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Based on our record, Digg seems to be a lot more popular than Scale Nucleus. While we know about 74 links to Digg, we've tracked only 2 mentions of Scale Nucleus. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
They are referring to digg who set up most AMA. Source: about 1 year ago
Or is it a success because Reddit Inc has shown its hand of not giving a shit about your average user and this site will bleed users as they, especially power users who actually post and moderate and build the communities in the first place flee to places where their countless hours of unpaid labor are appreciated (like lemmy, kbin, mastodon), and good old reddit becomes a ghost town like digg which is apparently... Source: about 1 year ago
It's the great unraveling. Communities are torn asunder. It's could very well be the first step of Reddits fall. Or reddit will just look and feel very different afterwards. A husk of an aggregator. Go to digg.com right now to see what reddit might be. Source: about 1 year ago
Reddit owes much of its success to the digg.com exodus, it would be fitting for its demise to be caused by a similar exodus. Source: about 1 year ago
I went over to see what digg.com was up to these days. Their comment section is comprised of reddit comments. Brutal. Source: about 1 year ago
At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago
To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 years ago
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Aquarium - Improve ML models by improving datasets they’re trained on
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