I think, like Obsidian, it stores them as markdown files.

Then Logseq. It’s an outliner (each line can be it’s own…thing…), but it’s open source and a direct competitor of Obsidian. In fact, I was ambivalent between the two when I first started with online note-taking.

Among respondents who own luxury brands that they themselves bought (e.g., Gucci, Versace, Rolex), 44% prefer to live in a world without any of those brands altogether. Among respondents not owning such brands, the fraction preferring to live in a world without them is 69%.

That’s interesting.

Actually, this is kinda like using fossil fuels. If we didn’t have fossil fuels our lives would be miserable. And while using them adds some utility, burning fossil fuels still leaves us miserable, particularly as climate change grows worse.And so, even though I use fossil fuels to fuel my car, heat my home, and cook my food, I’d still prefer to live in a world where its significantly reduced to phased out altogether.

Can you see bot accounts? You might have a bot message for some reason that isn’t showing.

Claude.ai. I took the transcript of the video and asked for an outline using a prompt I usually use for outlining textbook chapters lol.

Here’s an AI outline because this was actually a good talk:

• How Platforms Die

  • The speaker introduces the concept of platform decay or “enshittification” and how it leads to the death of internet platforms.
    • He defines platforms as firms like Uber, Amazon, and Facebook that connect users and business customers.
  • He outlines a 3-stage process called enshittification where platforms:
    • Are initially good to users
    • Abuse users to benefit business customers
    • Eventually abuse business customers to only benefit shareholders
  • This results in the platform becoming a “pile of shit” that dies.

• Facebook Case Study

  • He uses Facebook as a case study of enshittification’s 3 stages:
    • Initially attracted users by promising privacy protections and custom feeds
    • Then broke promises and sold user data to advertisers and flooded feeds with publisher content
    • Finally, reduced value to users and fees for publishers to extract all value for shareholders
      • This led to an angry user base and brittle equilibrium

• Causes of Enshittification

  • Lack of Competition
    • Weak antitrust enforcement has allowed consolidation across industries
    • Companies can use predatory pricing to undercut competitors
    • Mergers eliminate competition
      • Example: Google relying on acquisitions rather than in-house innovation
  • Unrestricted “Backend Tweaking”
    • Tech platforms control the algorithms and systems behind their products
    • They can arbitrarily change these to alter user experiences
      • e.g. Facebook reducing visibility of publisher content in feeds
    • Done without transparency, oversight or accountability
  • Bans on Reverse Engineering
    • Laws like DMCA 1201 and CFAA criminalize circumventing DRM and terms of service
    • Makes it illegal to reverse engineer platforms to enable interoperability
    • Tech companies use IP laws to prevent modding and adversarial interoperability
      • e.g. Apple using IP laws to prevent iOS modding

• Solutions

  • Strengthen Antitrust Enforcement
    • Block anti-competitive mergers
    • Break up existing tech giants
  • Pass Privacy, Labor and Consumer Protection Laws
    • Comprehensive federal privacy laws with private right of action
    • End worker misclassification through gig economy
    • Apply consumer protection standards to platforms
  • Allow Adversarial Interoperability
    • Roll back laws criminalizing modding, reverse engineering
    • Use government procurement to incentivize open ecosystems
    • Appoint special masters to oversee platform legal threats
  • Keep Interoperators in Check
    • Bind interoperators to the same privacy, fair trading and labor laws
    • Determined through democratic process vs corporate policy

• Conclusion

  • We need to prepare and spread these policy ideas to capitalize on the next crisis
  • Efforts are underway to enable a better internet through this approach

the best way to use LLMs - general definitions or framing / summarizing of issues. And then always check the sources to make sure it was accurate.

I agree. The criticism that they’re not accurate kinda misses the point of LLMs being tools. It’d be like complaining that a hammer doesn’t jam the nail in all the way after the first stroke. Hit it again…and maybe try hitting it straight this time instead of at an angle. It’s an iterative process that can be self-correcting when done thoughtfully.

Or the right one if I want to “be the change I want to see in the world”.

Oh boy. I do research on it for various things. Florida released some laws changing alimony and I researched it via Perplexity to understand what the problem was. It worked. I understood the issue.

Or carbon capture technology.

In any case, I do look directly at the sources. Perplexity.ai is useful for framing a topic, getting the gist of it, but for being sure I know wtf is going on, I personally need to look at the sources.

As someone getting an MBA that hates the idea of labor being displaced by AI, if I were an unethical business owner that treated labor as a cost to minimize, I’d use AI to generate content that’s “good enough” and use fewer people to make it exactly to my specification.

Perplexity.ai has been a solid addition to my internet searches.