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The CEO of the world’s largest data center company predicts will drive the business forward

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Adaire Fox-Martin understands the needs of Big Tech. Prior to becoming CEO of Equinix (No. 446 on the Fortune 500) last year, she held senior roles at Google, SAP and Oracle. Now, the Irish-born former teacher is driving the expansion of the world’s largest global data center network, with more than 273 data centers in 36 countries. Fox-Martin recently spoke with Fortune about what she learned in her first year in the job and where she wants to go from here. 

This interview has been edited and condensed for clarity. 

We last met when you were starting out in the role.

It’s been an incredible year of learning and realizing that this job doesn’t come with an instruction manual. You bring the experiences that you’ve had in the past to the decisions that you make for the company for the future. We’ve laid out the strategy and optimized it into 10 simple words. The first of those is “build bolder.” which is how we’re designing and constructing the infrastructure that underpins the digital economy.

The second part of our ten-word strategy is “solve smarter.” This is about how we abstract the complexity of networking and architecture, which is our secret sauce, and render that for our customers, making Equinix the Easy button. The third piece is to “serve better.” Most participants in the data center industry have five or six customers; we have more than 10,000 enterprise customers. So those are the three pillars. 

What are the other four words?

Underpinning that, we have “run simpler,” which sounds easy to say and is very hard to do. You’re taking complexity out of your business, looking at systems and processes. And the last piece is our people piece, which is to “grow together,” growing our business with our customers, linking our employee success to our customer success. 

Is that a big change?

Equinix has been a company in this segment for 27 years, so we’re one of the long-term players in this industry. And in the next five years, we’re planning to bring on as much capacity as we did in the last 27 years. That’s a big capital investment for us. 

Where do you sit in the data-center ecosystem?

I think there’s a general trend to think of data centers as a homogeneous mass of a singular thing. But there are four distinct categories of data centers, and each one has its own nuance and characteristics. We exist in one of those categories. There’s the hyperscale category, the ones built by cloud-service providers, where you see massive investment. The second category is wholesale, where you’re usually building a facility to lease back to one tenant, maybe two, usually supporting (AI) training. The third is enterprise, where big companies like banks want to have their own center structure. And the fourth category is colocation, which is where Equinix sits.

And what are the advantages of that? 

Think of us a little like an airport authority. It manages the runaways and the facilities of the airport and gives you the ability to rent ticketing and other kind of facilities in there. Then it manages the process of passenger engagement, so an airline comes in, like KLM, drops a passenger, and then magic happens in the background to move that passenger and their luggage to United to go on to California. We’re a little bit like the airport authority of the internet: a data package comes into Equinix and then moves on to where its next destination is. The difference between us and an airport authority is that the airport lines will compete whereas a lot of our customers colocate so they can collaborate. 

What do you do in terms of AI workloads? 

We do both training and inference. A pharmaceutical company would do their training privately at Equinix because in the pharma world much of their research and drug discovery processes have to go through private models for regulatory reasons or intellectual property protection. Training is like teaching the model and then inference really putting what the model has learned to work. 

What about the energy needs?

The different types of data centers have different characteristics when it comes to energy, who they’re starving, or how they’re supporting local economies and communities. 

We’re smack bang in the middle of what I would describe as an energy super cycle. Data centers are one component of it, but so is the electrification of everything. You have the speed of an AI meeting the pace of utilities, and it’s a headfirst collision. We don’t think it’s an insurmountable challenge but it’s going to require collaboration, innovation and time. 

How do you seeing it playing out?

Between now and 2028, it’s fair to say there is a power crunch.  Anything that we’re delivering until 2028, we understand where our power will come from. From 2028 to 2032, you’ll see an innovation click into the power landscape, in the form of data centers and data center operators looking at how they can self-generate, how they can generate on site, how they can innovate with the grid, and give power back to the grid, how they can be flexible on and off the grid.  You’ll see different aspects of innovation, including nuclear, looking at small modular reactors and how they can be utilized. 

From 2032 on, the utilities have introduced some changes. In the past, you would go to a utility and say, ‘I want this much here in this time, just-in-time power provision.’ For someone like us, which doesn’t have the same power draw as a hyperscale data center, that was usually good enough. But utilities are looking at their power framework in the form of cluster studies, taking a group of requirements together in a cluster at the same time. You define the load that you’re going to ramp up to and it will likely take the form of take or pay. If you said you’re going to use this much, you will pay for it, whether you use it or not. 

It’s important that large energy users, like data centers, pay a premium for what they’re utilizing so that we don’t impact small ratepayers, small energy users, so there’s a lot happening around collaboration. We’ve got a 27-year history of that kind of collaboration with the utilities and so we’re very involved in a number of those processes. 

Talk about the challenge of building these centers.

One is supply chain, the things that are needed to construct a data center, some of which have been subject to tariffs. In the short term, that’s not an issue but longer term, that may become something that we have to navigate our way through. And then there’s the workforce, the plumbers and mechanical engineers and welders who are maintaining our environments that keep the internet up. A lot of trade skills, construction skills and technical skills are necessary to create the data center. 

Are the centers you’re building for these workloads any larger than the ones that you built in the past? 

We do support our hyperscaler partners with the provision of data centers, through a vehicle called xScale, which is a joint venture. We have partners who fund our joint ventures, so we do participate in what I described as the wholesale economy by building what’s called a build-to-suit data center industry for a hyperscaler. So a Google would come to us and say, ‘do you guys have power and land in location X? And would you build for us?’ So we do that through a joint venture off our balance sheet because the capital-intensive nature of that is high. We own 25% of our America JV and we own 20% of our EMEA and our APAC JV. We have 15 centers that are already operational around the globe.

What do you think is underappreciated about your business model?

I think the connectivity of Equinix is underappreciated. We have 270 data centers around the world, so we’re the world’s largest independent data center operator that’s still a public company. People see the physical manifestations of those centers, but the secret sauce is the connections that sit in every single one of those data centers. They take three forms. First is the ability to interconnect a company to another company. We have the trading hubs: 72% of the world’s trading platforms operate on Equinix. You have a trading hub and all their partners located closely to them that need to be literally connected so there’s no latency between the transactions. We have 492,000 deep interconnections between the companies that operate in our centers, between value chains. 

The second piece of connectivity is to do with the clouds. They are an exceptionally important part of the technology landscape. Many customers store their data in clouds and most customers store their data in more than one cloud. They spread the love. We have a 35% market share in native cloud on ramps from our data centers. So you can pop into the cloud, get your data and bring it back.

And then the third piece is physically where we’re located. We’re not in the middle of the country. We are in cities, where human beings are with their devices. So many people refer to us as the metro edge, the city edge, the edge where people actually are. So we can connect the cloud, via the metro edge where humans are, to the far edge where devices might be utilized. 

Do you think people appreciate the role that data centers play in their lives?

In many countries, we are designated as critical infrastructure, in certain states, too, but not at the federal level. When I think about moving home: water, gas, electricity, internet becomes that fourth utility. And 95% of internet traffic runs through the Equinix environment. If you were on a Zoom call this morning, if you did a stream from any of the major providers, ordered an Uber, purchased a train ticket, you were on a platform accessing Equinix at some point. 

“95% of internet traffic runs through the Equinix environment.”Adaire Fox-Martin, CEO, Equinix

What are you seeing in terms of customer trends? 

Many of our customers are moving from the proof-of-concept phase of AI into the real-world-application phase of AI. There’s a lot to grapple with in that. It isn’t just about taking a business process and putting AI over the top of it. There are a whole series of considerations around governance and the management of data that haven’t really played into the business picture yet that are very real, especially for industries that are highly regulated. 

That’s why some have not even adopted that much AI. 

Right. Even if they are frontrunners, now it’s kind of like coming back and saying, ‘oh, how do we make sure that we’re audible, traceable, accountable, all of the things that are good governance for business. If we’re going to deploy a technology that can automate so many things and take my human out of the loop, how do I report, manage, and maintain the governance framework of those processes in my business?

We’re seeing a lot of pushback in local communities where these mega hyperscale data centers are being built.  How are you staking your claim to say we’re not that, but this is still critical infrastructure we need?

You look at it through the lens of what are the good things that a data center can do for a local community. We engage very strongly with local communities when we are beginning a construction. You do bring jobs to the area, particularly in the construction face, less so when you’re in the operation face because there isn’t a preponderance of humans across a data center.  Second, you’re obviously going to pay tax in that location and that has knock-on benefit. Thirdly, we employ and source locally. I’m very excited about our apprenticeship scheme, where young women and men who maybe didn’t have a formal education path can become data-center technicians or critical facility engineers. And when there’s a build of a data center, there’s often an upgrade of the infrastructure around it, like whether that’s the power capabilities, the roads and so on. 

Are people asking more questions about water, energy? 

For sure. And we recognize that these are extremely important parts of the life system of our planet. We were the first data center operator to begin reporting on our water usage. When you bring in power, you want to maximize the use of that energy in the deployment of workloads for customers and not just empowering the data center itself. We measure our power and how effective we are in using power. The best way to save energy to use less of it. That’s absolutely an industry standard now.

And water?

Water was never at the same level of investigation or scrutiny as power was. Now, there’s a measure of water-usage effectiveness and we were one of the first to report on that. It’s not as standardized as power and so we’re working in the industry to try and standardize that a little bit more. 

In the longer term, data centers will more than likely be cooled by liquid cooling, as opposed to air or evaporative cooling. And liquid cooling, in terms of water use, is a closed-use-loop system. You’re reusing the same water over and over again to cool the chips. The technology itself will become a determinant of sustainability. 

All the big tech companies are working to make these models smaller and more efficient. Eventually, they’re going to want to have many little data centers that are colocated. Do you think you’ll benefit from that? 

We believe the inference target addressable market, combined with the network, is about $250 billion outside of what the clouds are doing. By 2029, the inference opportunity will be twice the size of training. And that’s why we’re setting ourselves up for this opportunity. 

You can think about training as a centralized AI emotion whereas inference is very much a distributed emotion. It will initiate on a device or maybe through voice, or glass, 0r whatever the device is. And it will probably have an agent conduct its orchestra, in terms of instructing other agents to get data from more than one location. That’s why we’ve been very selective about where we built. 

You came to this job from Google almost a year and a half ago. Where are you now versus what you were thinking when you came in? 

I would say on a journey, not at the destination but heading in the right direction. I’m confident that we have such a unique combination of characteristics—the metro locations, the connectivity, the secret sauce—that we’re ready for prime time. I’m working through the dynamics of some of the negative feelings around data centers. The challenge around energy has been very real in Europe, in particular. There are countries that have just issued a moratorium on data-center builds, like Ireland, my home country, until they can kind of take a breath and understand whether they can do. These problems are absolutely addressable. They’re absolutely surmountable. It’s a time-based issue that’s going to require collaboration and innovation to solve. 

What about the regulatory environment? That’s been in flux.

There is a lot of noise on a variety of topics. I’m just working to control the controllable, and carry on the path that we believe for us is the right path. For example, Equinix has some goals around our sustainability narrative. By 2030, we set a goal for ourselves that we would be neutral as it relates to the use of carbon. We’re still on that track. And we’ve set a science-based goal for 2040 to be net zero and we will continue to innovate and work to do that. 

It’s not just that we believe there is an opportunity for technology and innovation to exist with good environmental stewardship. Our customers are continuing to ask us for reports on how their usage at Equinix is impacting things that we may be measure.

There’s a lot of what about AI. What will it do? But there’s a where about AI. And we’re like the where of AI. There are physical cables, even under the ocean, and cable trays and billions of wires. If you’re in California, you get to see the history of data centers. The internet will literally be above your head. We have three decades of data center history, from our very first one to our latest one. I never thought I would come into a company where we have 56 active construction projects all around the world.



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Billionaire Marc Benioff challenges the AI sector: ‘What’s more important to us, growth or our kids?’

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Imagine it is 1996. You log on to your desktop computer (which took several minutes to start up), listening to the rhythmic screech and hiss of the modem connecting you to the World Wide Web. You navigate to a clunky message board—like AOL or Prodigy—to discuss your favorite hobbies, from Beanie Babies to the newest mixtapes.

At the time, a little-known law called Section 230 of the Communications Safety Act had just been passed. The law—then just a 26-word document—created the modern internet. It was intended to protect “good samaritans” who moderate websites from regulation, placing the responsibility for content on individual users rather than the host company.

Today, the law remains largely the same despite evolutionary leaps in internet technology and pushback from critics, now among them Salesforce CEO Marc Benioff. 

In a conversation at the World Economic Forum in Davos, Switzerland, on Tuesday, titled “Where Can New Growth Come From?” Benioff railed against Section 230, saying the law prevents tech giants from being held accountable for the dangers AI and social media pose.

“Things like Section 230 in the United States need to be reshaped because these tech companies will not be held responsible for the damage that they are basically doing to our families,” Benioff said in the panel conversation which also included Axa CEO Thomas Buberl, Alphabet President Ruth Porat, Emirati government official Khaldoon Khalifa Al Mubarak, and Bloomberg journalist Francine Lacqua.

As a growing number of children in the U.S. log onto AI and social media platforms, Benioff said the legislation threatens the safety of kids and families. The billionaire asked, “What’s more important to us, growth or our kids? What’s more important to us, growth or our families? Or, what’s more important, growth or the fundamental values of our society?”

Section 230 as a shield for tech firms

Tech companies have invoked Section 230 as a legal defense when dealing with issues of user harm, including in the 2019 case Force v. Facebook, where the court ruled the platform wasn’t liable for algorithms that connected members of Hamas after the terrorist organization used the platform to encourage murder in Israel. The law could shield tech companies from liability for harm AI platforms pose, including the production of deepfakes and AI-Generated sexual abuse material.

Benioff has been a vocal critic of Section 230 since 2019 and has repeatedly called for the legislation to be abolished. 

In recent years, Section 230 has come under increasing public scrutiny as both Democrats and Republicans have grown skeptical of the legislation. In 2019 the Department of Justice under President Donald Trump pursued a broad review of Section 230. In May 2020, President Trump signed an Executive Order limiting tech platforms’ immunity after Twitter added fact-checks to his tweets. And in 2023, the U.S. Supreme Court heard Gonzalez v. Google, though, decided it on other grounds, leaving Section 230 intact.

In an interview with Fortune in December 2025, Dartmouth business school professor Scott Anthony voiced concern over the “guardrails” that were—and weren’t—happening with AI. When cars were first invented, he pointed out, it took time for speed limits and driver’s licenses to follow. Now with AI, “we’ve got the technology, we’re figuring out the norms, but the idea of, ‘Hey, let’s just keep our hands off,’ I think it’s just really bad.”

The decision to exempt platforms from liability, Anthony added, “I just think that it’s not been good for the world. And I think we are, unfortunately, making the mistake again with AI.”

For Benioff, the fight to repeal Section 230 is more than a push to regulate tech companies, but a reallocation of priorities toward safety and away from unfettered growth. “In the era of this incredible growth, we’re drunk on the growth,” Benioff said. “Let’s make sure that we use this moment also to remember that we’re also about values as well.”



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Palantir CEO says AI “will destroy” humanities jobs but there will be “more than enough jobs” for people with vocational training

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Some economists and experts say that critical thinking and creativity will be more important than ever in the age of artificial intelligence (AI), when a robot can do much of the heavy lifting on coding or research. Take Benjamin Shiller, the Brandeis economics professor who recently told Fortune that a “weirdness premium” will be valued in the labor market of the future. Alex Karp, the Palantir founder and CEO, isn’t one of these voices. 

“It will destroy humanities jobs,” Karp said when asked how AI will affect jobs in conversation with BlackRock CEO Larry Fink at the World Economic Forum annual meeting in Davos, Switzerland. “You went to an elite school and you studied philosophy — I’ll use myself as an example — hopefully you have some other skill, that one is going to be hard to market.”

Karp attended Haverford College, a small, elite liberal arts college outside his hometown of Philadelphia. He earned a J.D. from Stanford Law School and a Ph.D. in philosophy from Goethe University in Germany. He spoke about his own experience getting his first job. 

Karp told Fink that he remembered thinking about his own career, “I’m not sure who’s going to give me my first job.” 

The answer echoed past comments Karp has made about certain types of elite college graduates who lack specialized skills.

“If you are the kind of person that would’ve gone to Yale, classically high IQ, and you have generalized knowledge but it’s not specific, you’re effed,” Karp said in an interview with Axios in November. 

Not every CEO agrees with Karp’s assessment that humanities degrees are doomed. BlackRock COO Robert Goldstein told Fortune in 2024 that the company was recruiting graduates who studied “things that have nothing to do with finance or technology.” 

McKinsey CEO Bob Sternfels recently said in an interview with Harvard Business Review that the company is “looking more at liberal arts majors, whom we had deprioritized, as potential sources of creativity,” to break out of AI’s linear problem-solving. 

Karp has long been an advocate for vocational training over traditional college degrees. Last year, Palantir launched a Meritocracy Fellowship, offering high school students a paid internship with a chance to interview for a full-time position at the end of four months. 

The company criticized American universities for “indoctrinating” students and having “opaque” admissions that “displaced meritocracy and excellence,” in their announcement of the fellowship. 

“If you did not go to school, or you went to a school that’s not that great, or you went to Harvard or Princeton or Yale, once you come to Palantir, you’re a Palantirian—no one cares about the other stuff,” Karp said during a Q2 earnings call last year.

“I think we need different ways of testing aptitude,” Karp told Fink. He pointed to the former police officer who attended a junior college, who now manages the US Army’s MAVEN system, a Palantir-made AI tool that processes drone imagery and video.  

“In the past, the way we tested for aptitude would not have fully exposed how irreplaceable that person’s talents are,” he said. 

Karp also gave the example of technicians building batteries at a battery company, saying those workers are “very valuable if not irreplaceable because we can make them into something different than what they were very rapidly.”

He said what he does all day at Palantir is “figuring out what is someone’s outlier aptitude. Then, I’m putting them on that thing and trying to get them to stay on that thing and not on the five other things they think they’re great at.” 

Karp’s comments come as more employers report a gap between the skills applicants are offering and what employers are looking for in a tough labor market. The unemployment rate for young workers ages 16 to 24 hit 10.4% in December and is growing among college graduates. Karp isn’t too worried. 

“There will be more than enough jobs for the citizens of your nation, especially those with vocational training,” he said. 



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AI is boosting productivity. Here’s why some workers feel a sense of loss

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Welcome to Eye on AI, with AI reporter Sharon Goldman. In this edition…Why some workers feel a sense of loss while AI boosts productivity…Anthropic raising fresh $10 Billion at $350 billion valuation…Musk’s xAI closed $20 billion funding with Nvidia backing…Can AI do your job? See the results from hundreds of tests.

For months, software developers have been giddy with excitement over “vibe coding”– prompting desired software functions or features in natural language—with the latest AI code generation tools. Anthropic’s Claude Code is the darling of the moment, but OpenAI’s Codex, Cursor and other tools have also led engineers to flood social media with examples of tasks that used to take days and are now finished in minutes. 

Even veteran software design leaders have marvelled at the shift. “In just a few months, Claude Code has pushed the state of the art in software engineering further than 75 years of academic research,” said Erik Meijer, a former senior engineering leader at Meta

Skills honed seem less essential

However, that same delight has turned disorienting for many developers, who are grappling with a sense of loss as skills honed over a lifetime suddenly seem less essential. The feeling of flow—of being “in the zone”—seems to have vanished as building software becomes an exercise in supervising AI tools rather than writing code. 

In a blog post this week titled “The Grief When AI Writes All the Code,” Gergely Orosz of The Pragmatic Engineer, wrote that he is “coming to terms with the high probability that AI will write most of my code which I ship to production.” It already does it faster, he explained, and for languages and frameworks he is less familiar with, it does a better job. 

“It feels like something valuable is being taken away, and suddenly,” he wrote. “It took a lot of effort to get good at coding and to learn how to write code that works, to read and understand complex code, and to debug and fix when code doesn’t work as it should.” 

Andrew Duca, founder of tax software Awaken Tax, wrote a similar post this week that went viral, saying that he was feeling “kinda depressed” even though he finds using Claude Code “incredible” and has “never found coding more fun.” 

He can now solve customer problems faster, and ship more features, but at the same time “the skill I spent 10,000s of hours getting good at…is becoming a full commodity extremely quickly,” he wrote. “There’s something disheartening about the thing you spent most of your life getting good at now being mostly useless.” 

Software development has long been on the front lines of the AI shift, partly because there are decades of code, documentation and public problem-solving (from sites like GitHub) available online for AI models to train on. Coding also has clear rules and fast feedback – it runs or it doesn’t – so AI systems can easily learn how to generate useful responses. That means programming has become one of the first white-collar professions to feel AI’s impact so directly.

These tensions will affect many professions

These tensions, however, won’t be confined to software developers. White-collar workers across industries will ultimately have to grapple with them in one way or another. Media headlines often focus on the possibility of mass layoffs driven by AI; the more immediate issue may be how AI reshapes how people feel about their work. AI tools can move us past the hardest parts of our jobs more quickly—but what if that struggle is part of what allows us to take pride in what we do? What if the most human elements of work—thinking, strategizing, working through problems—are quietly sidelined by tools that prize speed and efficiency over experience?

Of course, there are plenty of jobs and workflows where most people are very happy to use AI to say buh-bye to repetitive grunt work that they never wanted to do in the first place. And as Duca said, we can marvel at the incredible power of the latest AI models and leap to use the newest features even while we feel unmoored. 

Many white-collar workers will likely face a philosophical reckoning about what AI means for their profession—one that goes beyond fears of layoffs. It may resemble the familiar stages of grief: denial, anger, bargaining, depression, and, eventually, acceptance. That acceptance could mean learning how to be the best manager or steerer of AI possible. Or it could mean deliberately carving out space for work done without AI at all. After all, few people want to lose their thinking self entirely.

Or it could mean doing what Erik Meijer is doing. Now that coding increasingly feels like management, he said, he has turned back to making music—using real instruments—as a hobby, simply “to experience that flow.”

With that, here’s more AI news.

Sharon Goldman
sharon.goldman@fortune.com
@sharongoldman

FORTUNE ON AI

As Utah gives the AI power to prescribe some drugs, physicians warn of patient risks – by Beatrice Nolan

Google and Character.AI agree to settle lawsuits over teen suicides linked to AI chatbots – by Beatrice Nolan

OpenAI launches ChatGPT Health in a push to become a hub for personal health data – by Sharon Goldman

Google takes first steps toward an AI product that can actually tackle your email inbox – by Jacqueline Munis

Fusion power nearly ready for prime time as Commonwealth builds first pilot for limitless, clean energy with AI help from Siemens, Nvidia – by Jordan Blum

AI IN THE NEWS

Anthropic raising fresh $10 Billion at $350 billion valuation. According to the Wall Street Journal, OpenAI rival Anthropic is planning to raise $10 billion at a roughly $350 billion valuation, nearly doubling its worth from just four months ago. The round is expected to be led by GIC and Coatue Management, following a $13 billion raise in September that valued the company at $183 billion. The financing underscores the continued boom in AI funding—AI startups raised a record $222 billion in 2025, per PitchBook—and comes as Anthropic is also preparing for a potential IPO this year. Founded in 2021 by siblings Dario Amodei and Daniela Amodei, Anthropic has become a major OpenAI rival, buoyed by Claude’s popularity with business users, major backing from Nvidia and Microsoft, and expectations that it will reach break-even by 2028—potentially faster than OpenAI, which is itself reportedly seeking to raise up to $100 billion at a $750 billion valuation.

Musk’s xAI closed $20 billion funding with Nvidia backing. Bloomberg reported that xAI, the AI startup founded by Elon Musk, has completed a $20 billion funding round backed by investors including Nvidia, Valor Equity Partners, and the Qatar Investment Authority, underscoring the continued flood of capital into AI infrastructure. Other backers include Fidelity Management & Research, StepStone Group, MGX, Baron Capital Group, and Cisco’s investment arm. The financing—months in the making—will fund xAI’s rapid infrastructure buildout and product development, the company said, and includes a novel structure in which a large portion of the capital is tied to a special-purpose vehicle used to buy Nvidia GPUs that are then rented out, allowing investors to recoup returns over time. The deal comes as xAI has been under fire for its chatbot Grok producing non-consensual “undressing” images of real people.

Can AI do your job? See the results from hundreds of tests. I wanted to shout-out this fascinating new interactive feature in the Washington Post, which presented a new study that found that despite fears of mass job displacement, today’s AI systems are still far from being able to replace humans on real-world work. Researchers from Scale AI and the Center for AI Safety tested leading models from OpenAI, Google, and Anthropic on hundreds of actual freelance projects—from graphic design and creating dashboards to 3D modeling and games—and found that the best AI systems successfully completed just 2.5% of tasks on their own. While AI often produced outputs that looked plausible at first glance, closer inspection revealed missing details, visual errors, incomplete work, or basic technical failures, highlighting gaps in areas like visual reasoning, long-term memory, and the ability to evaluate subjective outcomes. The findings challenge predictions that AI is poised to automate large swaths of human labor anytime soon, even as newer models show incremental improvement and the economics of cheaper, semi-autonomous AI work continue to put pressure on remote and contract workers.

EYE ON AI NUMBERS

91.8%

That’s the percentage of Meta employees who admitted to not using the company’s AI chatbot, Meta AI, in their day-to-day work, according to new data from Blind, a popular anonymous professional social network. 

 

According to a survey of 400 Meta employees, only 8.2% said they use Meta AI. The most popular chatbot was Anthropic’s Claude, used by more than half (50.7%) of Meta employees surveyed. 17.7% said they use Google’s Gemini and 13.7% said they used OpenAI’s ChatGPT. 

 

When approached for comment, Meta spokesperson pointed out that the number (400 of 77,000+ employees) is “not even a half percent of our total employee population.”

AI CALENDAR

Jan. 19-23: World Economic Forum, Davos, Switzerland.

Jan. 20-27: AAAI Conference on Artificial Intelligence, Singapore.

Feb. 10-11: AI Action Summit, New Delhi, India.

March 2-5: Mobile World Congress, Barcelona, Spain.

March 16-19: Nvidia GTC, San Jose, Calif.

April 6-9: HumanX, San Francisco. 



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