Twitter Space – Semi Most Important Tesla Product After Bot and Robotaxi

A Twitter Space with Brian Wang, Bradford Fergeson, Randy Kirk, Gary Carson, Larry Goldberg, Lars Strandridder (Best in Tesla), John Gibb (Dr Know it All).

Key insights – Tesla Semi could match the Tesla Car business in revenue if there is an accelerated shift to electric trucks by China and other nations in Asia.

The Tesla Semi will drive the need and build out of Megapack charging and the megacharging could match the terawatt hours of batteries used for Tesla Semi.

Tesla Semi is the most important for Tesla after Teslabot and Robotaxi. The reason is that it will be the main catalyst for Tesla Energy to reach terawatt per year scale and beyond.

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14 thoughts on “Twitter Space – Semi Most Important Tesla Product After Bot and Robotaxi”

  1. Tesla bot,robo taxi and semi are completely vaporware, if they wanted to deliver all three they could have if they had invested in it, but the stock price and Elon’s wealth is what matters not promises for fanciful products.
    Even SpaceX,the completely dominant launch provider delayed so long with the Starship that Artemis beat it to launch.

  2. Several years ago, I checked and discovered about six million people in the US make their living by driving taxis, buses, and trucks. I would guess about 100,000 people would be needed to be specialized programmers, database administrators, and engineers for self-driving technology. And almost none of them are going to be any of those six million unemployed drivers retraining themselves. They also won’t be getting jobs as brain surgeons and such. Oh sure, a couple will, and you will read their uplifting stories in Reader’s Digest, like those about the kids who fall in an icy covered lake and get saved after 30 minutes. The point being, in the greater scheme of things, that’s not going to change the situation much.

    Of course, then you have body shops doing less repairs, less trucks being made because they drive 24/7 except when loading/unloading or getting maintenance, less folks working in the DMV, less car insurance salespersons, less fry cooks and waitresses (truck stops mostly won’t need any), and so on.

    Sure, we will adjust. But it will come very quickly, to quickly to prevent a lot of pain (given that our so-called leaders will be useless in even addressing it, and no one can stop it. They may attempt legislation to slow it down but that will just make it all messier.

    Interesting times. Four kids and their spouses have finished school and entered the work force since I noticed all this (around 2010, when people still told me I was being ridiculous about the possibility of self-driving vehicles). Either the kids took me seriously or we were just lucky, but I don’t see any of them in the careers that are going to be adversely affected by at least the first several decades of automation.

    • But it’s getting harder to predict who is going to get disrupted next by ai. People assumed for a long time that ai would start at the lowest skilled/education jobs and work it’s way up to the white collar. But what we are seeing is perhaps a lawyer is easier to automate away than a janitor. And with chatGPT, dall-e and the like, the creatives (authors, artists, etc) seem to be most at risk of disruption.

      • Yes, it’s one thing that everyone got wrong about predicting “smart computers”.

        Everyone, from serious predictions through to science fiction movies all had robots and computers being serious, logical, boring without the ability to do art or music or jokes.
        It turns out the exact reverse. It’s a serious conversation about a logical subject where computers are still failing.
        That line from AI where Will Smith asks “Can a robot write a symphony? Can a robot turn a… canvas into a beautiful masterpiece?” … well the answer is yes. The real robot would not, however, be able to come up with the come back of asking the human “Can you?”

      • Economist Stuart W. Elliott prepared a paper titled “Projecting the Impact of Computers on Work in 2030” where he detailed what he called “Occupational Displacement” and suggesting that up to 60% of the jobs, excuse me, occupations, could be gone by 2030. He also detailed some steps that might make this trauma go a bit easier on us. It depended largely on a drastic re-engineering of the the educational process (probably the kind that every yearbook printer, class ring jeweler, teacher’s union, textbook printer, school photographer, football dad, and cheerleader mom would would rise up in arms to prevent).

        The kids that would be graduating from college and looking for work in non-existent occupations in 2030 were not yet born at the time I first wrote the previous paragraph. Now they are starting high school. That paper was published on the National Research Council’s web site in 2007. Not a thing has been done to act on it in 15 years. It’s not a problem any politician of either party will want to touch before it is impossible to ignore any longer (and probably not even then).

    • Think upcoming unemployment across so many fields is one reason Elon liked Andrew Yang’s futuristic Universal Basic Income idea.

      New opportunities are going to emerge and people will find new ways of making money. Do I know what these opportunities will be? No, and I do know people are adaptable and inventive. Some jobs will be robotaxi small fleet management, Tesla Bot mid-sized fleet rental management, robot repair, food fermentation, mining EV minerals, refining EV minerals, and more wind and solar design install/maintenance. As more cheap renewable energy becomes available, there will be more desalination and recycling jobs.

      • Well said. The types of available labor jobs, as well as jobs in the IT field, are definitely going to change over the next several decades. It’ll be interesting to see how we adapt.

        The adoption of renewable energy sources, the potential (and hopeful) adoption of fusion power generation (which, in turn, requires new jobs to overhaul and build out a new power grid) and even– dare I say it, maybe fifty years out– asteroid mining; these things will require new fields of expertise.

      • The emphasis on Teslabot makes this future clearer. The economy will become decoupled from human labor. This requires a more radical rethinking of the rules than simply having faith that new sorts of jobs will always arise. It’s critical that there is a form of Universal Basic Wealth that can keep pace with the replacement of human labor that once slavery was abolished was a capability owned by each individual inalienably. AI and robots will eliminate the importance of that distributed form of wealth – most labor will be performed by machines that are subject to concentrated ownership – unless that is rethought.

        As human labor become less necessary to the economy – every human needs to be guaranteed to own a share of the AI/Robotic capital equipment that replaces it – or the level of inequality will become unsustainable – if for no other reason than that demand will collapse. Robots and AI can contribute endlessly to supply but nothing to demand.

        • Well, “can contribute nothing to demand” is not *quite* true. Even robots have a demand for maintenance, which a kind of demand. Of course, it is very little in comparison to a human, and these things need to be thought through. I’m not sure Universal Basic Income is the answer — it sounds too much like letting Daddy Government rule over the masses by threatening to withhold their means of subsistence — but something will eventually be found, even if that something is “back to the ruins.”

          • That’s one side of common lowest standards for making a living, but with regarding how distracting it is for developing complicated and/or complex tasks (for being contribution to cultural (including technical) and social structures development) and narrowing down flexibility with being on a non-stable foundation considering food, habitation, safety&health, information&education, mobility it’s probably a lower price for modern (21st century) societies providing that humane and unelaborate level of welfare instead of fighting believed overcome symptoms of a spiral of poverty. I’ld say, it’s a low price for societies, with even encouraging increasing motivation for self-reliance/self-responsibility.

    • while looking into freight statistics (US) there’s some interesting summary on ‘Table 1-1 Economic and Social Characteristics of the United States: 2000, 2010, and 2014–2016’ (page 11, ~35MB)

      ( on percentage growth, mining jobs could be recommendable (~50%), but having lower impact on absolute numbers on ‘labor force’, ‘Manufacturing’, ‘Information’, ‘Agriculture, forestry, fishing, hunting’ lost working force, growth parts were ‘Educational and health services’ and ‘Professional and business services’, employees numbers increased )

    • while looking into freight statistics (US) there’s some interesting summary on ‘Table 1-1 Economic and Social Characteristics of the United States: 2000, 2010, and 2014–2016’ (page 11, ~35MB)

      ( on percentage growth, mining jobs could be recommendable (~50%), but having lower impact on absolute numbers on ‘labor force’, ‘Manufacturing’, ‘Information’, ‘Agriculture, forestry, fishing, hunting’ lost working force, growth parts were ‘Educational and health services’ and ‘Professional and business services’, employees numbers increased )

    • Data on the industry sectors affected by automation/AI disagree with your claim.
      AI and automation affect first and foremost high-paying jobs with sufficiently high levels of standardization as there is a big pressure to displace such jobs.
      -AI displaced thousands of jobs in the finance industry, and the same is true in the insurance sector.
      -While IT/coding is more heterogeneous than managing financial transactions, the coding languages are standardized, and the vast majority of the coding needs in the industry are not that unique. We already have examples of AI developing programs and I can imagine AI displacing thousands of software developers
      -Marketing/Advertising marketing, customer profiling and customer engagement are already mainly controlled by AI. There is still a human component in the creation of the advertisement but this can be displaced by AI generating art (see point below).
      -Art/Entertainment: AI producing drawings/pictures, movies, and literature is still in its infancy, but I can imagine that there will be a huge market for AI generated products that imitate and even improve the work of your favourite artist. While this might have legal implications for living artists and works still protected by copyright, I am pretty sure there will be big business opportunities for editors capable of producing at minimal cost hundreds of new works appealing to big established customer bases, and I am not even considering the case of AI artists producing new styles, new music, movies and so on…
      -Automated judiciary system, obviously judiciary evolves slowly (stenography is still used in court…) but I can imagine a not-too-far future where the corpus of laws, witness testimonies and court rulings is used to train judiciary and private arbitrage systems, allowing to save time and money and excluding the human bias.
      -Healthcare: AI is already used in diagnostics and surgical robots already assist surgeons. It is not difficult to imagine a robot that could operate exploiting more precise servos and better senses (like being able to see within you because it can reads an eco scan in real time)

      I see AI implementation in low-paying jobs as more difficult because cheap workers are indeed cheap, and they tend to work wherever they can, and the employer is relying on but not paying for the innate human ability to move around and cope with the unexpected/not standardized.

      -Fast food restaurants do not always have similar layouts, and kitchens usually do not have an optimal structure because owners tend to maximize the customer-accessible part of the venue-
      -Streets are not standardized either, there are underlying rules, but it is when exceptions occur that most accidents do happen.

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