Continuous Learning_Startup & Investment – Telegram
Continuous Learning_Startup & Investment
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We journey together through the captivating realms of entrepreneurship, investment, life, and technology. This is my chronicle of exploration, where I capture and share the lessons that shape our world. Join us and let's never stop learning!
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Punch Cards Era: The early days of computing required users to interact with machines using punch cards. These rectangular pieces of stiff paper had holes punched into them, representing data and commands. It was a labor-intensive process and the room for error was vast. If one card was misplaced, the whole sequence would be thrown off.
2. Command-Line Interfaces (CLI): The 1980s saw a shift from punch cards to command-line interfaces. Computers like the IBM PC and Apple Macintosh popularized the CLI. While it was more efficient than punch cards, it still required users to memorize commands and their syntax to communicate with the computer.
3. Graphical User Interfaces (GUI): As technology progressed, GUIs began to emerge in the late 1980s and early 1990s. The Apple Macintosh and Microsoft Windows operating systems popularized this interface. Icons, windows, and point-and-click mechanisms made computing more accessible and intuitive for the masses.
4. Touch Interfaces: The 2000s heralded the age of touchscreens. Devices like smartphones and tablets brought a more intimate and direct way of interacting with computers. Pinching, zooming, and swiping became the new language of interaction.
5. Voice Recognition: With the rise of digital assistants like Siri, Alexa, and Google Assistant, voice became a primary mode of interaction. This allowed for hands-free computing and made technology even more embedded in our daily lives.
6. Generative AI and Conversational Interfaces: Today, we're in the age of conversational AI, epitomized by platforms like ChatGPT. These systems not only understand human language but can also generate human-like responses. It feels less like communicating with a machine and more like having a conversation with another human.

https://www.linkedin.com/pulse/from-punch-cards-conversational-ai-evolution-computer-adriana-rocha-1f
“The question we always focus on is ‘can this company become a monopoly?’”

He then lists several things that can make a company a monopoly:

Super fast distribution on a very thin product (e.g. Twitter)

A technological advantage that is continually built upon: you come up with something new and steadily improve (e.g. enterprise SaaS software)

A truly brilliant breakthrough (e.g. Bitcoin)

However he argues that complex coordination—where you take a lot of little pieces and coordinate them into something new—is continually overlooked as a way to create a monopoly:

“This is the thing that’s maybe 180 degrees antithetical to the Lean Startup ethos. It’s complicated. You have to put all the pieces together in just the right way. I think this is on some level what really drove Apple as an innovative company in the last decade… What was new about the iPhone? There was no single component that was new. It was just that you put all of these things together in just the right way… and once you built it, it was actually super hard for people to replicate. You had an advantage for many years. You could get network lock in—in terms of the app community or the brand.”

He also points to Tesla and SpaceX as examples:

“There’s no component to the Tesla that’s actually that new. It’s just that you put all of the pieces together. You re-engineered the whole distributor network. It was this complex coordination that made it work. There’s like this lost art of accounting where you figure out how much things cost and add them all together. And Elon has discovered this lost art of accounting which no other people practice.”

https://x.com/mikemcg0/status/1711727266537812429?s=46&t=h5Byg6Wosg8MJb4pbPSDow
it’s official - I think GitHub Copilot is the first* generative AI product to publicly claim they’ve passed $100m ARR — enough to stand alone as a publicly listed company

Whenever people ask me “is AI a fad” the biggest thing I point to is “follow the money”:

- revenue, not just funding
- RECURRING, not tcosts on hype
- people publicly saying they’d pay 5x the cost

(*there’s likely a few others but none confirmed officially - see Anatomy of Autonomy post on @latentspacepod)
next up is @DedyKredo LIVE CODING a full test suite, making code changes, and automating commit and PR review, all assisted by @CodiumAI . audible “what the fuck” from @eugeneyan.

youtube.com/live/qw4PrtyvJ

ends with a powerful message for Israel. we stand with you @itamar_mar.
Probably an underestimate. In less than ten years each American will have a dozen or more AI agents constantly running around the net with AI that is 10x more powerful. Huge increase in per capita consumption of electricity. Add the consumption of electricity by EV's and we will get a suprising nexus that will make household electricity consumption estimate obsolete. nytimes.com/2023/10/10/cli

https://x.com/vkhosla/status/1711960673754992885?s=46&t=h5Byg6Wosg8MJb4pbPSDow
the cost of sequencing a human genome was over $300 million in 2001. today, it's a $200.

expect similar cost reduction curves in AI over the next 20 years.