Introduction
What is the point of the "Tech. Cars. Machines.", and why should you listen?
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An unedited transcript is below.
Welcome, welcome, welcome everyone to the Tech. Cars. Machines. podcast series. My name is Ali Tabibian and I'm with GTK Partners. I'm going to be your host, interview moderator and occasionally your monologist. And for both of our sakes, hopefully not too much of the latter. We're really excited to be bringing you this series of discussions. The point of the series is to talk technology, [00:00:30] and specifically, how new advances in technology, say sensors, wireless connectivity, artificial intelligence, are changing industry.
One thing to note, what we discovered in preparing our episodes is that for us to deliver insight on some occasionally complex subjects in a lucid and time efficient manner, it helps to script these shows a little more carefully than the typical podcast. If we sometimes sound more scripted than casual, that's why. Since cars are fun and accessible for everybody, [00:01:00] we'll start with the impact of technology on the automobile industry and move to industries that involve machinery.
Occasionally, we'll draw lessons from other areas of the economy, let's say healthcare, where the use of data analytics and artificial intelligence is ahead and sometimes way ahead of the way it's put to work in cars and machines. What you don't get in this podcast is the same stuff you'd find in a collection of news stories. Especially with these subjects, the news tends to be somewhere in the Bermuda Triangle of over-hyped, [00:01:30] shallow and just good old fashioned fake news.
A word about us. Again, I'm Ali Tabibian, and that's a name that's always worth repeating a few times. I'm a co-founder of GTK partners. I'm based in San Francisco and along with my partners around the globe, we at GTK focus on advising companies both large and small on mergers and acquisitions. We occasionally advise them on raising money, generally though that's when there are strategic investors involved. Sometimes we'll invest the firm's [00:02:00] own capital in early stage startups.
Some examples of our clients and companies who've provided executives to speak at our various private events include AAA Insurance, Bain Capital, Benchmark Capital, SisCo, Dignity Health, Mercedes Benz and SAP. The reason I took you through that list is because I want you to get a sense that our client base and who we work with is very relevant to the subjects at hand, you deserve to know that before you keep on listening.
Some more information that's about us, but relevant to the subject, our transaction [00:02:30] experience is very extensive. We've been around for a while, folks. Our industry experience is also pretty diverse. It goes well outside the realm of pure technology. Now, this gives us a big advantage in talking about tech, cars and machines. And that's because it's become pretty clear to everyone that to make sense of tech, cars and machines, you need to be pretty well versed in many, many aspects of the subject that you're talking about. Otherwise you'll come up with interesting commentary, often wrong, but we'd rather [00:03:00] do it the right way.
What we mean is to understand how tech changes cars and machines you need to understand in detail a lot of things. On the technology side, you need to understand the component technologies, sensors, software, micro-processors, the physics of radar, the physics of LIDAR, neural networks. You need to understand the equipment it's being applied to and you need to understand the industry the equipment is being deployed in and you need to understand the regulatory environment in which the industry [00:03:30] operates.
This means you need longevity and diversity of experience, and that's us. Now, I'm sure many of you have a sense for the influence of technology in cars, it's kind of around us all the time, and many of you have a sense for the influence of technology on machinery, but what's the connection the two? Why can we say tech, cars, machines in the same title? There's a lot in common, if not close, to most things that the world of advanced technology is bringing to those two separate [00:04:00] environments.
In each case, one of the biggest questions is which feature in an automobile or a machine is even worth measuring in the first place? In other words, when does it make sense to introduce another sensor into the contraption? This is a big question, because sensors cost money, they add cost to design, they add cost to production and they negatively affect maintenance. Equally critically, they affect reliability. More parts mean more parts to break, and remember, we're talking about some critical, [00:04:30] potentially deadly equipment. Cars and big machines can kill people.
Having a lot of things to measure can also result in over-provisioning of computing resources to handle all the measurements, which of course adds to costs and energy consumption, not things people are looking for. Once you have the sensors, here's some more common questions. For example, what type of data is worth collecting anyway? Should it be reviewed right away, in which case you need to add a lot of computing power, and therefore cost, again into the machine? Is the data going to be kept for a long [00:05:00] time? These are big questions.
Here's an example. If you decide to keep the data for a long time, you have to store it, back it up, and critically, that data may get hacked. Then, you're publicly embarrassed, your competence is questioned, congress may show up, the regulators may show up, all for the sake of data that was not worth having in the first place. More questions. Do I process that data in the car inside the machine, or do I send it some powerful data center somewhere? Or is the answer a little bit of both?
[00:05:30] If I want to send the data elsewhere, how do I get it there? Is it worth the cost of a wireless communication network or can it wait to be sent cheaply on a wired network? Do I have the energy, for example, the battery energy to send lots of data all the time? With respect to software, there's much that's in common between cars and machines in terms of the data analysis techniques. Both the simple stuff, running a regression, a Monte Carlos analysis, and the fancier things, neural networks and computer vision being two examples.
In both cars and machines, [00:06:00] the nuances of how you answer all these questions make a big difference in the outcomes and in the insights gained.
Speaker 2: Tech. Cars. Machines. Subscribe here, or at TechCarsMachines.com and GTKPartners.com
Ali Tabibian: You know, we used to discuss our thoughts on tech, cars and machines in one on one interactions with business executives. You know, sort of an investment banking style meeting. And these executives would range from board members to corporate executives, to venture capitalists [00:06:30] and other members of the species. A few years ago we started a roughly annual executive summit, and by the way, in your minds eye, I want you to capitalize the "E" in the executive and "S" in summit, because we're going back here a little bit, so think of it as Executive Summit.
Attendance at these summits was by invitation only and we got together, and we still do get together, about 200 executives and venture capitalists in Palo Alto, California, including guests from Asia and Europe. [00:07:00] Our first summit was keynoted by Paul Jacobs, who was then CEO and now chairman of Qualcomm. And as you know, Qualcomm is one of the largest and most successful technology companies in the world, especially in the world of wireless.
Most recently, our speakers have been chief information officers from Chevron and Dignity Health, a chief executive officer and founder of a major autonomous trucking company called Peloton. not to be confused with the biking company, the recent head of autonomy software from Mercedes Benz and multiple [00:07:30] executives from General Electric.
You know, the conference is great, but we wanted to more frequently and more broadly interact with our network. So in late 2017 we decided to give our content wider distribution via a newsletter, and something startling happened. Just to give you an idea, the experts told us when we first started thinking of a newsletter that about 1% of the people reading the newsletter would be fantastic. A 1% read rate was cause for celebration. Instead, [00:08:00] after two distributions of the newsletter, we achieved a 34% read rate for each newsletter. So phenomenal, phenomenal, and a cause for even louder celebration.
There was a real audience for our content and some pretty impressive people really liked it. By the way, when you're done listening to my luscious voice, you too can now subscribe to the newsletter at our website, GTKPartners.com, in the content [00:08:30] tab, or at TechCarsMachines.com. The newsletter went to about ten times the audience size of our conference, and we certainly liked that reach, but we really missed two things about the conference format.
First, was the amount of detail you could get into. The conference runs for about three hours of nonstop speaker presentations and panels, and surprisingly, we never really have much trouble keeping people's attention over that time because all of our partners, including yours truly, [00:09:00] really go out of our way and spend an enormous amount of time and preparation making sure the content is tight and sort of a golden thread runs through the whole event.
The second thing that we missed was the live interaction with our speakers. We had some phenomenal, accomplished people, and it was nice to be able to go back and forth with them in front of a crowd and in some cases, take audience questions. The podcast is hopefully offering us the best of both worlds. Now, you're probably asking yourself content, shmontent. How entertaining [00:09:30] is this podcast going to be? After all, many major diseases have been eradicated, famine has been eliminated in much of the world, there's a social safety net and fiscal policies keep inflating the idea of our investments without us doing any work. As a species, we don't really need to be serious people anymore, right? We can demand an all entertainment, all the time existence, right?
We feel like we should be using much more expensive equipment to record this podcast before we're qualified to answer [00:10:00] those types of questions. However, we are responsive people here at Tech. Cars. Machines. headquarters. We're going to make the episodes fun, we'll try to make them light. Occasionally, we'll treat you to what we hope is a pretty interesting diversion. But it's important for you to know that we only have one religion at GTK, and therefore for the Tech. Cars. Machines. podcast, and that is this: high quality content.
If you're the type of person that's going to get really excited by learning, if you're willing to give [00:10:30] us a chance to break down the issues for you so you can then build up your own predictions from a solid foundation, then this podcast is for you. In fact, our approach to financial advisory is for you. The next time you're in a room full of people after listening to an episode, we sincerely want you to be the most insightful person in the room on that episode's subject. We want your to be the Marie Curie, or Sherlock Holmes of the room, so to speak.
You know, we recorded an opener that we discarded and replaced [00:11:00] with this one. My partners quite rightfully didn't like the original opener because it wasn't positive enough. Remember, we live in the era of participation awards. But, I do want you to hear a segment of that original introduction because it'll tell you a lot about what we want to do and how we want to organize this podcast.
This podcast series, like all content we generate here at GTK, is built on our belief in the value of content. No fancy editing, no focus on entertainment, no soliloquies on our backgrounds, no witty [00:11:30] repartee, no loose language, no colloquialisms acting as filler. If you think deep learning, successful investing and successful inquiring are the best entertainment there is, this is for you.
We hope you enjoyed that little snippet. Generally, these podcasts with follow the content and the analysis of the newsletters. They'll add some detail, add some guests, and add the occasional diversion, as we mentioned.
Speaker 2: Here are the upcoming episodes.
Ali Tabibian: One, driverless cars are mostly fake news and two, what the [00:12:00] weird looks of self-driving cars mean for suppliers, vendors and investors. We've got additional subjects that are scheduled. We'll do a deep dive on, quote, artificial intelligence, lots of very fake news, we'll tell you what's exciting. We'll talk about why everyone hates Telsa in the auto industry. We'll have episodes about the selection criteria that consumers use when purchasing vehicles. We'll also discuss the world of machines and have interviews serve as the fulcrum of that series that discusses both heavy and light machinery. We really [00:12:30] hope you'll join us. We're really excited and we think you will be too.
Speaker 2: Tech. Cars. Machines. What more could you want? Click subscribe. Subscribe with a little button in your podcast app, or click the three dots in the little circle. Or visit us at TechCarsMachines.com and GTKPartners.com, where our subscribe buttons are much bigger.