FourWeekMBA

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Let's look at the evolution of AI business models as of now to understand what's commercial use cases are coming up to understand the landscape, threats, and opportunities.

Full video here: https://www.youtube.com/watch?v=r4enjNvU57M&t=57s

You can watch the video here:

https://www.youtube.com/watch?v=TgKlW4g7WRg&t=8s

In the FourWeekMBA AI interviews series, we look at an AI marketplace discovery platform.

The History of Amazon With Brad Stone, author of The Everything Store and Amazon Unbound.

Read next: 

• Apple Value Proposition
• Amazon Business Model
• Amazon Flywheel: Amazon Virtuous Cycle
• Receivables Turnover Ratio?
• Amazon Case Study
• Amazon Cash Machine Business Model
• AWS Business Model

Understanding the business engineering discipline, framed in the context of the FourWeekMBA research (since 2015) on digital business models.

Read: https://fourweekmba.com/business-engineer/

How Netflix is transitioning into a media company and what that implies for its business model.

Read: https://fourweekmba.com/how-does-netflix-make-money/

Framing business competition in an ambiguous business world.

Read: https://fourweekmba.com/how-does-netflix-make-money/

In this session, I interview Federico Faggin, physicist, engineer, inventor, and serial entrepreneur. Federico has been the protagonist and among the founding fathers of Silicon Valley. In fact, with his work at Intel, in the 1970s he has given birth to the family of microchips, on top of which a whole industry has been built upon! Today microchips are everywhere, and Federico’s creation has spurred a business world worth trillions. 

He’s also the author of an incredible book:

Silicon: From the Invention of the Microprocessor to the New Science of Consciousness 

Gennaro [FourWeekMBA]:

To get this conversation started, there are many that I’d like to cover, because your story, it’s interesting because it crossed a few industries that changed, let’s say, the business world in the last decades. 

The first time I heard your name, just for a bit of context, was in 2012. I remember I was reading the book by the Microsoft co-founder, Paul, Allen, and not everyone knows him.

But pretty much remember that this book was published in 2012, by the time I was living in San Diego, California, but pretty much I was reading this book, which is a memoir by Paul Allen. And in the introduction, actually, he mentioned how the project that you were working on back in the days, it was 1974, the 8080 with actually the 8080 chip, which we’ll see about this conversation, actually changed and created the whole industry. Actually, it created the context for companies like Microsoft to drive in the first place.

In the intro to his memoir, co-founder of Microsoft, Paul Allen, explained how Federico Faggin’s design of the 8080 would create the premise for Microsoft to be built in the first place!

• How did you get into engineering and computers when you were a young boy?
• How do transistors work? 
• Can you tell us about your years at Intel and how you got to design the chips that would open up a whole new market? 
• Intel was hesitant to move to the microprocessor, they didn’t think the real market value was going to be there? How did you convince them to move in that direction?
• The 8080 wasn’t just a little improvement on the previous chips. It was like a huge leap forward, right?
• And then you left Intel, of course, what happened there? Why did you eventually leave the company? What did you do next?
• Why do you think it took so long for Intel to actually realize the potential of the microprocessor? 
• How did IBM’s open computing strategy enable the whole ecosystem? 
• Did the antitrust case against IBM influence them in the open strategy decision to computing? 
• How did it go after Intel? Can you tell us a little bit about the companies that you founded after Intel?
• What were some of the lessons that you learned when you transitioned from being an engineer and a physicist to becoming an entrepreneur?
• Can you tell us a bit more about your theory of consciousness and how it connects to your lifelong work? 
• What’s your future objective on the consciousness project?
• Related

Federico:

Well, I was born and raised in Vicenza, Italy, in the Northeast of Italy. And since I remember, my interest was in airplanes and how machine works, cars and trucks, what have you, since I was a small boy. 

And then later, I got interested in computers when I was studying electronics at the Institutional Technical Rossi of Vicenza, which is a technical high school where many do engineering, beginning with engineering there.

And then I ended up working with Olivetti in 1960 and 1961. So I was 18 and 19 at that time. I had the privilege, I would say, to run a project where a small electronic computer was built using transistors. In those days, transistors were still a novelty. I never studied them at school. I had to learn them to work on it. 

It was through this project, where I designed about 60% of an experimental computer and built it with four technicians that worked for me, that I decided that I wanted to go back and study solid-state physics because I was intrigued by transistors.

I mean, clearly, they don’t work using the conventional classical physics that we study. I never studied quantum physics. And in those days, probably even today, in the high schools, you don’t study quantum physics. And so I wanted to understand. That was what brought me solid-state physics.

After I graduated in the University of Padua, I worked for SGS-Fairchild, which now is STMicro, and there, I developed the first MOS technology for STMicro using the metal gate. 

And then I was sent to the US for what was supposed to be six months as an exchange between engineers working for Fairchild, which was the company that invented the integrated circuits. It was there that I came up with the ideas and developed the silicon-gate technology, which was the technology to make integrated circuits that were much better than before. 

And they eventually became the main technology for pretty much all of the integrated circuits built in the world, until recently.

Now the new technology uses more sophisticated technology. But for 40, 45 years, silicon-gate technology was the technology to make integrated circuits. 

It was the technology that made possible the non-volatile memories, the microprocessors, the dynamic memories, the CCD images. Pretty much all the key components of today’s technology were made with that. So that was 1968.

And then in 1970, I joined Intel, and that’s when I designed the world’s first microprocessor. That was made possible with the silicon-gate technology. That was the 4004 four-bit microprocessor.

Gennaro [FourWeekMBA]:

Yeah. Of course, for a little bit of context to the audience on the other side, when you had this experience at Olivetti in the ’60s, actually, Olivetti was one of the first companies that managed to build the first programmable computer, as we’ll see throughout this conversation. But it was also an Italian giant computer company.

It is also worth highlighting that you mentioned a few companies, which history is critical because, in this actual series, I also interviewed the author of a book, which is called the Idea Factory. 

And this is the story of Bell Labs. Actually, before we got to Fairchild semiconductors, who, as you said, was a company who opened the market, was a main player in the transistor space, actually, before that, we had… 

One of the main geniuses at Bell Labs was William Shockley, who built what was called Shockley Semiconductor because he left the Bell Labs in the ’50s and he created his own company. We can say that he was one of the first Silicon Valley entrepreneurs because he moved from the east coast to the west coast. This is a critical step.

Now, Shockley Semiconductor, just for additional context to the audience, actually failed miserably after a few years, I think in 1960. But at the same time, it had assembled a team of very smart, smart people. And among them, of course, there was Gordon Moore would go on to found… within the group that actually later on created Fairchild and also Intel, which you later on worked.

This is pretty interesting because of how we can trace the roots of Silicon Valley. But on your end, when you actually started to work at Intel, it’s pretty interesting because there are many interesting aspects that you mentioned in the book, like for instance, how this was a sort of a side project for Intel. The microprocessor was not the main business of the company. And actually, for a few years, you had to work pretty hard to convince them to focus on that business.

Federico:

Well, in the late ’60s, it was clear that MOS Technology was the only technology that could potentially integrate eventually in the far future in those days, it was thought, a CPU on a chip. A CPU on a chip was sort of… 

But there were few of us that thought that that could be possible, but the technology in ’68, when I joined Intel, the metal gate, the MOS Technology was too slow and was not dense enough. It could only integrate, at best, half of the number of transistors that were required to make a CPU, a small CPU.

But even worse, it would’ve been too slow. It was five times slower than you needed to have a useful CPU because you need about a 10-microsecond instruction cycle if you want to do anything useful with a microprocessor and with a small CPU, irrespective of how much it cost. It was the silicon gate that achieved those two fundamental tasks, speed and density. And that was my work at Fairchild.

Intel understood that. I mean, the founders of Intel came from Fairchild, where I was working. In fact, my boss was one of the first employees of Intel, and Gordon Moore was the head of the lab where I developed this technology. 

So they knew that this was a fundamentally new step, and they basically decided to start their own company, taking that technology with them.

So when I joined Intel, what I wanted, I wanted to create the most advanced integrated circuit possible. The reason, at that time, was not so much that I wanted to make a microprocessor, but I wanted to show that silicon-gate technology was the technology of the future. 

Fairchild did not adopt the silicon-gate technology immediately because we couldn’t do the bootstrap loads with silicon-gate, which was an important circuit that was necessary for the way that logic circuits were done in those days.

And it was only after another year of work that I figured out how to do it. So, when Intel was formed, they didn’t know that you could do the bootstrap load leader. 

Their task was to do memories, which could be made with silicon-gate in those days, but not much more. So when I decided to leave, it was the time when I had developed the bootstrap load, and I wanted to now make the most complex circuits possible.

It was in Intel that they had already a custom project going, but they didn’t know how to do it. So it just happened to end in my lap, so to speak.

And I had the technology to do it, which was the silicon-gate with the bootstrap load and with the buried contact, which is a way to make direct contact within the polysilicon and the junctions so that you can make very dense random integrated circuits.

So that was the story. So I did not go to Intel with the idea of making a microprocessor, though the idea was already in the air. I mean, there were people that had already made CPUs with a number of chips. 

But if you make CPUs with a number of chips, they’re too slow. Or if you want to make them fast, you have to use a lot of power. So, that can be done only if you make special circuits systems for military things or a computer for your own… to sell the computer. In other words, not for commercial application.

:

The customer was Japanese, the customer of the first microprocessor. In fact, it was a family of chips. Was a Japanese customer. 

They wanted to make a set of chips, of which three chips were supposed to be a CPU. And at Intel, the head of the application group saw an opportunity to actually use silicon-gate to actually combine those three chips into a single one by using random access memory, instead of serial memory, which was the memory used in those days. There was no dynamic RAM in those days. Intel was just beginning to develop those.

:

So everything was ready for me to actually do the microprocessor. So when I joined Intel, it was already six months late because they didn’t know how to do it, so the project was sitting there. I picked up the project, and then nine months later, we had a microprocessor and the other three chips, they were the ROM, RAM, and I/O.

Federico:

No, no, this was an opportunistic project. Intel wanted to make memories. They have identified properly so that the magnetic core memories, which were the way memories were made in those days for large computers and also for many computers, were too expensive and too slow. And the technology, the MOS Technology, was really ready to overtake that technology.

:

So they had picked their site on that market. It was only because it took a while for their early memory chips to be adopted that they needed to have some other business. And they took on some custom projects, and one was the 4004. 

The other one was the 8008 that I also did. And the 8080, which was my idea, and I also did, was the microprocessor that opened up the floodgates of the personal computer. As you mentioned Paul Allen earlier, the 8080 was my project in ’73, and it was ready in ’74.

Federico:

Yeah. It was six times faster than the 8008 because in those days, Intel had this idea that they had to use only packages of 16 pins or 18 pins, which was, frankly, crazy, but that’s what they thought. And it took me a while to convince my boss to… First of all, I came up with the architecture of the 8080, which was a big improvement over the 8008, and a different architecture that used 40 pins that would allow to really get the speed that was necessary.

So we went from 12 microsecond access time to two microsecond access time for the 8080. And that was enough to make a personal computer.

Gennaro [FourWeekMBA]:

Yeah. And going a few steps backward, and just, again, to give the audience a full timeline, and then we move forward. When the first transistor was actually invented, I guess, at Bell Labs, it was an interesting invention, but in reality, I guess there wasn’t much that you could do for computing with the kind of transistors. So there were still many things that needed to be done.

One of the main proponents at Bell Labs of transistors, of course, was William Shockley as we said. Shockley left Bell Labs, created the Shockley Semiconductors, which actually assembled a team of very smart people, among which the people that would create the next wave of giants in the microprocessing industry. But the interesting part is that also Shockley was hooked, as we saw in the episode that related to Bell Labs.

Actually, he thought that the technology that would’ve changed the industry would be like the one connected to the germanium. But as you actually explained also in the book, the real jump forward was made when the silicon-gate technology came to life. 

So from there, we see the birth of a few companies, as we said, from Fairchild to Intel, and then, going forward, to other companies like IBM, Compaq, Microsoft, which gave rise to the next wave of development of PCs, which would come to the masses together, of course, with Apple and, going forward, to the internet and all the other waves that we live in today.

Sorry for going back again, but I think it’s very important to stress how important this moment was from a historic standpoint. 

Federico:

Well, just to complete the discussion that you started, the first transistor was a point junction transistor. Point contact transistor. Sorry. It was pretty useless, but it was a proof of concept, and it was done in 1947. And it was Shockley one of the co-inventors and also a Nobel Prize winner, together with the other two, Bardeen and Brattain.

But it took another five years before the first junction transistor using germanium, which was the same material as the original transistor, came to market. And those were the diffusion transistors. 

But germanium was too slow and also suffer from thermal runaway, especially power transistors could basically burn themself up if they were not designed properly and properly ventilated. So, it was really a technology looking for a better way of doing it.

And it was really with the silicon transistor, which was essentially developed by Fairchild. Shockley did not do that. Shockley started in that direction, but Bill Shockley wanted to develop something closer to a thyristor, which was a different kind of transistor with negative resistance. It was not really a good idea.

And so the eight of the founders of the early engineers decided to leave and start Fairchild, among them was Noyce, Moore, and the less known character, which was John Laney, who invented the planar process, which was the real technology, the real invention. 

They made possible very low-cost transistors, and most importantly, integrated circuits. Because the planar technology allowed to make many transistors at the same time on the surface of a silicon wafer. So instead of making one transistor at a time, which was the way they were done in the past, you could make many.

And then, because they were one next to each other in this silicon wafer, you could connect them together. So that was the seminal invention. And it is not told very well in history. John Laney was a Swiss engineer, then he went his own way. 

He, basically, is kind of forgotten, but really he’s the guy that made this seminal invention that changed the industry, because integrated circuits, of course, made it possible to make many transistors connect them together at the same time. 

And eventually, now we make tens of billions of transistors, even trillions of transistors in the flash memories that you have in your pocket.

One terabyte that you can buy is a chip that has more than 1 trillion transistors integrated, all silicon-gate in this case, in them. So this story sort of fixed deployment points. And then the silicone-gate technology was the technology with the idea of MOS transistor, instead of by bipolar transistor, which were all the early transistors, could move forward to a much better technology, because it could be made smaller and smaller and smaller.

Moore’s Law was fueled by the fact that these MOS devices were surface devices, that they could shrink in size. And as you shrunk the size, they were faster, cheaper, and also you could put more on a chip. And that was the key technology that moved forward, for the following 50 years, the industry.

So back to Intel after the 8080, I decided that… Because Intel was… they were a memory company, they wanted to make microprocessors to some memories. They didn’t see the potential of microprocessors. 

It took me nine months to convince my bosses to let me do the 8080, which was the product that really made a big turn in microprocessor because, for the first time, you have a two microsecond instruction cycle. They were close to many computers at that point. Many computers were around one microsecond, half a microsecond instruction cycles in those days.

So, all of a sudden, you have a real step forward, and I decided to start my own company. So I started Zilog, and Zilog developed the Z80. That was my other idea. The Z80 came out in 1976. That Z80 had… 

it was an improvement, much, much big improvement over the 8080. It was a set of chips with which you could build very powerful personal computers and computer systems and control systems at one microsecond access time as they came out. You could do better later on.

The Z80 actually was a very powerful microprocessor. It’s still in volume production today, by the way, 45 years later. So, it is one of the… it is like a Volkswagen that had a long life. So, that was my next move, which was to start my first company. And so I moved from engineering, essentially, to entrepreneurship. I became an entrepreneur, and the rest of my business life was as an entrepreneur.

Federico:

Well, it took a while for the microprocessor to reach the business level that memories were because dynamic memories became highly successful. And so the business of dynamic memories was much bigger than the business of microprocessors early on. 

And it was really because of IBM that Intel then decided to change course, actually two reasons. IBM, the fact that IBM adopted the 8086 of Intel or 8088, which is a version of the 8086, but also even more important because the Japanese developed dynamic memories that were much more reliable than the American manufacturer. And the Japanese started taking over the market.

Intel was in real trouble. If Intel did not have microprocessors in those days… I’m speaking about ’83, ’84… Intel would’ve probably failed. For example, Mostek, which was a major producer in those days of the dynamic memories, actually failed. It was a company that was doing very well, but they could not overcome the competition of the Japanese, and basically, the company failed. The company simply went down.

So at Intel, in ’84, they had to make the decision that they had to concentrate on microprocessor because they were losing their shirt on dynamic memories. And so they were lucky that IBM had adopted them, as you remember the C was 1981. So the PCBC was really a major development in the informational industry like the silicon technology was for the industry, because it changed the course of the industry.

The IBM development of the personal computer was what changed the history even of the personal computer. It wasn’t Apple that did it at that time. It was really IBM. Their adoption changed the landscape, and the personal computer became a business tool, in addition to a consumer good. Then Intel, their leadership ran as fast as they could to keep the competition from catching up with them and drove the industry for the following 25, 30 years. So, that’s what happened.

It was only… Apple, in fact, was almost done if it wasn’t because Steve Jobs going back to Apple. His vision was so powerful that, basically, it changed the industry again. But it was not in the PC that Apple changed the industry. It was in the iPhone, the iPod first, and the iPhone. 

And then of course their PC success is a consequence of having regained leadership in a new market in different ways than any other PC manufacturer did, because as you know, now Apple even makes their own microprocessors.

But IBM was the one that carried the day, so to speak. IBM and the clone manufacturers of IBM computers carried the day for the following 20 years, from the early ’80s until early 2000.

Gennaro [FourWeekMBA]:

Yeah. So it took like a decade almost to Intel to understand that they needed to jump on the other microprocessor market. And as you said, it took a lot of foresight to do it before, because the memory market was much larger.

 And when it comes to a futures market, it’s very hard to understand how big it’s going to be. So it’s a huge path. So it’s also understandable that it’s not easy to predict how big a market is going to be. Just a few people, as you said, like Steve Jobs with a huge vision managed to create those new industries that turned out to be much larger than the previous ones.

So, that’s not easy… One of the hardest things in business, I guess, it’s really to develop a whole market from scratch. This is probably one of the hardest challenges for anyone who is doing business. Also, as you point out in the book, in many cases, when it comes to new technologies, it’s not just the single technology itself, but the old ecosystem that needs to develop around the technology. So, that’s a huge, huge component.

And also another point, which I think it makes sense to emphasize, is also the fact that, as you mentioned, IBM opened a whole new industry, and it created a whole new set of players also because IBM went for an open system, which was something completely different than what the company had done in the past. 

Federico:

It was unexpected and, frankly, surprised everybody, because that was the opposite of what IBM… not just another way, the opposite of what IBM always did, which was to control every piece of their technology, including making transistors and the circuits. In those days, IBM was the largest producer of integrated circuits in the world. They were all used to making their own computers. IBM was a giant.

Basically, they almost committed harakiri with their decision, and it was because they did not understand the phenomenon that was just developing under their eyes. The personal computer took over the industry. 

And it was because the technology behind it, which is the semiconductor technology, could make almost progress, basically doubling every two years. After a few years, doubling every two years makes a big difference, as you know.

Nobody in those days could… and say the early ’80s, nobody thought that this Moore’s Law, so-called Moore’s Law, because it’s just an observation. Because the real law is the law of theming, that basically you can scale the transistors and make it smaller, and smaller, and smaller, and that could last so long.

I mean, basically, we didn’t think that we could go to three nanometers. I mean, just today, it’s crazy to think that you can make transistors that have a critical dimension of three nanometers. 10 atoms next to each other is a nanometer. I mean, it’s amazing.

Gennaro [FourWeekMBA]:

Yeah. That’s extremely important to keep in mind when new technologies are developing. In the early days, the way this technology could build up over time might seem impossible, but they tend to really align around very strong incentives. 

Also, of course, as you said, IBM almost killed itself in the long run, even though they didn’t understand it at the time, but it was eventually good for the industry because many other players came about. So definitely, overall, it was great for the industry.

Another thing, which I remember reading somewhere a few years back, actually, I think there was also a first antitrust case in ’69 against IBM, which might have also pushed the company toward needing an open approach. It wasn’t just, I think, they were blind. I think they were also trying to avoid anti-monopoly or antitrust cases against them. 

So maybe in this circumstance, it might be that IBM was also a bit threatened by the regulators. And so this fear might be that it made them completely change direction? 

Federico:

No, I don’t think so, Gennaro, because… It was because they couldn’t do all the pieces that were needed. So they decided to go, for example, get an operating system that probably 10 guys in their shop would’ve done in six months if they understood what they were getting into. 

But they were in a hurry. They wanted to come out with a product, and the product was done outside the watch of the divisions because it was done as a skunkworks in Florida under the CEO at that time.

It was just that it went out of hand, and they didn’t realize… And, of course, the people that they dealt with, like Microsoft, for example, Microsoft did not want to give them exclusivity. Most companies would’ve given them exclusivity, and therefore they would not have gotten themselves into this problem. 

But they accepted the conditions of Microsoft, and that actually allowed every other company they wanted to use to be in that business to have access to this software base, which was the real riches. And so that’s how it worked.

Gennaro [FourWeekMBA]:

Interesting. So it was really a huge, huge oversight.

Federico:

Yeah. No, no, because nobody could accuse IBM if they had made their own operating system or their own microprocessor. So there was nothing to do without being open in the industry, it is what anybody would do in those days, would’ve done those days. It was just… They just didn’t understand what they got into.

Gennaro [FourWeekMBA]:

Yeah. And most probably they also thought that this was still like a hardware game, not really a software game. 

Federico:

Absolutely. Absolutely. Because in those days, software was not a business to speak of as a software business. I mean, it was more of a custom thing, or you do your own, and that’s about it. It was not a market for software. I mean, it was a complete revolution that caught by surprise even the ones that should not have been caught by surprise.

Federico:

Well, I founded Zilog, and Zilog was quite successful in the early years. But the only venture capital that I found in 1975 was Exxon because there was no money in VC that year. That year was unbelievably unbelievable. It’s the low ever in the industry. There was only $10 million of VC invested in 1975. Now, of course, but even 10 years later, it was just one startup company that would get $10 million.

So we started Synaptics with half a million dollars. The only financiers that we could find was Exxon Enterprises that, in those days, was doing that work. But they had a hidden agenda, and I didn’t see it early on. So we found ourselves competing with IBM, essentially, in the PC business. That’s how the decision was made by IBM to not to use Zilog products because the Zilog products were better than Intel.

So basically, Zilog was after the IBM decision became and also ran their Z8000, which was a much better processor than the 8086. Basically, it was not adopted widely as the 8086. And that was really what…

But I didn’t know that when I left, because I left in 1980. At the end of 1980, I left Zilog because I just did not want to be a division of Exxon. And so that was not what I had started the company for. I didn’t want that. And I decided to change the road. So then I started a company that developed the first voice in data workstation, which was, unfortunately, was not successful, although the product was really amazing. It was an unbelievable product.

It made people understand what it means to integrate voice and data into a single unit. And I know that, in a very clear way, Steve Jobs was really amazed by that product, because he told me so. And in some way, that product became the iPhone 20 years later. It was really that kind of product, but of course, with the technology that was… they couldn’t do the many things that the iPhone did.

And then I started Synaptics where I worked with neural networks early on, when people thought the neural networks… The people that thought they knew about artificial intelligence thought that neural networks were a bad idea. But in fact, they were the right idea because now AI works because neural networks work.

And so I worked with those for a while, and then… But it was too early. And so I decided that it was time to come up with a product. Otherwise, the company would not have succeeded. And so we invented the touchpad and the touchscreen, which changed the way we interface with our computer. The company is now a major company that’s still one of the major suppliers for touchpads and touchscreens in the world.

And then I ran a company that was started by Synaptics and national and Caver Mead. And there was Foveon, making new imagers, special imagers with new technology, which that company was then sold to a Japanese company. And then, about 12 years ago, I decided that I had enough of business. And I wanted to dedicate myself to the study of consciousness, the study of what makes us different than machines. And that was something that started… my interest there started when I was working with neural networks and studying neuroscience back in the late ’80s.

And that is my current work and my current passion, and also my current contributions, because for the first time, we have a theory of consciousness that makes sense. In fact, it’s the first theory of consciousness, instead of being… just talk about consciousness. It’s a real theory developed with one of the top physicists in the world in the area of quantum information.

Gennaro [FourWeekMBA]:

Yeah. And before we jump to that, because finally, finally, your work is extremely valuable, the work toward creating a scientific theory of consciousness, especially where many scientists have neglected it over years, or at least they built a materialistic, as we’ll see, version of it. But anyhow, before we jump to that.

Federico:

Well, I think that the biggest thing for me was realizing that science cannot solve the problems that an entrepreneur can solve. Of course, it can help. But basically, an entrepreneur has to figure out how things are going to be two, or three, or four, five years from now. When you make a decision of what product to make, for example, you had to figure out what product the competition might develop that could compete with your product.

So those are all impossible-to-solve problems. When you develop a product, you have a technical problem, and those technical problems can be solved with the technology and the science that you know, is known. If not, you probably wouldn’t even think of doing it. And so, all the answers are under your capacity, but when you have to figure out the way the market will be five years from now, you cannot do that.

That’s where I had to rely more and more on intuition. I found that I had a good intuition, but I had neglected to pay attention to my intuition in the past, though, it served me well, also gave me I ideas for many inventions. They came through my intuitive channel. But when you had to run a company, intuition is even more important, because you had to do many things that you never did before, never even thought before.

And that was intoxicating almost. It was great. I mean, I loved it, even if it was quite stressful at times, because if you don’t know how you’re going to pay your employees-

Gennaro [FourWeekMBA]:

Very painful.

Federico:

If you don’t have any money, that’s not a fun place to be. Fortunately, I never found myself… I found myself close to that, but never where I had to sell my home to do that. 

But I would say that the job of running companies, starting companies then running companies was complementary to my technical ability. In fact, EU is my technical ability, but it developed parts of me that I didn’t know I had. I call them the belly part, the courage, taking risks, doing things that you don’t know whether they’re going to work or not, and generally being successful at that.

So I grew up a lot through that process. I look at life as an opportunity for growth, more than an opportunity to make money. And so for me, being an entrepreneur for 34 years has been really lots of fun and lots of learning. 

In fact, that’s what brought me to also open my heart, which is not what you would expect from an entrepreneur, but that’s what happened. And that was the third piece that was missing. The Head, heart, and belly are the three parts of us that need to come into harmony and develop so that we are full human beings.

Gennaro [FourWeekMBA]:

Yeah. And it’s worth highlighting how probably this, as you said, this journey as an entrepreneur that you actually developed other parts that went behind the logic as a physicist and as an engineer. 

And from there, actually, you developed a theory of consciousness, which it was very compelling to me. First of all, because it comes from someone who’s been a practitioner for many years, someone who has jumped to become an entrepreneur and someone who actually understand the world of quantum physics, which it’s worth remembering it is what enabled the innovation of microprocessor in the first place.

Your point of view, it’s so compelling because you say… Actually, your approach, it’s quite the opposite from traditional science of today, where consciousness is more a byproduct of random processes that happen in, let’s say, in the brain. According to you, it’s something completely different and it’s something completely much, much larger than the physical world. 

Federico:

Yeah. Well, basically, the question of what is… First of all, what is consciousness and where does it come from is a question that scientists really neglected. It’s been mostly a philosophical question or a religious question. But if we say, just without bringing religion into the before, just in terms of human thought, this really has been a philosophical issue since people started writing about.

So consciousness is the fact that we have an experience. We know because we experience through feelings and sensations. And so where are feelings and sensations coming from? Nobody knows. And in fact, nobody even tried to answer that for the longest time. It was only the success of materialism that started with the idea of explaining the outer world, the world of objects that interact in space and time. That was the physics that wanted to understand that world, and the success of physics brought with it, more and more, a way of thinking that got to the point where people were thinking that, “Well, consciousness has to come out from… has to emerge from the brain. The brain is a complex system.”

But that’s not an explanation. As you know, if you want to explain consciousness, you need to explain it as a mechanism. How can you get sensations and feelings out of electrical or biochemical signals? And nobody can do that. And in fact, it doesn’t make any sense. If you start thinking about, as I did, starting about 35 years ago, how can I make a conscious computer? You cannot make a conscious computer because a computer is deterministic.

So it means that the next instruction is what follows the previous destruction, as the program tells you what to do. So there is nothing to be conscious about. Consciousness, actually, is what actually gives life or gives meaning to information. Information without consciousness would make no sense.

If the world were a deterministic world, it would be exactly like a computer, and information would make no sense. Because the next signal, the next instruction would simply follow the previous one. And if you look at the probability of that, that probability will be one. Therefore, the information carried by the next state is zero, because the probability is the log of one over P, the probability. And so if the probability is one, basically you have no information. Basically, there is no surprise.

The next state is going to be deterministically determined by the previous state. And consciousness works because information is not zero. Information makes sense because it is never zero. It can be zero occasionally, but it is also some type of… some information is there, but it makes sense only if you’re conscious.

And so information and conscious, in other words, are two faces of the same coin. There would not be information if there were not consciousness. We would be machines, and we would be running like machines in the dark without any kind of experience, any kind of feeling, any kind of sensation. So if you start with that, then you say, “Okay, well, look, how come that quantum physics is probabilistic then?”

Quantum physics is describing a world made of probabilities. That’s interesting because that sounds like they’re describing information. And in fact, in this theory with D’Ariano, Professor D’Ariano, who is a… Professor D’Ariano is a professor of quantum physics and theoretical physics at University of… is the head of the theoretical physics group at University of Pavia. He and his collaborators have developed what is called OPT, Operational Probabilistic Theory, which is a new theory that derives quantum physics from purely informational postulates.

So quantum physics is about quantum information, and six postulates show you that you can build quantum… like Dirac equation, for example, out of this postulates, which are purely informational postulates. And so when I found this out six years ago, that was in line with what I thought, because I thought the conscious and information were two aspects of the same thing. So I started working with him and getting close.

Essentially, we developed this new theory, which is a panscientist theory of both consciousness and of free will, and because quantum physics is also compatible with free will. So basically, what he says is that a system, a quantum system that is in a pure state, which is a very distinct state, it’s a state that cannot be known from the outside because quantum information cannot be known from the outside. That’s a property of quantum information in a pure state, you cannot know it.

You can only… If you measure it, you can only know some of it, but you cannot know that state. We said, “Okay, that state is a conscious state to the system that is in the state, that’s a postulate.” So it means that consciousness is the feeling or the knowing that a system that is in a quantum state, in a definite state, but that cannot be known from the outside, but it can be known from the inside. And so that explains why we have experience.

You see, in other words, our experience is because our consciousness is a quantum system. It does not even exist in space and time. It exists in a vast reality, which is the reality from which there will be, according to physicists, the collapse of the wave function that shows some form of information, which is classical information into the space time, from a world which is vaster, that can only be expressed or described using Hilbert space, which is a space of end dimension and very large number.

And each dimension is a complex number. So it’s a very abstract mathematical space that describes states that have this property that cannot be copied. And exactly like my experience. My experience, I am the only one that can know my experience. I can tell you what I’m feeling. I can tell you what I’m thinking, but you cannot know my experience, and I cannot know yours.

Because consciousness is the fact that we have an experience, which is private, where classical information is a public information. You can take the information of a computer, you can copy into another memory. So a computer can never be conscious because it has no privacy. You see?

So starting this way, you find that you can explain all kinds of things that cannot be explaining any other way. And so its another way of saying that consciousness and free will are fundamental. They don’t come with the brain, they are the one that created the brain. They are the one that created the life that we live. So it is exactly the opposite of what science is saying.

Science is saying the conscious emerges after life. In fact, not even after life. After life is sufficiently complex to develop brains because it emerges from brains. But how can a brain made of matter, which is unconscious, create consciousness? It’s incongruent to think that you can get something out of something that doesn’t have it.

It will be like saying that matter, that has no charge or no magnetic spin, can create electromagnetic waves, when these waves requires that there be some fundamental properties in the elements of which all reality is made that has that property, which is, of course, the charge of electrons and the spin of electrons, and other particles. There is no explanation. Science has no explanation today for the fact that consciousness exists.

So now we have the first theory that tells you, you don’t have to have any explanation. We can show you how consciousness creates matter. So we don’t have to explain why matter exists, because matter in conventional science is taken for a fact, okay? Let’s take for a fact that there’s conscious in free will, which is consistent with quantum physics. And then we can show how matter emerges.

Matter is simply the play of information of entities, which are conscious that communicate with each other using symbols. So these symbols, which these entities communicate with each other, are what we describe as matter in physics. So the dance of those symbols are the laws of physics.

Gennaro [FourWeekMBA]:

Yeah. And these actually requires our restructuring of the way… As you said, the scientific approach looks at things, which is primarily mechanistic approach and an approach that looks at external things as it’s all that there is in the world. And that’s why it’s such an interesting perspective. And as you explain, also, these… Even when a machine, let’s say, a quantum computer is driven by a quantum processes, that still doesn’t make the machine conscious. 

Federico:

Basically, a quantum computer performs transformation, which are… they’re called unitary transformations. Those unitary transformations basically maintain… You could say that a quantum computer may be conscious, but it’s not self-conscious. And it doesn’t have free will, because free will require a consciousness, a real consciousness that allows you to do things knowing that it is you that is doing those things.

In other words, self-consciousness is something that goes beyond the simple awareness. In English, there is the word awareness, which is a softer form of consciousness, because the consciousness will be like self-awareness. It’s something deeper. In other words, conscious is awareness that is aware of itself. It’s aware of being aware. So that’s consciousness.

And consciousness is something that even a quantum computer cannot be. It may be aware, but not self-aware, unless you have a living system. But then even a living system, the consciousness of a living system is a quantum system that is connected with the living system, which is a quantum classical system. So a living system like you and I, our quantum classical systems… not classical. We are not like computers, we are much, much more sophisticated machines than computers. We are still machines, but we are control by a conscious entity, which is who we really are, which is not the body.

So our conscious is not in the body. Just like when you drive the drone, you control a drone, your consciousness is not in the drone nor in the program of the drone. I mean, the drone is something that is controlled by you, but you’re not in the drone. And in fact, even the you that controls the drone is another body, but is a quantum classical body instead of a classical body like the drone that is controlled by quantum body, which is a real consciousness. So when the body dies, we don’t go anywhere. We are still where we are, which is in this other reality, which is deeper than physical reality, which is, today, explained via the Hilbert space, the quantum systems in Hilbert space.

Gennaro [FourWeekMBA]:

Right. And this is also true when it comes to artificial intelligence approaches, which try to mimic the way we do things. Like, for instance, I’m thinking about one-shot learning, which is something that is becoming very popular now. So I guess still the machine follows different processes.

Federico:

Yeah. What I would like people to take seriously, these ideas, because this idea will completely change our worldview. Today, we are told that we are machines. And if we are machines, then we can be superseded by machines that are more intelligent than we are. So it is true that if we are machines, the machines could turn against us, but we are not machines. But if we think that we are machines, we’re going to behave like machines.

We are caught in this mirage that we think that we are machines because it looks like that we are machines. But if we actually begin to think about, experience who we are, learn about ourselves, quieter mind, and figure it out, then we can find that we are much more than machines. In fact, living systems are much more than machines. We don’t know how to build a living system. We do not know how to assemble a living system.

We start with life, we just around with it, and we get other life, but we cannot put together the pieces like we put together the pieces to build a computer. And the fact is that even living systems are not sophisticated enough to be conscious on their own, but they can be connected with conscious beings so that… They’re like the drones that are connected with our body that behaves like a classical computer when they talk to a… not a computer, like a drone.

There is three levels of reality. There is quantum reality. There is the quantum classical reality, which is the reality of our body that can be controlled by the quantum world. And then we can control classical systems like computers and drones. And so that’s the way that reality works. And if you begin to think in those terms, then the universe has meaning and purpose, which is not what science is telling us today. And that’s a big change of mind.

Gennaro [FourWeekMBA]:

Yeah, absolutely.

Federico:

And of heart.

Gennaro [FourWeekMBA]:

Absolutely. Huge change, and especially this is a change that will make technology really enhance humanity rather than try to destroy it. So it’s extremely important.

Gennaro [FourWeekMBA]:

Thank you, Federico, for taking the time. It was really a pleasure, a huge honor. Thanks again.

Federico:

Thank you, Gennaro. It’s a pleasure for me too.

Gennaro [FourWeekMBA]:

Thank you.

Listen Also:

• History of Bell Labs
• History of AOL
• History of PayPal
• History of SpaceX
• History of Tesla

In this session, I interview Tim Higgins, a reporter for The Wall Street Journal, and the author of a great book: 

Power Play: Tesla, Elon Musk, And The Bet Of The Century

Gennaro [FourWeekMBA]:

It's really my honor, because your book, it's one of the best business books I read so far. And I'm telling you, I read a lot of business books and it's a great book because it's very well done research into the whole history of Tesla. I mean, you can find many accounts about Elon Musk. I mean, he's one of the most popular business people in the world. But the whole story of Tesla, how you tell all the details and the evolution from the early days, I respect people that do well-done research, and this is incredible research. So thanks for that.

Tim Higgins:

Well, I appreciate that. I appreciate it. When I started working to write this book in 2018, I thought it was going to be about the collapse of Tesla because it looked pretty bleak. 

But as the years went on and I continued to work on it, it really became clear that this was going to be one of the most remarkable corporate turnarounds of a generation with the success of the Model 3 and Tesla becoming the world's most valuable automaker. 

So a lot of drama in there for the reader, which makes a good book.

Gennaro [FourWeekMBA]:

It would actually make a good movie. I actually realized that in this series, in this podcast, I'm interviewing a lot of authors about which books might actually make it into great movies or series. So let's get started from there because as you said, the near-death experience that you're talking about, of course, is one of the last and hear that experiences of Tesla in 2018. And then, as you said, one of the greatest turnarounds, but Tesla is a company that is around for many, many years. 

Tim Higgins:

Tesla began as really a very unlikely idea, a really wild startup in Silicon Valley. The founding CEO was a man named Martin Eberhard, and Martin was almost a serial entrepreneur in the Silicon Valley of the day, which was really much different than it is today, where you see these huge billion-dollar valuations. 

Back then, the ambitions were a little bit smaller, but the way to change the world perhaps was not. I mean, he wanted to bring out an electric car. He was a guy who was in middle age, going through a divorce, and the best anecdote for a divorce is to get a sports car. 

He was concerned about the environment. He was concerned about global warming, and he thought that an electric car would really be the way to go.

And as he was looking for an electric car that was cool, there really wasn't anything out there. There wasn't a sexy sports car. He wanted something like a Porsche, but electric and it just wasn't really available. 

That got him thinking that maybe there was room for that as the world, the early signs of potential electrification of the automobile were out there. 

You think about the Toyota Prius, which was a hybrid, people were concerned about these kinds of things. And so he thought maybe there was room there to create an electric sports car company.

Gennaro [FourWeekMBA]:

And as you point out in the book actually, even though we are in 2003, many people might not know that actually, other entrepreneurs were trying to build already electric cars. So there was already a history behind it. And actually, there is a detail in the book, which you mentioned, which is about the fact that even when gas-powered cars won against electric cars at the end of 1800, the beginning of 1900, there was still a battle going on. This idea of producing an electric car was something that was in the air.

Tim Higgins:

Right. It was not a new idea. The electrification of automobiles was not a new idea, but going back 100 years, the challenge really lay with the battery technology. We saw General Motors try to come out with a mainstream or a more mainstream electric vehicle ahead of Tesla called the EV1. 

The challenge that companies were having with batteries was there was a trade-off, whether it was cost or range. This was one of the really, the big stumbling blocks. One of the common things you saw from the established automakers as they thought about zero-emission vehicles, was as they were looking really for the perfect technology that they could introduce. 

Whereas, one of the insights that Martin Eberhard had early on, along with one of the key hires, JB Straubel, was the use of technology that was really already proven, and that is lithium-ion batteries.

Those are the cells you have in your laptops at the time. They were becoming popular because of the video cameras. Their thought was if they could take enough of those, they were fat finger size cells, and string them together and manage them with software, they perhaps create enough power or enough juice, if you will, to power an automobile. 

Martin's insight was that the calculation at the time was they were going to need about 6,000 of these cells in a car, that if they were buying 6,000 cells per car, and they were going to make thousands of cars, that they would immediately become one of the world's biggest buyers of lithium-ion cells. 

And then, in theory, that would give them scale that they could then get better pricing. And then that could help bring the price down to make it more affordable and more doable in the car.

And so that was the bet, and that was really the big insight that they brought. The challenge, however, was lithium-ion cells can be very volatile. As they were developing the early car, the early Roadster, they became to the realization that they have a challenge here. 

They had a real problem that a percentage, a very small percentage of cells being made are going to be defective and essentially become, they're going to ignite on fire. You're not even going to know which cell it is. 

If they were packing thousands of these cells together, then the likelihood of a car catching fire was actually not as remote as you might think, and that was going to be bad. That was a really existential moment for the early company. 

And that is really, they set out to figure out how to stop that. That's really the big technological innovation of Tesla, was figuring out how to manage the battery pack through a combination of mechanical engineering and software to prevent horrific fires from defective cells.

Gennaro [FourWeekMBA]:

So the first years really was the main challenge was really prototyping a vehicle electric, a vehicle that would work. As you said, this was a huge technological challenge. 

For a bit of context to the audience, as we said, we are in 2003, Elon Musk was already, I think, about a couple of years into SpaceX. He had sold PayPal, so he was already involved with another very challenging company. 

Tim Higgins:

So Martin Eberhard had founded Tesla Motors with the idea that he was going to create an electric sports car called the Roadster. He had a co-founder and a couple of co-founders and they had an office in the Valley, but really that's about all they had. They had a business plan and they were spending their time looking for funding. 

They had a prototype that they had worked with, a shop down in the LA area that had used some lithium-ion cells in a kit car, so they demonstrated the idea, but they needed money. 

And the problem with the idea of a car company was that the Valley at the time, the traditional Silicon Valley venture capitalists investors, were not geared towards the idea of taking these kinds of gambles.

They were really geared towards investing in software in part because you could see the returns faster, which they needed to do for their investors. And so they were really getting laughed out of the Valley. 

They came up with the idea that there was this guy who was clearly had an appetite for huge unconventional investments, so that was Elon Musk. He made his fortune, he made his second fortune, his real fortune through PayPal. 

And now, as you said, he left the Valley and he was in the LA area working on his rocket company with the idea of making space travel more affordable, and going to Mars with this really hairy, big, audacious idea. 

That's how he was getting some early attention. And so Martin Eberhard went down to pitch to Elon Musk, "Do you want to invest in Tesla?"

And Elon did. Little did Martin know the backstory of Elon's interest in electric cars. Elon had been interested in the idea of an electric car for a long time. He had pursued the idea of converting a sports car into an electric one with some other people. He, in fact, had already had a meeting with a promising young engineer out of the Valley named JB Straubel, who would later get hired by Tesla. 

JB had a very similar idea around the battery technology that we discussed on lithium-ion cells. And so Elon was primed if you will, for this pitch. He came in as the largest investor and became the chairman, and that's really when the company gets going with that money. 

Then it's a race to hire people. It's a race to figure out if they can find somebody to build the car. It's a race to figure out if they can actually do what they think they can do.

Gennaro [FourWeekMBA]:

And you pointed out a few key points, the early days and how Musk got involved. As we see, the history gets very interesting, and you mentioned really some of the key people like Straubel, who would really play a key role for years to come within Tesla. Probably one of the few key people that Musk could trust within Tesla. 

Tim Higgins:

Well, none of these people have experienced car guys, if you will. They didn't have experience in the art of bashing metal. A lot of startups don't have experience and that's sometimes why they are successful, is because they're looking at the world, looking at problems in a different way than established players.

And so the company was founded, Martin and his team had done research on what they thought and built it on basic assumptions and these sorts of things, while a lot of the assumptions just turned out to be too optimistic. 

A lot of the issue was around just the cost. The cost of everything was just more than they anticipated. The rate of the ability to do things was taking longer, which then, of course, makes it more costly. And then the reality is designing, developing, and building a car is incredibly complex.

At a certain point, it just became that the project became more complex than Martin Eberhard was accustomed to dealing with. Tesla had just become too big. The challenge of putting that car, the Roadster into production nearly did the company. 

It was monumental. They had problems with suppliers. They had problems with capabilities. They had problems with just the way that they were financing the company. And so all those things got away from them and really put them in a bad position financially at this point in 2007, 2008, when then the world changed as you recall. The great recession and liquidity around the world locked up, and Tesla was having a hard time accessing the cash it needed to stay alive. 

At the end of 2008, the company was very close to bankruptcy. It's one of those monumental periods where Elon Musk at this point, assumes control of the company. He becomes the CEO and he puts basically every penny he has left into keeping the company afloat, in order to make it to the next day to keep fighting.

Gennaro [FourWeekMBA]:

We can trace the first near-death experience of Tesla between 2006, 2008. There have been many near-death experiences throughout the years.

Tim Higgins:

The near-death experiences tend to come for Tesla and for all startup automakers when you're in this very delicate period of ramping up production and sales actually hitting where the money is coming in from the sale of the car. 

This is a very capital-intensive period, and it's very easy to make a mistake and the planning of the periods of production or delivery. This is just a really, really hard thing. I mean, it's ramping up a new car is hard for the most established carmakers, let alone for a company that doesn't have that experience or industry knowledge. 

And so in hindsight, it's not surprising that it nearly did them in. What's actually surprising is that they were able to survive. They were able to survive in part, because of Elon Musk's ability to sell the company.

The sale of the Roadster, which was their first electric car, was really basically $100,000, a two-seat sports car. Used a lot of the parts from a sports car made from Lotus. The guts of it, the internals were the electric vehicle, and it hit a core. It hit really very popular with early adopters, techies, people in California who were worried about the environment. 

And then one of the underlying things was, it was a cool car. It had a performance. The electric car was in a lot of ways, perfect for that sports car market, because the zero to 60 speed right off the line, which we call the torque, you just feel it instantly, it's a wild ride. 

That's really appealing to car buffs if you will. And so they had sold a lot of these vehicles, pre-sold them to these people who were very excited. And so that was really important.

What was really important, Elon Musk brought to the table as he was able to then sell the vision of what Tesla were wanting to accomplish in a multi-year, the future of the car. 

That really became very important in 2009, 2010, 2011, 2012, period, as the company is essentially trying to get the hundreds of millions and eventually billions of dollars it's going to need to go from being a niche sports car company, to doing 2,000 cars over the course of a few years, to tens of thousands, hundreds of thousands, millions of cars. 

The key thing was always the need for cash and new investor cash to keep the lights on, to keep that effort of development going. Elon Musk turned out to be very good at selling that vision to a lot of investors, even when the company was struggling to stay afloat.

Gennaro [FourWeekMBA]:

There is actually a recurring point in the history of Elon Musk, also looking back at the history of PayPal. There is an old episode on the series about that, where he doesn't want to be the CEO of the company, but he ends up in the position of becoming the CEO. The same happens to Tesla when eventually, Elon Musk 2008, appoints himself as the CEO of the company. 

Tim Higgins:

It doesn't end up well between Martin and Elon. It started off seemingly well. I've read the emails between the two. They seem to have some common bond over the idea of product development and the idea of what consumers were going to want and similar ambitions. 

But ultimately, when you work for Elon, it's Elon you're working for, and he's very demanding. Part of his success is not taking no for an answer. Part of his success is not resting on the easy way of doing something. 

And so you see a pattern over time of him struggling to trust the executives that he hires to do jobs. Not giving them a lot of rope to figure things out, and micromanaging them at very key times for the good and the bad.

Even to this day, he talks out how he doesn't want to be the CEO, how he doesn't like it. But make no mistake, he still wants to be the boss. 

He might not want to deal with the boring parts of running the company, but he wants to have the ability to put in place his broader vision, and not get tied up with the bureaucracies that you see at traditional big corporations that have concerns that are very, just understand if you're a publicly-traded company. 

He's thinking bigger, and that's some of the challenges you see over the years. And so when you talk about how his relationship with Martin ended up, it didn't end up well. From Elon's perspective, he would talk about how he felt like Martin wasn't keeping him in the loop about what was going on at the company.

Martin would argue, and Martin has argued in the past, that that wasn't the case. You look at the company records and it was very clear the board knew that it was struggling. Ultimately, it oftentimes comes down to Elon's risk tolerance as an entrepreneur. 

Somebody who did not come from a traditional corporate background has a risk tolerance that's unlike anyone out there. Willing to time and time again, bet everything on his vision. He looks at the probabilities and he's willing to go because he thinks that there's a chance of success. 

That oftentimes takes the company to the near brink, and he's able to figure out a way at the last minute to survive. When you bet big, you win big. And so they could have lost big and oftentimes he's been lucky or determined enough to win big, and then he will then again, double down. And so you've seen these huge bets after huge bets from the company.

Gennaro [FourWeekMBA]:

There was also a huge divergence in terms of vision because as you explain in the book, Elon Musk had this vision of translating Tesla into a new GM when many other people didn't think in this way; investors, also the top management.

Tim Higgins:

Absolutely. So the company is struggling to stay afloat early on. At this point, Martin has been pushed to the side. So his vision is not really part of the conversation. Elon and Tesla at this point, have taken on other investors that have smaller stakes, but still pretty big stakes. There's a natural conversation that occurs. 

What's Tesla going to become? Is Tesla going to pivot into becoming a supplier to car companies? They've proven that they can do these battery packs. This is really where their value is at that point in time. 

They were seeing early signs that car companies were willing to, at least expressing a willingness to buy their battery packs and they could start keeping the lights on rather than generating revenue, and there was this excitement around that.

But Elon was concerned about who they were going to work with. He had this insight that if there was a problem in a, let's say a General Motors car because of a Tesla battery pack, GM was going to blame Tesla. 

These things were going to be out of Tesla's hands perhaps, and it might not have been their fault. And so he was very concerned about that. That was part of controlling his vision is part of the success of Tesla. He's been able to do that when others have wanted to go other ways. He's also very pragmatic. So he keeps control of the company. 

At the beginning of 2009, he set this vision for the next car, which is the Model S. A car that's supposed to compete against the best of the best out there, a luxury sedan, all these things. He is also pragmatic and cuts some deals that really help the company.

He cuts a deal with the parent company of Mercedes, Daimler, to provide battery packs to their small car. He does a deal with Toyota, which is really important for keeping the company afloat. 

That gets them a car factory in California, outside of the San Francisco area, that Toyota was basically getting rid of. It also got them a deal to help build an electric version of the RAV4 as Toyota was experimenting with its electric car program. 

So those were really key deals in the early days of Tesla because it was generating revenue. It was giving Tesla experience working with traditional automakers to learn how to control quality and how to meet deadlines and these sorts of things. 

Getting money in the door as they were marching towards the Model S, which was really going to be the vehicle that would define Tesla and sell it to a larger audience.

If the Roadster was the proof of concept, the Model S was going to be an exclamation to the world that Tesla could make the best car in the world that just happened to be electric, and that was the challenge. 

That's really what Elon's bet was, was that if they could do that, they could show that there would be a huge demand for electric cars. 

And then they could really go on to the next idea, which would be a mainstream electric vehicle, which we now know as the Model 3. This would be the way that they become more of the General Motors of the electric car world, rather than let's say the Porsche of electric cars.

Gennaro [FourWeekMBA]:

There are a few things that came to mind as you were recalling the whole story. And of course, I guess there are three things that we can highlight. For a bit of context to the audience, as we said, the initial business plan of Tesla was brilliant in terms of targeting the market. Because again, the Tesla Roadster would actually prove to be a successful launch, and especially a successful showcase of a showing that you could build a very cool electric vehicle, even though very expensive. And of course, not ready yet for a scaled-up production, but yet you could be in a very cool vehicle. Of course, their initial idea assumptions of Eberhard were wrong in terms of execution, where he thought he could build it by outsourcing most of the pieces to others. Instead, it turned out to be a wrong assumption.

Of course, another point was about vision, as we said, where there was a divergence where Elon Musk wanted to keep Tesla on track to becoming a GM. One thing that also came up by covering up in this podcast series is the history of PayPal and the history of SpaceX, Elon Musk has those grandest visions. He also is very good at execution, where he's able to keep his whole team on track. Even though he's on top of many things, and he's a micromanager, he is able to keep his team on track with this vision. So he does it with a very good execution strategy. Indeed, he showed that when in 2006, he built the secret Tesla master plan, which was really three points that highlighted the execution strategy for the next decade of the company.

Another point is, as Tesla moved forward, we go toward 2009, 2010, it passed the first near-death experience as we go through the 2008 crisis. The company decides to go public, something that Musk doesn't necessarily love, as we see. The reason for keeping, for instance, SpaceX private is because he understood from all the ups and downs of Tesla in the short-term as a public company, to keep SpaceX as a private company. So it was a lesson for him, but he also became his own PR.

There is something that it's easy to forget, but before 2008, there was no Twitter. He started to tweet really, I think, in 2009. So as he goes through the IPO, he starts to become really his own medium. Before that, he had to connect with journalists to actually get coverage. Now, he can do it without any intermediary. 

He can start doing that through Twitter, and that changes the whole game. It was not easy for people around him to control his behavior, for instance, through the IPO in 2009. At the same time though, it was a very powerful strategy to have Musk become his own PR.

Tim Higgins:

Definitely has. He understands the media, he understands the power of communication and these sorts of things. And so when you go through an IPO, there's a lot of rules and there's a lot of lawyers and a lot of bankers, and that's really not really the thing he enjoys. 

He knows what he's selling. He knows how to sell. Which is a funny thing, because he's very dismissive of the idea of traditional sales methods and these sorts of things, but he is the ultimate salesman, and he knows how to communicate what Tesla is and why people should buy into it, whether the cars or the investment. 

And so you're right. In the early days of the IPO, there were clearly signs that there was going to be tension in running a publicly-traded company, which they needed to do because, at that point in time, that's the way you raised the money that they were going to need.

In recent years, we've seen from WeWork to Uber, the ability to raise billions in the private market. But at the time, getting the hundreds of millions that they needed really was a struggle and the IPO market was a way to do it. 

So there was that, but also being publicly traded meant that Elon was going to face certain rules and restrictions in the way that he could do things. And one of those key things is, if you're the CEO of a publicly-traded company, you have to be honest and straightforward, if you will, about the public comments you're making about the company and the material aspects of what's going on, so investors can decide if they want to invest or not and have the best information. 

There's been some tension between some of the comments that Elon makes publicly about the company and what's going on with the actual company. And that would really come to a head years later as the company was in trouble again. So you're right. The early seeds were being planted there when he was first getting on Twitter.

Gennaro [FourWeekMBA]:

Going forward, a very powerful strategy that Tesla picked up in the early days. It was a decision that they made in the early days was to go direct. This wasn't something to give for the grant, especially in the auto industry where no one had done it before. 

Tim Higgins:

So in the US, cars for generations, are sold through third parties. They're franchise dealers at the beginning and oftentimes would be generational families that would own groups or the local car dealership. 

And then it eventually became more like these large groups, in some cases, even publicly traded companies that have massive amounts of brands that they take care of. There's a lot of criticism over the years about the way that you buy cars in the US.

It can be cumbersome. It can be painful. It's oftentimes equated to going to the dentist. And so the idea of making it a better experience has been out there, but there are a lot of rules and regulations around the US that lock in that power of the car dealer. 

One of the things that Tesla had going for it is when they started out, they didn't have 100 years of history, 100 years of contracts with dealers around the country in the US. They had a green sheet. They had a green sheet of the ability to start anew, and so they started realizing what they could do direct. The idea of how Apple was selling.

You go to an Apple store. At the time, Apple was in these high-end malls, and early on for Apple, when they were going into the stores, the brand wasn't really known. You knew of Apple, but maybe you didn't know what an Apple computer was, or maybe you didn't know what an iPod was, or you didn't know what an iPhone was. The Apple store was, some of it was really about education. A lot of it was about getting hands-on experience with the brand and letting that experience sell the product. 

That's really what Tesla took inspiration from. They wanted to start creating facilities where people could go learn about electric cars because this was something different. It's one thing to buy an iPhone that's a little different, it's another thing to buy an electric car.

It's unproven technology. In the case of the Model S, close to $100,000. The idea was if they were going to become more mainstream, they were going to have to have these stores around to sell the car. 

They had debated going direct just online. That's always something Elon has talked about. You get back to the early days of electric cars and there was just really a belief that the customer is going to need a little hand-holding to learn about the electric car. 

How do you charge it? How do you maintain it? These sorts of things. 

The test drive really became key to selling these vehicles in that if you can get somebody behind the wheel and they could experience that torque if they could experience the quiet ride if they could just experience an electric car, that that was the point in time the emotional connection could come, and that's really where the sale could be completed.

So they were looking for ways to get people to think about electric cars and try electric cars when they weren't thinking about buying a car. Really in the US, car buyers tend to be pretty loyal to the brand they're already in. 

It's easy to go back to the Chevy dealer or the Ford dealer and just get the newest whatever. So if you're looking for an electric car, you're not really looking for an electric, you're just looking to get your new car. 

And so they needed to plant this idea of the electric car in people's heads when they weren't thinking about buying a car. 

So that then when they were, maybe this was an opportunity for them, that sort of thing. So that was the idea behind their stores, and they felt like they needed to control that by owning them.

Elon was concerned that a traditional car dealer if they started franchising, would not have the same motivations to direct people into electric cars, because they would be more concerned about the profits that they were making from selling traditional cars. 

The theory is that traditional cars have more parts, and so they need more maintenance and these sorts of things. And that's where car dealers make a lot of the monies and the maintenance and the warranty work down the road. So there's a lot of tension there, but one of the big insights that Tesla was doing was trying to sell directly to customers. They wanted to own that brand experience and that customer experience.

Gennaro [FourWeekMBA]:

Again, it seems like Tesla has borrowed a few things from Apple, and this was really one of those things, even though it was quite counterintuitive in the auto space. As you said, it's also interesting to point out that even when it comes to car dealers, as they sell the cars at very low-profit margins, most of the money is made in the service business. Though, when it comes to the service business, if you're a company like Tesla, you lose control of the customer experience because if the service is provided by the car dealers, the car dealers are not interested in selling just your brand. It's interested in actually providing service for many other brands, or actually building its own brand. So this might seem trivial, but even when you look at a company like Apple, a lot of revenues like we're talking about, billions and billions come from the service, and the services are provided within the Apple stores. So this is a very important point to emphasize.

If you don't have a place where customers can come in and talk directly with the company, you don't have control over the service business, which is not only very important, you can control the customer experience, but it's also the business that has higher margins. So I think it's a very important point to emphasize. So the retail store strategy is extremely expensive, but it works on both sides of the funnel. On top of the funnel, it's a branding educational strategy, and at the bottom of the funnel, to create a new revenue stream at high margins, which is the service business, which you can build when you have a successful product. So again, this choice has been made 15 years ago for Tesla. It was not a cheap strategy, was quite expensive, but they built the distribution that over time, is going to enable them to build a service business that might get even bigger than the whole auto business. Who knows? We'll see. I thought this was an interesting point to emphasize.

As we move forward through the story, it's interesting to notice that anyhow, it wasn't like other companies understood that Tesla was a potential threat. Also, the other companies had tried and attempted to build their own electric vehicle. At the point that actually Tesla was thinking to sell to Google in 2013, as you recall in the book. 

Tim Higgins:

Absolutely. So the success of the Model S, really made the company more appealing to investors. The Model S comes out in 2012 but really hits its stride in 2013. Tesla is profitable for the first quarter at that point, and really that's when you start to see the stock start to rebound, really accelerate. It allows the company to start raising the funds that it really needs to go to keep going. 

This is creating a lot of conversation, a lot of interest among traditional automakers, and as they look at the company, there are a few things going on.

There's a renewed idea that, okay, perhaps lithium-ion cells, which we've talked about, the electric vehicle, this could be potentially something that customers are going to want. You started to see companies like GM move faster. 

They have the Chevy Volt, which has been a hybrid be out there. You start to see them thinking about having more all-electric vehicles, that sort of thing. So that's going on. The other thing is that as companies study Tesla, they really were skeptical that it was going to be able to survive as a company. 

We just talked about that direct model approach, and as car companies looked at that, they were looking at the cost of building it out. More importantly, they're looking at the service end of that, that there was going to create all of this essentially, liability down the road for Tesla, delivering the car themselves, and then fixing them. They predicted that was going to be very messy and hard to do.

And so that was going to be an area that Tesla would struggle with. They looked at the production capabilities and were really questioning if they could really get the scale that they were going to need to bring down the cost to go mainstream and these sorts of things. And so that's out there. 

Really, the traditional car companies were struggling with this issue of they're making money from gas-powered cars, that's where their bread and butter is. This electric car thing, let's make a side bet that maybe this is the future and the future is way off. It's where you see the industry at that point.

The Model S success at Tesla is reinforcing Elon's vision and it's helping him raise the money he needs as he's thinking about that next step. We've talked about that three-point plan, which was to create a sports car to build excitement for the sedan. 

The Model S has come out and now the ideas move on to the next leg, which would be the mainstream automobile, which was supposed to be priced at a way that could be affordable to the masses and really get the scale and really change the world by putting the electrified automobile into the mainstream. 

And so what happens there is Elon starts making huge bets in that he's looking at the supply chain world and saying, there are not enough battery cells out there. The company really needs to start, if they're going to have millions of car sales, they're going to need way more capacity. So they need to figure out a way to get battery cell production to basically, grow dramatically.

They need to push forward the Model 3, which is going to be their mainstream car. These are the key things. They're putting the acceleration on trying to get the cost down to make it more mainstream, to take this momentum that they have with the Model S to the next level. They're moving faster than the traditional automakers are moving. That's one of the big things. GM sees and hears Tesla, and so they too have what they think is going to be something that competes against the Model 3, that's the Chevy Bolt. 

As the two companies, you can compare how they approach it. GM is hearing Tesla say that they're going to have a $35,000 car. Well, GM knows how to make a $35,000 car.

They were concerned about price and essentially the Bolt comes out and it's technologically pretty interesting. It's an interesting car. It's a small car, but it's not sexy. It's not designed in any way that it's going to be confused for a sports car. 

Maybe doesn't necessarily have the coolest interior. There's nothing luxury about it. Whereas the Model 3 is essentially the Model S, they figured out a way to take some of the cost out of it. The other thing is it's not a $35,000 car. 

Today, it sells for way more than that. It wasn't $35,000 at the time it was launched. That's one of the challenges and the problems you could say about Tesla is that they have a hard time getting the vehicle in at the price point that they say it's going to be.

This is one of the key things about the ability of Elon Musk as the CEO, and the ability is the guy who can go out and raise the capital that the company needs to keep going. When he's looking at the Model S, for example, he's wanting it to be the best car that happens to be electric. And so as they're developing it, he's developing something that he would like to drive. 

The car was supposed to be something like $50,000, but it comes out to be actually more like $100,000. If you're a General Motors and you're given the assignment of coming out with a $50,000 car, and it comes out at a $100,000 car, you're not really having a career at General Motors. That's not something you can do in the traditional auto world, or really any company.

But Elon Musk is Elon Musk. He's raising the money to keep the company going. It's his call, he's the boss. He's betting that having that Model S be the best car that it can be is actually going to be more valuable than the margin in the near term. 

That carries over to the Model 3. He gets in place a really good team that figures out how to do it more affordably, but still, it was never really a $35,000 car. So GM is coming out with its $35,000 car, and it's competing against a car that's really selling more like a $50 or $60,000, and they're just out of the league. 

But what happens is that creates huge excitement among the buyer for the Model 3. And so the Model 3 is revealed in 2016, and people haven't even been able to test drive it.

They don't even really know when it's going to come out, but they're literally lining up around the block of Tesla stores to put money down, to be able to be one of the first people to buy that car. Online deposits are going through the roof. That moment in time is very important because it shows that there is this pent-up interest in electric cars, more so than the auto industry ever thought was there. 

That's really when it's a wake-up call to the industry that something is going on, but by that point, it's almost too late. It takes many years to develop a car. And so the industry is trying to race to figure out how to do its electric car at that point. Whereas, Tesla is pretty close to putting one on the road.

Gennaro [FourWeekMBA]:

Very interesting. Of course, it's not just that people were interested in electric vehicles, it was also the ability of Tesla to create excitement, which could be compared to the excitement that Steve Jobs created by releasing new, very cool products back in the day. Just to emphasize a little bit and to go back and then we move forward. Tesla successfully launched its, let's say business plan, by proving the technology through the Roadsters. And then there was the point where the Model S became the car where Tesla could show that it could be something more scalable than just a sports car. So it moves from a very small niche of the market to have where this is more for people that know crossing the cusp. This is for real the innovators.

Those people that are interested are really interested in the technology. As it moves to the Model S, of course, it moves more toward the early adopters. Those people that yes, are interested in the technology, but they also want something that works extremely well. With the Model 3, we move toward the larger number of this early majority, where people start to be interested more in how cool is the product. So it's not just about the technology. As you pointed out, Tesla never managed to really lower the cost of the car to the point that Musk had promised over the years. But also, I don't think that this is probably the key, because going forward, there is another element on which Tesla may actually borrow something from Apple. Which is the fact that you don't have to have a cheap product to make it scale. What you need is actually find something or someone that is going to subsidize the product.

By looking at the Tesla business model, I was looking at it in the last few days. It's interesting to see also how the leasing arm of the company actually generated over 1.6 billion in 2021, which is about 3% of the revenues, but it's not really about the revenues. The fact that the company has a leasing arm, means that it can enable more people to purchase a Tesla by not paying it the full amount, which a few people can afford right now. It's just like the iPhone.

Many people in the US can afford it because they can amortize the price of the iPhone through the plan that they pay through the mobile carrier. So the leasing part of Tesla is extremely important to understand the scale that the company can reach over time, even though it might not be able in the short term to lower the cost of electric vehicles, because let's remember, the batteries are very expensive. It might be able to do that in, let's say five, 10 years, not necessarily in the short term. So I think this is a very important point to highlight. As we move forward from the Model 3 going forward, the problem is no anymore about prototyping. 

Now it's a problem of production, and that's where Elon Musk is going to focus.

Yeah. Production and execution, delivery. The challenge for the Model 3 is really going from doing tens of thousands of cars to hundreds of thousands, to millions of cars at that level of complexity, just is very hard. We started this conversation by talking about how it nearly did the company in 2018. 

And it really did get that production going on time. It was months late, running low on cash, concerns that maybe the company wouldn't be able to pull it off. Incredible tension at this point, because Tesla and Elon have been able to figure out a way to generate attention. So there was all this hype, and it was looking like the company was going to fail in a massive way. Really 2018, the summer of 2018 was really one of those periods where it didn't look good for the company.

The problem that happened was with the success of revealing what the Model 3 was going to be like in 2016, there was all this interest in the car. Elon wanted to pull ahead the production plans to capitalize on some of that success. You've got hundreds of thousands of people who have put money down that want it. 

Their production plans were much slower and smaller, and he wanted to get out there before maybe a rival could take some of that interest. But also the reality was there was all that interest in the car, there was now huge interest in the investor community to invest. And so he was able to raise a bunch of money to pay for that industrialization. The challenge is that ramping up production is very complicated.

One of the things he thought that they could maybe make it easier was by relying more on automation in the assembly line, going with more robots, these sorts of things. Anybody who has experience in car manufacturing knows that robots have their place, but they're also a level of complexity that can be hard to just turn on. That you've got to do it right or else you're going to have problems down the road. 

GM had struggled with it years earlier. Toyota actually doesn't try to rely on as many robots as some might think, because they find that having people work there is cheaper and allows greater flexibility. So you had this really quick push to try to automate a lot of the factories that they had. What turned out was they basically had tied everything up in knots and they were trying to figure out how to fix it was really hard.

And so you get into early 2018 and they still haven't turned on production in any meaningful way to get the levels they needed to get the sales that they needed to keep the lights on. Elon is sleeping on the factory floor and all of his key deputies are there day in and day out, just trying to knock down, what's like Whac-A-Mole, with problems. 

Ultimately, they were saved because the team that was responsible for developing the Model 3, had moved beyond the startup phase. The Roadster was developed and the Model S had been developed. Elon had hired a savvy executive from Apple who'd experienced overseeing the Mac computer lineup, and he'd come in. In a lot of ways, he, I don't want to use the term professionalized, but corporatized Tesla's development operations in a way that it needed to be done as it was moving from a startup to being a real corporation, a real car maker.

One of the things as they looked at the challenges of the Model S and the derivative of that vehicle called the Model X, which was a large SUV, was that it was hard to build, to physically make at the factory.

 An example, with the Model X, if you will, Elon really wanted these cool seats in the back that were on pedestals and that you would be able to look under the seat and you could see out, and they weren't going to be attached to the wall. This created all this complexity of assembling the seats, and people on the assembly line were having to go in with a wrench and twist their backs and get in there. It was really complicated.

Workers were getting repetitive injuries. It was hard to build. The Model 3 team was charged with the idea of we have to make a car that's really easy to make, because this is a problem for us. And so that was an important part, and that comes into play. 

Whereas the assembly line is in knots because of the automation, it's actually pretty easy to make the Model 3. One of the engineers says, "Well, why don't we just take it away from these robots and do more of it by hand?" That was a huge insight. Essentially, what they do is they start creating new assembly lines where it's less automated and the people can just put the car together.

In fact, they set up a giant tent outside of the factory where they can put one of these assembly lines. And then it's just a matter of putting a lot of people on it, and just here you go, just keep cranking it out. This is the solution. This saves the company. 

In the summer they start cranking out the number of cars they need to start generating the revenue, and they avoid basically collapse, but they're not out of the woods yet. Now they've got thousands of cars coming out of the factory. 

They've got to deliver those cars to people. As we talked about this idea of controlling their own sales and service operation really becomes a challenge, because they've basically run out of money and haven't been able to scale the sales and service operation.

It's just like what the traditional car companies had figured was going to happen years earlier, when they looked at Tesla and their ambitions and said, "This is going to be one of the bottlenecks." And it was. 

The challenge was in the third quarter of 2018, as they had all of these cars that they had now built. They had cost the company money. The company is nearly out of cash. They have to deliver thousands of these cars by the end of the quarter, or it's game over at that point. So there's this massive rush to deliver Model 3s around the US to make those sales because it doesn't count as a sale until it's in somebody's hand.

You see this crazy effort to do that. Included all sorts of untraditional ways of delivery from hiring people off the street essentially, to drive these cars to people's houses and giving to them, and then taking an Uber or a Lyft back to the Tesla operation and going get another car. 

Literally, hand-delivering them to their homes. At one point, Elon was putting out requests help from customers to come to the centers and help with the deliveries that were taking place at these delivery sales and service facilities, where people were coming to get their cars and they were being scheduled in advanced and slotted into 30 minutes to an hour period, where they would come and get their car, and they drive off, hopefully, happy customers.

And so just a mad dash to do that. And they pulled it off, which was remarkable. The other remarkable thing was these were not $35,000 cars. These were th