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Intel’s new CEO signals streamlining efforts but does not spell out exact layoff numbers

Lip-Bu Tan, the new CEO of Intel, sent out a blunt message to employees saying the company has to reorganize to be more efficient. He said there would be a reduction in employees but he did not announce an exact number of layoffs as expected. Bloomberg reported that Intel is rumored to be preparing to lay off as many as 20% of its workers, which at the end of 2024 was about 108,900 people. A 20% cut would amount to roughly 21,780 jobs lost. And while the changes Tan announced today could result in considerable job cuts that would start in the second quarter, he did not spell out expected numbers. Tan’s letter to employees coincided with the release of Q1 2025 quarterly numbers. For the earnings, Tan said, “It was a step in the right direction as we delivered revenue, gross margin and EPS (earnings per share) above our guidance, driven by [former interim co-CEOs Dave Zinsner and Michelle Johnston’s] leadership. I want to thank them both, and all of you, for the good execution.” But he quickly warned, “We need to build on this progress — and it won’t be easy. We are navigating an increasingly volatile and uncertain macroeconomic environment, which is reflected in our Q2 outlook. On top of that, there are many areas where we must improve. We need to confront our challenges head-on and take swift actions to get back on track.” “There is no way around the fact that these critical changes will reduce the size of our workforce. As I said when I joined, we need to make some very hard decisions to put our company on a solid footing for the future. This will begin in Q2 and we will move as quickly as possible over the next several months.” In his letter, Tan said Intel had not set any headcount reduction target. “What we have set is a new non-GAAP operating expense target to approximately $17 billion in 2025, down from our previously stated goal of $17.5 billion, and $16 billion in 2026,” he said. “There is no way around the fact that these critical changes will reduce the size of our workforce. As I said when I joined, we need to make some very hard decisions to put our company on a solid footing for the future. This will begin in Q2 and we will move as quickly as possible over the next several months.” Tan’s view of Intel’s culture Intel is using glass substrates to speed up chip communication. Tan inherited a tough situation as Intel has been losing in the AI/graphics market to Nvidia and in the x86 processor market to Advanced Micro Devices. He didn’t mince words about criticizing Intel’s culture as a big company. “As I have said, this starts by revamping our culture. The feedback I have received from our customers and many of you has been consistent. We are seen as too slow, too complex and too set in our ways — and we need to change,” he wrote. He said that the “flatter Executive Team (ET) structure that I shared last week was a first step.” The next step is to drive greater simplicity, speed and collaboration across the entire company, he said. And so he has changes coming. Among them: remaking the company’s AI strategy, Tan said in an analyst call. He also said Intel’s financial performance is not where it needs to be and that Intel would reduce its capital spending. He also said Intel would not spin off Intel Capital and invest in external companies. Intel is selling 51% of its Altera programmable logic division to Silver Lake Partners. Altera has a value of $9 billion, and so that deal will generate considerable cash for Intel. “We need to get back to our roots and empower our engineers. That’s why I elevated our core engineering functions to the ET. And many of the changes we will be driving are designed to make engineers more productive by removing burdensome workflows and processes that slow down the pace of innovation,” Tan said. To make necessary investments in engineering talent and technology roadmaps, Intel needs to find new ways to reduce costs, he said. “While we have taken significant actions in the last year, our current cost structure is still well above competitive benchmarks. With that in mind, we have reduced our operating expense and capital spending targets going forward, which I will discuss during our investor call this afternoon,” he said. “As we refocus on engineering, we will also remove organizational complexity. Many teams are eight or more layers deep, which creates unnecessary bureaucracy that slows us down. I have asked the ET to take a fresh look at their respective orgs, with a focus on removing layers, increasing spans of control and empowering top performers. Our competitors are lean, fast and agile — and that’s what we must become to improve our execution,” he said. As a longtime chip engineer, it’s no surprise that Tan is focused on empowering engineers to do more. He wrote, “I’ve been surprised to learn that, in recent years, the most important KPI for many managers at Intel has been the size of their teams. Going forward, this will not be the case. I’m a big believer in the philosophy that the best leaders get the most done with the fewest people. We will embrace this mindset across the company, which will include empowering our top talent to make decisions and take greater ownership of key priorities.” He said the company would empower smaller teams to move faster and make better decisions and reduce the number of layers in the way. He said Intel would balance reductions against the need to retain and recruit key talent. He said he would keep the team informed. Streamlining processes Intel has a bunch of new Core processors coming at CES 2025. Tan said it has been eye-opening for him to see how much time and energy is spent on internal administrative work that does not move the business forward. “We need to radically simplify this to maximize the time spent focusing on our customers,” he said. “I am instructing our leaders to eliminate unnecessary meetings and significantly reduce the number of meeting attendees. Too much valuable time is being wasted. We will also modernize processes with a focus on live dashboards and better data to ensure we have the real-time insights we need to make better and faster decisions,” he wrote. One of the things he is making optional is Intel’s traditions of formal Insights and OKR requirements. He thinks staying accountable and absorbing feedback can be done in a simpler and more flexible way. He said the company will return to work at the office four days a week, instead of the current required three days a week on site. The four-day-in-office plan goes into effect on September 1, 2025. He said, “I realize this is a lot to take in, but we are playing from behind and we need to rally as a team to put ourselves in the best possible position to win.” It’s pretty tough medicine, and not unlike the tough policies that Intel’s former longtime CEO, Andy Grove, would do. A look at Intel’s Ocotillo chip fab. I’m talking about the opportunity to fundamentally reinvent an industry icon. To pull off a comeback that will be studied in business schools for generations to come. To create new technologies and deploy them at scale to change the world for the better. “Intel was once widely seen as the world’s most innovative company. There’s no reason we can’t get back there, so long as we drive the changes needed to improve,” Tan wrote. “It’s going to be hard. It will require painful decisions. But we will make them knowing it’s what we must do to serve our customers better as we build a new Intel for the future – and I have great confidence in the power of our team and our people to make it happen.” In closing, he thanked employees “for everything you did in Q1.” In an analyst call, he noted he joined five weeks ago. He replaced the interim bosses as well as former CEO Pat Gelsinger, who resigned in December 2024. Tan said his motto was to under promise and over deliver, and he would not rest until Intel regained the trust of its customers. Intel said that tariffs would certainly affect its business, partly because of the caution it would generate among customers.

Lip-Bu Tan, the new CEO of Intel, sent out a blunt message to employees saying the company has to reorganize to be more efficient. He said there would be a reduction in employees but he did not announce an exact number of layoffs as expected.

Bloomberg reported that Intel is rumored to be preparing to lay off as many as 20% of its workers, which at the end of 2024 was about 108,900 people. A 20% cut would amount to roughly 21,780 jobs lost. And while the changes Tan announced today could result in considerable job cuts that would start in the second quarter, he did not spell out expected numbers.

Tan’s letter to employees coincided with the release of Q1 2025 quarterly numbers. For the earnings, Tan said, “It was a step in the right direction as we delivered revenue, gross margin and EPS (earnings per share) above our guidance, driven by [former interim co-CEOs Dave Zinsner and Michelle Johnston’s] leadership. I want to thank them both, and all of you, for the good execution.”

But he quickly warned, “We need to build on this progress — and it won’t be easy. We are navigating an increasingly volatile and uncertain macroeconomic environment, which is reflected in our Q2 outlook. On top of that, there are many areas where we must improve. We need to confront our challenges head-on and take swift actions to get back on track.”

“There is no way around the fact that these critical changes will reduce the size of our workforce. As I said when I joined, we need to make some very hard decisions to put our company on a solid footing for the future. This will begin in Q2 and we will move as quickly as possible over the next several months.”

In his letter, Tan said Intel had not set any headcount reduction target.

“What we have set is a new non-GAAP operating expense target to approximately $17 billion in 2025, down from our previously stated goal of $17.5 billion, and $16 billion in 2026,” he said. “There is no way around the fact that these critical changes will reduce the size of our workforce. As I said when I joined, we need to make some very hard decisions to put our company on a solid footing for the future. This will begin in Q2 and we will move as quickly as possible over the next several months.”

Tan’s view of Intel’s culture

Intel is using glass substrates to speed up chip communication.
Intel is using glass substrates to speed up chip communication.

Tan inherited a tough situation as Intel has been losing in the AI/graphics market to Nvidia and in the x86 processor market to Advanced Micro Devices. He didn’t mince words about criticizing Intel’s culture as a big company.

“As I have said, this starts by revamping our culture. The feedback I have received from our customers and many of you has been consistent. We are seen as too slow, too complex and too set in our ways — and we need to change,” he wrote.

He said that the “flatter Executive Team (ET) structure that I shared last week was a first step.” The next step is to drive greater simplicity, speed and collaboration across the entire company, he said. And so he has changes coming. Among them: remaking the company’s AI strategy, Tan said in an analyst call. He also said Intel’s financial performance is not where it needs to be and that Intel would reduce its capital spending.

He also said Intel would not spin off Intel Capital and invest in external companies. Intel is selling 51% of its Altera programmable logic division to Silver Lake Partners. Altera has a value of $9 billion, and so that deal will generate considerable cash for Intel.

“We need to get back to our roots and empower our engineers. That’s why I elevated our core engineering functions to the ET. And many of the changes we will be driving are designed to make engineers more productive by removing burdensome workflows and processes that slow down the pace of innovation,” Tan said.

To make necessary investments in engineering talent and technology roadmaps, Intel needs to find new ways to reduce costs, he said.

“While we have taken significant actions in the last year, our current cost structure is still well above competitive benchmarks. With that in mind, we have reduced our operating expense and capital spending targets going forward, which I will discuss during our investor call this afternoon,” he said.

“As we refocus on engineering, we will also remove organizational complexity. Many teams are eight or more layers deep, which creates unnecessary bureaucracy that slows us down. I have asked the ET to take a fresh look at their respective orgs, with a focus on removing layers, increasing spans of control and empowering top performers. Our competitors are lean, fast and agile — and that’s what we must become to improve our execution,” he said.

As a longtime chip engineer, it’s no surprise that Tan is focused on empowering engineers to do more. He wrote, “I’ve been surprised to learn that, in recent years, the most important KPI for many managers at Intel has been the size of their teams. Going forward, this will not be the case. I’m a big believer in the philosophy that the best leaders get the most done with the fewest people. We will embrace this mindset across the company, which will include empowering our top talent to make decisions and take greater ownership of key priorities.”

He said the company would empower smaller teams to move faster and make better decisions and reduce the number of layers in the way. He said Intel would balance reductions against the need to retain and recruit key talent. He said he would keep the team informed.

Streamlining processes

Intel has a bunch of new Core processors coming at CES 2025.
Intel has a bunch of new Core processors coming at CES 2025.

Tan said it has been eye-opening for him to see how much time and energy is spent on internal administrative work that does not move the business forward.

“We need to radically simplify this to maximize the time spent focusing on our customers,” he said.

“I am instructing our leaders to eliminate unnecessary meetings and significantly reduce the number of meeting attendees. Too much valuable time is being wasted. We will also modernize processes with a focus on live dashboards and better data to ensure we have the real-time insights we need to make better and faster decisions,” he wrote.

One of the things he is making optional is Intel’s traditions of formal Insights and OKR requirements. He thinks staying accountable and absorbing feedback can be done in a simpler and more flexible way.

He said the company will return to work at the office four days a week, instead of the current required three days a week on site. The four-day-in-office plan goes into effect on September 1, 2025.

He said, “I realize this is a lot to take in, but we are playing from behind and we need to rally as a team to put ourselves in the best possible position to win.”

It’s pretty tough medicine, and not unlike the tough policies that Intel’s former longtime CEO, Andy Grove, would do.

A look at Intel's Ocotillo chip fab.
A look at Intel’s Ocotillo chip fab.

I’m talking about the opportunity to fundamentally reinvent an industry icon. To pull off a comeback that will be studied in business schools for generations to come. To create new technologies and deploy them at scale to change the world for the better.

“Intel was once widely seen as the world’s most innovative company. There’s no reason we can’t get back there, so long as we drive the changes needed to improve,” Tan wrote. “It’s going to be hard. It will require painful decisions. But we will make them knowing it’s what we must do to serve our customers better as we build a new Intel for the future – and I have great confidence in the power of our team and our people to make it happen.”

In closing, he thanked employees “for everything you did in Q1.” In an analyst call, he noted he joined five weeks ago. He replaced the interim bosses as well as former CEO Pat Gelsinger, who resigned in December 2024.

Tan said his motto was to under promise and over deliver, and he would not rest until Intel regained the trust of its customers. Intel said that tariffs would certainly affect its business, partly because of the caution it would generate among customers.

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The Rise of AI Factories: Transforming Intelligence at Scale

AI Factories Redefine Infrastructure The architecture of AI factories reflects a paradigm shift that mirrors the evolution of the industrial age itself—from manual processes to automation, and now to autonomous intelligence. Nvidia’s framing of these systems as “factories” isn’t just branding; it’s a conceptual leap that positions AI infrastructure as the new production line. GPUs are the engines, data is the raw material, and the output isn’t a physical product, but predictive power at unprecedented scale. In this vision, compute capacity becomes a strategic asset, and the ability to iterate faster on AI models becomes a competitive differentiator, not just a technical milestone. This evolution also introduces a new calculus for data center investment. The cost-per-token of inference—how efficiently a system can produce usable AI output—emerges as a critical KPI, replacing traditional metrics like PUE or rack density as primary indicators of performance. That changes the game for developers, operators, and regulators alike. Just as cloud computing shifted the industry’s center of gravity over the past decade, the rise of AI factories is likely to redraw the map again—favoring locations with not only robust power and cooling, but with access to clean energy, proximity to data-rich ecosystems, and incentives that align with national digital strategies. The Economics of AI: Scaling Laws and Compute Demand At the heart of the AI factory model is a requirement for a deep understanding of the scaling laws that govern AI economics. Initially, the emphasis in AI revolved around pretraining large models, requiring massive amounts of compute, expert labor, and curated data. Over five years, pretraining compute needs have increased by a factor of 50 million. However, once a foundational model is trained, the downstream potential multiplies exponentially, while the compute required to utilize a fully trained model for standard inference is significantly less than

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Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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