pgao

8 ms·

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Show HN: Tidepool – analytics for large text datasets(tidepool.so)
5 points by pgao 3y ago|1 comments
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Tidepool: Product analytics for AI text interfaces(tidepool.so)
6 points by pgao 3y ago|1 comments
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by pgao 3y ago
With the last few months, there's been a Cambrian explosion of products integrating AI. A big part of this is because LLMs enable users to get good performance on a lot of NLP tasks out-of-the-box by calling an API or running a pre-tra
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To Make Your Model Better, First Figure Out What’s Wrong(aquariumlearning.com)
1 points by pgao 4y ago|0 comments
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Few Shot Learning with Embeddings(pgao.medium.com)
1 points by pgao 4y ago|1 comments
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by pgao 4y ago
From previous experience doing applied ML, it's pretty hard to do pretty basic operations on data - splitting broad classes into fine classes, collecting data that the model struggles on, etc. However, there's been a lot of recent
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Lessons from Deploying Deep Learning to Production(thegradient.pub)
16 points by pgao 4y ago|0 comments
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Aquarium (YC S20) is hiring engineers to build the platform for data-centric ML(aquariumlearning.com)
1 points by pgao 4y ago
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by pgao 5y ago
Aquarium ( https://aquariumlearning.com/ ) | Remote Only (North American Timezones) | Full Time Aquarium is an ML data management system that helps ML teams improve their models by improving their datasets. Aquarium uncovers
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The Unreasonable Effectiveness of Neural Network Embeddings(medium.com)
4 points by pgao 6y ago|0 comments
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by pgao 6y ago
I think active learning has a time and a place. If you're getting started with a project from scratch, you probably don't need active learning for the exact reasons you describe - as long as you still get good improvements to mode
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by pgao 6y ago
Former self-driving engineer here. I'm also pretty skeptical about synthetic data. For the scenario you described, it turns out that if you drive enough, you'll eventually see some examples of ambulances at night in the rain. If i
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by pgao 6y ago
Here's a great paper to get started with! https://arxiv.org/abs/1703.04977
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Scaling An ML Team From 0–10 People(medium.com)
3 points by pgao 6y ago|0 comments
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It's the Data, Stupid Adventures in ML Engineering(medium.com)
4 points by pgao 6y ago|0 comments
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by pgao 6y ago
Yup, I saw your form submission through our site! I reached out to you over email, I'm confident we can help out :)
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by pgao 6y ago
Thanks! We don't expect users to upload all data to our service - the type of data we're interested in is "metadata." URLs to the raw data, labels, inferences, embeddings, and any additional attributes for their dataset.
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by pgao 6y ago
Thanks for the shoutout! We got connected to jononor through our previous r/machinelearning launch: https://www.reddit.com/r/MachineLearning/comments/hjbl4h/p_l...
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by pgao 6y ago
Thanks a bunch! I think the biggest issues with this approach is the requirement for embeddings. It's hard sometimes for a customer to understand what layer to pull out of their net to send to us, so sometimes we just use a pretrained
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by pgao 6y ago
I absolutely, 120% agree on the importance of adding the right data. Aquarium helps you with: "what data should I be collecting to improve my model" and "where do I find that data?" For the latter, Aquarium treats the pr
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by pgao 6y ago
Yes, your interpretation is correct. I don't think we're going to get into synthetic data generation in the near term, mainly due to the amount of effort required + questions about domain transfer. However, we do improve dataset q
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by pgao 6y ago
Hey there, it's a product right now! Our goal is to make it self serve, but we're currently onboarding people one-by-one manually until we can streamline the onboarding flow and build out a self serve process. Feel free to DM me o
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Launch HN: Aquarium (YC S20) – Improve Your ML Dataset Quality
167 points by pgao 6y ago|19 comments
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Study reveals average tech worker's wardrobe is 85% free tech t-shirts(haltingproblem.tumblr.com)
18 points by pgao 12y ago|5 comments
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Pinterest's Diversity Numbers(engineering.pinterest.com)
3 points by pgao 12y ago|0 comments