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Snorkel AI

Company blog · snorkel.aiaidata

Snorkel AI is the company blog at snorkel.ai, writing about ai and data. Since 2020, 16 different Hacker News readers have linked it 18 times, most often “Snorkel AI: Putting Data First in ML Development”. It is still writing: the last post was on 2026-10-16, and you can follow it by feed.

Visit the blog
18mentions?
16HN people?
2020–2025first – last linked?
Links on Hacker News per year · peak 7 in 2020

Too few sampled comments (7) to say how often HN recommends it.?

Why HN links it

HN readers link Snorkel AI's site for its data labeling and annotation pages and its customer case studies. Commenters also discuss the company's data-labeling work and its research papers.

Summarised by Claude from a sample of 7 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Snorkel AI builds specialized training data, benchmarks, and evaluation environments that help frontier models and agents perform in high-stakes domains.

Most-linked posts?

  1. /case-studies
    3 people · 3 mentions · first linked 2020-07-16
  2. Snorkel AI: Putting Data First in ML Development
    2 people · 2 mentions · first linked 2020-07-14
  3. Snorkel AI: Putting Data First in ML Development
    2 people · 2 mentions · first linked 2020-07-14

What Hacker News says?

  1. > In my opinion, being able to write the code to do the thing is effectively the same exact thing as doing the thing That's great, but it's demonstrably false. I can write code that calculates the average letter frequency across any Wikipedia article. I can't do that in my head without tools because of the rule of seven[1]. Tool use is absolutely an intelligence amplifier but it isn't the same thing. > Because again…

    Comment linking /blog/introducing-snorkelspatial/

    on “Gemini 3 Pro: the frontier of vision AI”
  2. Submitted Snorkel AI: Putting Data First in ML Development as a story · 81 points

    HN discussion
  3. Snorkel AI | Senior Software Engineer | Palo Alto | Full Time At Snorkel AI, we’re redefining how people and organizations build AI applications. We are building a higher-level interface for machine learning through programmatically labeled and managed training data and our application has been deployed at some of the some of the world’s largest institutions including Google, Stanford, DARPA and IBM. We’re looking f…

    Comment linking /careers

    on “Ask HN: Who is hiring? (May 2021)”
  4. Submitted Snorkel AI: Putting Data First in ML Development as a story · 12 points

    HN discussion
  5. Just look for any company that offers data annotation as a service, they seem happy to explain their process in detail[0]. There's even a link to a paper from OpenAI[1] and some news about the contractor count[2]. [0]: https://snorkel.ai/data-labeling/#Data-labeling-in-the-age-o... [1]: https://cdn.openai.com/papers/Training_language_models_to_fo... [2]: https://www.businessinsider.com/chatgpt-openai-contractor-la...

    Comment linking /data-labeling/

    on “What happens when people don't understand how AI works”
  6. Submitted Machine learning on Kubernetes: wisdom learned at Snorkel AI as a story · 3 points

    HN discussion
  7. If you included the previous and following sentences, it's at least to me clear what they mean: However, existing methods for training such models still rely heavily on vast human-curated tasks and labels, typically via fine-tuning or reinforcement learning, which poses a fundamental bottleneck to advancing AI systems toward capabilities beyond human intelligence To overcome this limitation, we introduce R-Zero, a f…

    Comment linking /blog/large-language-model-training-three-phases-shape-llm-training/

    on “R-Zero: Self-Evolving Reasoning LLM from Zero Data”
  8. Submitted Using few-shot learning language models as weak supervision as a story · 3 points

    HN discussion
  9. Hi all, this is Alex from the Snorkel team- thanks for all the great comments! Excited to respond to a few questions directly, but first highlighting some up here: - Where to find more about the core Snorkel concepts: We've published 36+ peer-reviewed papers, along with blog posts, talks, office hours, etc over the years (see https://www.snorkel.ai/technology and https://www.snorkel.ai/case-studies ), so I'll defer…

    Comment linking /case-studies

    on “Snorkel AI: Putting Data First in ML Development”
  10. Submitted Evaluating Coding Agents with Terminal-Bench 2.0 as a story · 2 points

    HN discussion
  11. There are some case studies on the website [0], but I would be wary of them. My experience from working in these kind of research environments is that the case studies are consulting jobs where a few PhD students do work for a company, and in return you can use the company name and write on your website whatever you want. They are probably not actually using the product. I'd be interested to hear about actual users…

    Comment linking /case-studies

    on “Snorkel AI: Putting Data First in ML Development”
  12. Submitted Liger: Fusing foundation model embeddings and weak supervision as a story · 2 points

    HN discussion
  13. Take a look at case studies: https://www.snorkel.ai/case-studies

    Comment linking /case-studies

    on “Snorkel AI: Putting Data First in ML Development”
  14. Submitted Snorkel AI: Putting Data First in ML Development as a story · 2 points

    HN discussion
  15. Submitted Snorkel AI: Putting Data First in ML Development as a story · 2 points

    HN discussion
  16. Submitted Enterprise Alignment from Snorkel AI as a story · 1 points

    HN discussion
  17. Submitted Redesigning Snorkel’s interactive machine learning systems as a story · 1 points

    HN discussion

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