dog to smell and then you look at the dog and you say is it acting like it smelled it or not but this is making it more precise I guess. >> Yeah this is really cool and actually I was telling you earlier that I'm really excited that maybe I'll integrate this into my research because we do something similar. So first of all I'm in awe of their system like I'm nerding out as a scientist like I don't know what kind of money they got but or if they're just really smart but it looks really cool. So each dog has a little workstation with like a little bowl with its sample of the the cloth mask in it. Um each workstation has synchronized video and infrared sensors. So when the dog gets in, it triggers kind of a synchronization. This is all synced up with a Raspberry Pi, which again like the stuff you tinker with at home, scientists are also tinkering with. >> Um and then each dog has a really cute uh little sensor suit and a hat. [laughter] So he looks like a super dog. >> Electro uh an EEG cap, so like to measure brain waves mounted on a custom 3D printed hat on its head and also a chest harness that has an accelerometer and a gyroscope. So basically just detecting motion. Um and they use QR scanners to detect each dog. So it basically it'll scan in like this is Phto. Phto gets licked into this gate and then there's a timer of how long they're allowed to do this and then they get rewarded with a treat. Um, and I thought this is really cool. And they explained, so they really look at the dogs as collaborators. And I was wondering like why do you have an EEG and a harness with an accelerometer and all these like video detection? Not only obviously you want multiple kinds of data, but they said each dog detects in a different way. So one of them might sit down and that's where the gyroscope would come in and another might just like breathe really fastly. So they're measuring um different kinds for different dogs. And basically and they call it the sniff anal sniff analytics. [laughter] sniff analysis. Um, how they parse the data and line it up and it's actually really well done. I'm not going to go into the the specifics the sniff specifics. >> The sniff. [laughter] Yeah, the specific. >> It's very cool how they um basically they'll take all this data and they'll say, you know, if you get this specific set of combinations, that's a yes from this dog. And if the sample they train them on, you know, they know which ones have cancer initially as a training sample. That's how they figure that out. So like a lot of machine learning, it's speeding up and making more accurate what a human could do, right? You you could have a really good dog trainer understand the body language of the dog and figure out their behavior. U but >> it's really trained from humans initially as well. >> Yeah. Yeah. Yeah. >> 100%. I think from what I understand the most of the machine learning is coming from the behavioral analysis, but it looks like it's also used to like sync up all the data and make outputs. But it is it looks like it's very much just trained on humans and then like do it times >> and that that was the part that I wasn't sure about when when I first sent this to you. I'm like Dr. Nikki is going to tell me like you don't need the AI [laughter] to do this. You could just look at the dog. And so it's interesting that you looked at it like no it looks like this is actually a valuable addition to >> and I have this from like experience because we we've talked about on the show but I do video analysis for behavior analysis for my goats and we have like 6,000 hours of video and there's only so many that my undergrads can count. Like I actually really want machine learning to do a good job at this because this human hours that we could be doing something else. So >> yeah that's a great idea. I emphasize with this a lot. >> All right. So how do we know this works? We know that there's research that shows that the dogs can smell this and that there's actually compounds, but how do we know this particular system is actually working? >> So, even more proof, if you weren't convinced, um they have published their phase 2 trials in the journal of clinical oncology, and they report a 90% sensitivity for early stage cancer, which is even more impressive because you would assume there's less um you know, volatile compounds in an early stage. And this was done on about over a thousand participants. And so since they've published that, they started phase three trials. So this is the largest largest scale uh in April enrolling over 10,000 people. And the the company is now targeting a million tests a year with just 30 dogs. So those dogs are like pumping those tests out. Um, and they have plans for US facility in 2027 or 2028 pending regulatory hurdles because you have a combination of animal ethics here and FDAish stuff where you don't know if diagnosis sits really in FDA or not, but it they're confident. >> Yeah. And I was reading that uh in India there's less of a burden for detection style diagnosis like this versus the United States where you do have to get approved for that. Uh so another reason that they're rolling this out in India and from what you can tell the dogs are happy with this like >> yeah so they have a very big emphasis on like these dogs are really well treated they you know they adopt them and then they train them and um I would treat them really well too if they were pumping out you know a million uh diagnosis they I would assume that they're at least from the pictures and like from the setup uh and from what they say on their website they're and even in the publication they emphasize like we see the dogs as collaborators they go willing ly to do this training. We don't force them, you know, and you know how dogs are. If they have a job, usually they like doing it. >> So, as far as I can tell, it looks actually really smart >> and I'm really inspired by this and I might integrate it into my own work. >> That's amazing that this might actually end up uh helping your your actual scientific work. >> Have to put DTNS in the acknowledgements or something. [laughter] >> You don't have to do that. >> I always do anyway. But uh yeah, I uh while this study gave me pause, it seems like it's a uh a fur way down the line, you know. Uh so thank you for telling us the tale. >> Yeah, I'm glad we sniffed out the truth here. >> Indeed. [laughter] Uh Dr. Nikki, if people want to find more of what you do, where should they go? >> I am over at nicoleman's.com. Same handle on blue sky. And if you want more fun science and tech, you can check out my new show with Wu Dao in the DTNS family podcast. It is technical tea. Our new episode is going to be about eponym. So next month, come check that out. >> Fantastic. Thanks, Dr. Dicki. >> Thank you. >> I like this. It's got cute dogs. It's going to help fight cancer. What's not to love? >> Um you there have been studies and there have been, you know, dogs that sniff cancer out. people who had no idea that they had it. This has been happening for decades now. >> So if we can use a little AI, if we can use, you know, um if we can use robots to actually improve it, that is a good thing. This is this is where I where I see AI and robots being good for humanity to figure out things. Cancer is such a scourge, you know, you know, on health for Earth. If you can do something to help people get better diagnoses earlier, I'm all for it. >> And 100%. Folks, we end every episode of DTS with some shared perspectives. Today, Jeff in Knoxville, Tennessee, has added context to the story about Pringles using a digital twin to perfect its chip stacking. Yeah, a lot of people like that uh story even though it was real quick. Uh Jeff wrote, "Last week you covered the recent story about the makers of Pringles creating a digital twin of their factory to optimize their production. I felt compelled to point out that Pringles has a long history of using technology like this. The shape of Pringles was optimized on a Cray supercomput, a Cray 1, if my memory serves me, to give them a more aerodynamic shape and prevent them from literally flying off the production line at high speeds. Back when I worked for Cray, this was my favorite story. Whenever someone asked me what sorts of important worldchanging problems are being solved by supercomputers, I'd imagine that you're hardressed to find a more techn technologically forward snack food than Pringles. I like Pringles. This makes me proud to uh to like a stackable chip. >> This is cool. We used a Cray supercomput to figure out how to make Pringles better. Can Can we legally call Pringles chips? I There's debates on that. I don't I don't know. >> I mean, then you got to start to get into the whole English thing about crisps and chips and, you know, you go down a rabbit hole. [laughter] >> But this this is it's it's pretty cool, though. I mean, we're using it to solve problems that we really have. These chips are different. They're light. They fly off the machine. We need to figure out how to make them stick. >> Yeah. No, I love it. >> Well, folks, we love to know what you're thinking about. So, if you've got insights into a story, please, please, please share it with us at feedback at Dailytechnewshow.com. Yeah. Big thanks to Jeff for contributing to today's show. Thank you for being along for Daily Tech News Show. You're the folks that keep us in business. Uh, if you want to directly support the show and get no ads, become a patron. You can do it easy. patreon.com/dtns. [music] The DTNS family [music] of podcasts, helping each other understand. >> Diamond Club hopes you have enjoyed this broker. 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