What to expect from Neuralink in 2025

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What to expect from Neuralink in 2025

In November, a young man named Noland Arbaugh announced he’d be livestreaming from his home for three days straight. His broadcast was in some ways typical fare: a backyard tour, video games, meet mom. The difference is that Arbaugh, who is paralyzed, has thin electrode-studded wires installed in his brain, which he used to move a computer mouse on a screen, click menus, and play chess. The implant, called N1, was installed last year by neurosurgeons working with Neuralink, Elon Musk’s brain-interface company. The possibility of listening to neurons and using their signals to move a computer cursor was first demonstrated more than 20 years ago in a lab setting. Now, Arbaugh’s livestream is an indicator that Neuralink is a whole lot closer to creating a plug-and-play experience that can restore people’s daily ability to roam the web and play games, giving them what the company has called “digital freedom.” But this is not yet a commercial product. The current studies are small-scale—they are true experiments, explorations of how the device works and how it can be improved. For instance, at some point last year, more than half the electrode-studded “threads” inserted into Aurbaugh’s brain retracted, and his control over the device worsened; Neuralink rushed to implement fixes so he could use his remaining electrodes to move the mouse. Neuralink did not reply to emails seeking comment, but here is what our analysis of its public statements leads us to expect from the company in 2025. More patients How many people will get these implants? Elon Musk keeps predicting huge numbers. In August, he posted on X: “If all goes well, there will be hundreds of people with Neuralinks within a few years, maybe tens of thousands within five years, millions within 10 years.” In reality, the actual pace is slower—a lot slower. That’s because in a study of a novel device, it’s typical for the first patients to be staged months apart, to allow time to monitor for problems. Neuralink has publicly announced that two people have received an implant: Arbaugh and a man referred to only as “Alex,” who received his in July or August. Then, on January 8, Musk disclosed during an online interview that there was now a third person with an implant. “We’ve got now three patients, three humans with Neuralinks implanted, and they are all working …well,” Musk said. During 2025, he added, “we expect to hopefully do, I don’t know, 20 or 30 patients.” Barring major setbacks, expect the pace of implants to increase—although perhaps not as fast as Musk says. In November, Neuralink updated its US trial listing to include space for five volunteers (up from three), and it also opened a trial in Canada with room for six. Considering these two studies only, Neuralink would carry out at least two more implants by the end of 2025 and eight by the end of 2026. However, by opening further international studies, Neuralink could increase the pace of the experiments. Better control So how good is Arbaugh’s control over the mouse? You can get an idea by trying a game called Webgrid, where you try to click quickly on a moving target. The program translates your speed into a measure of information transfer: bits per second. Neuralink claims Arbaugh reached a rate of over nine bits per second, doubling the old brain-interface record. The median able-bodied user scores around 10 bits per second, according to Neuralink. And yet during his livestream, Arbaugh complained that his mouse control wasn’t very good because his “model” was out of date. It was a reference to how his imagined physical movements get mapped to mouse movements. That mapping degrades over hours and days, and to recalibrate it, he has said, he spends as long as 45 minutes doing a set of retraining tasks on his monitor, such as imagining moving a dot from a center point to the edge of a circle. Noland Arbaugh stops to calibrate during a livestream on X@MODDEDQUAD VIA X Improving the software that sits between Arbaugh’s brain and the mouse is a big area of focus for Neuralink—one where the company is still experimenting and making significant changes. Among the goals: cutting the recalibration time to a few minutes. “We want them to feel like they are in the F1 [Formula One] car, not the minivan,” Bliss Chapman, who leads the BCI software team, told the podcaster Lex Fridman last year. Device changes Before Neuralink ever seeks approval to sell its brain interface, it will have to lock in a final device design that can be tested in a “pivotal trial” involving perhaps 20 to 40 patients, to show it really works as intended. That type of study could itself take a year or two to carry out and hasn’t yet been announced. In fact, Neuralink is still tweaking its implant in significant ways—for instance, by trying to increase the number of electrodes or extend the battery life. This month, Musk said the next human tests would be using an “upgraded Neuralink device.” The company is also still developing the surgical robot, called R1, that’s used to implant the device. It functions like a sewing machine: A surgeon uses R1 to thread the electrode wires into people’s brains. According to Neuralink’s job listings, improving the R1 robot and making the implant process entirely automatic is a major goal of the company. That’s partly to meet Musk’s predictions of a future where millions of people have an implant, since there wouldn’t be enough neurosurgeons in the world to put them all in manually. “We want to get to the point where it’s one click,” Neuralink president Dongjin Seo told Fridman last year. Robot arm Late last year, Neuralink opened a companion study through which it says some of its existing implant volunteers will get to try using their brain activity to control not only a computer mouse but other types of external devices, including an “assistive robotic arm.” We haven’t yet seen what Neuralink’s robotic arm looks like—whether it’s a tabletop research device or something that could be attached to a wheelchair and used at home to complete daily tasks. But it’s clear such a device could be helpful. During Aurbaugh’s livestream he frequently asked other people to do simple things for him, like brush his hair or put on his hat. Arbaugh demonstrates the use of Imagined Movement Control.@MODDEDQUAD VIA X And using brains to control robots is definitely possible—although so far only in a controlled research setting. In tests using a different brain implant, carried out at the University of Pittsburgh in 2012, a paralyzed woman named Jan Scheuermann was able to use a robot arm to stack blocks and plastic cups about as well as a person who’d had a severe stroke—impressive, since she couldn’t actually move her own limbs. There are several practical obstacles to using a robot arm at home. One is developing a robot that’s safe and useful. Another, as noted by Wired, is that the calibration steps to maintain control over an arm that can make 3D movements and grasp objects could be onerous and time consuming. Vision implant In September, Neuralink said it had received “breakthrough device designation” from the FDA for a version of its implant that could be used to restore limited vision to blind people. The system, which it calls Blindsight, would work by sending electrical impulses directly into a volunteer’s visual cortex, producing spots of light called phosphenes. If there are enough spots, they can be organized into a simple, pixelated form of vision, as previously demonstrated by academic researchers. The FDA designation is not the same as permission to start the vision study. Instead, it’s a promise by the agency to speed up review steps, including agreements around what a trial should look like. Right now, it’s impossible to guess when a Neuralink vision trial could start, but it won’t necessarily be this year. More money Neuralink last raised money in 2003, collecting around $325 million from investors in a funding round that valued the company at over $3 billion, according to Pitchbook. Ryan Tanaka, who publishes a podcast about the company, Neura Pod, says he thinks Neuralink will raise more money this year and that the valuation of the private company could triple. Fighting regulators Neuralink has attracted plenty of scrutiny from news reporters, animal-rights campaigners, and even fraud investigators at the Securities and Exchange Commission. Many of the questions surround its treatment of test animals and whether it rushed to try the implant in people. More recently, Musk has started using his X platform to badger and bully heads of state and was named by Donald Trump to co-lead a so-called Department of Government Efficiency, which Musk says will “get rid of nonsensical regulations” and potentially gut some DC agencies. During 2025, watch for whether Musk uses his digital bullhorn to give health regulators pointed feedback on how they’re handling Neuralink. Other efforts Don’t forget that Neuralink isn’t the only company working on brain implants. A company called Synchron has one that’s inserted into the brain through a blood vessel, which it’s also testing in human trials of brain control over computers. Other companies, including Paradromics, Precision Neuroscience, and BlackRock Neurotech, are also developing advanced brain-computer interfaces. Special thanks to Ryan Tanaka of Neura Pod for pointing us to Neuralink’s public announcements and projections.

The difference is that Arbaugh, who is paralyzed, has thin electrode-studded wires installed in his brain, which he used to move a computer mouse on a screen, click menus, and play chess. The implant, called N1, was installed last year by neurosurgeons working with Neuralink, Elon Musk’s brain-interface company.

The possibility of listening to neurons and using their signals to move a computer cursor was first demonstrated more than 20 years ago in a lab setting. Now, Arbaugh’s livestream is an indicator that Neuralink is a whole lot closer to creating a plug-and-play experience that can restore people’s daily ability to roam the web and play games, giving them what the company has called “digital freedom.”

But this is not yet a commercial product. The current studies are small-scale—they are true experiments, explorations of how the device works and how it can be improved. For instance, at some point last year, more than half the electrode-studded “threads” inserted into Aurbaugh’s brain retracted, and his control over the device worsened; Neuralink rushed to implement fixes so he could use his remaining electrodes to move the mouse.

Neuralink did not reply to emails seeking comment, but here is what our analysis of its public statements leads us to expect from the company in 2025.

More patients

How many people will get these implants? Elon Musk keeps predicting huge numbers. In August, he posted on X: “If all goes well, there will be hundreds of people with Neuralinks within a few years, maybe tens of thousands within five years, millions within 10 years.”

In reality, the actual pace is slower—a lot slower. That’s because in a study of a novel device, it’s typical for the first patients to be staged months apart, to allow time to monitor for problems.

Neuralink has publicly announced that two people have received an implant: Arbaugh and a man referred to only as “Alex,” who received his in July or August.

Then, on January 8, Musk disclosed during an online interview that there was now a third person with an implant. “We’ve got now three patients, three humans with Neuralinks implanted, and they are all working …well,” Musk said. During 2025, he added, “we expect to hopefully do, I don’t know, 20 or 30 patients.”

Barring major setbacks, expect the pace of implants to increase—although perhaps not as fast as Musk says. In November, Neuralink updated its US trial listing to include space for five volunteers (up from three), and it also opened a trial in Canada with room for six. Considering these two studies only, Neuralink would carry out at least two more implants by the end of 2025 and eight by the end of 2026.

However, by opening further international studies, Neuralink could increase the pace of the experiments.

Better control

So how good is Arbaugh’s control over the mouse? You can get an idea by trying a game called Webgrid, where you try to click quickly on a moving target. The program translates your speed into a measure of information transfer: bits per second.

Neuralink claims Arbaugh reached a rate of over nine bits per second, doubling the old brain-interface record. The median able-bodied user scores around 10 bits per second, according to Neuralink.

And yet during his livestream, Arbaugh complained that his mouse control wasn’t very good because his “model” was out of date. It was a reference to how his imagined physical movements get mapped to mouse movements. That mapping degrades over hours and days, and to recalibrate it, he has said, he spends as long as 45 minutes doing a set of retraining tasks on his monitor, such as imagining moving a dot from a center point to the edge of a circle.

Noland Arbaugh stops to calibrate during a livestream on X

@MODDEDQUAD VIA X

Improving the software that sits between Arbaugh’s brain and the mouse is a big area of focus for Neuralink—one where the company is still experimenting and making significant changes. Among the goals: cutting the recalibration time to a few minutes. “We want them to feel like they are in the F1 [Formula One] car, not the minivan,” Bliss Chapman, who leads the BCI software team, told the podcaster Lex Fridman last year.

Device changes

Before Neuralink ever seeks approval to sell its brain interface, it will have to lock in a final device design that can be tested in a “pivotal trial” involving perhaps 20 to 40 patients, to show it really works as intended. That type of study could itself take a year or two to carry out and hasn’t yet been announced.

In fact, Neuralink is still tweaking its implant in significant ways—for instance, by trying to increase the number of electrodes or extend the battery life. This month, Musk said the next human tests would be using an “upgraded Neuralink device.”

The company is also still developing the surgical robot, called R1, that’s used to implant the device. It functions like a sewing machine: A surgeon uses R1 to thread the electrode wires into people’s brains. According to Neuralink’s job listings, improving the R1 robot and making the implant process entirely automatic is a major goal of the company. That’s partly to meet Musk’s predictions of a future where millions of people have an implant, since there wouldn’t be enough neurosurgeons in the world to put them all in manually.

“We want to get to the point where it’s one click,” Neuralink president Dongjin Seo told Fridman last year.

Robot arm

Late last year, Neuralink opened a companion study through which it says some of its existing implant volunteers will get to try using their brain activity to control not only a computer mouse but other types of external devices, including an “assistive robotic arm.”

We haven’t yet seen what Neuralink’s robotic arm looks like—whether it’s a tabletop research device or something that could be attached to a wheelchair and used at home to complete daily tasks.

But it’s clear such a device could be helpful. During Aurbaugh’s livestream he frequently asked other people to do simple things for him, like brush his hair or put on his hat.

Arbaugh demonstrates the use of Imagined Movement Control.

@MODDEDQUAD VIA X

And using brains to control robots is definitely possible—although so far only in a controlled research setting. In tests using a different brain implant, carried out at the University of Pittsburgh in 2012, a paralyzed woman named Jan Scheuermann was able to use a robot arm to stack blocks and plastic cups about as well as a person who’d had a severe stroke—impressive, since she couldn’t actually move her own limbs.

There are several practical obstacles to using a robot arm at home. One is developing a robot that’s safe and useful. Another, as noted by Wired, is that the calibration steps to maintain control over an arm that can make 3D movements and grasp objects could be onerous and time consuming.

Vision implant

In September, Neuralink said it had received “breakthrough device designation” from the FDA for a version of its implant that could be used to restore limited vision to blind people. The system, which it calls Blindsight, would work by sending electrical impulses directly into a volunteer’s visual cortex, producing spots of light called phosphenes. If there are enough spots, they can be organized into a simple, pixelated form of vision, as previously demonstrated by academic researchers.

The FDA designation is not the same as permission to start the vision study. Instead, it’s a promise by the agency to speed up review steps, including agreements around what a trial should look like. Right now, it’s impossible to guess when a Neuralink vision trial could start, but it won’t necessarily be this year.

More money

Neuralink last raised money in 2003, collecting around $325 million from investors in a funding round that valued the company at over $3 billion, according to Pitchbook. Ryan Tanaka, who publishes a podcast about the company, Neura Pod, says he thinks Neuralink will raise more money this year and that the valuation of the private company could triple.

Fighting regulators

Neuralink has attracted plenty of scrutiny from news reporters, animal-rights campaigners, and even fraud investigators at the Securities and Exchange Commission. Many of the questions surround its treatment of test animals and whether it rushed to try the implant in people.

More recently, Musk has started using his X platform to badger and bully heads of state and was named by Donald Trump to co-lead a so-called Department of Government Efficiency, which Musk says will “get rid of nonsensical regulations” and potentially gut some DC agencies.

During 2025, watch for whether Musk uses his digital bullhorn to give health regulators pointed feedback on how they’re handling Neuralink.

Other efforts

Don’t forget that Neuralink isn’t the only company working on brain implants. A company called Synchron has one that’s inserted into the brain through a blood vessel, which it’s also testing in human trials of brain control over computers. Other companies, including Paradromics, Precision Neuroscience, and BlackRock Neurotech, are also developing advanced brain-computer interfaces.

Special thanks to Ryan Tanaka of Neura Pod for pointing us to Neuralink’s public announcements and projections.

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Modernizing Legacy Data Centers for the AI Revolution with Schneider Electric’s Steven Carlini

As artificial intelligence workloads drive unprecedented compute density, the U.S. data center industry faces a formidable challenge: modernizing aging facilities that were never designed to support today’s high-density AI servers. In a recent Data Center Frontier podcast, Steven Carlini, Vice President of Innovation and Data Centers at Schneider Electric, shared his insights on how operators are confronting these transformative pressures. “Many of these data centers were built with the expectation they would go through three, four, five IT refresh cycles,” Carlini explains. “Back then, growth in rack density was moderate. Facilities were designed for 10, 12 kilowatts per rack. Now with systems like Nvidia’s Blackwell, we’re seeing 132 kilowatts per rack, and each rack can weigh 5,000 pounds.” The implications are seismic. Legacy racks, floor layouts, power distribution systems, and cooling infrastructure were simply not engineered for such extreme densities. “With densification, a lot of the power distribution, cooling systems, even the rack systems — the new servers don’t fit in those racks. You need more room behind the racks for power and cooling. Almost everything needs to be changed,” Carlini notes. For operators, the first questions are inevitably about power availability. At 132 kilowatts per rack, even a single cluster can challenge the limits of older infrastructure. Many facilities are conducting rigorous evaluations to decide whether retrofitting is feasible or whether building new sites is the more practical solution. Carlini adds, “You may have transformers spaced every hundred yards, twenty of them. Now, one larger transformer can replace that footprint, and power distribution units feed busways that supply each accelerated compute rack. The scale and complexity are unlike anything we’ve seen before.” Safety considerations also intensify with these densifications. “At 132 kilowatts, maintenance is still feasible,” Carlini says, “but as voltages rise, data centers are moving toward environments where

Google Backs Advanced Nuclear at TVA’s Clinch River as ORNL Pushes Quantum Frontiers

Inside the Hermes Reactor Design Kairos Power’s Hermes reactor is based on its KP-FHR architecture — short for fluoride salt–cooled, high-temperature reactor. Unlike conventional water-cooled reactors, Hermes uses a molten salt mixture called FLiBe (lithium fluoride and beryllium fluoride) as a coolant. Because FLiBe operates at atmospheric pressure, the design eliminates the risk of high-pressure ruptures and allows for inherently safer operation. Fuel for Hermes comes in the form of TRISO particles rather than traditional enriched uranium fuel rods. Each TRISO particle is encapsulated within ceramic layers that function like miniature containment vessels. These particles can withstand temperatures above 1,600 °C — far beyond the reactor’s normal operating range of about 700 °C. In combination with the salt coolant, Hermes achieves outlet temperatures between 650–750 °C, enabling efficient power generation and potential industrial applications such as hydrogen production. Because the salt coolant is chemically stable and requires no pressurization, the reactor can shut down and dissipate heat passively, without external power or operator intervention. This passive safety profile differentiates Hermes from traditional light-water reactors and reflects the Generation IV industry focus on safer, modular designs. From Hermes-1 to Hermes-2: Iterative Nuclear Development The first step in Kairos’ roadmap is Hermes-1, a 35 MW thermal demonstration reactor now under construction at TVA’s Clinch River site under a 2023 NRC license. Hermes-1 is not designed to generate electricity but will validate reactor physics, fuel handling, licensing strategies, and construction techniques. Building on that experience, Hermes-2 will be a 50 MW electric reactor connected to TVA’s grid, with operations targeted for 2030. Under the agreement, TVA will purchase electricity from Hermes-2 and supply it to Google’s data centers in Tennessee and Alabama. Kairos describes its development philosophy as “iterative,” scaling incrementally rather than attempting to deploy large fleets of units at once. By

NVIDIA Forecasts $3–$4 Trillion AI Market, Driving Next Wave of Infrastructure

Whenever behemoth chipmaker NVIDIA announces its quarterly earnings, those results can have a massive influence on the stock market and its position as a key indicator for the AI industry. After all, NVIDIA is the most valuable publicly traded company in the world, valued at $4.24 trillion—ahead of Microsoft ($3.74 trillion), Apple ($3.41 trillion), Alphabet, the parent company of Google ($2.57 trillion), and Amazon ($2.44 trillion). Due to its explosive growth in recent years, a single NVIDIA earnings report can move the entire market. So, when NVIDIA leaders announced during their August 27 earnings call that Q2 2026 sales surged 56% to $46.74 billion, it was a record-setting performance for the company—and investors took notice. Executive VP & CFO Colette M. Kress said the revenue exceeded leadership’s outlook as the company grew sequentially across all market platforms. She outlined a path toward substantial growth driven by AI infrastructure. Foreseeing significant long-term growth opportunities in agentic AI and considering the scale of opportunity, CEO Jensen Huang said, “Over the next 5 years, we’re going to scale into it with Blackwell [architecture for GenAI], with Rubin [successor to Blackwell], and follow-ons to scale into effectively a $3 trillion to $4 trillion AI infrastructure opportunity.” The chipmaker’s Q2 2026 earnings fell short of Wall Street’s lofty expectations, but they did demonstrate that its sales are still rising faster than those of most other tech companies. NVIDIA is expected to post revenue growth of at least 42% over the next four quarters, compared with an average of about 10% for firms in the technology-heavy Nasdaq 100 Index, according to data compiled by Bloomberg Intelligence. On August 29, two days after announcing their earnings, NVIDIA stocks slid 3% and other chip stocks also declined. This came amid a broader sell-off after server-maker Dell, a customer of those chipmakers,

Cologix and Lambda Debut NVIDIA HGX B200 AI Clusters in Columbus, Ohio

In our latest episode of the Data Center Frontier Show, we explore how powerhouse AI infrastructure is moving inland—anchored by the first NVIDIA HGX B200 cluster deployment in Columbus, Ohio. Cologix, Lambda, and Supermicro have partnered on the project, which combines Lambda’s 1-Click Clusters™, Supermicro’s energy-efficient hardware, and Cologix’s carrier-dense Scalelogix℠ COL4 facility. It’s a milestone that speaks to the rapid decentralization of AI workloads and the emergence of the Midwest as a serious player in the AI economy. Joining me for the conversation were Bill Bentley, VP Hyperscale and Cloud Sales at Cologix, and Ken Patchett, VP Data Center Infrastructure at Lambda. Why Columbus, Why Now? Asked about the significance of launching in Columbus, Patchett framed the move in terms of the coming era of “superintelligence.” “The shift to superintelligence is happening now—systems that can reason, adapt, and accelerate human progress,” Patchett said. “That requires an entirely new type of infrastructure, which means capital, vision, and the right partners. Columbus with Cologix made sense because beyond being centrally located, they’re highly connected, cost-efficient, and built to scale. We’re not chasing trends. We’re laying the groundwork for a future where intelligence infrastructure is as ubiquitous as electricity.” Bentley pointed to the city’s underlying strengths in connectivity, incentives, and utility economics. “Columbus is uniquely situated at the intersection of long-haul fiber,” Bentley said. “You’ve got state tax incentives, low-cost utilities, and a growing concentration of hyperscalers and local enterprises. The ecosystem is ripe for growth. It’s a natural geography for AI workloads that need geographic diversity without sacrificing performance.” Shifting—or Expanding—the Map for AI The guests agreed that deployments like this don’t represent a wholesale shift away from coastal hyperscale markets, but rather the expansion of AI’s footprint across multiple geographies. “I like to think of Lambda as an AI hyperscaler,”

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.

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

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

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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