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Updated November 2, 2022Youβre reading an excerpt of Making Things Think: How AI and Deep Learning Power the Products We Use, by Giuliano Giacaglia. Purchase the book to support the author and the ad-free Holloway reading experience. You get instant digital access, plus future updates.
This chapter reflects recent developments and was last updated in October of 2022.
This landscape of the top artificial intelligence teams aims to track the most prominent teams developing products and tools in each of several areas. Tracking these teams gives a good starting point of the activity of where future development will be.
2022 has seen remarkable tools being developed by top teams, including some, especially DALL-E 2, that are so impressive they have gone viral. This builds on high-profile tools released to the public in the past two years, including GPT-3 in 2020 and GitHub CoPilot (based on GPT-3) in June 2021, which now enjoys widespread use by almost 2 million developers.
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In 2022, we continue to see the growing size of neural networks, even though there hasnβt been a new development in neural networks as game-changing as Transformers in 2017. In 2021, Microsoft released a 135 billion parameter neural network model, and at the end of 2021, Nvidia together with Microsoft released an even larger model, called Megatron-Turing NLG, with 530 billion parameters. There is no reason to believe that the growth will stop any time soon. We havenβt seen a model of headline-grabbing size as of July 2022, but that could change by the end of the year.
Credit: Generated with DALL-E 2.