AI/ML
AI winner Nvidia faces competition with new super chip delayed
The Clear AI Winner Is: Nvidia!
Strong AI spending should help Nvidia make its own ambitious numbers when it reports earnings at the end of the month (it’s 2Q-2024 ended July 31st). Analysts are expecting nearly $25 billion in data center revenue for the July quarter—about what that business was generating annually a year ago. But the latest results won’t quell the growing concern investors have with the pace of AI spending among the world’s largest tech giants—and how it will eventually pay off.
In March, Nvidia unveiled its Blackwell chip series, succeeding its earlier flagship AI chip, the GH200 Grace Hopper Superchip, which was designed to speed generative AI applications. The NVIDIA GH200 NVL2 fully connects two GH200 Superchips with NVLink, delivering up to 288GB of high-bandwidth memory, 10 terabytes per second (TB/s) of memory bandwidth, and 1.2TB of fast memory. The GH200 NVL2 offers up to 3.5X more GPU memory capacity and 3X more bandwidth than the NVIDIA H100 Tensor Core GPU in a single server for compute- and memory-intensive workloads. The GH200 meanwhile combines an H100 chip [1.] with an Arm CPU and more memory.
Photo Credit: Nvidia
Note 1. The Nvidia H100, sits in a 10.5 inch graphics card which is then bundled together into a server rack alongside dozens of other H100 cards to create one massive data center computer.
This week, Nvidia informed Microsoft and another major cloud service provider of a delay in the production of its most advanced AI chip in the Blackwell series, the Information website said, citing a Microsoft employee and another person with knowledge of the matter.
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Nvidia Competitors Emerge – but are their chips ONLY for internal use?
In addition to AMD, Nvidia has several big tech competitors that are currently not in the merchant market semiconductor business. These include:
- Huawei has developed the Ascend series of chips to rival Nvidia’s AI chips, with the Ascend 910B chip as its main competitor to Nvidia’s A100 GPU chip. Huawei is the second largest cloud services provider in China, just behind Alibaba and ahead of Tencent.
- Microsoft has unveiled an AI chip called the Azure Maia AI Accelerator, optimized for artificial intelligence (AI) tasks and generative AI as well as the Azure Cobalt CPU, an Arm-based processor tailored to run general purpose compute workloads on the Microsoft Cloud.
- Last year, Meta announced it was developing its own AI hardware. This past April, Meta announced its next generation of custom-made processor chips designed for their AI workloads. The latest version significantly improves performance compared to the last generation and helps power their ranking and recommendation ads models on Facebook and Instagram.
- Also in April, Google revealed the details of a new version of its data center AI chips and announced an Arm-based based central processor. Google’s 10 year old Tensor Processing Units (TPUs) are one of the few viable alternatives to the advanced AI chips made by Nvidia, though developers can only access them through Google’s Cloud Platform and not buy them directly.
As demand for generative AI services continues to grow, it’s evident that GPU chips will be the next big battleground for AI supremacy.
References:
AI Frenzy Backgrounder; Review of AI Products and Services from Nvidia, Microsoft, Amazon, Google and Meta; Conclusions
https://www.nvidia.com/en-us/data-center/grace-hopper-superchip/
https://www.theverge.com/2024/2/1/24058186/ai-chips-meta-microsoft-google-nvidia/archives/2
https://news.microsoft.com/source/features/ai/in-house-chips-silicon-to-service-to-meet-ai-demand/
AI wave stimulates big tech spending and strong profits, but for how long?
Big tech companies have made it clear over the last week that they have no intention of slowing down their stunning levels of spending on artificial intelligence (AI), even though investors are getting worried that a big payoff is further down the line than most believe.
In the last quarter, Apple, Amazon, Meta, Microsoft and Google’s parent company Alphabet spent a combined $59 billion on capital expenses, 63% more than a year earlier and 161 percent more than four years ago. A large part of that was funneled into building data centers and packing them with new computer systems to build artificial intelligence. Only Apple has not dramatically increased spending, because it does not build the most advanced AI systems and is not a cloud service provider like the others.
At the beginning of this year, Meta said it would spend more than $30 billion in 2024 on new tech infrastructure. In April, he raised that to $35 billion. On Wednesday, he increased it to at least $37 billion. CEO Mark Zuckerberg said Meta would spend even more next year. He said he’d rather build too fast “rather than too late,” and allow his competitors to get a big lead in the A.I. race. Meta gives away the advanced A.I. systems it develops, but Mr. Zuckerberg still said it was worth it. “Part of what’s important about A.I. is that it can be used to improve all of our products in almost every way,” he said.
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This new wave of Generative A.I. is incredibly expensive. The systems work with vast amounts of data and require sophisticated computer chips and new data centers to develop the technology and serve it to customers. The companies are seeing some sales from their A.I. work, but it is barely moving the needle financially.
In recent months, several high-profile tech industry watchers, including Goldman Sachs’s head of equity research and a partner at the venture firm Sequoia Capital, have questioned when or if A.I. will ever produce enough benefit to bring in the sales needed to cover its staggering costs. It is not clear that AI will come close to having the same impact as the internet or mobile phones, Goldman’s Jim Covello wrote in a June report.
“What $1 trillion problem will AI solve?” he wrote. “Replacing low wage jobs with tremendously costly technology is basically the polar opposite of the prior technology transitions I’ve witnessed in my 30 years of closely following the tech industry.” “The reality right now is that while we’re investing a significant amount in the AI.space and in infrastructure, we would like to have more capacity than we already have today,” said Andy Jassy, Amazon’s chief executive. “I mean, we have a lot of demand right now.”
That means buying land, building data centers and all the computers, chips and gear that go into them. Amazon executives put a positive spin on all that spending. “We use that to drive revenue and free cash flow for the next decade and beyond,” said Brian Olsavsky, the company’s finance chief.
There are plenty of signs the boom will persist. In mid-July, Taiwan Semiconductor Manufacturing Company, which makes most of the in-demand chips designed by Nvidia (the ONLY tech company that is now making money from AI – much more below) that are used in AI systems, said those chips would be in scarce supply until the end of 2025.
Mr. Zuckerberg said AI’s potential is super exciting. “It’s why there are all the jokes about how all the tech C.E.O.s get on these earnings calls and just talk about A.I. the whole time.”
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Big tech profits and revenue continue to grow, but will massive spending produce a good ROI?
Last week’s Q2-2024 results:
- Google parent Alphabet reported $24 billion net profit on $85 billion revenue.
- Microsoft reported $22 billion net profit on $65 billion revenue.
- Meta reported $13.5 billion net profit on $39 billion revenue.
- Apple reported $21 billion net profit on $86 billion revenue.
- Amazon reported $13.5 billion net profit on $148 billion revenue.
This chart sums it all up:
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References:
https://www.nytimes.com/2024/08/02/technology/tech-companies-ai-spending.html
https://www.axios.com/2024/08/02/google-microsoft-meta-ai-earnings
https://www.nvidia.com/en-us/data-center/grace-hopper-superchip/
AI Frenzy Backgrounder; Review of AI Products and Services from Nvidia, Microsoft, Amazon, Google and Meta; Conclusions
Microsoft choses Lumen’s fiber based Private Connectivity Fabric℠ to expand Microsoft Cloud network capacity in the AI era
Lumen Technologies and Microsoft Corp. announced a new strategic partnership today. Microsoft has chosen Lumen to expand its network capacity and capability to meet the growing demand on its datacenters due to AI (i.e. huge processing required for Large Language Models, including data collection, preprocessing, training, and evaluation). Datacenters have become critical infrastructure that power the compute capabilities for the millions of people and organizations who rely on and trust the Microsoft Cloud.
Microsoft claims they are playing a leading role in ushering in the era of AI, offering tools and platforms like Azure OpenAI Service, Microsoft Copilot and others to help people be more creative, more productive and to help solve some of humanity’s biggest challenges. As Microsoft continues to evolve and scale its ecosystem, it is turning to Lumen as a strategic supplier for its network infrastructure needs and is investing with Lumen to support its next generation of applications for Microsoft platform customers worldwide.
Lumen’s Private Connectivity Fabric℠ is a custom network that includes dedicated access to existing fiber in the Lumen network, the installation of new fiber on existing and new routes, and the use of Lumen’s new digital services. This AI-ready infrastructure will strengthen the connectivity capabilities between Microsoft’s datacenters by providing the network capacity, performance, stability and speed that customers need as data demands increase.
Art by Midjourney for Fierce Network
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“AI is reshaping our daily lives and fundamentally changing how businesses operate,” said Erin Chapple, corporate vice president of Azure Core Product and Design, Microsoft. “We are focused both on the impact and opportunity for customers relative to AI today, and a generation ahead when it comes to our network infrastructure. Lumen has the network infrastructure and the digital capabilities needed to help support Azure’s mission in creating a reliable and scalable platform that supports the breadth of customer workloads—from general purpose and mission-critical, to cloud-native, high-performance computing, and AI, plus what’s on the horizon. Our work with Lumen is emblematic of our investments in our own cloud infrastructure, which delivers for today and for the long term to empower every person and every organization on the planet to achieve more.”
“We are preparing for a future where AI is the driving force of innovation and growth, and where a powerful network infrastructure is essential for companies to thrive,” said Kate Johnson, president and CEO, Lumen Technologies (a former Microsoft executive). “Microsoft has an ambitious vision for AI and this level of innovation requires a network that can make it reality. Lumen’s expansive network meets this challenge, with unique routes, unmatched coverage, and a digital platform built to give companies the flexibility, access and security they need to create an AI-enabled world.”
Lumen has launched an enterprise-wide transformation to simplify and optimize its operations. By embracing Microsoft’s cloud and AI technology, Lumen can reduce its overall technology costs, remove legacy systems and silos, improve its offerings, and create new solutions for its global customer base. Lumen will migrate and modernize its workloads to Microsoft Azure, use Microsoft Entra solutions to safeguard access and prevent identity attacks and partner with Microsoft to create and deliver new telecom industry-specific solutions. This element alone is expected to improve Lumen’s cash flow by more than $20 million over the next 12 months while also improving the company’s customer experience.
“Azure’s advanced global infrastructure helps customers and partners quickly adapt to changing economic conditions, accelerate technology innovation, and transform their business with AI,” said Chapple. “We are committed to partnering with Lumen to help deliver on their transformation goals, reimagine cloud connectivity and AI synergies, drive business growth, and help customers achieve more.”
This collaboration expands upon the longstanding relationship between Lumen Technologies and Microsoft. The companies have worked together for several years, with Lumen leveraging Copilot to automate routine tasks and reduce employee workloads and enhance Microsoft Teams.
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Lumen’s CMO Ryan Asdourian hinted the deal could be the first in a series of such partnerships, as network infrastructure becomes the next scarce resource in the era of AI. “When the world has talked about what’s needed for AI, you usually hear about power, space and cooling…[these] have been the scarce resources,” Asdourian told Fierce Telecom. Asdourian said Lumen will offer Microsoft access to a combination of new and existing routes in the U.S., and will overpull fiber where necessary. However, he declined to specify the speeds which will be made available or exactly how many of Microsoft’s data centers it will be connecting.
Microsoft will retain full control over network speeds, routes and redundancy options through Lumen’s freshly launched Private Connectivity Fabric digital interface. “That is not something traditional telecom has allowed,” Asdourian said.
Asdourian added that Lumen isn’t just looking to enable AI, but also incorporate it into its own operations. Indeed, part of its partnership deal with Microsoft involves Lumen’s adoption of Azure cloud and other Microsoft services to streamline its internal and network systems. Asdourian said AI could be used to make routing and switching on its network more intelligent and efficient.
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About Lumen Technologies:
Lumen connects the world. We are igniting business growth by connecting people, data, and applications – quickly, securely, and effortlessly. Everything we do at Lumen takes advantage of our network strength. From metro connectivity to long-haul data transport to our edge cloud, security, and managed service capabilities, we meet our customers’ needs today and as they build for tomorrow. For news and insights visit news.lumen.com, LinkedIn: /lumentechnologies, Twitter: @lumentechco, Facebook: /lumentechnologies, Instagram: @lumentechnologies and YouTube: /lumentechnologies.
About Microsoft:
Microsoft (Nasdaq “MSFT” @microsoft) creates platforms and tools powered by AI to deliver innovative solutions that meet the evolving needs of our customers. The technology company is committed to making AI available broadly and doing so responsibly, with a mission to empower every person and every organization on the planet to achieve more.
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References:
https://news.lumen.com/2024-07-24-Microsoft-and-Lumen-Technologies-partner-to-power-the-future-of-AI-and-enable-digital-transformation-to-benefit-hundreds-of-millions-of-customers
https://fierce-network.com/cloud/microsoft-taps-lumens-fiber-network-help-it-meet-ai-demand
AI Frenzy Backgrounder; Review of AI Products and Services from Nvidia, Microsoft, Amazon, Google and Meta; Conclusions
Lumen, Google and Microsoft create ExaSwitch™ – a new on-demand, optical networking ecosystem
ACSI report: AT&T, Lumen and Google Fiber top ranked in fiber network customer satisfaction
Lumen to provide mission-critical communications services to the U.S. Department of Defense
Dell’Oro: Optical Transport market to hit $17B by 2027; Lumen Technologies 400G wavelength market
SK Telecom and Singtel partner to develop next-generation telco technologies using AI
SK Telecom (South Korea) and Singtel (Singapore) have initiated a two-year project to develop advanced telecommunication networks. This collaboration aims to drive innovation, improve network performance and security, and enhance customer experiences through the use of artificial intelligence (AI), orchestration tools, and network virtualization.
The project will focus on creating innovative solutions like Edge-AI Infrastructure to enhance connectivity and provide unique AI service offerings. A white paper will describe advancements to assist other global telcos to harnessing the capabilities of 5G and preparing for 6G.
This MOU initiative is expected to not only enhance connectivity but also provide customers with unique AI service offerings and enable the operators to restore services faster, thus improving the customer experience.
Additionally, SKT and Singtel will be putting together a white paper on their advancements in areas such as virtualization, slicing and network evolution that can help other telcos globally to capitalize on the capabilities of 5G and to prepare for 6G in 2030.
SK Telecom (SKT) has signed a Memorandum of Understanding (MOU) with Singtel, Singapore’s leading telecommunications provider, to collaborate on the application of AI technology in communication networks, the development of use cases for 5G network slicing technology, and preparation for 6G technology, aimed at fostering advancements in 5G and next-generation communication technologies. Photo Courtesy of SKT
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Kang Jong-ryeol, SKT’s Head of ICT Infra(CSPO) stated, “The collaboration between SKT and Singtel marks a significant first step in shaping the future of the global telecommunications industry.” He further emphasized, “By combining the strengths of both companies, we aim to achieve efficient high-performance network construction, enhance network stability, and discover new network-based services. Additionally, we will strive to make significant advancements in next-generation communication technologies, including AI-powered wired and wireless infrastructure.”
Tay Yeow Lian, Singtel’s Managing Director, Networks, said, “As a global leader in 5G technology, we’re keen to capitalize on the myriad of capabilities this technology has to offer, especially in the areas of network slicing and with the inclusion of AI. With SKT, we’re looking to not only enhance the experience of our customers but to also drive industry innovation and help us prepare for the evolution to 6G.”
ANNEX: Singtel’s 5G advancements
· Developed Paragon, the industry’s first all-in-one aggregation and business orchestration platform, which allows enterprises to interact with and manage networks, clouds and multi-access edge computing (MEC) infrastructure and applications
· Developed Singtel CUBΣ, a Network-as-a-Service (NaaS) that makes it easier for enterprises to subscribe and manage desired services and multiple vendors as well as gain insights on network utilisation, workload performance and sustainability metrics via a single sign-on digital portal. CUBΣ leverages and integrates AI into its network management systems to deliver enhanced services such as proactive user experience monitoring, incident automation and predictive analytics to anticipate, detect and address incidents faster. This results in improved network performance, optimised resource allocation, enhanced security protocols, elevated the overall user experience, and the development of a network that learns, evolves and self-improves over time – all of which enable faster digital transformation for greater economic growth and innovation.
Major 5G developments from Singtel:
2022
· Launched first public multi-access edge compute for enterprises in Asia with Microsoft
· Launched iSHIP to provide critical satellite-enabled connectivity and digital services for the maritime industry
2023
· Singapore’s first 5G-enabled smart retail showcase
· Achieved 5G upload speed of more than 1.6Gbps in an enterprise deployment
· Completed more than 30 5G trials at Sentosa
· Successfully trialed RedCap technology for better energy savings for IoT devices
2024
· Addition of Starlink satellites for maritime connectivity
· Offered the 5G Express Pass service to concertgoers for Coldplay and Taylor Swift
· Pioneered app-based network slicing, aka User Equipment Route Selection Policy
· Singtel Paragon integrated into Telkomsel’s enterprise product portfolio
· Launch of Paragon-S to spur digital transformation for satellite operators
About SK Telecom:
SK Telecom has been leading the growth of the mobile industry since 1984. Now, it is taking customer experience to new heights by extending beyond connectivity. By placing AI at the core of its business, SK Telecom is rapidly transforming into an AI company with a strong global presence. It is focusing on driving innovations in areas of AI Infrastructure, AI Transformation (AIX) and AI Service to deliver greater value for industry, society, and life.
References:
https://www.koreaittimes.com/news/articleView.html?idxno=132974
SK Telecom, DOCOMO, NTT and Nokia develop 6G AI-native air interface
SK Telecom, Intel develop low-latency technology for 6G core network
SK Telecom and Thales Trial Post-quantum Cryptography to Enhance Users’ Protection on 5G SA Network
Vodafone: GenAI overhyped, will spend $151M to enhance its chatbot with AI
GenAI is probably the most “overhyped” technology for many years in the telecom industry, said Vodafone Group’s chief technology officer (CTO) Scott Petty at a press briefing this week. “Hopefully, we are reaching the peak of those inflated expectations, because we are about to drop into a trough of disillusionment,” he said.
“This industry is moving too quickly,” Petty explained. “The evolution of particularly GPUs and the infrastructure means that by the time you’d actually bought them and got them installed you’d be N minus one or N minus two in terms of the technology, and you’d be spending a lot of effort and resource just trying to run the infrastructure and the LLMs that sit around that.”
Partnerships with hyper-scalers remain Vodafone’s preference, he said. Earlier this year, Vodafone and Microsoft signed a 10-year strategic agreement to use Microsoft GenAI in Vodafone’s network.
Vodafone is planning to invest some €140 million ($151 million) in artificial intelligence (AI) systems this year to improve the handling of customer inquiries, the company said on July 4th. Vodafone said it is investing in advanced AI from Microsoft and OpenAI to improve its chatbot, dubbed TOBi, so that it can respond faster and resolve customer issues more effectively.
The chatbot was introduced into Vodafone’s customer service five years ago and is equipped with the real voice of a Vodafone employee.
The new system, which is called SuperTOBi in many countries, has already been introduced in Italy and Portugal and will be rolled out in Germany and Turkey later this month with other markets to follow later in the year, Vodafone said in a press release.
According to the company, SuperTOBi “can understand and respond faster to complex customer enquiries better than traditional chatbots.” The new bot will assist customers with various tasks, such as troubleshooting hardware issues and setting up fixed-line routers, the company said.
Vodafone is not about to expose Vodafone’s data to publicly available models like ChatGPT. Nor will the UK based telco create large language models (LLMs) on its own. Instead, a team of 50 data scientists are working on fine-tuning LLMs like Anthropic and Vertex. Vodafone can expose information to those LLMs by dipping into its 24-petabyte data “ocean,” created with Google. Secure containers within public clouds ensure private information is securely cordoned off and unavailable to others.
According to Petty’s estimates, the performance speed of LLMs has improved by a factor of 12 in the last nine months alone, while operational costs have decreased by a factor of six. A telco that invested nine months ago would already have outdated and expensive technology. Petty, moreover, is not the only telco CTO wary of plunging into Nvidia’s GPU chips.
“This is a very weird moment in time where power is very expensive, natural resources are scarce and GPUs are extremely expensive,” said Bruno Zerbib, the CTO of France’s Orange, at the 2024 Mobile World Congress in Barcelona, Spain. “You have to be very careful with your investment because you might buy a GPU product from a famous company right now that has a monopolistic position.”
Petty thinks LLM processing may eventually need to be processed outside hyper-scalers’ facilities. “To really create the performance that we want, we are going to need to push those capabilities further toward the edge of the network,” he said. “It is not going to be the hype cycle of the back end of 2024. But in 2025 and 2026, you’ll start to see those applications and capabilities being deployed at speed.”
“The time it takes for that data to get up and back will dictate whether you’re happy as a consumer to use that interface as your primary interface, and the investment in latency is going to be critically important,” said Petty. “We’re fortunate that 5G standalone drives low latency capability, but it’s not deployed at scale. We don’t have ubiquitous coverage. We need to make sure that those things are available to enable those applications.”
Data from Ericsson supports that view, showing that 5G population coverage is just 70% across Europe, compared with 90% in North America and 95% in China. The figure for midband spectrum – considered a 5G sweet spot that combines decent coverage with high-speed service – is as low as 30% in Europe, against 85% in North America and 95% in China.
Non-standalone (NSA) 5G, which connects a 5G radio access network (RAN) to a 4G core (EPC), is “dominating the market,” said Ericsson.
Vodafone has pledged to spend £11 billion (US$14 billion) on the rollout of a nationwide standalone 5G network in the UK if authorities bless its proposed merger with Three. With more customers, additional spectrum and a bigger footprint, the combined company would be able to generate healthier returns and invest in network improvements, the company said. But a UK merger would not aid the operator in Europe’s four-player markets.
Petty believes a “pay for search” economic model may emerge using GenAI virtual assistants. “This will see an evolution of a two-sided economic model that probably didn’t get in the growth of the Internet in the last 20 years,” but it would not be unlike today’s market for content delivery networks (CDNs).
“Most CDNs are actually paid for by the content distribution companies – the Netflixes, the TV sports – because they want a great experience for their users for the paid content they’ve bought. When it’s free content, maybe the owner of that content is less willing to invest to build out the capabilities in the network.”
Like other industry executives, Petty must hope the debates about net neutrality and fair contribution do not plunge telcos into a long disillusionment trough.
References:
Vodafone CTO: AI will overhaul 5G networks and Internet economics (lightreading.com)
Vodafone UK report touts benefits of 5G SA for Small Biz; cover for proposed merger with Three UK?
Data infrastructure software: picks and shovels for AI; Hyperscaler CAPEX
For many years, data volumes have been accelerating. By 2025, global data volumes are expected to reach 180 zettabytes (1 zettabyte=1 sextillion bytes), up from 120 zettabytes in 2023.
In the age of AI, data is viewed as the currency for large language models (LLMs) and AI–enabled offerings. Therefore, demand for tools to integrate, store and process data is a growing priority amongst enterprises.
The median size of datasets required to train AI models increased from 5.9 million data points in 2010 to 750 billion in 2023, according to BofA Global Research. As demand rises for AI-enabled offerings, companies are prioritizing tools to integrate, store, and process data.
In BofA’s survey, data streaming/stream processing and data science/ML were selected as key use cases in regard to AI, with 44% and 37% of respondents citing usage, respectively. Further, AI enablement is accelerating data to the cloud. Gartner estimates that 74% of the data management market will be deployed in the cloud by 2027, up from 60% in 2023.
Data infrastructure software [1.] represents a top spending priority for the IT department. Survey respondents cite that data infrastructure represents 35% of total IT spending, with budgets expected to grow 9% for the next 12 months. No surprise that the public cloud hyper-scaler platforms were cited as top three vendors. Amazon AWS data warehouse/data lake offerings, Microsoft Azure database offerings, and Google BigQuery are chosen by 45%, 39% and 35% of respondents, respectively.
Note 1. Data infrastructure software refers to databases, data warehouses/lakes, data pipelines, data analytics and other software that facilitate data management, processing and analysis.
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The top three factors for evaluating data infrastructure software vendors are security, enterprise capabilities (e.g., architecture scalability and reliability) and depth of technology.
BofA’s Software team estimates that the data infrastructure industry (e.g., data warehouses, data lakes, unstructured databases, etc.) is currently a $96bn market that could reach $153bn in 2028. The team’s proprietary survey revealed that data infrastructure is 35% of total IT spending with budgets expected to grow 9% over the next 12 months. Hyperscalers including Amazon and Google are among the top recipients of dollars and in-turn, those companies spend big on hardware.
Key takeaways:
- Data infrastructure is the largest and fastest growing segment of software ($96bn per our bottom-up analysis, 17% CAGR).
- AI/cloud represent enduring growth drivers. Data is the currency for LLMs, positioning data vendors well in this new cycle
- BofA survey (150 IT professionals) suggests best of breeds (MDB, SNOW and Databricks) seeing highest expected growth in spend
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BofA analyst Justin Post expects server and equipment capex for mega-cap internet companies (Amazon, Alphabet/Google, Meta/Facebook) to rise 43% y/y in 2024 to $145bn, which represents $27bn of the $37bn y/y total capex growth. Despite the spending surge, Mr. Post thinks these companies will keep free cash flow margins stable at 22% y/y before increasing in 2025. The technical infrastructure related capex spend at these three companies is expected to see steep rise in 2024, with the majority of the increase for servers and equipment.
Notes:
- Alphabet categorizes its technical infrastructure assets under the line item ‘Information Technology Assets‘
- Amazon take a much a broader categorization and includes Servers, networking equipment, retail related heavy equipment & fulfillment equipment under ‘Equipment‘.
- Meta gives more details and separately reports Server & Networking, and Equipment assets.
In 2024, BofA estimates CAPEX for the three hyperscalers as follows:
- Alphabet‘s capex for IT assets will increase by $12bn y/y to $28bn.
- Meta, following a big ramp in 2023, server, network and equipment asset spend is expected to increase $7bn y/y to $22bn.
- Amazon, equipment spend is expected to increase $8bn y/y to $41bn (driven by AWS, retail flattish). Amazon will see less relative growth due to retail equipment capex leverage in this line.
On a relative scale, Meta capex spend (% of revenue) remains highest in the group and the company has materially stepped up its AI related capex investments since 2022 (in–house supercomputer, LLM, leading computing power, etc.). We think it‘s interesting that Meta is spending almost as much as the hyperscalers on capex, which should likely lead to some interesting internal AI capabilities, and potential to build a “marketing cloud“ for its advertisers.
From 2016-22, the sector headcount grew 26% on average. In 2023, headcount decreased by 9%. BofA expects just 3% average. annual job growth from 2022-2026. Moreover, AI tools will likely drive higher employee efficiency, helping offset higher depreciation.
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Source for all of the above information: BofA Global Research
Big Tech post strong earnings and revenue growth, but cuts jobs along with Telecom Vendors
Tech companies have been consistently laying off employees since late 2022. As of April 25th, some 266 tech companies have laid off nearly 75,000 workers in 2024, according to the independent layoff-tracking site layoffs.fyi. A total of 262,682 workers in tech lost their jobs in 2023 compared with 164,969 in 2022. The volume of layoffs in 2023 — a total of 1,186 companies — also surpassed 2022, when 1,061 companies in tech laid off workers — and that total was more than in 2020 and 2021 combined.
Big Tech companies Alphabet (Google’s parent), Amazon, Apple, Meta, Microsoft and Netflix, collectively cut nearly 45,500 jobs in their most recent full fiscal year. Since 2020, however, they have added more than 358,500, bringing total headcount to nearly 2,170,000. Excluding Amazon, which accounts for 70% of that figure, job numbers fell by around 29,700 last year but have grown by 131,500 since 2020 (data from earnings reports and SEC filings – see chart below).
- Today, Amazon reported better-than-expected earnings and revenue for the first quarter, driven by growth in advertising and cloud computing. Operating income soared more than 200% in the period to $15.3 billion, far outpacing revenue growth, the latest sign that the company’s cost-cutting measures and focus on efficiency is bolstering its bottom line. AWS accounted for 62% of total operating profit. Net income also more than tripled to $10.4 billion, or 98 cents a share, from $3.17 billion, or 31 cents a share, a year ago. Sales increased 13% from $127.4 billion a year earlier.
- Google parent Alphabet also posted robust profits, with net income in the latest quarter soaring 57% to $23.7 billion while revenue grew 15% in the quarter. That’s despite job cuts of 12,115 and net headcount reduction of ~8,000 in 2023.
- Microsoft last week managed 20% year-over-year growth in third-quarter net income, to around $21.9 billion, on 17% growth in sales, to $61.9 billion. The number of Microsoft employees was unchanged in 2023 from the previous year, despite the company laying off 11,158 employees. Future headcount reductions may be necessary to help pay for Microsoft’s multi-billion-dollar splurge on AI and the data centers needed to train the Large Language Models and associated generative AI technology. But few expect job cuts to slow Microsoft down.
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As expected, telecom vendors, which have many fewer employees, than Big Tech had a higher percentage of job reductions. CommScope, Corning, Dell, Ericsson, and Nokia, suppliers to some of the world’s biggest telcos, shed nearly 36,500 jobs last year as large IT customers spent less on new equipment.
The following table shows the total number of jobs per year for many vendors/cloud service providers.
Source: Light Reading & company reports/SEC filings
Huawei was the exception to the telecom vendor layoff craze (even ZTE reduced its workforce in 2023). Despite U.S. sanctions and a European backlash against the company, Huawei gained 12,000 employees in 2022, giving it a workforce of 207,000 that year. The number was unchanged in 2023, according to its recently published annual report. Restrictions have not been as effective at hindering Huawei’s progress as the U.S. had hoped.
On the semiconductor side, Intel experienced a net workforce reduction of 7,100 jobs. Profits have tanked because of market share losses, a downturn in customer spending on equipment (explained partly by the earlier build-up of inventory that happened after the pandemic) and investments in new foundries designed to challenge the Asian giants of TSMC and Samsung. Big Tech moves to build in-house AI augmented processor chips that can substitute for Intel’s microprocessors are among the problems the company faces. Intel’s profits have collapsed, just as they have at the mobile networks business group of silicon customer Nokia, and it is at risk of displacement by chip rivals in important markets.
These big tech layoffs are a peculiar outlier in an otherwise strong employment environment: The unemployment rate has hovered between 3.4% and 3.8% since Feb. 2022, bureau data shows. And quit rates, which reflect a lack of worker confidence, this year are consistently at some of the highest levels in more than 20 years, according to the Federal Reserve Bank of St. Louis.
In summary, Big Tech companies continue to thrive financially, but they are also making strategic adjustments, including job cuts, as they navigate the evolving landscape of technology and generative AI. The emphasis on AI development, large language models, and cloud services remains a key driver for their growth and profitability. Telecom vendors are facing tremendous pain due to continued reduction in telco CAPEX which may persists for many years.
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References:
https://www.nerdwallet.com/article/finance/tech-layoffs
US cable and telecom network operators feel the pain
Bloomberg: Higher borrowing costs hurting indebted wireless companies; industry is 2nd largest source of distressed debt
Telecom layoffs continue unabated as AT&T leads the pack – a growth engine with only 1% YoY growth?
High Tech Layoffs Explained: The End of the Free Money Party
Quintessent: Supporting “newer AI workloads” with lasers and DWDM
Integrated-photonics companies have increasingly seized on the opportunities in advanced AI. Many are building high-speed optical interconnects for data centers, with the electrical–optical conversion as close as possible to the number-crunching GPU or application-specific integrated circuit (ASIC).
However, Goleta, CA based startup Quintessent, is focusing on solving what it says is a major bottleneck hindering commercial deployment of such high-speed optical interconnects for AI – the light source or laser, which is currently the “weakest link” in system reliability and scalability, according to co-founder and CEO, Alan Liu.
Quintessent’s answer lies in part in its laser technology, incorporating quantum dots (QDs)—the semiconductor nanocrystals celebrated in the 2023 Nobel Prize in Chemistry—and multiwavelength comb lasers. The firm believes that combination can boost bandwidth, improve efficiency and cut latency by enabling highly parallel dense wavelength-division multiplexed (DWDM) optical links for computing clusters and data centers. And in late March, the company announced that it had secured US$11.5 million in new seed funding to push its vision closer to commercialization.
Quintessent was co-founded in 2019 by Optica Fellow John Bowers of the University of California, Santa Barbara (UCSB), USA, who serves as the company’s board chairman, and Liu, formerly a student in Bowers’ lab. In a conversation with OPN in November 2023, Liu noted that his Ph.D. work in the lab, which spanned the years from 2011 to 2017, focused on what he called “one of the glaring holes in silicon photonics”: how to integrate the light source. His work specifically involved integration of QD lasers with silicon photonics, which subsequently became “one of the core technologies for Quintessent.”
Quintessent co-founders Alan Liu (left) and John Bowers. Image: Courtesy of A. Liu.
Even at that time, Liu had some stirrings in the direction of commercializing the technology. Ultimately, though, after earning his Ph.D. in 2017, he left Santa Barbara for a two-year stint at a consulting firm in the Washington, DC, area. There, he worked as a subject-matter expert in photonics on projects for the US Department of Defense’s advanced-research arm, DARPA, and the US Department of Energy’s counterpart, ARPA-E.
Still, the entrepreneurial itch never quite left Liu. Nor did his fascination with the promise of QD laser technology, as he saw subsequent work done in Bowers’ lab to further advance the performance of those lasers and demonstrate new functions with them, including multiwavelength comb sources.
In 2019, Liu says, he got a call from Bowers, who noted that he was seeing “a lot of interest” from industry in the technology the lab was developing, but that there was “no company to sell it.” When Bowers asked if he wanted to help start one up, Liu recalls, “it didn’t take me long to sign on and say yes.” In the course of the next few years, they built Quintessent’s core team, drawing on numerous other contacts both within and outside of Bowers’ UCSB lab, and pulled in a mix of government R&D and venture funding, including the $11.5 million seed round announced in March 2024. The business case for Quintessent, Liu says, rests largely on “some of the newer AI workloads that were coming into the fray” beginning in the late 2010s, and their immense appetite for computing resources and power.
“If you’re going to be optimizing for power efficiency and bandwidth and latency, the required architecture is one that’s wide and parallel,” he explains. And for optics, at some point, trying to achieve that level of parallelism by adding more and more spatial or fiber channels becomes unwieldy.
The alternative solution, Liu says, is a highly parallel DWDM architecture—using not lots of fibers but “lots of lambdas.” For the crushing workloads of advanced AI, DWDM is optimal, as it “allows you to both simultaneously optimize bandwidth and minimize power and latency,” without relying on digital signal processing or a potential rat’s nest of individual fiber interconnects to boost overall bandwidth.
One key for achieving that vision was “enabling a new kind of laser, and using that laser to enable new communication and transceiver architectures,” according to Liu. “That was a common gap I saw across the industry.” Particularly in the context of AI, Liu observes, a big argument for better lasers has to do with reliability.
Particularly in the context of AI, Liu observes, a big argument for better lasers—and especially for Quintessent’s concept of simplifying wavelength scaling using multiwavelength comb sources fabricated from InAs/GaAs QD material—has to do with reliability. “Optical solutions for AI are going to have to be at least an order of magnitude more reliable than what we see today in existing transceivers,” he maintains. “If you imagine a scenario where there’s 10 times more optics deployed, and your failure rates stay the same, then you’ve got 10 times more failures you’re asking the customer to deal with. That gets a little dicey.”
An atomic force microscopy (AFM) image of InAs/GaAs quantum dots. Image: Courtesy of A. Liu
Getting to better overall reliability will require much more reliable lasers, Liu believes, as lasers are “kind of the weakest link at the moment.” And he and the Quintessent team think that QD lasers offer a way forward, as they are “intrinsically more reliable than quantum well materials today.”
Tobias Egle, a materials scientist who works with M Ventures, one of the partners in the most recent Quintessent funding round, explained the difference further in a separate call with OPN. “These QD lasers are not as affected by material defects, dislocations and so on,” Egle says. “Simply put, a single dislocation through the facet or active region of a traditional laser can lead to complete failure. In contrast, when you have billions of QDs which are independent of one another, the presence of a single dislocation has a negligible impact on your overall performance.”
Quintessent experienced a milestone a year ago, when the company and Tower Semiconductor—the Israel-based global foundry firm with which Quintessent had partnered since 2021—announced that they had achieved what they called the world’s first heterogenous integration of GaAs quantum dot lasers in a commercial foundry silicon photonics process. The pair also unveiled a foundry silicon platform, PH18DB, targeted for the telecom and datacom optical transceiver market, and an accompanying process development kit (PDK).
Meanwhile, on the funding side, Quintessent announced an oversubscribed US$11.5 million seed round in March 2024, with an investment group led by Osage University Partners (OUP) and including, in addition to M Ventures, participation by previous Quintessent funders Sierra Ventures, Foothill Ventures and Entrada Ventures. In a press release accompanying the recent funding announcement, Liu said the new money would let the company “grow our team and accelerate the development of highly scalable and highly reliable optical interconnects that transcend the scaling limitations of incumbent solutions,” based on the firm’s core technology of QD-enabled multiwavelength comb lasers.
Operationally, Liu told OPN that—having “checked off all of the fundamental technology questions” regarding the laser technology’s feasibility—Quintessent is now focused on optimizing the laser design, which he calls “a key Lego block,” and of other pieces of the overall architecture to validate system-level functionality. Then, an important next step will be getting chips into customers’ hands for ground-truthing and feedback, and using that feedback to “drive forward the commercialization roadmap.”
“So samples, then low-volume pilots, then high-volume manufacturing—simple, right?” he laughs. Liu seems exhilarated by the challenge. “I’m one of those people that liked to play video games in the hard, hard mode,” he says. “If it’s too easy, you don’t get much enjoyment out of it.”
References:
https://www.optica-opn.org/Home/Industry/2024/April/Quintessent_Targets_Lasers_for_AI
Co-Packaged Optics to play an important role in data center switches
Ranovus Monolithic 100G Optical I/O Cores for Next-Generation Data Centers
Dell’Oro: DWDM equipment market to exceed $17 billion by 2026
NTT & Yomiuri: ‘Social Order Could Collapse’ in AI Era
From the Wall Street Journal:
Japan’s largest telecommunications company and the country’s biggest newspaper called for speedy legislation to restrain generative artificial intelligence, saying democracy and social order could collapse if AI is left unchecked.
Nippon Telegraph and Telephone, or NTT, and Yomiuri Shimbun Group Holdings made the proposal in an AI manifesto to be released Monday. Combined with a law passed in March by the European Parliament restricting some uses of AI, the manifesto points to rising concern among American allies about the AI programs U.S.-based companies have been at the forefront of developing.
The Japanese companies’ manifesto, while pointing to the potential benefits of generative AI in improving productivity, took a generally skeptical view of the technology. Without giving specifics, it said AI tools have already begun to damage human dignity because the tools are sometimes designed to seize users’ attention without regard to morals or accuracy.
Unless AI is restrained, “in the worst-case scenario, democracy and social order could collapse, resulting in wars,” the manifesto said.
It said Japan should take measures immediately in response, including laws to protect elections and national security from abuse of generative AI.
A global push is under way to regulate AI, with the European Union at the forefront. The EU’s new law calls on makers of the most powerful AI models to put them through safety evaluations and notify regulators of serious incidents. It also is set to ban the use of emotion-recognition AI in schools and workplaces.
The Biden administration is also stepping up oversight, invoking emergency federal powers last October to compel major AI companies to notify the government when developing systems that pose a serious risk to national security. The U.S., U.K. and Japan have each set up government-led AI safety institutes to help develop AI guidelines.
Still, governments of democratic nations are struggling to figure out how to regulate AI-powered speech, such as social-media activity, given constitutional and other protections for free speech.
NTT and Yomiuri said their manifesto was motivated by concern over public discourse. The two companies are among Japan’s most influential in policy. The government still owns about one-third of NTT, formerly the state-controlled phone monopoly.
Yomiuri Shimbun, which has a morning circulation of about six million copies according to industry figures, is Japan’s most widely-read newspaper. Under the late Prime Minister Shinzo Abe and his successors, the newspaper’s conservative editorial line has been influential in pushing the ruling Liberal Democratic Party to expand military spending and deepen the nation’s alliance with the U.S.
The two companies said their executives have been examining the impact of generative AI since last year in a study group guided by Keio University researchers.
The Yomiuri’s news pages and editorials frequently highlight concerns about artificial intelligence. An editorial in December, noting the rush of new AI products coming from U.S. tech companies, said “AI models could teach people how to make weapons or spread discriminatory ideas.” It cited risks from sophisticated fake videos purporting to show politicians speaking.
NTT is active in AI research, and its units offer generative AI products to business customers. In March, it started offering these customers a large-language model it calls “tsuzumi” which is akin to OpenAI’s ChatGPT but is designed to use less computing power and work better in Japanese-language contexts.
An NTT spokesman said the company works with U.S. tech giants and believes generative AI has valuable uses, but he said the company believes the technology has particular risks if it is used maliciously to manipulate public opinion.
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From the Japan News (Yomiuri Shimbun):
Challenges: Humans cannot fully control Generative AI technology
･ While the accuracy of results cannot be fully guaranteed, it is easy for people to use the technology and understand its output. This often leads to situations in which generative AI “lies with confidence” and people are “easily fooled.”
･ Challenges include hallucinations, bias and toxicity, retraining through input data, infringement of rights through data scraping and the difficulty of judging created products.
･ Journalism, research in academia and other sources have provided accurate and valuable information by thoroughly examining what information is correct, allowing them to receive some form of compensation or reward. Such incentives for providing and distributing information have ensured authenticity and trustworthiness may collapse.
A need to respond: Generative AI must be controlled both technologically and legally
･ If generative AI is allowed to go unchecked, trust in society as a whole may be damaged as people grow distrustful of one another and incentives are lost for guaranteeing authenticity and trustworthiness. There is a concern that, in the worst-case scenario, democracy and social order could collapse, resulting in wars.
･ Meanwhile, AI technology itself is already indispensable to society. If AI technology is dismissed as a whole as untrustworthy due to out-of-control generative AI, humanity’s productivity may decline.
･ Based on the points laid out in the following sections, measures must be realized to balance the control and use of generative AI from both technological and institutional perspectives, and to make the technology a suitable tool for society.
Point 1: Confronting the out-of-control relationship between AI and the attention economy
･ Any computer’s basic structure, or architecture, including that of generative AI, positions the individual as the basic unit of user. However, due to computers’ tendency to be overly conscious of individuals, there are such problems as unsound information spaces and damage to individual dignity due to the rise of the attention economy.
･ There are concerns that the unstable nature of generative AI is likely to amplify the above-mentioned problems further. In other words, it cannot be denied that there is a risk of worsening social unrest due to a combination of AI and the attention economy, with the attention economy accelerated by generative AI. To understand such issues properly, it is important to review our views on humanity and society and critically consider what form desirable technology should take.
･ Meanwhile, the out-of-control relationship between AI and the attention economy has already damaged autonomy and dignity, which are essential values that allow individuals in our society to be free. These values must be restored quickly. In doing so, autonomous liberty should not be abandoned, but rather an optimal solution should be sought based on human liberty and dignity, verifying their rationality. In the process, concepts such as information health are expected to be established.
Point 2: Legal restraints to ensure discussion spaces to protect liberty and dignity, the introduction of technology to cope with related issues
･ Ensuring spaces for discussion in which human liberty and dignity are maintained has not only superficial economic value, but also a special value in terms of supporting social stability. The out-of-control relationship between AI and the attention economy is a threat to these values. If generative AI develops further and is left unchecked like it is currently, there is no denying that the distribution of malicious information could drive out good things and cause social unrest.
･ If we continue to be unable to sufficiently regulate generative AI — or if we at least allow the unconditional application of such technology to elections and security — it could cause enormous and irreversible damage as the effects of the technology will not be controllable in society. This implies a need for rigid restrictions by law (hard laws that are enforceable) on the usage of generative AI in these areas.
･ In the area of education, especially compulsory education for those age groups in which students’ ability to make appropriate decisions has not fully matured, careful measures should be taken after considering both the advantages and disadvantages of AI usage.
･ The protection of intellectual property rights — especially copyrights — should be adapted to the times in both institutional and technological aspects to maintain incentives for providing and distributing sound information. In doing so, the protections should be made enforceable in practice, without excessive restrictions to developing and using generative AI.
･ These solutions cannot be maintained by laws alone, but rather, they also require measures such as Originator Profile (OP), which is secured by technology.
Point 2: Legal restraints to ensure discussion spaces to protect liberty and dignity, and the introduction of technology to cope with related issues
･ Ensuring spaces for discussion in which human liberty and dignity are maintained has not only superficial economic value, but also a special value in terms of supporting social stability. The out-of-control relationship between AI and the attention economy is a threat to these values. If generative AI develops further and is left unchecked like it is currently, there is no denying that the distribution of malicious information could drive out good things and cause social unrest.
･ If we continue to be unable to sufficiently regulate generative AI — or if we at least allow the unconditional application of such technology to elections and security — it could cause enormous and irreversible damage as the effects of the technology will not be controllable in society. This implies a need for rigid restrictions by law (hard laws that are enforceable) on the usage of generative AI in these areas.
･ In the area of education, especially compulsory education for those age groups in which students’ ability to make appropriate decisions has not fully matured, careful measures should be taken after considering both the advantages and disadvantages of AI usage.
･ The protection of intellectual property rights — especially copyrights — should be adapted to the times in both institutional and technological aspects to maintain incentives for providing and distributing sound information. In doing so, the protections should be made enforceable in practice, without excessive restrictions to developing and using generative AI.
･ These solutions cannot be maintained by laws alone, but rather, they also require measures such as Originator Profile (OP), which is secured by technology.
Point 3: Establishment of effective governance, including legislation
･ The European Union has been developing data-related laws such as the General Data Protection Regulation, the Digital Services Act and the Digital Markets Act. It has been developing regulations through strategic laws with awareness of the need to both control and promote AI, positioning the Artificial Intelligence Act as part of such efforts.
･ Japan does not have such a strategic and systematic data policy. It is expected to require a long time and involve many obstacles to develop such a policy. Therefore, in the long term, it is necessary to develop a robust, strategic and systematic data policy and, in the short term, individual regulations and effective measures aimed at dealing with AI and attention economy-related problems in the era of generative AI.
･However, it would be difficult to immediately introduce legislation, including individual regulations, for such issues. Without excluding consideration of future legislation, the handling of AI must be strengthened by soft laws — both for data (basic) and generative AI (applied) — that offer a co-regulatory approach that identifies stakeholders. Given the speed of technological innovation and the complexity of value chains, it is expected that an agile framework such as agile governance, rather than governance based on static structures, will be introduced.
･ In risk areas that require special caution (see Point 2), hard laws should be introduced without hesitation.
･ In designing a system, attention should be paid to how effectively it protects the people’s liberty and dignity, as well as to national interests such as industry, based on the impact on Japan of extraterritorial enforcement to the required extent and other countries’ systems.
･ As a possible measure to balance AI use and regulation, a framework should be considered in which the businesses that interact directly with users in the value chain, the middle B in “B2B2X,” where X is the user, reduce and absorb risks when generative AI is used.
･ To create an environment that ensures discussion spaces in which human liberty and dignity are maintained, it is necessary to ensure that there are multiple AIs of various kinds and of equal rank, that they keep each other in check, and that users can refer to them autonomously, so that users do not have to depend on a specific AI. Such moves should be promoted from both institutional and technological perspectives.
Outlook for the Future:
･ Generative AI is a technology that cannot be fully controlled by humanity. However, it is set to enter an innovation phase (changes accompanying social diffusion).
･ In particular, measures to ensure a healthy space for discussion, which constitutes the basis of human and social security (democratic order), must be taken immediately. Legislation (hard laws) are needed, mainly for creating zones of generative AI use (strong restrictions for elections and security).
･ In addition, from the viewpoint of ecosystem maintenance (including the dissemination of personal information), it is necessary to consider optimizing copyright law in line with the times, in a manner compatible with using generative AI itself, from both institutional and technological perspectives.
･ However, as it takes time to revise the law, the following steps must be taken: the introduction of rules and joint regulations mainly by the media and various industries, the establishment and dissemination of effective technologies, and making efforts to revise the law.
･ In this process, the most important thing is to protect the dignity and liberty of individuals in order to achieve individual autonomy. Those involved will study the situation, taking into account critical assessments based on the value of community.
References:
‘Joint Proposal on Shaping Generative AI’ by The Yomiuri Shimbun Holdings and NTT Corp.
Major technology companies form AI-Enabled Information and Communication Technology (ICT) Workforce Consortium
MTN Consulting: Generative AI hype grips telecom industry; telco CAPEX decreases while vendor revenue plummets
Cloud Service Providers struggle with Generative AI; Users face vendor lock-in; “The hype is here, the revenue is not”
Amdocs and NVIDIA to Accelerate Adoption of Generative AI for $1.7 Trillion Telecom Industry
Major technology companies form AI-Enabled Information and Communication Technology (ICT) Workforce Consortium
A consortium of major tech companies, including Cisco, Accenture, Eightfold, Google, IBM, Indeed, Intel, Microsoft and SAP have formed the AI-Enabled Information and Communication Technology (ICT) Workforce Consortium with the aim of assessing “AI’s impact on technology jobs” and identifying “skills development pathways for the roles most likely to be affected by artificial intelligence.”
Francine Katsoudas, executive VP and chief people, policy and purpose officer at Cisco, stated:
“AI is accelerating the pace of change for the global workforce, presenting a powerful opportunity for the private sector to help upskill and re-skill workers for the future. The mission of our newly unveiled AI-Enabled Workforce Consortium is to provide organisations with knowledge about the impact of AI on the workforce and equip workers with relevant skills. We look forward to engaging other stakeholders – including governments, NGOs, and the academic community – as we take this important first step toward ensuring that the AI revolution leaves no one behind.”
The formation of the Consortium is catalyzed by the work of the U.S.-EU Trade and Technology Council Talent for Growth Task Force, Cisco Chair and CEO Chuck Robbins’ participation in the Task Force, and input from the U.S. Department of Commerce.
Advisors include the American Federation of Labor and Congress of Industrial Organizations, CHAIN5, Communications Workers of America, DIGITALEUROPE, the European Vocational Training Association, Khan Academy, and SMEUnited.
Working as a private sector collaborative, the Consortium is evaluating how AI is changing the jobs and skills workers need to be successful. The first phase of work will culminate in a report with actionable insights for business leaders and workers. Further details will be shared in the coming months. Findings will be intended to offer practical insights and recommendations to employers that seek ways to reskill and upskill their workers in preparation for AI-enabled environments.
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Author’s Note: The consortium was likely formed to retrain workers to use AI technology, else they would be laid off or fired. In a recent survey from McKinsey, 25% of business professionals said that they expect their employer to lay off staff as a result of AI adoption. Their pessimism isn’t misplaced. According to one estimate, around 4,000 workers have lost their jobs to AI since May. And in a poll from Beautiful.ai, which makes AI-powered presentation software, nearly half of managers said that they’re hoping to replace workers with AI.
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Consortium members represent a cross section of companies innovating on the cutting edge of AI that also understand the current and impending impact of AI on the workforce. Individually, Consortium members have documented opportunities and challenges presented by AI. The collaborative effort enables their organizations to coalesce insights, recommend action plans, and activate findings within their respective broad spheres of influence.
The Consortium’s work is inspired by the TTC’s Talent for Growth Task Force and Cisco Chair and CEO Chuck Robbins’ leadership of its skills training workstream, and input from the U.S. Department of Commerce. The TTC was established in June 2021 by U.S. President Biden, European Commission President von der Leyen, and European Council President Michel to promote U.S. and EU competitiveness and prosperity through cooperation and democratic approaches to trade, technology, and security.
“At the U.S. Department of Commerce, we’re focused on fueling advanced technology and deepening trade and investment relationships with partners and allies around the world. This work is helping us build a strong and competitive economy, propelled by a talented workforce that’s enabling workers to get into the good quality, high-paying, family-sustaining jobs of the future. We recognize that economic security and national security are inextricably linked. That’s why I’m proud to see the efforts of the Talent for Growth Task Force continue with the creation of the AI-Enabled ICT Workforce Consortium,” said U.S. Secretary of Commerce Gina Raimondo.
“I am grateful to the consortium members for joining in this effort to confront the new workforce needs that are arising in the wake of AI’s rapid development. This work will help provide unprecedented insight on the specific skill needs for these jobs. I hope that this Consortium is just the beginning, and that the private sector sees this as a call to action to ensure our workforces can reap the benefits of AI.”
The AI-Enabled ICT Workforce Consortium’s efforts address a business critical and growing need for a proficient workforce that is trained in various aspects of AI, including the skills to implement AI applications across business processes. The Consortium will leverage its members and advisors to recommend and amplify reskilling and upskilling training programs that are inclusive and can benefit multiple stakeholders – students, career changers, current IT workers, employers, and educators – in order to skill workers at scale to engage in the AI era.
In its first phase of work, the Consortium will evaluate the impact of AI on 56 ICT job roles and provide training recommendations for impacted jobs. These job roles include 80% of the top 45 ICT job titles garnering the highest volume of job postings for the period February 2023-2024 in the United States and five of the largest European countries by ICT workforce numbers (France, Germany, Italy, Spain, and the Netherlands) according to Indeed Hiring Lab. Collectively, these countries account for a significant segment of the ICT sector, with a combined total of 10 million ICT workers.
Consortium members universally recognize the urgency and importance of their combined efforts with the acceleration of AI in all facets of business and the need to build an inclusive workforce with family-sustaining opportunities. Consortium members commit to developing worker pathways particularly in job sectors that will increasingly integrate artificial intelligence technology. To that end, Consortium members have established forward thinking goals with skills development and training programs to positively impact over 95 million individuals around the world over the next 10 years.
Consortium member goals include:
- Cisco to train 25 million people with cybersecurity and digital skills by 2032.
- IBM to skill 30 million individuals by 2030 in digital skills, including 2 million in AI.
- Intel to empower more than 30 million people with AI skills for current and future jobs by 2030.
- Microsoft to train and certify 10 million people from underserved communities with in-demand digital skills for jobs and livelihood opportunities in the digital economy by 2025.
- SAP to upskill two million people worldwide by 2025.
- Google has recently announced EUR 25 million in funding to support AI training and skills for people across Europe.
Accenture
“Helping organizations identify skills gaps and train people at speed and scale is a major priority for Accenture, and this consortium brings together an impressive ecosystem of industry partners committed to growing leading-edge technology, data and AI skills within our communities. Reskilling people to work with AI is paramount in every industry. Organizations that invest as much in learning as they do in the technology not only create career pathways, they are well positioned to lead in the market.” – Ellyn Shook, Chief Leadership & Human Resources Officer, Accenture
Eightfold
“The dynamics of work and the very essence of work are evolving at an unprecedented pace. Eightfold examines the most sought-after job roles, delving into the needs for reskilling and upskilling. Through its Talent Intelligence Platform, it empowers business leaders to adapt swiftly to the changing business environment. We take pride in contributing to the creation of a knowledgeable and responsible resource that assists organizations in preparing for the future of work.” – Ashutosh Garg, CEO and Co-Founder, Eightfold AI
“Google believes the opportunities created by technology should truly be available to everyone. We’re proud to join the AI-Enabled Workforce Consortium, which will advance our work to make AI skills training universally accessible. We’re committed to collaborating across sectors to ensure workers of all backgrounds can use AI effectively and develop the skills needed to prepare for future-focused jobs, qualify for new opportunities, and thrive in the economy.” – Lisa Gevelber, Founder, Grow with Google
IBM
“IBM is proud to join this timely business-led initiative, which brings together our shared expertise and resources to prepare the workforce for the AI era. Our collective responsibility as industry leaders is to develop trustworthy technologies and help provide workers—from all backgrounds and experience levels—access to opportunities to reskill and upskill as AI adoption changes ways of working and creates new jobs.” – Gian Luigi Cattaneo, Vice President, Human Resources, IBM EMEA
Indeed
“Indeed’s mission is to help people get jobs. Our research shows that virtually every job posted on Indeed today, from truck driver to physician to software engineer, will face some level of exposure to GenAI-driven change. We look forward to contributing to the Workforce Consortium’s important work. The companies who empower their employees to learn new skills and gain on-the-job experience with evolving AI tools will deepen their bench of experts, boost retention and expand their pool of qualified candidates.” – Hannah Calhoon, Head of AI Innovation at Indeed
Intel
“At Intel, our purpose is to create world-changing technology that improves the lives of every person on the planet, and we believe bringing AI everywhere is key for businesses and society to flourish. To do so, we must provide access to AI skills for everyone. Intel is committed to expanding digital readiness by collaborating with 30 countries, empowering 30,000 institutions, and training 30 million people for current and future jobs by 2030. Working alongside industry leaders as part of this AI-enabled ICT workforce consortium will help upskill and reskill the workforce for the digital economy ahead.” – Christy Pambianchi, Executive Vice President and Chief People Officer at Intel Corporation
Microsoft
“As a global leader in AI innovation, Microsoft is proud to join the ICT Workforce Consortium and continue our efforts to shape an inclusive and equitable technology future for all. As a member of the consortium, we will work with industry leaders to share best practices, create accessible learning opportunities, and collaborate with stakeholders to ensure that workers are equipped with the technology skills of tomorrow,” – Amy Pannoni, Vice President and Deputy General Counsel, HR Legal at Microsoft
SAP
“SAP is proud to join this effort to help prepare our workforce for the jobs of the future and ensure AI is relevant, reliable, and responsible across businesses and roles. As we navigate the complexities of our ever-evolving world, AI has the potential to reshape industries, revolutionize problem-solving, and unlock unprecedented levels of human potential, enabling us to create a more intelligent, efficient, and inclusive workforce. Over the years, SAP has supported many skills building programs, and we look forward to driving additional learning opportunities, innovation, and positive change as part of the consortium.” – Nicole Helmer, Vice President & Global Head of Development Learning at SAP
About Cisco
Cisco (NASDAQ: CSCO) is the worldwide technology leader that securely connects everything to make anything possible. Our purpose is to power an inclusive future for all by helping our customers reimagine their applications, power hybrid work, secure their enterprise, transform their infrastructure, and meet their sustainability goals. Discover more on The Newsroom and follow us on X at @Cisco.
Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco’s trademarks can be found at www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company.
Executive Vice President of the European Commission and Commissioner for Competition Margaret Vestager and US Secretary of Commerce Gina Raimondo join Consortium members in Belgium. Photo Credit: Cisco
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References:
Big tech companies form new consortium to allay fears of AI job takeovers