The hottest Substack posts of Michael Mignano's Newsletter

And their main takeaways

Who Loses When the Algorithms Win?

157 implied HN points • 04 Aug 22
  1. Recommendation media is more efficient and controlled by platforms, impacting content distribution and engagement.
  2. Photographers and influencers may lose out in a recommendation media world due to increased focus on video content over photos.
  3. Startups face challenges in a recommendation media landscape, but social media startups may find opportunities to fill the gap in human connection left by algorithmic content distribution.

The End of Social Media and the Rise of Recommendation Media

39 implied HN points • 27 Jul 22
  1. Recommendation media is the new standard for content distribution, shifting away from friend graphs to algorithmic experiences.
  2. Social media platforms face challenges like problematic content distribution and echo chambers, leading to high moderation costs.
  3. In recommendation media, algorithms decide content distribution, optimizing for engagement and providing a more efficient consumption experience.

Fictional Reality: Why the Real Metaverse Doesn't Require a Headset

7 HN points • 09 Dec 22
  1. AI is enabling us to live out alternative realities online without the need for futuristic devices like VR headsets.
  2. Fictional Reality involves crafting online versions of our identities, relationships, and experiences for positive reasons.
  3. Through platforms like Lensa and ChatGPT, people are increasingly embracing fictional identities and relationships online.

The Standards Innovation Paradox

1 HN point • 12 Jul 22
  1. Standards facilitate faster product development by providing a common language for interaction.
  2. Adopting standards can lead to market fragmentation and hinder innovation in the long run.
  3. The Standards Innovation Paradox presents a trade-off between quick market access and long-term innovation when developing products based on standards.
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Training Data Mines

0 implied HN points • 05 Jun 23
🕹 Technology AI Data Platforms NLP
  1. Unique training data is highly valuable for AI in an AI-first world.
  2. Platforms like Reddit are charging for access to their data due to its value for AI training.
  3. Reddit's content diversity and user interactions make its data beneficial for training AI models.