Remove 2016 Remove Artificial Intelligence Remove Supervised Learning
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Counting shots, making strides: Zero, one and few-shot learning unleashed 

Data Science Dojo

In the dynamic field of artificial intelligence, traditional machine learning, reliant on extensive labeled datasets, has given way to transformative learning paradigms. Source: Photo by Hal Gatewood on Unsplash In this exploration, we navigate from the basics of supervised learning to the forefront of adaptive models.

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AI 101: A beginner’s guide to the basics of artificial intelligence

Dataconomy

With the rise of AI-generated art and AI-powered chatbots like ChatGPT, it’s clear that artificial intelligence has become a ubiquitous part of our daily lives. But amidst all the hype, it’s worth asking ourselves: do we really understand the basics of artificial intelligence? What is artificial intelligence?

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How to tackle lack of data: an overview on transfer learning

Data Science Blog

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves. That is, is giving supervision to adjust via.

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Data Science Dojo - Untitled Article

Data Science Dojo

Counting Shots, Making Strides: Zero, One and Few-Shot Learning Unleashed In the dynamic field of artificial intelligence, traditional machine learning, reliant on extensive labeled datasets, has given way to transformative learning paradigms. Welcome to the frontier of machine learning innovation!

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Foundation models: a guide

Snorkel AI

Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning?

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Interactive Fleet Learning

BAIR

Figure 1: “Interactive Fleet Learning” (IFL) refers to robot fleets in industry and academia that fall back on human teleoperators when necessary and continually learn from them over time. Waymo , for example, has over 700 self-driving cars operating in Phoenix and San Francisco and is currently expanding to Los Angeles.

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Explosion in 2017: Our Year in Review

Explosion

We founded Explosion in October 2016, so this was our first full calendar year in operation. spaCy In 2017 spaCy grew into one of the most popular open-source libraries for Artificial Intelligence. We set ourselves ambitious goals this year, and we’re very happy with how we achieved them. Here’s what we got done.