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IDTechEx Reports on The Age of Artificial Intelligence: AI Chips to 2034

Published

8 months ago

January 29, 2024

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The Age of Artificial Intelligence: AI Chips to 2034
Artificial Intelligence is transforming the world as we know it; from the success of DeepMind over Go world champion Lee Sedol in 2016 to the robust predictive abilities of OpenAI’s ChatGPT, the complexity of AI training algorithms is growing at a startlingly fast pace, where the amount of compute necessary to run newly-developed training algorithms appears to be doubling roughly every four months. In order to keep pace with this growth, hardware for AI applications is needed that is not just scalable – allowing for longevity as new algorithms are introduced while keeping operational overheads low – but is also able to handle increasingly complex models at a point close to the end-user.
Drawing from the “AI Chips: 2023–2033” and “AI Chips for Edge Applications 2024–2034: Artificial Intelligence at the Edge” reports, IDTechEx predicts that the growth of AI, both for training and inference within the cloud and inference at the edge, is due to continue unabated over the next ten years, as our world and the devices that inhabit them become increasingly automated and interconnected.
The why and what of AI chips
The notion of designing hardware to fulfill a certain function, particularly if that function is to accelerate certain types of computations by taking control of them away from the main (host) processor, is not a new one; the early days of computing saw CPUs (Central Processing Units) paired with mathematical coprocessors, known as Floating-Point Units (FPUs). The purpose was to offload complex floating point mathematical operations from the CPU to this special-purpose chip, as the latter could handle computations more efficiently, thereby freeing the CPU up to focus on other things.
As markets and technology developed, so too did workloads, and so new pieces of hardware were needed to handle these workloads. A particularly noteworthy example of one of these specialized workloads is the production of computer graphics, where the accelerator in question has become something of a household name: the Graphics Processing Unit (GPU).
Just as computer graphics required the need for a different type of chip architecture, the emergence of machine learning has brought about a demand for another type of accelerator, one that is capable of efficiently handling machine learning workloads. Machine learning is the process by which computer programs utilize data to make predictions based on a model and then optimize the model to better fit with the data provided, by adjusting the weightings used. Computation, therefore, involves two steps: Training and Inference.
The first stage of implementing an AI algorithm is the training stage, where data is fed into the model, and the model adjusts its weights until it fits appropriately with the provided data. The second stage is the inference stage, where the trained AI algorithm is executed, and new data (not provided in the training stage) is classified in a manner consistent with the acquired data.
Of the two stages, the training stage is more computationally intense, given that this stage involves performing the same computation millions of times (the training for some leading AI algorithms can take days to complete). As such, training takes place within cloud computing environments (i.e. data centers), where a large number of chips are used that can perform the type of parallel processing required for efficient algorithm training (CPUs process tasks in a serialized manner, where one execution thread starts once the previous execution thread has finished. In order to minimize latency, large and numerous memory caches are utilized so that most of the execution thread’s running time is dedicated to processing. By comparison, parallel processing involves multiple calculations occurring simultaneously, where lightweight execution threads are overlapped such that latency is effectively masked. Being able to compartmentalize and carry out multiple calculations simultaneously is a major benefit for training AI algorithms, as well as in many instances of inference). By contrast, the inference stage can take place within both cloud and edge computing environments. The aforementioned reports detail the differences between CPU, GPU, Field Programmable Gate Array (FPGA) and Application-Specific Integrated Circuit (ASIC) architectures, and their relative effectiveness in handling machine learning workloads.
Within the cloud computing environment, GPUs currently dominate and are predicted to continue to do so over the next ten-year period, given Nvidia’s dominance in the AI training space. For AI at the edge, ASICs are preferred, given that chips are more commonly designed with specific problems in mind (such as for object detection within security camera systems, for example). As the below graph shows, Digital Signal Processors (DSPs) also account for a significant share of AI coprocessing at the edge, though it should be noted that this large figure is primarily due to Qualcomm’s Hexagon Tensor Processor (which is found in their modern Snapdragon products) being a DSP. Should Qualcomm redesign the HTP such that it strays from being a DSP, then the forecast would heavily skew in favour of ASICs.
AI as a driver for semiconductor manufacture
Chips for AI training are typically manufactured at the most leading-edge nodes (where nodes refer to the transistor technology used in semiconductor chip manufacture), given how computationally intensive the training stage of implementing an AI algorithm is. Intel, Samsung, and TSMC are the only companies that can produce 5 nm node chips. Out of these, TSMC is the furthest along with securing orders for 3 nm chips. TSMC has a global market share for semiconductor production that is currently hovering at around 60%. For the more advanced nodes, this is closer to 90%. Of TSMC’s six 12-inch fabs and six 8-inch fabs, only two are in China, and one is in the USA. The rest are in Taiwan. The semiconductor manufacture part of the global supply chain is therefore heavily concentrated in the APAC region, principally Taiwan.
Such a concentration comes with a great deal of risk should this part of the supply chain be threatened in some way. This is precisely what occurred in 2020 when a number of complementing factors (discussed further in the “AI Chips: 2023 – 2033” report) led to a global chip shortage. Since then, the largest stakeholders (excluding Taiwan) in the semiconductor value chain (the US, the EU, South Korea, Japan, and China) have sought to reduce their exposure to a manufacturing deficit, should another set of circumstances arise that results in an even more exacerbated chip shortage. This is shown by the government funding announced by these major stakeholders in the wake of the global chip shortage, represented below.
These government initiatives aim to spur additional private investment through the lure of tax breaks and part-funding in the way of grants and loans. While many of the private investments displayed pictorially below were made prior to the announcement of such government initiatives, other additional and/or new private investments have been announced in the wake of them, spurred on as they are by the incentives offered through these initiatives.
A major reason for these government initiatives and additional private spending is the potential of realizing advanced technology, of which AI can be considered. The manufacture of advanced semiconductor chips fuels national/regional AI capabilities, where the possibility for autonomous detection and analysis of objects, images, and speech are so significant to the efficacy of certain products (such as autonomous vehicles and industrial robots) and to models of national governance and security, that the development of AI hardware and software has now become a primary concern for government bodies that wish to be at the forefront of technological innovation and deployment.
Growth of AI chips over the next decade
Revenue generated from the sale of AI chips (including the sale of physical chips and the rental of chips via cloud services) is expected to rise to just shy of USD$300 billion by 2034, at a compound annual growth rate of 22% from 2024 to 2034. This revenue figure incorporates the use of chips for the acceleration of machine learning workloads at the edge of the network, for telecom edge, and within data centers in the cloud. As of 2024, chips for inference purposes (both at the edge and within the cloud) comprise 63% of revenue generated, with this share growing to more than two-thirds of the total revenue by 2034.
This is in large part due to significant growth at the edge and telecom edge, as AI capabilities are harnessed closer to the end-user. In terms of industry vertical, IT & Telecoms is expected to lead the way for AI chip usage over the next decade, with Banking, Financial Services & Insurance (BFSI) close behind, and Consumer Electronics behind that. Of these, the Consumer Electronics industry vertical is to generate the most revenue at the edge, given the further rollout of AI into consumer products for the home. More information regarding industry vertical breakout can be found in the relevant AI reports.
The “AI Chips for Edge Applications 2024–2034: Artificial Intelligence at the Edge” report gives analysis pertaining to the key drivers for revenue growth in edge AI chips over the forecast period, with deployment within the key industry verticals – consumer electronics, industrial automation, and automotive – reviewed. More generally, the report covers the global edge AI Chips market across six industry verticals, with 10-year granular forecasts in six different categories (such as by geography, by chip architecture, and by application). IDTechEx also offers expert-led data and analysis on these and other related topics through a market intelligence subscription.
This article is from “Technology Innovations Outlook 2024-2034”, a complimentary magazine of analyst-written articles by IDTechEx providing insights into a number of areas of technology innovation, assessing the landscape now and giving you the outlook for the next decade.

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Prime Minister concludes successful visit from President of France to Canada

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1 day ago

September 27, 2024

Wladimir P.

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The Prime Minister, Justin Trudeau, welcomed the President of France, Emmanuel Macron, to Canada from September 25 to 26, 2024. With stops in Ottawa, Ontario, and Montréal, Quebec, the visit helped further strengthen the close ties between our countries and advance our shared priorities.
The leaders announced three key declarations that will align Canada and France’s work to preserve peace and security, take ambitious climate action, protect the environment, and responsibly harness the full potential of artificial intelligence (AI).
The first of these three declarations, the Canada-France Declaration on a Stronger Defence and Security Partnership, underscores Canada and France’s steadfast commitment to supporting Ukraine in the face of Russia’s illegal invasion. It also reaffirms our contributions to regional stability and security in the Indo-Pacific and reflects our co-operation in managing emergencies, modernizing our armed forces, and combatting foreign interference.
The two leaders discussed shared, ongoing work to respond to the humanitarian situation in Haiti and reiterated their support for the United Nations-authorized Multinational Security Support mission in the country. Canada and France are in steadfast support of Haitian-led solutions to the conflict that will make a meaningful and lasting difference in the lives of the Haitian people – and build a better future.
Building on the progress made at the United Nations General Assembly and the Summit of the Future earlier this week, Prime Minister Trudeau and President Macron highlighted the critical importance of continued action to fight climate change and protect our oceans. In the Canada-France Declaration on the Ocean, the leaders underlined the vital role that oceans play for the environment, the climate, the economy, and food and energy security throughout the world. To advance our work, Prime Minister Trudeau announced Canada’s membership in the Paris Pact for People and the Planet. The Pact, led by France and in partnership with global leaders, emphasizes collective action to accelerate sustainable development and create opportunities to help lift vulnerable populations out of poverty.
During the visit, the Prime Minister and the President met with AI experts, entrepreneurs, and industry leaders to discuss the risks and benefits of this new technology. Canada and France have world-leading AI ecosystems, including leadership roles in the Global Partnership on Artificial Intelligence (GPAI), which has 29 members worldwide. A testament to our progress in growing a dynamic AI industry, GPAI’s first two centres of expertise opened in Canada and France. Moving forward on this work, the Prime Minister and the President announced the Canada-France Declaration on Artificial Intelligence. The Declaration reiterates our countries’ commitment to a safe use of AI that respects human rights and democratic values.
During President Macron’s visit, Canada was also named Country of the Year for the Viva Technology 2025 technology conference, which will be held in Paris next year. At this event, Canada’s delegation will collaborate with the international community and meet with thousands of visionary start-ups, investors, organizations, and researchers to leverage advances in AI to strengthen our economy, increase productivity, and create new opportunities for Canadians. SCALE AI, Canada’s Global Innovation Cluster dedicated to AI, will lead Canada’s business delegation.
Prime Minister Trudeau and President Macron reaffirmed their commitment to promoting the French language and La Francophonie’s institutions ahead of the next Sommet de la Francophonie, which will be held in Villers-Cotterêts and Paris, France, on October 4 and 5, 2024. They also renewed their commitment to strengthening strategic coordination in preparation for the successive G7 Presidencies that Canada and France will hold, in 2025 and 2026 respectively.
Quote“Canada and France’s relationship is built on shared history, a common language, and democratic values. President Macron’s visit to Canada is a testament to the enduring friendship between our two countries, and with the progress we have made over this visit, we will move forward to build a fairer and more prosperous future for our peoples.”— The Rt. Hon. Justin Trudeau, Prime Minister of Canada
Quick Facts

This was President Macron’s second visit to Canada. It followed both leaders’ participation in the United Nations General Assembly and Summit of the Future in New York City, United States of America.
As a permanent member of the United Nations Security Council, the North Atlantic Treaty Organization (NATO), the G7 and the G20, a founding member of the European Union, and a key partner in the Organisation internationale de la Francophonie, France is a key ally for Canada on the international stage.
In 2023, France was Canada’s third largest merchandise export market in the European Union, and its 12th largest trade partner globally, with two-way merchandise trade totalling $12.9 billion.
That same year, Canadian exports to France amounted to $4.3 billion, while imports from France totalled $8.7 billion.
In France, Canada is represented by an embassy in Paris and consulates in Lyon, Nice, and Toulouse. France is represented in Canada by its embassy in Ottawa and consulates in Vancouver, Toronto, Montréal, Québec, and Moncton.

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Relativity Spotlights Legal Industry Leaders at the 2024 Innovation Awards

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1 day ago

September 27, 2024

Wladimir P.

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Relativity, a global legal technology company, today announced the winners of this year’s Innovation Awards at Relativity Fest. The Innovation Awards celebrate the trailblazing individuals and teams building custom solutions, empowering their peers and forging new paths to improve the legal industry and its communities.
“Another year of the Innovation Awards signals another opportunity to celebrate our community’s dedication to making a positive impact– whether that be through developing new solutions, providing excellent customer service, or elevating and advocating for their peers in the legal industry,” said Laurie Usewicz, Chief Partner Officer at Relativity. “This year’s winners exemplify the impassioned and innovative spirit that makes the future of our industry a bright one.”
The winners hail from, or work directly with law firms, financial institutions and consultant management companies large and small, private and public. Through a combined process of a judging committee and a community vote, Best Innovation winners are selected based on how they’ve leveraged the Relativity application programming interfaces in creative ways to solve Relativity’s customers’ most unique challenges.
In addition to the standard six individual and two Best Innovation awards, a new Best Innovation category was added for this year, Developer Partner. This award recognizes solutions created by Relativity’s independent software vendor (ISV) community that are offered directly to customers. Eligibility is restricted to solutions that are not owned by an Enterprise or Solution, Advisor, or Provider Partner.
The 2024 Innovation Awards winners are:

Artificial Intelligence: Ben Sexton, Vice President, JND eDiscovery
Customer Experience: Jenna Rooney, Director, Client Services, Arete Incident Response
Education & Mentorship: Deedra Smith, Managing Director, FTI Consulting
Inclusion: Vazantha Meyers, Vice President, Discovery Services, Haystack ID
Security: Jenna Rooney, Director, Client Services, Arete Incident Response
Stellar Women: Stephanie L. Goutos, Lead Practice Innovation Attorney, Gunderson Dettmer
Best Innovation: Developer Partner: Redaction Suggestions in Blackout by Milyli
Best Innovation: Enterprise: Flywheel by Troutman Pepper eMerge
Best Innovation: Partner: GenAI Toolbox by EY Switzerland

Each of the award winners above exemplify what it means to be a changemaker at the individual, organizational and industry levels. All award winners are determined by a combination of Relativity judging committees unique to each category and a community vote.
Relativity congratulates all submissions for the innovative work delivered this past year.
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MC Digital Realty wins Frost & Sullivan’s 2024 Japan Data Center Services Company of the Year Award

Published

1 day ago

September 27, 2024

Wladimir P.

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Digital Realty (NYSE: DLR), the largest global provider of cloud- and carrier-neutral data center, colocation, and interconnection solutions, today announced that MC Digital Realty: A Mitsubishi Corporation and Digital Realty Company, has been awarded Frost & Sullivan’s 2024 Company of the Year award for Japan’s data center services industry.
MC Digital Realty is at the forefront of the market, delivering advanced technologies and strategic investments that provide Japanese businesses with secure, innovative, and sustainable infrastructure that enables artificial intelligence (AI) innovation.
MC Digital Realty’s state-of-the-art data centers are optimized for AI, offer the necessary flexibility and scalability for intensive model training and real-time inferencing, and provide advanced liquid cooling systems that ensure optimal performance for demanding AI tasks. Demonstrating its commitment to sustainability, MC Digital Realty leverages its relationship with Mitsubishi Corporation to prioritize energy efficiency, matching electricity usage in its colocation data halls with 100% renewable energy to minimize its carbon footprint.
Frost & Sullivan also recognized MC Digital Realty’s operational excellence. The company’s robust network of resilient data centers is strategically located in low-seismic regions and employs cutting-edge seismic isolation technology to protect its infrastructure, ensuring uninterrupted service and maximum reliability.
MC Digital Realty’s data centers also leverage the power of PlatformDIGITAL®, Digital Realty’s global data center platform. It provides customers access to a vast ecosystem of over 1,100 cloud and IT services, as well as 1,200 network services across 300+ data centers in 50+ metros worldwide.
“The company demonstrates a strong focus on the Japanese market through its continued investments. Strategic partnerships and innovations aligning with transforming customer expectations enable the service provider to achieve success in the country,” said Nishchal Khorana, Global Vice President of ICT at Frost & Sullivan.
Serene Nah, Digital Realty’s Managing Director and Head of Asia Pacific, said: “We are honored to receive the award and recognition from Frost & Sullivan, which validates MC Digital Realty’s commitment to serving partners and customers as they accelerate their AI innovation journeys in Japan. As AI continues to shape the future, Digital Realty remains committed to optimizing data center infrastructure for peak workload performance, and to meet the highest standards of innovation, while ensuring sustainability, security, and resilience.”
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