The road to artificial general intelligence

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The road to artificial general intelligence

In partnership withArm Artificial intelligence models that can discover drugs and write code still fail at puzzles a lay person can master in minutes. This phenomenon sits at the heart of the challenge of artificial general intelligence (AGI). Can today’s AI revolution produce models that rival or surpass human intelligence across all domains? If so, what underlying enablers—whether hardware, software, or the orchestration of both—would be needed to power them? Dario Amodei, co-founder of Anthropic, predicts some form of “powerful AI” could come as early as 2026, with properties that include Nobel Prize-level domain intelligence; the ability to switch between interfaces like text, audio, and the physical world; and the autonomy to reason toward goals, rather than responding to questions and prompts as they do now. Sam Altman, chief executive of OpenAI, believes AGI-like properties are already “coming into view,” unlocking a societal transformation on par with electricity and the internet. He credits progress to continuous gains in training, data, and compute, along with falling costs, and a socioeconomic value that is“super-exponential.” Optimism is not confined to founders. Aggregate forecasts give at least a 50% chance of AI systems achieving several AGI milestones by 2028. The chance of unaided machines outperforming humans in every possible task is estimated at 10% by 2027, and 50% by 2047, according to one expert survey. Time horizons shorten with each breakthrough, from 50 years at the time of GPT-3’s launch to five years by the end of 2024. “Large language and reasoning models are transforming nearly every industry,” says Ian Bratt, vice president of machine learning technology and fellow at Arm. Download the full report. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

In partnership withArm

Artificial intelligence models that can discover drugs and write code still fail at puzzles a lay person can master in minutes. This phenomenon sits at the heart of the challenge of artificial general intelligence (AGI). Can today’s AI revolution produce models that rival or surpass human intelligence across all domains? If so, what underlying enablers—whether hardware, software, or the orchestration of both—would be needed to power them?

Dario Amodei, co-founder of Anthropic, predicts some form of “powerful AI” could come as early as 2026, with properties that include Nobel Prize-level domain intelligence; the ability to switch between interfaces like text, audio, and the physical world; and the autonomy to reason toward goals, rather than responding to questions and prompts as they do now. Sam Altman, chief executive of OpenAI, believes AGI-like properties are already “coming into view,” unlocking a societal transformation on par with electricity and the internet. He credits progress to continuous gains in training, data, and compute, along with falling costs, and a socioeconomic value that is
“super-exponential.”

Optimism is not confined to founders. Aggregate forecasts give at least a 50% chance of AI systems achieving several AGI milestones by 2028. The chance of unaided machines outperforming humans in every possible task is estimated at 10% by 2027, and 50% by 2047, according to one expert survey. Time horizons shorten with each breakthrough, from 50 years at the time of GPT-3’s launch to five years by the end of 2024. “Large language and reasoning models are transforming nearly every industry,” says Ian Bratt, vice president of machine learning technology and fellow at Arm.

Download the full report.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

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Cisco strengthens AI networking story

“Overall, AI demand in the enterprise will grow over time. But enterprise customers need to see the value, see the ROI. Also, they have to have a well-defined use case,” Wollenweber said, noting that the 12-month innovation cycles of GPU vendors can be problematic if customers choose the wrong platform.

DEF CON research takes aim at ZTNA, calls it a bust

Major vendor vulnerabilities span authentication and design flaws The research exposed critical vulnerabilities across Check Point, Zscaler and Netskope that fell into three primary categories: authentication bypasses, credential storage failures and cross-tenant exploitation. Authentication bypass vulnerabilities Zscaler’s SAML implementation contained the most severe authentication flaw. The researchers discovered that the

Trump meets with Intel CEO after calling for his resignation

The call for Tan’s resignation coincided with an Aug. 6 letter Sen. Tom Cotton (R-AK) sent to Intel Chairman Frank Yeary, in which he expressed concerns about “Intel’s operations and its potential impact on U.S. national security,” citing a report alleging Tan’s links to Chinese firms and the fact Cadence

US to maintain lower tariff rates on China imports for 90 more days

The U.S. is extending its pause on additional retaliatory tariffs for imports from China until Nov. 10, according to an executive order signed by President Donald Trump on Monday. The order said the extension is appropriate following “significant steps” from China on addressing U.S. trade concerns in ongoing discussions between the

Energy Department Announces Actions to Secure American Critical Minerals and Materials Supply Chain

Proposed funding will accelerate the growth of the U.S. critical minerals and materials sector. WASHINGTON—The U.S. Department of Energy (DOE) today announced its intent to issue notices of funding opportunities (NOFO) totaling nearly $1 billion to advance and scale mining, processing, and manufacturing technologies across key stages of the critical minerals and materials supply chains. The funding announcements, issued in accordance with President Trump’s Executive Order Unleashing American Energy, will help ensure a more secure, predictable, and affordable supply of critical minerals and materials that are foundational to American energy dominance, national security, and industrial competitiveness. “For too long, the United States has relied on foreign actors to supply and process the critical materials that are essential to modern life and our national security,” said U.S. Secretary of Energy Chris Wright. “Thanks to President Trump’s leadership, the Energy Department will play a leading role in reshoring the processing of critical materials and expanding our domestic supply of these indispensable resources.” Proposed NOFOs announced today include: Critical Minerals and Materials Accelerator The Advanced Materials and Manufacturing Technologies Office expects to release a NOFO of up to $50 million early this fall through the Critical Minerals and Materials (CMM) Accelerator program. The CMM Accelerator promotes technology maturation that can unlock capital investments and facilitate domestic commercialization. The proposed NOFO addresses several areas of interest, including processes in the rare-earth magnet supply chain; processes to refine and alloy gallium, gallium nitride, germanium, and silicon carbide for use in semiconductors; cost-competitive technologies for direct lithium extraction and separation; and critical-material separation technologies that allow for the co-production of useful products from byproducts and scrap. Mines & Metals Capacity Expansion – Piloting Byproduct Critical Minerals and Materials Recovery at Domestic Industrial Facilities The Office of Fossil Energy and Carbon Management is announcing its intent to issue a NOFO to support approximately

Oil Drops on Stockpile Rise

Oil dropped as a larger-than-expected US crude inventory gain and a bearish report from the International Energy Agency added to a gloomy outlook for markets. West Texas Intermediate fell 0.8% to settle below $63 a barrel in a thin summer trading session. Prices tumbled after US crude stockpiles rose about 3 million barrels last week to the highest level in two months, according to government data. Adding to a bearish trading day, the IEA said global oil inventories are poised for a record glut next year, a day after the US government also bolstered its view for a surplus in 2026. Against that backdrop, traders are looking ahead to a meeting between US President Donald Trump and his Russian counterpart in Alaska on Friday geared toward ending the war in Ukraine. Trump warned he would impose “very severe consequences” if Vladimir Putin didn’t agree to a ceasefire agreement later this week. Ukrainian President Volodymyr Zelenskiy said he won’t cede the eastern region of Donbas to Russia — a condition demanded by Putin to unlock a ceasefire — and pushed for Kyiv to be included in the talks. The country claimed an attack on a Russian oil-pumping station on Wednesday, though the impact was unclear and it wasn’t possible to independently verify Ukraine’s claims. Crude prices have dropped about 13% this year as OPEC+ accelerated output hikes, though moves have been more muted in recent days amid thin summer trading. Oil traders are closely tracking preparations for the talks, given that they may result in an easing of US sanctions on OPEC+ member Russia. “Markets continue to remain in a wait and see approach as we await the big Trump-Putin meeting in Alaska,” said Keshav Lohiya, founder of consultant Oilytics. OilPrices WTI for September delivery fell 52 cents to settle at

Chevron Phillips Chemical Co Cuts 130 Jobs

Chevron Phillips Chemical Co., a 50-50 joint venture between Chevron Corp. and Phillips 66, has cut roughly 130 jobs in the latest in a round of reductions sweeping through the Texas oil and chemicals sector. The cuts primarily involve corporate roles including information technology, supply-chain management and logistics rather than chemical plants, according to people familiar with the matter who requested anonymity discussing non-public information. Affected employees were informed in early August, just weeks after CPChem moved into a new 360,000 square-foot headquarters in the Houston suburb of The Woodlands. “These changes reflect opportunities to outsource, centralize work, optimize leader spans of control and reduce organizational layers,” Chief Executive Officer Steve Prusak wrote in internal email to employees seen by Bloomberg News. “This is the first step to ensure our organizational structure aligns with industry realities and is prepared for what is ahead.” Major energy companies are reducing headcount to curb costs as weak commodity prices and lackluster demand growth hurt profits, despite President Donald Trump’s vocal support for the sector. Prices for chemicals used to make plastics and other consumer products are under particular strain after giant new plants came online in China in recent years. CPChem “is working to improve operational efficiency and manage costs as we position the company for long-term competitiveness,” the company said in a separate statement. The relocation of CPChem’s headquarters had been planned since 2023 and is “unrelated” to current economic conditions, it said. Affected employees were notified by managers via video call on Aug. 1 after several months of working with consultants to assess what work could be transferred to vendors or overseas, the people said. The departing workers were offered severance and transition-support services, CPChem noted. “These were difficult decisions, and we were committed to handling them with care and consideration,” the company

EPA plans to revise coal-fired power plant wastewater rules

The Environmental Protection Agency intends to delay a compliance deadline for owners of coal-fired power plants affected by zero-discharge wastewater standards, according to a Monday court filing by the agency. The case centers on updates to effluent limitation guidelines the EPA issued in April 2024. The rule sets more stringent limits for flue gas desulfurization wastewater, bottom ash transport water and combustion residual leachate. Wastewater discharges from coal-fired power plants into bodies of water include toxic and bioaccumulative pollutants including heavy metals, halogen compounds, nutrients and total dissolved solids, according to the EPA. Power plant owners must meet the new requirements by Dec. 31, 2029, and file notice of intent to retire plants that cannot meet the new standards by the end of this year. In its filing Monday, the EPA asked the U.S. Court of Appeals for the Eighth Circuit in St. Louis to suspend litigation utilities and trade groups brought against the rule until after the agency extends the end-of-year deadline. After the agency extends the deadline, the EPA plans to propose revising the technology basis for limits on discharges of unmanaged combustion residual leachate — essentially, leaks from landfills or other impoundments. The EPA said it may also seek to change its zero-discharge limits and standards for coal-fired power plants. The agency submitted a proposal on Monday to the White House Office of Information and Regulatory Affairs, which vets federal regulations, to extend the Dec. 31 deadline. It estimates the wastewater rule would cut pollution from coal-fired power plants by more than 660 million pounds a year and produce $3.2 billion in annual benefits. It also said the rule could lead to about 5,780 MW in power plant retirements by 2035. However, the EPA may pare back the effluent rule as part of a broad push by the Trump administration to

DOE taps 10 advanced reactor companies for expedited nuclear pilot

Dive Brief: The U.S. Department of Energy on Tuesday selected 11 advanced reactor projects to participate in a nuclear pilot program that aims to expedite deployment without Nuclear Regulatory Commission licensing, according to a June request for applications. DOE wants to achieve criticality of at least three test reactors using an expedited authorization process by July 4, 2026. Oklo and its Atomic Alchemy subsidiary were selected to develop three of the projects. DOE “is opening the door to the market so new ideas, new approaches, and new designs can be built more quickly and efficiently,” Oklo CEO Jacob DeWitte said in a statement. Dive Insight: DOE unveiled its reactor pilot program in June, building on a May executive order signed by President Donald Trump that reformed reactor testing. The program aims to expedite testing of reactor designs authorized by DOE and located outside of the national laboratories. DOE cited the Atomic Energy Act’s authorization of reactors under the agency’s “sufficient control,” in authorizing the pilot. “Reactors built and operated pursuant to the DOE pilot program will not require Nuclear Regulatory Commission licensing,” the June request for applications said. “Nevertheless, DOE-approved reactor designs can and will be fast tracked for future NRC licensing. … [The pilot will] provide a fast track to an NRC license, and hence, commercialization for authorized reactor design.” DOE on Tuesday named 10 companies that could access a “fast-tracked approach to future commercial licensing activities.” They are: Aalo Atomics; Antares Nuclear; Atomic Alchemy; Deep Fission; Last Energy; Oklo; Natura Resources; Radiant Industries; Terrestrial Energy; and Valar Atomics. Each company will be responsible for all costs associated with designing, manufacturing, constructing, operating, and decommissioning their test reactors, the DOE said. “Seeking DOE authorization provided under the Atomic Energy Act will help today’s selected companies … unlock private funding and

ISO-NE should make its governance transparent, accessible and accountable

Mireille Bejjani is co-executive director of Slingshot and facilitator of the Fix the Grid Campaign. Steven Botkin is a volunteer with Fix the Grid and No Coal No Gas. ISO New England recently announced that Gordon van Welie, its longtime CEO, would be stepping down, to be replaced by Dr. Vamsi Chadalavada, the current chief operating officer. Mr. van Welie’s departure after 25 years marks the end of an era, as he has directed the ISO almost from its inception in 1997. The timing of this leadership change couldn’t be more important. The climate crisis is driving a transition from fossil fuels to renewable energy, and public interest in the electric power grid has increased dramatically with programs such as net metering, demand response and community aggregation. Thus, new leadership at ISO New England must create opportunities to embrace new approaches to governance that reflect these emerging realities. No longer hidden Until very recently, public awareness of independent system operators and regional transmission organizations has been virtually nonexistent. For years, grid operators, particularly ISO New England, were able to operate in the shadows with little accountability for their decision-making. However, as evidence of the climate crisis becomes increasingly apparent, the public has become more interested in how the ISO resists and delays the transition from fossil fuels to clean energy. To that end, clean energy and grid advocates from across New England have been calling on ISO New England to facilitate a rapid and just transition to renewable energy, and to see the public as valued stakeholders in planning for the future of the grid. At the same time, New England state senators and governors, as well as the New England States Committee on Electricity, sent letters and reports to van Welie calling for critical changes to ISO New

New Compute Exchange service answers GPU pricing queries

Compute Exchange and Silicon Data, Bochev added “are also working on developing clearer benchmarks for the compute market, and will have more details to share on that in the coming weeks.” PIC ‘should serve to keep suppliers honest ..’ Scott Bickley, an advisory fellow at Info-Tech Research Group, said he views the offering “as a way for enterprises to source short-term GPU capacity and possibly get a deal, especially if it is stranded capacity from the neocloud providers.” This, he said, “would also help to benchmark costs when purchasing this capacity in general, so it’s good, but it is also straightforward in terms of the value proposition.” He also noted that most companies are not buying GPU capacity directly; “This is for those that are building their own models or deploying their own AI applications atop existing models.” Bickley added, “it should serve to keep suppliers honest to some degree in terms of the floors and ceilings of the price to access GPU capacity.” Soon after Compute Exchange first launched in February, Matt Kimball, VP and principal analyst for data center compute and storage at Moor Insights & Strategy, described the GPU compute situation as “pretty dire. This is driven by what most view as a single supplier (Nvidia) selling GPUs before they can even be made to a market that has an insatiable thirst.” On Tuesday, following the announcement, he said that the concept of PIC is appealing: “I really like the idea of PIC as a tool for customers and seeing the compute exchange become an arbitrageur of sorts. This delivers a real value to [anyone] who is looking to utilize AI infrastructure,” he said.

Data center sustainability efforts stall slightly in 2025

Data center operators reported limited advances—and even some declines—in energy efficiency, carbon tracking, and water usage due in part to rising power demand and easing regulatory pressure in some regions, according to the recently released results of the Uptime Institute’s 15th Annual Global Data Center Survey 2025. As artificial intelligence workloads continue to grow and legacy data centers remain operational, sustainability initiatives have stalled, according to the Uptime Institute, which attributes this in part to reporting challenges. Uptime Institute’s 2025 data center survey was conducted online from April 2025 to May 2025 and collected responses from more than 800 data center owners and operators and more than 1,000 vendors and consultants. “What’s interesting this year is that we have seen a far from startling increase over the last few years of the data being collected, but this year it actually fell. And this obviously led to some speculation that there is a backing off of sustainability, and that it is no longer a high priority,” said Andy Lawrence, executive director of research at Uptime Institute, during a webinar sharing the survey results. “I think that the data center industry has not yet adapted to being very good at sustainability reporting.”

Arista’s latest networking results: 4 critical takeaways

“We also think UALink is another spec that’s coming out, and that may run as an overlay on top of an Ethernet underlay. There needs to be some firm standards there because today, scale-up is frankly all proprietary NV Link. And we’re encouraged by—just like we worked hard to found the Ultra Ethernet Consortium as a member for some of the back-end Ethernet, and the migration from InfiniBand to Ethernet is literally happening in 3 to 5 years. We expect the same phenomenon on scale-up,” Ullal said. “The rise in Agentic AI ensures any-to-any conversations with bidirectional bandwidth utilization. Such AI agents are pushing the envelope of LAN and WAN traffic patterns in the enterprise,” Ullal said. Work to do on VeloCloud integration The recent acquisition of VeloCloud was also a hot topic of the second quarter results that included the introduction of former Cisco exec and industry veteran Todd Nightingale, as its newly appointed President & COO. “It’s only been a month, but I can’t tell you how impressed I am with the passion and focus of the team, the trust that Arista customers have in the technology and the enormous opportunity we have ahead of us in data center, AI, and in the campus,” Nightingale said. “VeloCloud’s secure AI optimized WAN portfolio offers seamless application-aware solutions to connect customer branch sites, complementing Arista’s leading spines in the data center and campus,” Ullal said. “In a classic leaf-spine atomic identifier, we are enabling multipathing, encryption, in-band network telemetry, segmentation, application identification, and traffic engineering across distributed enterprise sites. We are so excited to fill this missing void in our distributed enterprise puzzle to bring that holistic branch solution.” “We also intend to work closely with best-of-breed security partners to enable SASE overlays. Please do note that VeloCloud is not

Enterprise tips for cloud success

The remaining tips were cited by roughly two-thirds of the enterprises. Tip number three is to look especially at applications whose users are widely dispersed. And by “widely” here, they mean on different continents, not just different neighborhoods. The reason is that quality of experience and even availability can be compromised when work has to transit a lot of networks just to get to where it’s processed. This can lead to user dissatisfaction, and dispersing resources closer to the users may be the only solution. If an enterprise doesn’t already have their own data center located close to each user concentration, chances are that putting a new hosting point in themselves couldn’t achieve reasonable economy of scale in capex, power and cooling, and operations costs. The cloud would be cheaper. A qualifying comment here is to take great care in evaluating the real impact of dispersion of application users. In some cases, there may not be enough of a difference in QoE or availability to require dispersing hosting points, and in fact it may be that where the application is hosted isn’t even the problem. “The cloud may look like the easy way out,” one enterprise said, “but it may not be the economical way.” See where your QoE issues really lie before you go to the cloud’s distributed hosting to fix them. Tip four is to examine the user-to-application interaction model carefully, to see if there’s a large non-transactional component. Mission-critical business systems, and business core databases, are almost always in the data center. The stuff that changes them are the transactions that add, update, and delete records. If an application’s user interaction is tightly coupled to the creation of transactions, then its processing is tied to those data center resources. That makes it harder to move the user-interface

Stargate’s slow start reveals the real bottlenecks in scaling AI infrastructure

The CFO emphasized that SoftBank remains committed to its original target of $346 billion (JPY 500 billion) over 4 years for the Stargate project, noting that major sites have been selected in the US and preparations are taking place simultaneously across multiple fronts. Requests for comment to Stargate partners Nvidia, OpenAI, and Oracle remain unanswered. Infrastructure reality check for CIOs These challenges offer important lessons for enterprise IT leaders facing similar AI infrastructure decisions. Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research, said that Goto’s confirmation of delays “reflects a challenge CIOs see repeatedly” in partner onboarding delays, service activation slips, and revised delivery commitments from cloud and datacenter providers. Oishi Mazumder, senior analyst at Everest Group, noted that “SoftBank’s Stargate delays show that AI infrastructure is not constrained by compute or capital, but by land, energy, and stakeholder alignment.” The analyst emphasized that CIOs must treat AI infrastructure “as a cross-functional transformation, not an IT upgrade, demanding long-term, ecosystem-wide planning.” “Scaling AI infrastructure depends less on the technical readiness of servers or GPUs and more on the orchestration of distributed stakeholders — utilities, regulators, construction partners, hardware suppliers, and service providers — each with their own cadence and constraints,” Gogia said.

Incentivizing the Digital Future: Inside America’s Race to Attract Data Centers

Across the United States, states are rolling out a wave of new tax incentives aimed squarely at attracting data centers, one of the country’s fastest-growing industries. Once clustered in only a handful of industry-friendly regions, today’s data-center boom is rapidly spreading, pushed along by profound shifts in federal policy, surging demand for artificial intelligence, and the drive toward digital transformation across every sector of the economy. Nowhere is this transformation more visible than in the intensifying state-by-state competition to land massive infrastructure investments, advanced technology jobs, and the alluring prospect of long-term economic growth. The past year alone has seen a record number of states introducing or expanding incentives for data centers, from tax credits to expedited permitting, reflecting a new era of proactive, tech-focused economic development policy. Behind these moves, federal initiatives and funding packages underscore the essential role of digital infrastructure as a national priority, encouraging states to lower barriers for data center construction and operation. As states watch their neighbors reap direct investment and job creation benefits, a real “domino effect” emerges: one state’s success becomes another’s blueprint, heightening the pressure and urgency to compete. Yet, this wave of incentives also exposes deeper questions about the local impact, community costs, and the evolving relationship between public policy and the tech industry. From federal levels to town halls, there are notable shifts in both opportunities and challenges shaping the landscape of digital infrastructure advancement. Industry Drivers: the Federal Push and Growth of AI The past year has witnessed a profound federal policy shift aimed squarely at accelerating U.S. digital infrastructure, especially for data centers in direct response both to the explosive growth of artificial intelligence and to intensifying international competition. In July 2025, the administration unveiled “America’s AI Action Plan,” accompanied by multiple executive orders that collectively redefined

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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