The world is being transformed by Artificial Intelligence, from beating the world champion in Go in 2016 to the robust predictive abilities of OpenAI’s ChatGPT. Now, the complexity of AI training algorithms is growing at a rapid pace. To keep pace, hardware for AI applications is needed that is scalable and can handle complex models close to the end-user.
According to reports AI Chips: 2023–2033 and AI Chips for Edge Applications 2024–2034: Artificial Intelligence at the Edge by IDTechEx, growth of AI for training and inference within the cloud and on the edge is expected to continue over the next decade as our world and the devices within it become increasingly automated and interconnected.
Designing hardware for a particular function, particularly to accelerate certain types of computations, has been around for some time. Early computing days saw CPUs paired with mathematical coprocessors known as Floating-Point Units. Graphics processing also saw new pieces of hardware developed for specialized workloads. Similarly, the emergence of machine learning has brought about a demand for another type of accelerator which efficiently handles workloads. From computer graphics to machine learning workloads, AI has paved the way for a new type of accelerator that can efficiently handle complex workloads.
The reports detail differences in chip architectures and their effectiveness in handling machine learning workloads, outlining details on the leading AI algorithms that may take days to complete.
The growth of AI chips over the next decade is set to achieve huge profits, generating close to USD$300 billion by 2034. Large profits are forecasted in the IT & Telecoms industry and the Consumer Electronics industry as AI capabilities are deployed closer to the end-user. For more detailed insights, there are two reports by IDTechEx: “AI Chips: 2023–2033” and “AI Chips for Edge Applications 2024–2034: Artificial Intelligence at the Edge“.
The two reports cover the AI Chips market across eight industry verticals and six industry verticals respectively, with granular forecasts in seven different categories in “AI Chips: 2023–2033” and six different categories in “AI Chips for Edge Applications 2024–2034: Artificial Intelligence at the Edge” The reports present deep insights into the semiconductor industry for the next decade.
Is your business or organization looking to capitalize on these emerging technologies and trends?Contact IDTechEx or visit http://www.IDTechEx.com for more information.
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