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Elements of AI is a massive open online course (MOOC) teaching the basics of artificial intelligence. [1] The course, originally launched in 2018, is designed and organized by the University of Helsinki and learning technology company MinnaLearn . [ 2 ]
According to Google Research, chain-of-thought (CoT) prompting is a technique that allows large language models (LLMs) to solve a problem as a series of intermediate steps before giving a final answer. In 2022, the Brain team of Google also claimed that chain-of-thought prompting improves reasoning ability by inducing the model to answer a ...
Google collects its AI initiatives under Google.ai. Archived October 8, 2018, at the Wayback Machine. Google collects AI-based services across the company into Google.ai – "Google.ai is a collection of products and teams across Alphabet with a focus on AI." Google's deep focus on AI is paying off. Archived October 20, 2020, at the Wayback ...
Coursera Inc. (/ k ər ˈ s ɛ r ə /) is an American global massive open online course provider. It was founded in 2012 [2] [3] by Stanford University computer science professors Andrew Ng and Daphne Koller. [4] Coursera works with universities and other organizations to offer online courses, certifications, and degrees in a variety of subjects.
He is also co-founder of Coursera, a massive open online course (MOOC) education platform, with Daphne Koller. Peter Norvig – co-author, with Stuart Russell, of Artificial Intelligence: A Modern Approach, now the leading college text in the field. He is also Director of Research at Google, Inc.
In the context of AI, it is particularly used for embedded systems and robotics. Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6]
In 2011, Ng founded the Google Brain project at Google, which developed large-scale artificial neural networks using Google's distributed computing infrastructure. [43] Among its notable results was a neural network trained using deep learning algorithms on 16,000 CPU cores , which learned to recognize cats after watching only YouTube videos ...
For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...
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