Google is making its own custom AI chips
Many of the breakthroughs in artificial intelligence have only been made possible because companies now have access to previously unimaginable amounts of computing power, but now there is an arms race to create the "best" AI infrastructure stack
Cite or link to this article
Griffin, M. (2016) 'Google is making its own custom AI chips', 311 Institute, 18 May. Available at: https://www.311institute.com/google-is-making-its-own-custom-ai-chips/ (Accessed: 1 October 2026).
Google CEO Sundar Pichai announced today at the Google I/O developer conference that Google have begun to build its own custom Application-Specific Integrated Circuit (ASIC) chips called Tensor Processing Units (TPUs), after the name of it's open source deep learning framework TensorFlow. But the technology is one of a kind - something that makes sense only at Google's hyper scale.
These TPUs were the ones used in the AlphaGo artificial intelligence (AI) powered Go player that beat top ranked Go player Lee Sedol earlier this year and they've also already been put to work inside Google search and Google Street View. Now it sounds like they will become available for other companies to use, too.
“When you use the Google Cloud Platform, you can take advantage of TPUs as well,” said Pichai, but Google aren't just relying on new speciality hardware to take on public cloud leader Amazon Web Services (AWS), over time Google will expose more and more machine learning APIs, Pichai said. Google has already launched the Cloud Machine Learning Platform service and the Vision API.
“Our goal is to lead the industry on machine learning and make that innovation available to our customers,” said Google distinguished hardware engineer Norm Jouppi.
“Building TPUs into our infrastructure stack will allow us to bring the power of Google to developers across software like TensorFlow and Cloud Machine Learning with advanced acceleration capabilities. Machine Learning is transforming how developers build intelligent applications that benefit customers and consumers, and we’re excited to see the possibilities come to life.”
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Why does this matter?
Many of the breakthroughs in artificial intelligence have only been made possible because companies now have access to previously unimaginable amounts of computing power, but now there is an arms race to create the "best" AI infrastructure stack
About the author
Matthew Griffin Founder, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Sources and further reading
- Application specific integrated circuit en.wikipedia.org
- TensorFlow tensorflow.org
- Cloud Machine Learning Platform cloud.google.com
Source: first published by the 311 Institute on 18 May 2016. Cite as: Griffin, M. (2016). Google is making its own custom AI chips. 311 Institute. https://www.311institute.com/google-is-making-its-own-custom-ai-chips/
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