Drones and Robots are Becoming Common Food Deliverers - DTNS 5333
Watch on YouTubeVideo summary
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.
Read the full video transcript
[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. [laughter]