2024 Recap & 2nd Annual Saucies!

In this episode, we recap our favorite episodes from 2024!

This podcast is sponsored by Mouser Electronics. 

Episode Notes

(04:44) - 163. Creating 3D Objects With AI

(07:40) - 168. Neuroprosthetics: The Next Step Towards Limb Reconstruction

(10:37) - 164. Dyson’s Automated, Self-sustaining Strawberry Farm

(13:40) - 177. Did A Shrimp Fry This Rice? No, A Robot Did

(16:47) - 172. Don’t Throw Away Coffee Grounds; They Could Solve The World’s Water Crisis!

(19:49) - 191. From Prevention to Recovery: AI in Disaster Management

(22:29) - 181. Why Audi Uses 3D Printers For The R8

(25:35) - 199. Will AI Assistants Make Your Doctor Better?

(28:32) - 189. Stanford & Toyota Drift Cars With AI

(31:50) - 173. Get 3 Days of Your Life Back Every Year with Smart Stoplights

(33:44) - 192. Karsten Roscher & The Need For Safe AI (Interview)

This episode was brought to you by Mouser, our favorite place to get electronics parts for any project, whether it be a hobby at home or a prototype for work. Click HERE to learn more about the speed-bumps of AI a la data!

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Transcript

Folks, welcome back to the NextByte, Happy 2025. Before we kick off the new year, we wanna wrap up what we did last year. So, you know what that means, right? Welcome to the Saucies for 2024.

What's up friends, this is the NextByte podcast where one gentleman and one scholar explore the secret sauce behind cool tech and make it easy to understand.

Farbod: All right, folks, welcome back to the NextByte Podcast and happy 2025. I can't believe the year just went by. It's been what? Four years now that we've been doing this.

Daniel: Yeah. Craziness.

Farbod: I still, I still remember when we were sitting down and coming up with the idea of doing this podcast and again, can't believe it's been four years, but with that out of the way, the little trip down memory lane, let's take a little glance at what 2024 held with the Saucies. This is the second annual Saucies. And if you're new to it, we always talk about the secret sauce. So, in the Saucies, we like to look back and give the sauce awards to some of the episodes that stood out to us. But before we do that today, let's talk about today's sponsor. And that's Mouser Electronics. Folks, if you've been rocking with us, you know we love Mouser because Mouser is pretty aligned with our mission. And that mission is to bring interesting tech in an easy to digest manner to the average folk. And they do this by creating these technical resources. They are one of the world's biggest electronic suppliers and with that, they have a lot of great relationships with academia and industry, and occasionally they write about the things that are going on at that level.

Daniel: They sure do.

Farbod: One of the things that I think is at the top of everyone's mind and has been on top of people's minds for the past year is AI. All the breakthroughs with chat GPT, image generation, data privacy, et cetera, et cetera. And with all the craze going on, Mouser wrote this really nice piece that we're gonna link in the show notes about the currency of AI. Specifically, they just wanna focus on data and its importance and what the future of AI holds if we can't get good data. You know, spoiler, bad data in, bad AI out. So, they dig a little bit deeper into that. They kind of, if you've been paying attention to the old CTO of OpenAI talking about how the hardware is advancing, but the data is finite because the internet is finite, they harp on that a little bit. So, if this is something that's interesting to you, even remotely, definitely make sure you check it out.

Daniel: And it's a primer in understanding what the bottlenecks are for the future of AI, which is interesting to us, and we hope it's interesting to you.

Farbod: If it's gonna be a technology that we're gonna use on a daily basis, might as well have some idea about what's going on and what the future of it holds.

Daniel: Exactly.

Farbod: With that said, let's get into the sassies. Dan, do you wanna go first or am I doing the first one?

Daniel: Well, let me give a little prelude first. Okay. And then I would like you to kick it off, that's okay.

Farbod: Yeah.

Daniel: Like Farbod mentioned, right, the most, I think some of our most impactful work came in 2024 because the most impactful technology came in 2024. So, our Saucy Awards, I don't know why it took us three years to come up with the Saucy Awards, but our annual Saucy Awards, second annual Saucy Awards, that is, award the topics that we discussed last year that we think brought the most spice to the secret sauce, so to speak. We are always looking for the best secret sauce behind technology, trying to explore it, trying to explain it in a way that everyone can understand. We are trying to share some of our favorites from the last year. Doesn't cover everything, but it certainly covers a lot of the ones that we thought were most memorable, ones that we thought were most impactful. And if you want to check them out, we're going to link every single one of these episodes in the show notes. So, this is an awesome opportunity for you to kind of get an understanding if you're new to the show or if you are catching up. What did we cover in the last 365 days? What are the highlights that you should go hit as a primer before we get back into talking about 2025 and new tech and making sure that everyone's primed to understand what's going on in the real world?

Farbod: Absolutely. And with that, let's kick it off with the first category, because this time around, we're gonna try our hand at the category on the awards side. I feel like all the good awards have categories, right? So, the first one is potential. A lot of times we talk about fascinating technologies, and Daniel says this a lot, but it's awesome when you can focus on something that has a potential application in the real world, and it's not just locked up somewhere. It might not be mature yet, it's taking the first baby steps, but it has the potential. The award for that will go to “anything.xyz”. This is episode 163 where you could create pretty much any object with AI. It was a two-part system. The first part was chat GPT, essentially. You have an LLM that would take whatever input you gave, like, I don't know, a spoon where the base is Pikachu. And then it would feed it into code that was hooked up to some sort of CAD system, let's say like Fusion360 or whatever, that used code to generate that object. So, it was really fun. Daniel and I had a chance to play around with it. We gave feedback in this episode on what was good, what was bad, some of the ideas that we had about it being used in industry versus like personal projects. And eventually we actually got to touch base with the founder as well. So that was a nice little trivia there on what the next…

Daniel: That’s what I going to say, we use this as an opportunity to connect with Raymond, Raymond Whitecamp, who's the founder. We have to have Raymond on the show. It's something that I think we've been talking about for a little while. So, Raymond, if you're listening, even if you're not, I'm going to send you a link to this. If you're listening, this is our call to action. We want to get you on the show. Talk about anything or talk about some of the other interesting stuff that you're working on.

Farbod: Literally anything.

Daniel: One other thing I want to mention, ha ha, anything. One other interesting thing I wanted to mention for about, how active are you on Twitter or X these days. I don't know if you saw, there was like some big beef over the last two days talking about CAD and AI and like is new AI enabled CAD software actually gonna move the needle for people who are professionals and use it in their day to day lives? And there's a lot of arguments going on. I think that it would be an awesome opportunity to bring Raymond on and kind of get his take because not only is he working at the forefront of AI with anything.xyz, that's kind of like a side, side project, a side hustle for him. In his day job, he's been working on materials for 3D printing. So, like he also understands like from a fundamental perspective, what do professionals need with 3D designing and 3D manufacturing? I think he would have a really unique perspective. So, Raymond, again, hope you're listening. We're using this as an opportunity, revisiting what we talked about last year to try and bring you on the show this year.

Farbod: Yeah, this is our bat signal. So, be on the lookout.

Daniel: Exactly. Love this. I'm gonna give my first award, which is for the best biohacking. And we talk a lot about biohacking. It's kind of like a, a buzzy term. And in some ways, I don't think that anything truly is biohacking or very few things actually are truly biohacking. A lot of times people say like, oh, I found out this biohack. Like if you wake up and look at the sunrise, then it helps you wake up earlier the next day. I'm like, that's not really hacking. Like you're just using the systems that already exist in your body and you've just figured out how the body works. So, you're not, you're not hacking, but true hacking which I feel like we did cover for one of the first times last year was an episode 168, which was neuroprosthetics from ETH Zurich. And what they did is they found a way to use a robotic foot essentially, and mimicked natural nervous signals to pump signals back through the nervous system into the brain using state of the art neuroprosthetics and essentially allowed the person who had had an amputated foot, and then they had a prosthetic foot put on, a robotic prosthetic foot, allowed their brain to feel sensation and to feel movement of this limb, even though it was a robot, not a human limb. So, I think this is one of the rare examples of real biohacking, definitely something super interesting and was memorable to me when we were looking back over all the episodes that we published in the last year, definitely something that is worth checking out.

Farbod: Dude, I totally agree. And I remember at first when I was reading it, I didn't really understand what the impact of this could be, getting some level of feeling back. But if I remember correctly, the natural gait pattern that was a consequence of this achievement allowed people to walk more effectively. They were more, like, less prone to falling, I think. And they could be more independent in comparison to, like, the other methods of traversing with older, more traditional prosthetic. So super impactful and that's a really really good pick.

Daniel: Yeah, they just to close the loop on that because I had the article open in another chat. Not only were the test subjects able to climb steps faster they also made fewer mistakes in tasks that require them to climb the same steps while spelling words backwards. Biomimetics neurostimulation allows subjects to concentrate on other things while walking right so instead of having a limb that you feel like you have to focus all of your effort on it, um, to make sure that you're controlling it. In this case, it felt as though that prosthetic limb was a part of the body and could subconsciously be controlled, allowing them to work on conscious other subjects such as spelling words backwards. So, super interesting to how they measured like not only success of the limb, but then also are you deloading the brain by using this biohacking of the nervous system and they, they determined that they were able to do that, which is pretty awesome.

Farbod: Yeah. Yeah. Great pick. And I will now segue into my next pick, which, how do I phrase this? I call it the intersection award. I feel like both you and I love the episodes where it's not just mechanical, it's not just aerospace, it's not just AI, it's some combination of at least two, ideally more. So, this one really stood out to me, and it's episode 164, which was about Dyson and the self-sustaining strawberry farm. This was completely out of left field for me. Dyson makes vacuum cleaners, Dyson makes hairdryers, Dyson strawberries or farms were not on my bingo card for 2024, but that's the beauty of doing what we do, right? You uncover some really cool stuff. And what was going on with this farm is they wanted to produce the best possible strawberries. Which they did by having a fully automated strawberry greenhouse that has robots checking in. Instead of using pesticides, they had these robots that could use lasers to zap out any insects or pests or whatever. And it would analyze the color and the shape of the strawberry to pick them at their perfect ripe time. On top of that, though, this piece of land that they acquired in the United Kingdom, they had a whole facility for creating compost and manure. And that was what was sustaining their farm. And then from the excess of that, they were able to generate gases that were then cleanly burned to generate electricity for like an entire town. And Dyson was using this operation to kind of showcase what the future of farming could be like. So, it was cool on multiple fronts for me. You know, you have, you and I are food enthusiasts. We love the idea of getting perfect produce anywhere in the world, which is cool. Then you have the engineering aspect, which is you created a fully automated system pretty much. Like of course there's still humans involved, but thinking about how, I know that topic of automation is a hot one, but getting humans out of the loop on things that might be monotonous and take a toll on you physically and having robots take over that and humans’ kind of manage the process, that's really exciting. And then the last bit is a sustainable net energy positive and net carbon negative process, which could be great for the overall health of our planet.

Daniel: And not only that, right? They were able to extend the growing season of strawberries.

Farbod: Yes.

Daniel: I'm not sure if it was year-round, but it was definitely a lot longer than the natural growing season or even the normal greenhouse growing season because they were so intentional about making this a full closed loop system without any waste. They were using the heat generated from the electricity generation process from the gas, from the manure.

Farbod: To heat the green house.

Daniel: And they're using the excess heat from there to heat the greenhouse to extend the growing season of strawberries, which is awesome because I don't know if you're feeling this pain right now, like if you try and get strawberries in the winter, they either have to come from somewhere across the world, or if they're locally grown, they don't taste good. So, this is an awesome impact that hits home for me, right? Just had some strawberries the other day that didn't taste that good, and that's probably because they were tried to be grown somewhere where they were not completely in season.

Farbod: There you go. Direct impact too. Wow. What a good pick. Shout out to Dyson and congrats on your intersection Saucy award.

Daniel: And I will say this is a good, good way for me to segue here. I'm picking up what you're putting down. We're doing this. We do this good dance together. We talked about tasty strawberries. I actually want to talk about what I thought was the tastiest episode of the year. Which is a big deal. When we're talking about secret sauce, I mentioned episode 177, which is the Stanford University mobile Aloha robot that learned how to sauté shrimp. And essentially the secret sauce of what they did here is this talented team of researchers, they created a robotic platform that was capable of learning tasks through imitation rather than programming. So, they used artificial intelligence and machine learning to help a robot learn how to do something at as it was being controlled by a human who was controlling it. Right. And then afterward it was able to take the learnings from those and apply it to complete other different tasks. And they were able to find a robot or train this robot to complete over 850 common household tasks in a much shorter time period than if they had done it with the traditional programming method. And one of the things that was really awesome is it was able to create shrimp fried rice. And, you know, we're, we're big on naming conventions often when we find a piece of technology that's named really well, we like to give it a one through 10 rating. I think this is not only the tastiest episode, I'm gonna pat ourselves on the back here. I think this is the best titled episode of the year as well.

Farbod: I was gonna say, I agree.

Daniel: Because the title for this episode, again, you guys should click it in the show notes and check it out, but all credits to Farbod on this one. Episode 177, did a shrimp fry this rice? No, a robot did. Fresh from Fried Rice. I love it.

Farbod: I just remember when we were discussing potential episodes for that week and I just sent you this. I was like, dude, we have to do this. And the only reason if it's based on the potential title alone. Yeah. Solid pick again. Incredible.

Daniel: Congratulations to Stanford for the tastiest episode of the year.

Farbod: We got it like 3d print something and send them out. Yeah. This isn't good enough to just say it.

Daniel: Little sauce bottles.

Farbod: Yeah, oh yeah, and then put the sauce guy on it.

Daniel: Yeah, there we go.

Farbod: Oh, we can't see the sauce guy anyways, no Let's see my novel novel is my next one, you know something that's just super innovative. And really stands out and you know what I was a little biased with this one, but that's okay. It's our show this is episode 172 where we went back to our alma mater George Mason University and It was a professor from our department actually Professor Moran and his team where they use spent coffee grounds to clean the water. Spent coffee grounds has been a hot topic in the material world, hotter than I think anyone would have expected. Couple years ago, Ford was using it with a partnership with McDonald's where they would take spent coffee grounds and use it as a composite for their headlights. So, in this like sector of green technologies, spent coffee grounds has been unlikely champion. In this research though, they were using spent coffee grounds and I think a metal oxide to bind to oil particles in water and then the spent coffee grounds that had the metal oxide on them would become magnetic so then you could just filter them out very easily. They did a quick demonstration of this. I think Professor Moran was leading the research with another professor but then there was a high school student I think that was working with them as well. There are two things that I loved about it. One, the impact of this, right? Oil spill is super dangerous. What was it, 2010, where the Gulf of Mexico thing happened and I think we're still feeling the repercussions of that event. So, making sure things like this don't happen and cleaning up our oceans, awesome idea. And then in addition to that, it's so affordable and simple. I think in one of their interviews, the student that was working on this, they were like, this experiment and this research has taught me that science is so accessible. It doesn't have to be this incredibly complex thing. So not only is it simple and therefore feasible for the average Joe to do an experiment of their own or for a company to scale this up, but it's also a sign to others that you can get into science and it's not intimidating. So yeah, that's why it took the novel award for me.

Daniel: And we love Dr. Maron.

Farbod: We do, he's the best.

Daniel: Yeah. Not that we're biased at all.

Farbod: No, for sure. We got our uh, what is it? Uh Journalistic integrity.

Daniel: Yeah, whatever that is. Yeah, I forgot. But yeah, I agree man definitely the most novel and you know, dare I say one of the most surprising Innovations that we've covered in the last year agree. I'm gonna bridge right over to what I think is the best life-saving technology or has the potential to save the most lives was a recent one, episode 191. We talked about a critical AI developed by Texas A&M. This team of researchers was looking at all the phases of disaster management and where we can inject artificial intelligence to try and improve the way that we prevent future disasters, the way that we recover from certain disasters. And kind of one of the things that I thought was made this potentially the most likely to save lives, so to speak, is the way that they were plugged into and understood how the stakeholders work in a crisis response situation. They're working on being plugged in to public safety and helping improve outcomes in crisis situations. This makes me think of future hurricanes, future floods, future pandemic outbreaks, right? What are the ways that governments really are the ones that lead the response. What are the ways that governments can lead a response to a certain incoming crisis in a way that evacuates people from the right locations to make sure that they aren't impacted by an incoming tsunami wave, and then also prioritizes recovery response once the disaster is hit to make sure that you're saving the most lives possible. In my mind, this is like a really, really high leverage life-saving solution. You're not only creating a technology that for each use, saves one person's life, which even that would be incredible. You're creating a technology that per each use could save thousands or hundreds of thousands of lives, which is crazy. And in a world where the world is getting hotter and the climate's getting crazier, I imagine we will experience more natural disasters. Not that I want to, but I imagine that we'll experience more natural disasters and something like this will become more commonplace, become a part of what hopefully every local government in a state of emergency does and uses as part of their toolkit to try and save some lives.

Farbod: Completely agree. I remember when we aired that episode a couple weeks after that the flooding in Spain happened and it was quite disastrous. And I remember thinking wow the system that we just talked about would have been so helpful here because that the folks didn't evacuate on time because the authorities hadn't given them the heads up and something like that could have been super helpful. So once again solid pick my next one is practicality so the most practical word. I guess the best way to define this is something that has a direct impact to its users. And we see the output of that right away. So, in episode 181, we talked about the Audi R8 plant. And it's not just the R8. The R8 is kind of outgoing now, but you got the e-tron GT, all the high-performance cars that Audi makes. And the whole episode was about how these cars have to be perfect. The customers are expecting a level of quality and the manufacturer has to deliver so traditionally those people working on the line are using jigs to help them line stuff up and assemble things in an easier and more efficient manner but also in the most perfect way possible. Traditionally to make a jig you would have to outsource it or get a mechanical designer's help and then have the manufacturing for it and it would take months and months and thousands of dollars to get in which is an ideal but you know it's kind of what you had to do. The age of additive manufacturing has kind of changed that up where you can just make whatever jig you want in-house. But on top of that, there was a software that we discussed which allowed someone that might not even know how to do mechanical design to just kind of explain what they want to do and it would kind of help you generate your idea and get it printed pretty easily. What was fascinating about it is that the Audi folks kind of expect that if they were making a hundred jigs that with this new setup, those the work for those hundred jigs would just now be automated, not only did that happen, but the demand for jigs kept going up because now the people that were working on the line knew that they weren't causing friction to anyone else when they wanted something new. So, they felt more empowered to go and ask for new things. I think by the time we did the episode, there was like a couple hundred jigs that were flying around the Audi workshop. And that was like a testament to the power of additive manufacturing and generative design to me. So, it was really exciting to see that a powerhouse like Audi was leveraging it this way.

Daniel: One is one of these things where like people could be excited about injecting 3D printing into this process.

Farbod: Yeah.

Daniel: And then in practicality or in actuality, like the practical implications of it were not strong enough that like anyone would want to use something that's 3D printed versus something that was made in the traditional manner. I think that happens a lot when people get excited about technology before actually testing it in the real world.

Farbod: Yep.

Daniel: In this case, they had a completely different outcome where they thought they would be using this like five or ten times per day as an example and then they got hundreds of requests from people saying oh, can you help me 3d print this jig? Can you help me 3d print this jig and you know in a world like automotive where new technologies are coming in constantly. There's often some resistance among the people like at the forefront doing the manufacturing to say like “oh, do we actually want to experiment with this new technology because like this is actually someone's job doing this thing hundreds of times per day make sure that it's safe, make sure that we can trust it, et cetera”. In this case, they got a taste of the 3D printing and they're like, man. Give me more of that, because that stuff's good. And I agree, right? I think maybe the impacts of 3D printing initially were overblown. Everyone's saying, oh, everything in the world is going to be 3D printed and nothing's ever going to be made with traditional manufacturing ever again. That's not quite the case today. But in something like making custom jigs that have to have really, really high dimensional stability, but are made in really, really low volume production runs. 3D printing is a perfect example of how to do that and do it in a way that the supply chain is actually at the same location as the usage location, which is awesome.

Farbod: Great.

Daniel: Use this as a way to go to what made me most excited. So personally, most exciting for me was episode 199. Another recent one, we talked about a team from MIT who are creating AI co-pilots for doctors. I personally have, I would say, I'm not completely maligned against the medical system, but I have a lot of cynicism with the medical system. And I personally believe that like, there are lots of good doctors out there and lots of great people that wanna save lives, but the way that the system is set up, the incentives are such that like, it doesn't always deliver the best care or the best outcome to the patient. You need a patient who's either really knowledgeable and good at advocating for themselves or a doctor who cares enough to bridge that gap for people. And part of the issue there is because of how much administrative work and administrative load that's required of doctors. So, they'd spend a lot less of their time doing proper decision-making and patient care, and they spend a lot more of their time doing paperwork and the annoying stuff, which often ends up in mistakes, and then they have to do it again and again, because it's confusing with the insurance system. So, in that episode, we talked about a team from MIT that created an AI co-pilot for doctors. Helped with medical transcription, helped with filing certain treatments against insurance codes, and helped make sure that doctors can spend their time on decision-making and on patient care and doing the things that have high leverage toward the actual patient outcome and spend less time doing the administrative work, which to me made me super excited to be a part of a future medical system where my doctor is able to pay more attention to me and advocate for my outcomes.

Farbod: I think the statistic in that episode, something like a third of a doctor's time was just going to these administrative tests that were now being automated, that really stood out to me. Because I feel like, you know, qualitatively I could feel that, but just getting the numbers out there was a little scary, to be honest. So, I'm with you, man. I'm excited for this one. And, you know, I'll use this opportunity to plug my personal favorite of the year. It's gonna be episode 189. Bit of a shift from what yours was because this one was from Stanford University and their efforts with tandem drifting of cars using AI. So, the Stanford Autonomy Laboratory, they've been doing great work on autonomous vehicles for quite some time. But then they released this video of these two Toyota Supras tandem drifting. This was in collaboration with the Toyota research division. Dude, I think I just, again, this was another episode, right? I was like, just to say the video, like we have to do this. Well, this is so cool. We love cars. It just, I think I played the video five times probably before we even started shooting.

Daniel: I watched the video five times as well. And then I sent you a link to a Fast and Furious drift scene. And we were like, we have to do this. I think it was in Tokyo Drift.

Farbod: It was.

Daniel: The one where the guys, there's one car in the middle and the other one's doing circles around it.

Farbod: Yep, yep, yep. And it's-

Daniel: In my mind, I was like, yes, we love cars. We love drifting. We love robots. Yes.

Farbod: Again, like this is a personal favorite because of how cool it is, but it also has like, it's not just drifting for the sake of drifting. The technology they came up with had these two cars autonomously drifting, sometimes at like a few centimeters away from each other. So, when you talk about developing technologies for autonomous driving, right? Where you have real world scenarios and sometimes as a driver, you need to make split second decisions where your car is very close to another car. You want technology like this, which is able to adjust itself on the fly very quickly. And that's what they're actually demonstrating here. So, it scratched both itches for me, very cool and very impactful. And that's why it's a personal favorite.

Daniel: I with you, man. And I think this is one of those things where the headline or the, the attention grabber video is actually satisfied by the research that comes behind it. Right. It's not a…

Farbod: A hundred percent.

Daniel: It's not a cliff bait or click bait rather, right. Just if I, this is something where like, you know, it's a buzzy headline about tandem drifting and doing it autonomously, but they actually had the science, the developments to back it up, which we often try to steer away from things that sound overly buzzy if we think that they're a risk of being click-baity. So, we try and make sure that the research behind it is substantive. And this is one of those things where I was pleasantly surprised to find like, oh yeah, there's a lot of work behind this and it has a lot of potential real-world impact, but also look at these cars drift, it's awesome.

Farbod: Yeah, yeah.

Daniel: I'm gonna, this is my last award of this episode.

Farbod: Yeah, I got one more too.

Daniel: The most relatable, and this is personally relatable to me, and I'm hoping it's personally relatable to a lot of people listening to this episode right now, because I know that statistically, a large percentage of podcasts are listened to while someone's on their daily commute. And so, we're talking about episode 173, where we talked about researchers from University of Michigan. They tested this in a small city by connecting GPS to connected cars and then having smart stoplights that can be controlled essentially in response to traffic data, they were able to think, or they could save the extent of about three days of person's life every year by reducing their commute time simply by making sure that the stoplights were orchestrated in tandem with the traffic that's going by. And you know, it was a relatively simple software stack, relatively simple solution. But one of the very unique applications that I think will have an impact that's relatable to just about everyone is if you're not stuck at a light waiting arbitrarily, or if the light cycle feels too short for the amount of traffic that's sitting there, or if the light cycle feels too long for the amount of psych traffic that's sitting there. Imagine a world where in the future your commute, the traffic lights are responsive to the amount of traffic that's there. Using GPS data from connected cars, essentially able to give you three days of your life back every single year based off the average commute time of a person in the US.

Farbod: There's this movie called Margin Call about the collapse of the US economy and the hedge fund that worked on it. Long story short, there's a scene with a guy who was a civil engineer that built a bridge, and he's like, by building that bridge, I saved something like 500 years of people's lives because it cut their commute by X number of minutes. This episode reminded me of that because if you can cut my commute even by like five minutes a day. It adds up over time and there's a lot of people on my commute.

Daniel: So same with Steve Jobs in the Mac boot sequence.

Farbod: Yep, listen to his biography right now and that came up. It's you know, think what you want of the guy but that's a pretty baller line and hit the nail on the head.

Daniel: Same thing right at economies of scale a lot of people waiting at lights a lot of people waiting to boot their laptops if you can make an incremental change there to reduce the amount of time that they're waiting and reduce idle time and give people time in their lives back. You can have a massive impact in the overall productivity and gift people more time back, which is I think a very noble cause for technology.

Farbod: Agreed. Great. And I'll wrap this round of sausage up with an honor roll mention. This one's going to go out to episode one 92, which was actually an interview episode with Karsten Roscher from, Oh God, why am I blanking on the name of the Institute?

Daniel: The Fraunhofer.

Farbod: Fraunhofer, the Fraunhofer Institute. He was working on this tool, RoboScoop, that helped developers test their AI models and benchmark it properly, which we did a short form episode about it, but the reason that the interview episode is here and not the short form episode is because the conversation itself actually was not just about that tool. It was more broad. We talked about you know, AI safety in general and, you know, his expertise is on autonomous vehicles. So, you know, we asked him his thoughts on AVs and if he feels comfortable about it and policymaking and how technologists, how much they should be involved versus like scientists and if we're being too conservative or if not. So that conversation in whole was pretty exciting to me. We said it in the interview, but we're hoping to stay more in touch with him as time goes on because this is like an active thing. Laws are changing on a daily basis. We're seeing autonomous vehicles in the United States being deployed more and more. So, it's kind of an exciting area to keep the conversation going around.

Daniel: Well, and I think just keeping a quick tally here, right? I think we've given. What's these 11 awards in this saucy's episode? One, two, three, four, five, six, seven, eight, nine, nine of the 11 awards, were related to technologies that leveraged AI, machine learning AI. Some form of this technology. I can't state this with enough emphasis. This is the technology that I think is most impactful in 2024 will continue to be the most impactful in 2025. And having some knowledge of the potential unintended consequences and or how to maintain safety and or how does AI interact with society and with government and with policy and with people and their privacy and their safety, et cetera. Karsten is an expert at understanding how to develop new AI and then also an expert at understanding how to maintain safety with it. I think I'm with you, man. If, you know, maybe deserves a little more than an honorable mention, but folks should check out this interview because Karsten knows a lot about how this very impactful technology will interact with the real world essentially and the guardrails that we set for it and how that will impact the outcomes that our society has in the future. So, I'm with you. Very important, very impactful. And Karsten's also just a really nice guy. So, it was great interviewing with him and I hope folks are willing to go check out that interview episode as well.

Farbod: Yeah, for sure. With that, I think we're good to wrap up the saucies for 2024. Yeah.

Daniel: Yes, sir. 2024 saucies is a wrap. Thank you to our community. This, that's the biggest part of why we do this and why we continue to do this even four plus years into it, is the folks that are part of this community that help us select the topics, right? They tell us what's interesting to them. They send us something cool when it pops up. But they also make it interesting. So that, people like Karsten, interesting people who are movers and shakers in the real world, are willing to come talk to us on our podcast because they care about the community that we're able to reach. So, appreciate everyone who's a part of our community and appreciate you rocking with us last year and I hope you continue rocking with us into the next year.