WEBVTT - Beep - Autonomous Mobility for Al 0:00:04.440 --> 0:00:08.440 Welcome to tech Stuff, a production from iHeartRadio. 0:00:12.080 --> 0:00:13.480 Hey there, tech Stuff listeners. 0:00:13.640 --> 0:00:17.480 This is Jonathan Strickland, executive producer at iHeart Podcasts, and 0:00:17.680 --> 0:00:20.400 what I have for you today is an episode of 0:00:20.440 --> 0:00:23.799 a new podcast we launched earlier this year in partnership 0:00:23.800 --> 0:00:28.680 with Intel. The show is called Technically Speaking, an Intel Podcast, 0:00:29.200 --> 0:00:32.840 and it focuses on all things artificial intelligence. Now, y'all 0:00:32.840 --> 0:00:36.159 have heard me talk about AI tons of times on 0:00:36.240 --> 0:00:38.239 tech Stuff, and I'm sure you've got a pretty good 0:00:38.280 --> 0:00:42.680 handle on my general thoughts and opinions about artificial intelligence. 0:00:42.720 --> 0:00:44.920 But that's not to say that my point of view 0:00:45.000 --> 0:00:48.680 is the only one, or heaven knows, it's not necessarily 0:00:48.720 --> 0:00:52.519 the correct one, or anything like that. This show features 0:00:52.520 --> 0:00:58.960 hosts Graham Class exploring bleeding edge implementations of AI and 0:00:59.040 --> 0:01:03.959 how AI is making incredible changes in the way we 0:01:04.040 --> 0:01:06.280 do different types of work and how it can help 0:01:06.360 --> 0:01:10.080 people in various ways. And he has conversations with pioneers 0:01:10.080 --> 0:01:13.800 and innovators in the space. So check out this episode 0:01:13.840 --> 0:01:16.600 and to hear more, make sure you subscribe to Technically 0:01:16.600 --> 0:01:21.760 Speaking and Intel podcast. Wherever you get your podcasts enjoy. 0:01:22.959 --> 0:01:26.280 Where do world changing ideas get their start at Intel. 0:01:26.319 --> 0:01:29.399 It starts with real solutions, and real solutions start with 0:01:29.480 --> 0:01:34.480 exceptional engineering, the quantum computing revolution, the next generation of 0:01:34.520 --> 0:01:38.560 AI experts, the renewable energy grid, liquid cooling, data centers, 0:01:38.680 --> 0:01:42.760 early diagnosis for cancer, water restoration, and even farmland protection. 0:01:43.120 --> 0:01:46.360 The examples are countless, the impacts are endless, but the 0:01:46.440 --> 0:01:50.160 foundation is always the same. It starts with Intel. Join 0:01:50.240 --> 0:01:53.080 us in redefining what's achievable through the power of AI. 0:01:53.600 --> 0:02:01.400 Learn more at Intel dot com slash stories. Welcome to 0:02:01.600 --> 0:02:06.280 Lake Nona, a beautiful residential and commercial oasis where the 0:02:06.320 --> 0:02:10.400 future has arrived. Lake Nona is a seventeen square mile 0:02:10.440 --> 0:02:14.920 community in Orlando, Florida that has established new standards of 0:02:15.000 --> 0:02:20.080 living that integrate the latest technology into every facet of life, including, 0:02:20.320 --> 0:02:23.560 but not limited to the way its citizens get around. 0:02:24.000 --> 0:02:27.280 Picture this. A person stands in the warm Florida sun 0:02:27.520 --> 0:02:30.400 at a designated bus stop, waiting for the next shuttle 0:02:30.400 --> 0:02:33.839 to arrive. And here it comes, not with the roar 0:02:33.880 --> 0:02:36.320 of an engine, but with the gentle hum of an 0:02:36.400 --> 0:02:40.280 energy efficient electric mona. The busk glides to a halt, 0:02:40.800 --> 0:02:45.280 and as the doors open, something is missing. There's no 0:02:45.320 --> 0:02:48.400 one in the driver's seat. That's because Lake Nona is 0:02:48.440 --> 0:02:51.359 home to one of the country's largest and longest running 0:02:51.360 --> 0:02:55.919 single site autonomous vehicle fleets. These energy efficient, self driving 0:02:55.960 --> 0:02:59.119 buses have transformed the way residents travel in this community, 0:02:59.720 --> 0:03:03.320 say and easily accessible. They whisk people from place to place, 0:03:04.000 --> 0:03:08.800 freeing hands, reducing traffic congestion, and embracing a sustainable future. 0:03:09.720 --> 0:03:12.560 What else can a world of autonomous public transportation do? 0:03:13.400 --> 0:03:17.000 How else may impact the way a community operates in 0:03:17.040 --> 0:03:19.680 this bright and sunny corner of the world. The horizon 0:03:19.720 --> 0:03:32.760 is limitless and our journey is full of possibilities. Hey there, 0:03:32.919 --> 0:03:36.760 I'm Grain Class and this is technically speaking an Intel podcast. 0:03:37.360 --> 0:03:40.920 The show is dedicated to highlighting technology is revolutionizing the 0:03:40.960 --> 0:03:44.920 way we live, work, and move. In every episode, we'll 0:03:44.960 --> 0:03:48.200 connect with innovators in areas like artificial intelligence to better 0:03:48.280 --> 0:03:52.480 understand the human centered technology they've developed. Thus far, we've 0:03:52.520 --> 0:03:57.160 explored how AI impacts society in the ways of agriculture, accessibility, 0:03:57.440 --> 0:04:00.240 and mental health. But one of the ways technology and 0:04:00.360 --> 0:04:04.920 especially artificial intelligence impact society is through its structures. AI 0:04:05.080 --> 0:04:07.880 is advancing the way cities are able to serve their citizens. 0:04:08.480 --> 0:04:10.720 There's a very interesting example of this happening in a 0:04:10.720 --> 0:04:13.920 small town in the United States. But before we go 0:04:13.960 --> 0:04:18.839 any further, I need to introduce my guests. Joining me 0:04:18.920 --> 0:04:21.960 now is Joey Morow, the CEO of BEEP, which is 0:04:22.000 --> 0:04:25.440 a company that offers autonomous mobility solutions in public and 0:04:25.480 --> 0:04:29.000 private communities across the US. His career has spanned the 0:04:29.080 --> 0:04:33.200 technology arena, from hardware and software to IT services. He 0:04:33.240 --> 0:04:37.360 has spearheaded groundbreaking enterprise projects in cutting edge startups to 0:04:37.560 --> 0:04:42.520 multi billion dollar enterprises. Joe's expertise in innovation, strategy and 0:04:42.560 --> 0:04:45.800 transformative technologies paved the way for his role at BEEP, 0:04:46.080 --> 0:04:49.560 where he now leads a new team transforming mobility as 0:04:49.560 --> 0:04:52.440 we know it. We are so excited to have you on, Joe. 0:04:52.680 --> 0:04:54.240 Thank you, Graham, glad to be here. 0:04:54.920 --> 0:04:57.799 Also joining us as Juan Santos, the senior vice president 0:04:57.920 --> 0:05:01.840 of Brand Experience and Innovation at Tavas Group. At table Stock, 0:05:01.920 --> 0:05:05.120 He's part of a multi disciplinary team that uses design 0:05:05.160 --> 0:05:08.720 thinking to build places where people can thrive. One is 0:05:08.760 --> 0:05:13.960 a recognized expert in design thinking, user generated content, virtual worlds, 0:05:14.320 --> 0:05:16.640 physical and digital, and loyalty and rewards. 0:05:17.160 --> 0:05:18.360 Welcome to the chop one. 0:05:18.520 --> 0:05:19.200 Thank you very much. 0:05:19.240 --> 0:05:25.920 Green, I'll start with you, Joe, Can you just tell 0:05:25.960 --> 0:05:29.120 us a little bit more about Beep and in particular 0:05:29.360 --> 0:05:33.200 your personal story around why you decided to get involved 0:05:33.200 --> 0:05:33.799 with the company. 0:05:34.360 --> 0:05:37.080 Yeah, I'm happy to Graham, and thanks again for having us. 0:05:37.120 --> 0:05:41.800 So Beep was founded on the premise that autonomous mobility 0:05:42.360 --> 0:05:45.760 is going to be proven out in i'll see incremental 0:05:45.880 --> 0:05:49.640 use cases. I know everybody has had different experiences and 0:05:49.800 --> 0:05:52.880 or has read a little bit about what driving and 0:05:52.920 --> 0:05:55.200 mobility is about. You know, I would tell you if 0:05:55.240 --> 0:05:58.520 you think of the technologies and the work that we're doing, 0:05:58.560 --> 0:06:02.720 it's very focused on on shorthaul first mile last mile 0:06:02.800 --> 0:06:06.760 type use cases in public and private communities, solving for 0:06:07.360 --> 0:06:11.120 that micro transit gap across many areas of our country. 0:06:11.839 --> 0:06:15.480 Second is very important that it's a shared platform, so 0:06:15.520 --> 0:06:20.760 we focus on more controlled speed, GEO fenced use cases, 0:06:21.440 --> 0:06:24.839 but in a shared mobility form factor, meaning a shuttle 0:06:24.880 --> 0:06:28.480 that seats a ten to twelve passengers and really represents 0:06:28.880 --> 0:06:33.240 that ability to provide a good balance of yes, personal mobility, 0:06:33.279 --> 0:06:37.280 but also community mobility. So the business was founded by 0:06:37.320 --> 0:06:40.200 a group of us that are also investors in the company. 0:06:40.600 --> 0:06:44.080 We've been entrepreneurs across a couple of funds, so we're 0:06:44.160 --> 0:06:47.480 venture capitalists as well as operators. And again, as we 0:06:47.560 --> 0:06:50.680 looked at this key inflection point in the area of 0:06:50.760 --> 0:06:56.000 technology specific to autonomy, made a very calculated approach to 0:06:56.080 --> 0:06:59.520 focusing on this micro segment of the larger market of 0:06:59.600 --> 0:07:06.200 autono enemy around this electric shared autonomous mobility in these 0:07:06.320 --> 0:07:08.520 micro transit use cases. 0:07:09.920 --> 0:07:13.040 BEEP is a turnkey mobility solution with the goal of 0:07:13.040 --> 0:07:18.120 providing stress free transportation, reducing carbon emissions, and improving road safety. 0:07:18.760 --> 0:07:23.480 Offering autonomous transportation to thousands of people, beep's technology focuses 0:07:23.520 --> 0:07:27.440 on community and offers localized travel solutions that reflect the 0:07:27.440 --> 0:07:32.440 way people want to engage with their neighborhood. Are these 0:07:32.600 --> 0:07:36.400 vehicles going to be driver lists or driver assisted? How 0:07:36.480 --> 0:07:38.000 is that currently being played out? 0:07:38.400 --> 0:07:41.600 Yeah, it's a great question. We work in partnership with 0:07:41.640 --> 0:07:46.000 the US Department of Transportation, who oversees the use of 0:07:46.040 --> 0:07:49.720 these vehicles on our roadways today. So the vehicles are 0:07:49.760 --> 0:07:54.360 operating in a very high percentage fully autonomous. But we 0:07:54.480 --> 0:07:59.360 do have safety attendants or ambassadors on board whose responsibility 0:07:59.480 --> 0:08:03.280 is to both educate welcome passengers and introduce them to 0:08:03.320 --> 0:08:07.480 the technology, help them feel comfortable with these types of services, 0:08:07.520 --> 0:08:11.200 but also to take over manual control should that be 0:08:11.280 --> 0:08:14.040 needed if there's an event on the roadway that requires 0:08:14.080 --> 0:08:18.920 some level of intervention. Fast forward a couple of short years, 0:08:19.600 --> 0:08:23.520 and those attendants are going to be virtual or remote. 0:08:24.000 --> 0:08:27.280 So we will in our types of services always have 0:08:27.480 --> 0:08:29.920 a human in the loop. It will shift from being 0:08:29.960 --> 0:08:34.360 an onboard attendant to a virtual attendant. And you can 0:08:34.400 --> 0:08:39.200 only imagine, especially in the area of public transportation, if 0:08:39.240 --> 0:08:43.440 there is some circumstance, be that a traffic jam or 0:08:43.480 --> 0:08:48.000 a pothole on a roadway or some other eventuality, you 0:08:48.080 --> 0:08:50.880 still have to be able to communicate with passengers on 0:08:51.000 --> 0:08:53.400 board if there's a reason to pull a vehicle off 0:08:53.480 --> 0:08:56.640 the side of the road, let people know what's going 0:08:56.679 --> 0:08:58.200 on and what to do about it. 0:08:58.360 --> 0:09:02.319 Okay, great, I'll bring one into that discussion. Now, can 0:09:02.400 --> 0:09:04.320 you just tell us a little bit about your work 0:09:04.360 --> 0:09:05.600 at Tavasot Group. 0:09:06.600 --> 0:09:11.360 So I lead innovation and a brand experience in what 0:09:11.679 --> 0:09:15.760 most people would traditionally think of as a development company. However, 0:09:15.920 --> 0:09:19.040 Tavisak Development, which is the area that I focus mostly in, 0:09:19.480 --> 0:09:22.720 is not your traditional developer. We are actually an owner 0:09:22.800 --> 0:09:26.120 operator and in the case of BEEP, we have a 0:09:26.120 --> 0:09:29.600 place called Lakenona where directly contiguous to the Orlando Airport. 0:09:29.640 --> 0:09:32.600 We're proud citizens of the city of Orlando, but we 0:09:32.679 --> 0:09:36.120 represent an advanced district in the city, and it's a 0:09:36.160 --> 0:09:39.960 fairly large advanced district. We're approximately seventeen square miles to 0:09:40.000 --> 0:09:43.200 give you a point of comparison, Manhattan's twenty two, so 0:09:43.240 --> 0:09:45.800 it's a fairly large swath of land. And then we 0:09:45.880 --> 0:09:49.760 have pretty much every use case inside like no, no, I mean, 0:09:49.800 --> 0:09:54.079 we have universities, high schools, people can go to preschool, 0:09:54.120 --> 0:09:58.280 there's micro apartments, there's large homes, so it becomes this 0:09:58.760 --> 0:10:02.120 really interesting place. It's for people to live, but also 0:10:02.480 --> 0:10:05.920 for companies that are on the forefront of technology to 0:10:06.000 --> 0:10:08.720 use us a living lab. The reason BEEP is a 0:10:08.720 --> 0:10:13.079 critical partner for Lignona is because we believe mobility is 0:10:13.200 --> 0:10:15.240 one of those things that create a lot of friction 0:10:15.440 --> 0:10:17.719 inside a community. Right you come to a place and 0:10:18.120 --> 0:10:21.080 parking is difficult moving from one place to the other. 0:10:21.320 --> 0:10:24.120 That's really kind of like they're not so enjoyable, not 0:10:24.280 --> 0:10:28.000 so great parts of being in communities that are successful. 0:10:28.240 --> 0:10:32.040 In Lignona, we've tackled that friction with immobility by a 0:10:32.120 --> 0:10:36.600 variety of things, but we've also incorporated BEEP under autonomou 0:10:36.600 --> 0:10:40.440 shuttle operation as a critical part to provide that first 0:10:40.480 --> 0:10:44.720 and last mile mile and a half inside the community 0:10:45.200 --> 0:10:47.800 for people to traverse, and it's something that has been 0:10:47.880 --> 0:10:51.720 running now for multiple years. We have what I believe 0:10:51.800 --> 0:10:55.240 today is the largest and longest running autonomous shuttle operation 0:10:55.800 --> 0:10:58.520 in the United States in Lakenona. It's actually so prevalent 0:10:58.960 --> 0:11:01.160 now that we're coming close to the end of the 0:11:01.240 --> 0:11:04.760 year where we had a kid, you know, last Halloween 0:11:04.800 --> 0:11:07.800 actually dressed up as one of the autonomous shuttles. So 0:11:07.840 --> 0:11:11.760 it's something that's both an incredible service that reliefs striction, 0:11:11.880 --> 0:11:16.120 but it's become a natural part of the ecosystem that 0:11:16.160 --> 0:11:18.680 people live with and live in in Lachdana. 0:11:19.200 --> 0:11:23.920 Yeah, I'm interested in how that autonomous shuttle bus started 0:11:24.400 --> 0:11:27.960 and was there any I guess pushback or were any 0:11:28.040 --> 0:11:31.079 challenges with the community to try and get this sort 0:11:31.120 --> 0:11:32.240 of thing deployed. 0:11:33.080 --> 0:11:36.680 Actually, it was incredibly well received. It started in a 0:11:36.720 --> 0:11:39.720 conversation with the founders of BEEP. We were actually having 0:11:39.720 --> 0:11:42.760 a conversation about a different topic and the topic of 0:11:42.760 --> 0:11:47.640 autonomous mobility came up, and after that conversation. Fast forward 0:11:47.679 --> 0:11:51.600 eleven months and the company had been created, the vehicles 0:11:51.640 --> 0:11:54.079 have been brought into the US. We've worked with Department 0:11:54.120 --> 0:11:57.520 of Transportation and NITSA to make it happen, and from 0:11:57.520 --> 0:12:01.280 a community perspective, we actually did an outreach process where 0:12:01.320 --> 0:12:03.920 we actually allowed critical members of the community to be 0:12:03.960 --> 0:12:08.240 a part of understanding what the vehicles would do. For example, 0:12:08.320 --> 0:12:11.640 we had a specific day where the beeps were on 0:12:11.800 --> 0:12:15.720 preview just for first responders, so we showed our police 0:12:15.720 --> 0:12:19.040 department and the fire department how to work with the vehicles, 0:12:19.040 --> 0:12:21.560 how to operate them, how to move them if necessary, 0:12:21.920 --> 0:12:24.760 and when the vehicles rolled for the first time, we 0:12:24.800 --> 0:12:28.080 had a community that was ready, so we didn't have 0:12:28.240 --> 0:12:32.200 much pushback. Now we had people have to adapt to 0:12:32.440 --> 0:12:35.360 having a vehicle with no driver right because even though 0:12:35.360 --> 0:12:38.720 there's a safety attendant on board, the vehicles operating on 0:12:38.760 --> 0:12:42.800 its own and it operates differently than a humanly controlled vehicle. 0:12:43.240 --> 0:12:46.680 So we had some situations where people were like learning 0:12:46.720 --> 0:12:49.600 to interact with them, but for the most part, it 0:12:49.679 --> 0:12:53.480 was very well received. One of the hallmarks of known 0:12:53.520 --> 0:12:57.440 as a community is that our citizens, they think of 0:12:57.520 --> 0:13:01.839 themselves almost like citizen scientists. They're almost asking us what's 0:13:01.880 --> 0:13:04.679 new every week. It's like, what's the new thing to try. 0:13:05.120 --> 0:13:09.160 They've come to expect strange things to happen, you know, 0:13:09.200 --> 0:13:12.080 in the roads and other places in Lignona. So I 0:13:12.120 --> 0:13:16.079 think it was significantly better received because of the education 0:13:16.200 --> 0:13:18.960 that we did, because the first responders were on board, 0:13:19.360 --> 0:13:22.240 because we gave community previews, so it was not like suddenly, 0:13:22.760 --> 0:13:25.760 you know, self driving car shows up in the middle 0:13:25.760 --> 0:13:26.760 of the community. 0:13:26.400 --> 0:13:27.360 Right okay. 0:13:27.400 --> 0:13:29.400 And in terms of I mean we've talked about the 0:13:29.440 --> 0:13:32.640 autonomous side of things and the AI. Are there any 0:13:32.679 --> 0:13:36.400 other AI techniques or technology that has been used for 0:13:37.160 --> 0:13:40.520 general community planning and development? Are there any other tools 0:13:40.559 --> 0:13:42.480 out there that is currently being used? 0:13:43.280 --> 0:13:47.360 So from a legnano perspective, it's pretty significant. We actually 0:13:47.440 --> 0:13:52.800 have a very detailed data overlay that actually shows us 0:13:52.840 --> 0:13:56.880 how the city is behaving. Everything is private, so there 0:13:56.960 --> 0:14:00.960 is no personally identifiable information being collected, but we collect 0:14:01.120 --> 0:14:04.800 a wide variety of behaviors. I know how long people 0:14:04.880 --> 0:14:08.640 wait for an uber, I know the specific state of 0:14:08.880 --> 0:14:12.240 parking garages. Every spot is instrumental, so we know if 0:14:12.280 --> 0:14:15.000 there's a weight for them. We know how the beaps 0:14:15.000 --> 0:14:18.319 are flowing inside the community, and that is fed into 0:14:18.360 --> 0:14:23.000 a large data environment where we actually use AI driven 0:14:23.040 --> 0:14:27.040 tools to both predict and model the behavior of the environment. 0:14:27.080 --> 0:14:31.720 We've done presophisticated prediction on mobility using AI, but we 0:14:31.760 --> 0:14:35.040 also use it for energy consumption. We use it to 0:14:35.120 --> 0:14:39.560 detect unknown patterns, like, for example, the impact of having 0:14:39.640 --> 0:14:43.080 pets in the environment and how that changes visitation. So 0:14:43.520 --> 0:14:47.479 when you look behind the scenes at what allows Lakenna 0:14:47.520 --> 0:14:51.200 to operate and what allows Beep to find such a 0:14:51.240 --> 0:14:56.280 fertile environment for testing and operating these vehicles here, there's 0:14:56.320 --> 0:15:01.160 a significant amount of AI and data that actually powers 0:15:01.160 --> 0:15:01.760 our community. 0:15:02.320 --> 0:15:05.400 Yeah, that's pretty cool. Just as you're describing the amount 0:15:05.440 --> 0:15:07.800 of data and be able to find all their starts. 0:15:07.800 --> 0:15:11.080 It just reminded me of the SimCity series of games 0:15:11.080 --> 0:15:14.240 that I used to play quite a bit, and using 0:15:14.280 --> 0:15:16.720 that to make decisions to make your citizens happy. 0:15:17.480 --> 0:15:20.480 I may have said once or twice that I get 0:15:20.480 --> 0:15:23.200 to play SimCity with a real city to a degree, 0:15:23.280 --> 0:15:24.920 so I know exactly what you mean. 0:15:28.680 --> 0:15:40.120 We'll be right back after a quick break. Where do 0:15:40.240 --> 0:15:43.800 world changing ideas get their start? At Intel? It starts 0:15:43.800 --> 0:15:47.760 with real solutions, and real solutions start with exceptional engineering. 0:15:48.360 --> 0:15:52.400 Empowering those with disabilities starts with assistive AI, and stopping 0:15:52.440 --> 0:15:56.680 crop loss from infestation starts with thermal imaging and open technology, 0:15:57.240 --> 0:16:01.760 while artificial intelligence that predicts depression starts with educational programs 0:16:01.800 --> 0:16:05.240 like Intel's AI for Youth. And that's just the start 0:16:06.600 --> 0:16:10.920 the quantum computing revolution. The next generation of AI experts 0:16:11.600 --> 0:16:17.040 the renewable energy grid, liquid cooling, data centers, radiation exposure 0:16:17.040 --> 0:16:22.480 prevention in space, water restoration, and early cancer detection. The 0:16:22.520 --> 0:16:26.480 examples are countless, the impacts are endless, but the foundation 0:16:26.640 --> 0:16:31.600 is always the same. It starts with Intel. Learn more 0:16:31.640 --> 0:16:42.440 at Intel dot com, Forward Slash Stories Welcome back to 0:16:42.520 --> 0:16:50.400 Technically Speaking, an Intel podcast. When you think about AI 0:16:50.680 --> 0:16:54.560 in our environment, the question of oversight often comes into play. 0:16:55.160 --> 0:16:58.320 How did these tools manage incidents in the community. What 0:16:58.480 --> 0:17:01.440 metrics or data are you to determine when an AI 0:17:01.480 --> 0:17:05.080 tool should engage or intervene. I often think of the 0:17:05.119 --> 0:17:08.720 pacemaker as an example of how AI can be used 0:17:08.720 --> 0:17:12.399 to positively impact our lives. A monitoring system that is 0:17:12.400 --> 0:17:15.120 set up to only act when a severe change has occurred. 0:17:15.800 --> 0:17:18.879 BEEP is creating a system with checks and balances that 0:17:19.000 --> 0:17:23.200 can be more reliable than humans in reporting incidents. Vehicles 0:17:23.200 --> 0:17:27.159 are constantly collecting information inside and outside around what it 0:17:27.200 --> 0:17:31.000 observes and encounters that can make the community safer and 0:17:31.080 --> 0:17:31.680 more efficient. 0:17:34.440 --> 0:17:36.720 If you think of the in cab and environments and 0:17:36.760 --> 0:17:40.320 you think of the scenario of not having a person 0:17:40.359 --> 0:17:42.840 of authority on board, there is no driver, there is 0:17:42.880 --> 0:17:47.720 no attendant. In the future, I mean, we're developing tools 0:17:47.760 --> 0:17:54.480 and techniques that monitor the activities of the writers to 0:17:54.680 --> 0:17:57.879 ensure we understand that if there is a health event, 0:17:58.119 --> 0:18:02.440 you know, somebody crouches over their chair as an example, 0:18:03.119 --> 0:18:07.280 if there's an unfortunate situation like somebody were to present 0:18:07.320 --> 0:18:10.280 a weapon. You have to think of all these types 0:18:10.320 --> 0:18:13.960 of use cases, and what's critical about that is being 0:18:14.000 --> 0:18:19.840 able to process that observation and quickly align that with 0:18:20.080 --> 0:18:23.320 how we would get some communication into the vehicle and 0:18:23.600 --> 0:18:27.560 or immediately dispatch support or services. You know, one of 0:18:27.560 --> 0:18:32.920 the things that is so important about these vehicles is 0:18:33.880 --> 0:18:39.840 in the event of an incident, you have the perfect eyewitness. 0:18:40.040 --> 0:18:45.720 Every time you're videotaping what's happened in an intersection, you're 0:18:46.480 --> 0:18:50.760 leveraging that information and data to measure exactly how did 0:18:50.800 --> 0:18:55.560 an autonomous vehicle respond and so an important piece of 0:18:56.400 --> 0:18:59.440 leveraging data in the future for the work that we're 0:18:59.480 --> 0:19:04.479 doing is going to really reinvent how we do things 0:19:04.720 --> 0:19:09.360 like supporting police activities out there in the area of 0:19:09.960 --> 0:19:14.720 data collection and determining fault in scenarios, but most importantly 0:19:14.800 --> 0:19:18.920 taking that data back and improving situations that may be 0:19:19.320 --> 0:19:23.480 hazardous to roadway conditions that result in accidents and things 0:19:23.480 --> 0:19:26.679 of that nature. Externally, if you think of all the 0:19:26.880 --> 0:19:31.639 data that is being collected, simple things that we're able 0:19:31.720 --> 0:19:34.800 to determine by being out there on the roadways in 0:19:34.880 --> 0:19:38.960 these different traffic scenarios are used to improve traffic flow 0:19:39.000 --> 0:19:41.120 and one hit on some of the things they do 0:19:41.880 --> 0:19:45.480 in standing road infrastructure that can also be done in 0:19:45.560 --> 0:19:49.720 the data that's collected through these vehicles. There are scenarios 0:19:49.800 --> 0:19:54.000 where public works departments can utilize the data and we 0:19:54.040 --> 0:19:57.919 can send them examples of where a tree limb is 0:19:57.960 --> 0:20:02.120 growing out over a power line, or potholes in the road, 0:20:02.280 --> 0:20:06.639 or other circumstances that may create a safety issue that 0:20:06.720 --> 0:20:10.359 need to be addressed. And so there's just an enormous 0:20:10.440 --> 0:20:15.080 amount of observation that's going on every time we are 0:20:15.080 --> 0:20:18.560 on a route that that can serve so many important purposes, 0:20:19.240 --> 0:20:23.000 just to proactively address things before they come problems. 0:20:23.600 --> 0:20:27.600 I think it's pretty unique that you have now these 0:20:27.720 --> 0:20:32.359 autonomous vehicles moving throughout communities. They carry people and provide service, 0:20:32.840 --> 0:20:35.800 but they're also a very accurate scanner. 0:20:36.280 --> 0:20:36.520 Right. 0:20:36.960 --> 0:20:40.679 Autonomous vehicles have cameras, they have light ar. When you 0:20:40.760 --> 0:20:43.600 ride the beeps, you actually see in a display what 0:20:43.680 --> 0:20:47.240 the vehicle is seeing, and it's like recording every minute 0:20:47.320 --> 0:20:50.240 detail of the environment, and it's a three D view 0:20:50.520 --> 0:20:52.760 of the world around it. So it's I think a 0:20:52.920 --> 0:20:56.280 unique opportunity and one that we haven't fully utilized yet 0:20:56.840 --> 0:20:59.679 of having these objects that are three D scanners that 0:20:59.760 --> 0:21:03.920 are traversion the community thousands of times a month, and 0:21:04.119 --> 0:21:07.040 they can provide us with an incredible amount of information. 0:21:07.200 --> 0:21:10.600 So I think it's a unique opportunity and one would 0:21:10.600 --> 0:21:13.920 we haven't utilized as much of the data that the 0:21:14.000 --> 0:21:15.480 vehicles generate as we could. 0:21:16.840 --> 0:21:19.200 But there's a lot more to Lake Nona than their 0:21:19.240 --> 0:21:23.360 revolutionary public transportation. One that stands out to me, which 0:21:23.400 --> 0:21:26.600 I hope more towns and cities will consider, is Wi 0:21:26.600 --> 0:21:30.280 Fi access for all its residents, something that's quickly becoming 0:21:30.320 --> 0:21:34.480 an essential utility. Lakenona is also home to the most 0:21:34.480 --> 0:21:38.399 technologically advanced hotel in the world, the Lake Nona Wave Hotel. 0:21:39.040 --> 0:21:42.680 Beyond the new fangled tech for residents and visitors, Lakenona 0:21:42.800 --> 0:21:46.600 also considers itself a living lab community where companies and 0:21:46.640 --> 0:21:51.240 innovators can connect, collaborate, and test their prototypes and ideas 0:21:51.280 --> 0:21:57.240 in a real world setting. And in terms of the 0:21:57.359 --> 0:22:01.200 partnership with Intel, while our start with you, what were 0:22:01.200 --> 0:22:05.680 some of the technologies and help that Intel provided your project? 0:22:06.600 --> 0:22:10.919 So we are primarily an Intel shop when it comes 0:22:10.920 --> 0:22:16.240 to processing. We utilize Intel CPUs for a variety of 0:22:16.280 --> 0:22:19.800 the data that we collect, and we're even experimenting right 0:22:19.840 --> 0:22:23.080 now with Intel GPUs as a way to actually do 0:22:23.240 --> 0:22:27.440 some of the heavier data processing. So it's one thing 0:22:27.480 --> 0:22:32.280 that's always running and always behind the scenes from our perspective. Now, 0:22:32.800 --> 0:22:36.080 we have a variety of partners like people that actually 0:22:36.240 --> 0:22:40.359 engage in some of the more advanced technologies that Intel 0:22:40.400 --> 0:22:43.919 has to offer. But from our part, it's a strong 0:22:43.960 --> 0:22:48.439 combination of tried and true you know CPUs and you know, 0:22:48.480 --> 0:22:53.000 we're getting some pretty interesting performance results from Intel GPUs 0:22:53.040 --> 0:22:56.240 now that make them usable for a variety of data 0:22:56.240 --> 0:22:59.560 crunching tasks for large data sets that we find interesting. 0:23:00.160 --> 0:23:02.960 Yeah, I just want to switch now a little bit 0:23:03.000 --> 0:23:05.960 to the safety side of things. I've actually got a 0:23:06.000 --> 0:23:08.200 bit of a background in mining, and I was around 0:23:08.359 --> 0:23:11.960 with the advent of the whole autonomous mining vehicles with 0:23:12.000 --> 0:23:15.639 those huge dump trucks being in a loaded and driven 0:23:16.359 --> 0:23:19.280 without any drivers, which is a real site to see. 0:23:19.920 --> 0:23:23.840 Going through some of that technology, they had a very strict, 0:23:24.160 --> 0:23:27.560 multi layer approach to safety. There was like seven tiers 0:23:28.119 --> 0:23:30.800 right down to people having actual buttons they can press, 0:23:30.840 --> 0:23:34.480 and it just shuts everything down. How have you tackled 0:23:34.480 --> 0:23:37.760 the approach of safety, particularly in a much more open 0:23:37.840 --> 0:23:39.680 environment than a mind sight. 0:23:40.720 --> 0:23:44.920 First, I would tell you as you look at autonomous mobility, 0:23:45.320 --> 0:23:49.480 safety is the primary driver of why these technologies exist. 0:23:49.680 --> 0:23:52.800 You know, in the US, ninety four percent of all 0:23:53.000 --> 0:23:56.240 accidents and many tens of thousands of fatalities a year 0:23:56.320 --> 0:24:02.000 a result of human distraction, impairmile and error, and that's 0:24:02.040 --> 0:24:07.280 a well known fact. Obviously, taking some of the faults 0:24:07.320 --> 0:24:11.159 of the driver out of the equation by utilizing technology 0:24:11.280 --> 0:24:16.679 that's never distracted, never impaired, and always on is an 0:24:16.720 --> 0:24:21.679 important aspect of this. But It's not just about achieving 0:24:21.720 --> 0:24:24.920 an equivalent level of safety, which is a common phrase 0:24:25.119 --> 0:24:27.359 used at the standards of how do you choose to 0:24:27.400 --> 0:24:30.280 put an autonomous vehicle on the road. You have to 0:24:30.359 --> 0:24:34.119 prove that it's equal to or better than the driven 0:24:34.200 --> 0:24:37.040 vehicle in the eyes of our government, the US Department 0:24:37.080 --> 0:24:41.600 of Transportation and Knits in particular. Well, if you think 0:24:41.680 --> 0:24:45.080 of the opportunity and one hit on some of the 0:24:45.160 --> 0:24:51.159 technologies in Lake Nona to have roadside infrastructure that is 0:24:51.960 --> 0:24:56.959 looking down a roadway, communicating with our vehicles and telling 0:24:57.040 --> 0:25:00.560 us that the trajectory of a particular car at a 0:25:00.600 --> 0:25:03.960 particular speed is telling us it's very likely to run 0:25:04.000 --> 0:25:08.240 that red light. So it's not just about the vehicles themselves, 0:25:08.320 --> 0:25:12.640 it's about that entire connected infrastructure and how you use 0:25:12.720 --> 0:25:17.800 other technologies to give you views of scenarios or predict 0:25:18.600 --> 0:25:22.400 the event that may happen. Given the information that we're 0:25:22.440 --> 0:25:27.639 perceiving from roadside infrastructure or intersection infrastructure, that can be 0:25:27.680 --> 0:25:33.480 fed to these vehicles to dramatically improve safety and reduce 0:25:34.080 --> 0:25:36.960 some of these scenarios that candidly a human would never 0:25:37.480 --> 0:25:40.760 see or understand from their vantage point just behind the 0:25:40.760 --> 0:25:43.520 wheel of a car, and so I think those things 0:25:43.560 --> 0:25:46.200 are equally as important as the great work that's going 0:25:46.240 --> 0:25:49.320 on with the autonomous platforms themselves. 0:25:50.080 --> 0:25:54.520 Now looking into the future, Joe, as you know, AI 0:25:54.600 --> 0:25:58.960 is evolving very rapidly, particularly around generative AI and even 0:25:59.000 --> 0:26:01.960 just the visual AI capabilities. With new GPUs coming out 0:26:01.960 --> 0:26:06.080 all the time, how do you place BEEP strategically so 0:26:06.160 --> 0:26:08.679