Difference between revisions of "AI & Machine Learning"
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<q>the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, learning, decision-making, and natural language processing</q> | <q>the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, learning, decision-making, and natural language processing</q> | ||
:: -- [https://globalpolicy.ieee.org/wp-content/uploads/2019/06/IEEE18029.pdf IEEE.org] | :: -- [https://globalpolicy.ieee.org/wp-content/uploads/2019/06/IEEE18029.pdf IEEE.org] | ||
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| + | ===Open Source AI=== | ||
| + | |||
| + | :* [https://openai.com OpenAI] an AI research and deployment company | ||
| + | :* [https://www.datamation.com/open-source/open-source-artificial-intelligence-50-top-projects/ 50 top open source AI projects] | ||
| + | :* [https://techcrunch.com/2022/12/02/openais-chatgpt-shows-why-implementation-is-key-with-generative-ai/ TechCrunch article about OpenAI's ChatGPT] | ||
==Machine Learning (ML)== | ==Machine Learning (ML)== | ||
Revision as of 14:52, 3 December 2022
this page is under construction
Contents
Definitions
Also see the Glossary on this site
Artificial Intelligence (AI)
the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, learning, decision-making, and natural language processing
- -- IEEE.org
Open Source AI
- OpenAI an AI research and deployment company
- 50 top open source AI projects
- TechCrunch article about OpenAI's ChatGPT
Machine Learning (ML)
In general, ML is the use of computer algorithms that can learn and adapt from processing digital data.
- --Rohit Sharma in Introduction to TinyML
Deep Learning (DL)
[a subfield of ML] that relies heavily on neural networks to process data and produce results
- --Rohit Sharma in Introduction to TinyML
TinyML
Tiny machine learning is broadly defined as a fast growing field of machine learning technologies and applications including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery operated devices.
References
- TinyML book homepage (with videos & large sample PDF)
- TinyML book on Amazon
- New thoughts on number representation for ML - article
- TinyML Cookbook
- Introduction to TinyML
