The hottest Search Algorithms Substack posts right now

And their main takeaways
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Top Technology Topics

Embeddings are a good starting point for the AI curious app developer

Bryant’s Newsletter • 572 HN points • 17 Apr 24
🕹 Technology AI App Development Database Management Search Algorithms
  1. Vector embeddings are essential for search and recommendations, measuring similarity in various languages and providing efficiency in AI app development.
  2. Pgvector, a Postgres extension, is a powerful tool for storing and querying embeddings and combining standard SQL logic with embedding operations.
  3. Working with embeddings feels like regular code compared to more complex language models, offering a simpler and more deterministic approach to AI development.

Emerging Wedges in Vertical AI Startups

Tanay’s Newsletter • 75 implied HN points • 16 Dec 24
🕹 Technology AI Startups Voice technology Search Algorithms Content Generation
  1. Voice AI helps businesses automate customer interaction, making it easier to handle calls and inquiries. This saves time and cuts costs while providing support 24/7.
  2. Unstructured data parsing allows companies to turn messy, unorganized information into useful data. This helps employees work faster and more accurately by reducing the need for manual data entry.
  3. Verticalized search tools aid in focused research by retrieving relevant, domain-specific information. They are particularly useful in fields like law and finance where specific data is crucial for decision-making.

Google Search's AI is (or should be) about cognitive load

The End(s) of Argument • 239 implied HN points • 16 May 24
🕹 Technology AI Information literacy Search Algorithms
  1. Web searching is like a rummage sale where finding specific answers to questions can be challenging, requiring skill and effort.
  2. Traditional search skills like reading search result pages and using ctrl-f are important in reducing cognitive load while navigating online information.
  3. Google Search's AI should focus on helping users handle the cognitive load of information by summarizing search results effectively, though it's not a replacement for comprehensive answers.

What is Sundar Pichai thinking?

Technology Made Simple • 39 implied HN points • 26 Mar 22
🕹 Technology AI Machine Learning Data Analysis Search Algorithms Consulting
  1. Google invests significantly in AI and Machine Learning research to enhance their business model - focusing on data-driven ads and boosting operational efficiency.
  2. Google's AI projects often revolve around solving complex search problems, which aligns with their goal of improving search algorithms for hyper-specific advertising.
  3. By mastering core skills like math, theoretical knowledge, problem-solving, and coding, individuals can prepare themselves to tackle challenges at scale similar to what Google does.
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