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Dale Markowitz

Personal blog · daleonai.comaiprogramming

Dale Markowitz writes Dale on AI, a personal blog at daleonai.com about ai and programming. Since 2020, 10 different Hacker News readers have linked it 16 times, most often “Transformers, Explained: Understand the Model Behind GPT-3, Bert, and T5”. No feed was found, so read it on the site itself.

No feed foundVisit the blog
16mentions?
10HN people?
2020–2024first – last linked?
Links on Hacker News per year · peak 6 in 2020

Too few sampled comments (3) to say how often HN recommends it.?

Why HN links it

HN readers link Dale Markowitz's posts for a plain-language explanation of transformers and the attention mechanism, and for a technical write-up on building AI-powered searchable video from a family archive.

Summarised by Claude from a sample of 3 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Dale Markowitz talks about AI

Most-linked posts?

  1. Transformers, Explained: Understand the Model Behind GPT-3, Bert, and T5
    4 people · 4 mentions · first linked 2021-08-24
  2. Building an AI-Powered Searchable Video Archive
    3 people · 3 mentions · first linked 2020-06-19
  3. AI Dubs over Subs? Translating and Dubbing Videos with AI
    2 people · 2 mentions · first linked 2021-02-03

What Hacker News says?

  1. I strongly agree with Steve on the potential of Nobel prize for the discovery and I want to add that the team probably going to win it within 10 years. For reference, Jack Kilby won his shared Nobel prize on integrated circuit (IC) that transforms the electronics and computer industry after more than 40 years of the original invention. Here is a very informative video and blog by Google Cloud Tech team explaining th…

    Comment linking /transformers-explained

    on “Ask HN: Can someone ELI5 Transformers and the “Attention is all we need” paper”
  2. Submitted You, Me, and My AI-Generated Alternate Identity as a story · 3 points

    HN discussion
  3. cratermoon · 2023-05-17Recommends
    One or both of these might help Transformers, Explained: Understand the Model Behind GPT-3, BERT, and T5: https://daleonai.com/transformers-explained Transformers from Scratch: https://e2eml.school/transformers.html The first link covers Attention well.

    Comment linking /transformers-explained

    on “Ask HN: Can someone ELI5 Transformers and the “Attention is all we need” paper”
  4. Submitted How Dalle Works in Under 5 Minutes as a story · 3 points

    HN discussion
  5. tastroder · 2020-07-28Recommends
    The post links to the authors technical write-up that's a little less of a simple ad for Google Vision: https://daleonai.com/building-an-ai-powered-searchable-video...

    Comment linking /building-an-ai-powered-searchable-video-archive

    on “30 years of family videos in an AI archive”
  6. Submitted Building an AI-Powered Searchable Video Archive as a story · 3 points

    HN discussion
  7. Submitted Transformers, Explained: Understand the Model Behind GPT-3, Bert, and T5 as a story · 2 points

    HN discussion
  8. Submitted AI Dubs over Subs? Translating and Dubbing Videos with AI as a story · 2 points

    HN discussion
  9. Submitted Experiments with 1M Token Context Windows as a story · 1 points

    HN discussion
  10. Submitted Transformers, Explained: Understand the Model Behind GPT-3, Bert, and T5 (2021) as a story · 1 points

    HN discussion
  11. Submitted Machine Learning's Most Useful Multitool: Embeddings as a story · 1 points

    HN discussion
  12. Submitted Translate and Dub Videos with Machine Learning as a story · 1 points

    HN discussion
  13. Submitted Build Apps Powered by Language with Semantic ML as a story · 1 points

    HN discussion
  14. Submitted GPT3 Explained in Under 3 Minutes as a story · 1 points

    HN discussion
  15. Submitted Building an AI-Powered Searchable Video Archive as a story · 1 points

    HN discussion
  16. Submitted Building a Discord AI Moderator Bot with the Perspective API as a story · 1 points

    HN discussion

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