Introducing Surge AI: High-Quality Data Labeling for NLP

In 2016, DeepMind began building an AI to beat StarCraft II — and by the end of 2019, its AlphaStar AI reached GrandMaster level. https://www.youtube.com/watch?v=5iZlrBqDYPM

👀 What’s happened since then?

A GPT-3-written blog post on productivity that reached the top of Hacker News. https://liamp.substack.com/p/my-gpt-3-blog-got-26-thousand-visitors

Then where’s the revolution?

https://www.theverge.com/2018/1/12/16882408/google-racist-gorillas-photo-recognition-algorithm-ai

What’s wrong with today’s data? Garbage in, garbage out 🦝

https://twitter.com/DeepStateExpose/status/1281503301540995072
https://twitter.com/sryxhaunting/status/1273413264769257473

🧗 What advancements do we need?

  1. Skilled, high-quality labelers who understand the problem you’re trying to solve 🎒
https://twitter.com/alexismadrigal/status/1278186137115217920

🤖 A data-driven AI future

So in order to build high-quality models, shouldn’t building high-quality datasets, and making sure they match the problem at hand, be the most important skill of an ML engineer?

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The world’s most powerful data labeling platform, designed from the ground up for stunning NLP. https://www.surgehq.ai

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Surge AI

Surge AI

The world’s most powerful data labeling platform, designed from the ground up for stunning NLP. https://www.surgehq.ai

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