174: Twitter Interest Graph & Creation, Capped Growth Thought Experiment, Copying Products, Amazon, Big Apple App Store Change, Sugar & Carbs, and Marc Rubinstein
174: Twitter Interest Graph & Creation, Capped Growth Thought Experiment, Copying Products, Amazon, Big Apple App Store Change, Sugar & Carbs, and Marc Rubinstein
Although it is very common to attach the cause of obesity to the volume of sugar or carbs eaten, it’s one that leads to the wrong conclusion. However, it’s one the agriculture industry would like us to believe. There is a definite correlation here but not causation. Non-industry-driven peer reviewed research as consistently demonstrated that sugar isn’t the driver behind obesity as sugar is easily converted to heat (thermogenesis) by the body. That being said, the mistake can be forgiven since it’s the norm to call “sugar treats” things that are in reality full of fat (cakes, cookies, pastries, pies, etc. ). Weight loss/gain is an easy science. If you go over your caloric threshold, your body will want to eliminate or store whatever is in excess through the most efficient process. Converting carbs to fat is a very inefficient process and it won’t be the bodies first choice when handling excess calories. Turning fat into stored fat, however, is something the body is very good at. So when we eat more calories than our body needs and all the fat we require for normal body functions has been absorbed, the excess fat will be converted into stored fat.
Regarding fast competition- Tesla Model S was launched in CY12. First direct competitor (EQS) will be available from CY22. It’s amazing that competition was in ‘sleep’ mode.
In this case, it feels like incentives matter a lot. There's been few pure play EV companies yet (that have actual production), and most of the legacy makers have such huge investments in the old tech that they've been dragging their feet and trying to extract as much as possible out of ICE before having to switch over.
They have plenty of grandiose press releases, but very few widely available, mass-produced EVs that are designed to be most attractive to a broad segment of the public (ie. Why did the Nissan LEAF look that strange? Why not just make the equivalent of an electric Altima or Sentra?).
Your articles on Nvidia were very helpful, especially the importance of software plus hardware integration and importance of long term vision and focus. I was hoping at least by mid CY19, traditional players would take EVs more seriously and not as an emission compliance to do list. There seem to be some similarities in Tesla’s approach too vs traditional hardware focused peers -
When I landed at Tesla, I hadn’t realized how much the company was impregnated by Silicon Valley’s software culture. I’m not talking only about the car itself, but also how the whole innovation process is organized.
My first conversation with software manager Craig Carlson was a telling example. Craig was vice president for firmware and electrical integration at Tesla Motors at the time. He was in charge of all software systems and low-voltage electronics for the car, from the numerous firmware to the design of hardware and software that run the center display, or the mobile apps and server-based system that connect with the car. I was first stunned by the size of Craig’s troops relative to the rest of Tesla’s engineering staff: he managed almost half of the 700 engineers at the company. To put things in perspective, in 2011, Renault and Volkswagen didn’t have a single in-house software engineer. The code was handled by suppliers.
That month, September 2011, as VP Quality for the Model S, I arranged a meeting with Craig to probe him on how quality was handled in his department. In the car industry, at least as I knew it, everything — including software — is managed with a set of specifications defined at an early stage of the development of the car, which will eventually be modified at each major iteration of the model.
Craig doesn’t have a clue of what I am talking about. Coming from Intuit, Craig sees his work through the lenses of a software engineer, Silicon Valley-like. Hence his puzzlement with my question. “You are asking me about firmware specs?”, he asks in surprise. “We don’t have such things. This is not the way we do things here…” I realized that, unlike the traditional car industry where every piece of code is carved in stone years ahead, Tesla is functioning as a pure software company. As Craig later explained to me, his team relies on a bucket of features, bug corrections, etc. Developers draw from the bucket, based on priorities: number 1 is for the vehicle’s critical functions such as power management, braking, steering, safety features; 2 is for key functionalities of the car; 3 is for secondary features such as the electric windows or rear-view mirrors and 4 is for the rest. At regular intervals, releases are pushed over-the-air (OTA) to the car hardware, exactly like apps are updated on a smartphone. In the early days of the Tesla program, releases were made every two weeks. I quickly came to the conclusion that, when it came to software quality, I had no choice but to trust Craig and his team.
Later, I witnessed another example of Tesla’s agility as a software company. One day at the cafeteria, I overheard a conversation between a test engineer and his colleagues. The guy was senior enough to drive a pre-series of the car on a daily basis. Each day, when arriving home, he had to manually adjust the air suspension to prevent the front spoiler from scraping its driveway. Certainly not a major nuisance, but we could do better, he thought. “Why not having the GPS ‘talk’ to the suspension of the car, then when approaching my bumpy driveway, it would automatically lift the car to prevent any damage?”, he asked. “ — Well, that’s not complicated, frankly”, replied a software engineer, “This is actually a few lines of code”. The next day, they ran the idea to Jerome Guillen, at the time the head of the Model S project, and the modification was added to the bucket, most likely with a low priority assigned to it. But the feature was also low complexity, and it was implemented in the next release. Done.
I’m sharing this anecdote to illustrate the Grand Canyon-wide gap there is between Tesla and traditional automakers like Audi or Renault.
It was clear the Roadster was not a car that appealed to a huge population, so we quickly developed the Model S, and the Model S NPI is built on an iterative model—still at Tesla today, NPI is a continuous integration.
When we launched the Model S in 2012, the powertrain was based on a Toyota RAV4 powertrain Tesla designed in 2011, and the chassis and body were all new. Then the Model S had integrations through its life including autopilot, performance plus, dual motor all wheel drive (AWD) and many cost-down programs. It was common for the NPI team to be managing 50 part changes every month. The entire motivation behind dual motor, Tesla’s AWD, was to mature the Model S powertrain in preparation for Model X, an SUV which would of course have to offer AWD. When Model X launched, it was built on the powertrain of the Model S with a new taller body. Within the first year of production, the Model X chassis was redesigned to be the same as Model S. Unlike the Roadster, which was the Big Bang, “here it is” moment, the S and X are iterations upon iterations.
Although it is very common to attach the cause of obesity to the volume of sugar or carbs eaten, it’s one that leads to the wrong conclusion. However, it’s one the agriculture industry would like us to believe. There is a definite correlation here but not causation. Non-industry-driven peer reviewed research as consistently demonstrated that sugar isn’t the driver behind obesity as sugar is easily converted to heat (thermogenesis) by the body. That being said, the mistake can be forgiven since it’s the norm to call “sugar treats” things that are in reality full of fat (cakes, cookies, pastries, pies, etc. ). Weight loss/gain is an easy science. If you go over your caloric threshold, your body will want to eliminate or store whatever is in excess through the most efficient process. Converting carbs to fat is a very inefficient process and it won’t be the bodies first choice when handling excess calories. Turning fat into stored fat, however, is something the body is very good at. So when we eat more calories than our body needs and all the fat we require for normal body functions has been absorbed, the excess fat will be converted into stored fat.
Just thought I’d throw that in :)
Regarding fast competition- Tesla Model S was launched in CY12. First direct competitor (EQS) will be available from CY22. It’s amazing that competition was in ‘sleep’ mode.
That's one I often think about.
In this case, it feels like incentives matter a lot. There's been few pure play EV companies yet (that have actual production), and most of the legacy makers have such huge investments in the old tech that they've been dragging their feet and trying to extract as much as possible out of ICE before having to switch over.
They have plenty of grandiose press releases, but very few widely available, mass-produced EVs that are designed to be most attractive to a broad segment of the public (ie. Why did the Nissan LEAF look that strange? Why not just make the equivalent of an electric Altima or Sentra?).
Your articles on Nvidia were very helpful, especially the importance of software plus hardware integration and importance of long term vision and focus. I was hoping at least by mid CY19, traditional players would take EVs more seriously and not as an emission compliance to do list. There seem to be some similarities in Tesla’s approach too vs traditional hardware focused peers -
Different SW approach vs peers
https://mondaynote.com/code-on-wheels-a4715926b2a2
When I landed at Tesla, I hadn’t realized how much the company was impregnated by Silicon Valley’s software culture. I’m not talking only about the car itself, but also how the whole innovation process is organized.
My first conversation with software manager Craig Carlson was a telling example. Craig was vice president for firmware and electrical integration at Tesla Motors at the time. He was in charge of all software systems and low-voltage electronics for the car, from the numerous firmware to the design of hardware and software that run the center display, or the mobile apps and server-based system that connect with the car. I was first stunned by the size of Craig’s troops relative to the rest of Tesla’s engineering staff: he managed almost half of the 700 engineers at the company. To put things in perspective, in 2011, Renault and Volkswagen didn’t have a single in-house software engineer. The code was handled by suppliers.
That month, September 2011, as VP Quality for the Model S, I arranged a meeting with Craig to probe him on how quality was handled in his department. In the car industry, at least as I knew it, everything — including software — is managed with a set of specifications defined at an early stage of the development of the car, which will eventually be modified at each major iteration of the model.
Craig doesn’t have a clue of what I am talking about. Coming from Intuit, Craig sees his work through the lenses of a software engineer, Silicon Valley-like. Hence his puzzlement with my question. “You are asking me about firmware specs?”, he asks in surprise. “We don’t have such things. This is not the way we do things here…” I realized that, unlike the traditional car industry where every piece of code is carved in stone years ahead, Tesla is functioning as a pure software company. As Craig later explained to me, his team relies on a bucket of features, bug corrections, etc. Developers draw from the bucket, based on priorities: number 1 is for the vehicle’s critical functions such as power management, braking, steering, safety features; 2 is for key functionalities of the car; 3 is for secondary features such as the electric windows or rear-view mirrors and 4 is for the rest. At regular intervals, releases are pushed over-the-air (OTA) to the car hardware, exactly like apps are updated on a smartphone. In the early days of the Tesla program, releases were made every two weeks. I quickly came to the conclusion that, when it came to software quality, I had no choice but to trust Craig and his team.
Later, I witnessed another example of Tesla’s agility as a software company. One day at the cafeteria, I overheard a conversation between a test engineer and his colleagues. The guy was senior enough to drive a pre-series of the car on a daily basis. Each day, when arriving home, he had to manually adjust the air suspension to prevent the front spoiler from scraping its driveway. Certainly not a major nuisance, but we could do better, he thought. “Why not having the GPS ‘talk’ to the suspension of the car, then when approaching my bumpy driveway, it would automatically lift the car to prevent any damage?”, he asked. “ — Well, that’s not complicated, frankly”, replied a software engineer, “This is actually a few lines of code”. The next day, they ran the idea to Jerome Guillen, at the time the head of the Model S project, and the modification was added to the bucket, most likely with a low priority assigned to it. But the feature was also low complexity, and it was implemented in the next release. Done.
I’m sharing this anecdote to illustrate the Grand Canyon-wide gap there is between Tesla and traditional automakers like Audi or Renault.
Non traditional hardware approach vs peers
https://www.machinepix.com/p/machinepix-weekly-36-milo-werner
It was clear the Roadster was not a car that appealed to a huge population, so we quickly developed the Model S, and the Model S NPI is built on an iterative model—still at Tesla today, NPI is a continuous integration.
When we launched the Model S in 2012, the powertrain was based on a Toyota RAV4 powertrain Tesla designed in 2011, and the chassis and body were all new. Then the Model S had integrations through its life including autopilot, performance plus, dual motor all wheel drive (AWD) and many cost-down programs. It was common for the NPI team to be managing 50 part changes every month. The entire motivation behind dual motor, Tesla’s AWD, was to mature the Model S powertrain in preparation for Model X, an SUV which would of course have to offer AWD. When Model X launched, it was built on the powertrain of the Model S with a new taller body. Within the first year of production, the Model X chassis was redesigned to be the same as Model S. Unlike the Roadster, which was the Big Bang, “here it is” moment, the S and X are iterations upon iterations.