Stay Ahead, Stay ONMINE

Introducing WeatherNext 3, our most advanced and accurate global weather AI model

Real-world data at continuous global scaleWeatherNext 3’s biggest leap forward is what it learns from. Most AI weather models, including WeatherNext 2, are trained on data from numerical weather prediction (NWP) models. Although useful, NWP models are complex, supercomputer-driven physics simulations that carry a six-hour data lag. This lag can lead to biases for fast-changing variables like rain or surface temperature.By ingesting a mosaic of live, global geostationary satellite data, our new model gains a rich, continuously updating view of the atmosphere. This allows the model to generate a new forecast every hour, each one grounded in the most recent satellite observations available, at up to 5-kilometer resolution.This is important because critical weather develops fast. When storms, fronts, or precipitation systems materialize suddenly, our rapid update cycle and higher resolution provides earlier, more detailed insights needed to help drive an effective response.Some variables, like temperature and humidity, can fluctuate dramatically over just a few kilometers, which is particularly relevant for communities near coastlines, valleys, or mountain ranges. Traditional models struggle here because they train on representations of the atmosphere that lack detail and miss extreme local variations.To address this, WeatherNext 3 instead trains directly on sparse weather station observation data. This allows us to make global forecasts on a 5-kilometer grid that account for regional details like topography.This breakthrough is particularly vital for regions across Latin America, Africa, and Asia-Pacific that have historically been underserved by high-resolution forecasting due to the immense supercomputing costs of traditional regional models. It brings localized, high-fidelity forecasting to billions of people and local businesses in these areas.Beyond improved resolution and forecast frequency, our model introduces predictions specifically engineered for renewable energy production. The model forecasts 100-meter wind speeds (roughly at turbine-height) for precise wind-energy output, alongside high-resolution cloud cover and sun radiation levels to help solar farms estimate how much light they will receive on the ground.This data is crucial for global clean energy planning, allowing grid operators and renewables developers to accurately predict how much power their clean energy assets will generate and match it with consumer demand.Precipitation forecasting at breakthrough accuracyGlobal weather models notoriously struggle to accurately predict precipitation. Rain and snow systems are driven by fast-moving cloud processes on tiny scales that are hard to model accurately using traditional physics-based simulations. Consequently, AI forecasts often produce blurry estimates or miss the boundaries of severe storms entirely.To solve this, we train our model on two exceptionally high-quality sources of precipitation data: NASA’s satellite-based Integrated Multi-satellite Retrievals for GPM (IMERG) and our own global precipitation reanalysis based on satellite radar.The result is a significant leap in precipitation forecasting accuracy. In medium-range global forecasts, evaluations against baselines show a Continuous Ranked Probability Score (CRPS) improvement of up to 60% against IMERG, 30% for MRMS, and 10% against rain gauge measurements for early lead times.

Real-world data at continuous global scale

WeatherNext 3’s biggest leap forward is what it learns from. Most AI weather models, including WeatherNext 2, are trained on data from numerical weather prediction (NWP) models. Although useful, NWP models are complex, supercomputer-driven physics simulations that carry a six-hour data lag. This lag can lead to biases for fast-changing variables like rain or surface temperature.

By ingesting a mosaic of live, global geostationary satellite data, our new model gains a rich, continuously updating view of the atmosphere. This allows the model to generate a new forecast every hour, each one grounded in the most recent satellite observations available, at up to 5-kilometer resolution.

This is important because critical weather develops fast. When storms, fronts, or precipitation systems materialize suddenly, our rapid update cycle and higher resolution provides earlier, more detailed insights needed to help drive an effective response.

Some variables, like temperature and humidity, can fluctuate dramatically over just a few kilometers, which is particularly relevant for communities near coastlines, valleys, or mountain ranges. Traditional models struggle here because they train on representations of the atmosphere that lack detail and miss extreme local variations.

To address this, WeatherNext 3 instead trains directly on sparse weather station observation data. This allows us to make global forecasts on a 5-kilometer grid that account for regional details like topography.

This breakthrough is particularly vital for regions across Latin America, Africa, and Asia-Pacific that have historically been underserved by high-resolution forecasting due to the immense supercomputing costs of traditional regional models. It brings localized, high-fidelity forecasting to billions of people and local businesses in these areas.

Beyond improved resolution and forecast frequency, our model introduces predictions specifically engineered for renewable energy production. The model forecasts 100-meter wind speeds (roughly at turbine-height) for precise wind-energy output, alongside high-resolution cloud cover and sun radiation levels to help solar farms estimate how much light they will receive on the ground.

This data is crucial for global clean energy planning, allowing grid operators and renewables developers to accurately predict how much power their clean energy assets will generate and match it with consumer demand.

Precipitation forecasting at breakthrough accuracy

Global weather models notoriously struggle to accurately predict precipitation. Rain and snow systems are driven by fast-moving cloud processes on tiny scales that are hard to model accurately using traditional physics-based simulations. Consequently, AI forecasts often produce blurry estimates or miss the boundaries of severe storms entirely.

To solve this, we train our model on two exceptionally high-quality sources of precipitation data: NASA’s satellite-based Integrated Multi-satellite Retrievals for GPM (IMERG) and our own global precipitation reanalysis based on satellite radar.

The result is a significant leap in precipitation forecasting accuracy. In medium-range global forecasts, evaluations against baselines show a Continuous Ranked Probability Score (CRPS) improvement of up to 60% against IMERG, 30% for MRMS, and 10% against rain gauge measurements for early lead times.

Shape
Shape
Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy,  bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Shape

IBM aims to simplify mainframe modernization with AI-powered insight

“IBM Z Atlas’ system intelligence is built on a foundation of automated discovery, topology modeling, dependency analysis, natural-language interactions, and AI-powered workflows to create impact assessments and change evidence. Together, these capabilities are intended to create a continuously updated understanding of the IBM Z environment and the relationships between its

Read More »

NaaS hasn’t lived up to the hype. Is it still worth it?

Meter, for example, offers LAN hardware such as switches, firewalls, wireless access points, and power distribution units, security tools,  as well as services such as network design, configuration and installation, and management. It connects to outside providers for Internet and cellular connectivity and with Lumen for integrated WAN connectivity. Chief

Read More »

Chevron preps for big 2027 exploration capex ramp

Chevron Corp., Houston, could increase its exploration capital budget by more than $500 million in 2027 as executives look to capitalize on strong commodity markets and build on an organizational shuffle that has centralized and accelerated decision-making. Speaking after Chevron reported its third-quarter results, vice-chairman Mark Nelson told analysts that

Read More »

ADIPEC 2026: ADNOC takes FID on Ruwais Diyab unconventional gas development

Abu Dhabi National Oil Co. (ADNOC) has taken final investment decision (FID) on its Ruwais Diyab unconventional gas development in Abu Dhabi. The company made this announcement at Abu Dhabi International Petroleum Exhibition and Conference (ADIPEC), underway now, and described the project as “advancing its integrated global gas growth strategy and unlocking a new source of reliable energy for the domestic and international markets.” Ruwais Diyab will deliver 345 MMscfd of raw gas from 2029 over a 25-year span, with the potential to reach up to 1 bscfd, ADNOC said. Gas will be processed on site and connected to the UAE’s gas network through new pipeline infrastructure, strengthening domestic supply and supporting the company’s LNG export plans. FID followed technical studies, field testing, and subsurface analysis, delivered by ADNOC Onshore under a design-build-operate model, to reduce development risk. ADNOC’s 9.6-million tonne/year Ruwais LNG project will be the region’s first all-electric plant, with commercial production expected by second-half 2028. The plant will more than double ADNOC Gas PLC’s LNG production. The company earlier this year took FID on Phases 2 and 3 of its rich-gas development project and let an engineering, procurement, and construction contract to Maire SPA subsidiary Tecnimont SPA, describing the project as its largest-ever gas processing expansion. The UAE holds the seventh-largest gas reserves in the world, according to ADNOC, with 298 tscf of conventional gas and 160 tscf of unconventional gas resources.

Read More »

San Mateo to expand Delaware basin gas processing capacity under new producer agreements

Subject to permitting, procurement, and construction activities, the Marlan expansion is targeted for completion by yearend 2028. The company said the project will increase its expected 2026 midstream capital expenditures by about $25 million, raising its estimated midstream capital budget for the year to $170-190 million. Commercial agreements The agreements consist of a new long-term fixed-fee gas gathering and processing contract and an extension of an existing gas gathering and processing agreement. Under the new agreement, San Mateo will gather and treat natural gas from newly dedicated acreage in Lea and Eddy Counties, NM, and process the volumes at the Marlan complex. The agreement includes a large-scale acreage dedication in the northern Delaware basin. Separately, San Mateo amended an existing gas gathering and processing agreement covering production from Eddy County. Under the extension, gas will continue to be gathered, treated, and processed at the Black River gas processing plant in Eddy County for several years beyond the original contract term. The extension builds on a gas gathering and processing agreement San Mateo announced in October 2018, the company noted. Upon completion of the Marlan expansion, San Mateo’s total natural gas processing capacity will exceed 1.3 bcfd, nearly tripling the 460-MMcfd capacity it had before Matador contributed Pronto Midstream LLC to the venture in December 2024.

Read More »

ADIPEC 2026: TotalEnergies to acquire operated interest in gas fields offshore Malaysia

TotalEnergies has agreed to acquire an operated stake in the SK410B Lang Lebah and B14 fields off the coast of Sarawak, offshore East Malaysia, through a series of farm-out agreements. The agreements, signed with Petronas Carigali Sdn Bhd (PCSB), PTTEP, and KUFPEC, will give TotalEnergies a 30% operated interest in Lang Lebah, one of Malaysia’s largest offshore gas discoveries, and the nearby B14 field. An integrated development plan is expected to unlock more than 6.5 tcf of gas resources to supply the existing Malaysia LNG liquefaction plant with a production plateau of around 10 billion cu m/year, the company said. “The development of Lang Lebah and B14 resources will allow the creation of another large-scale gas hub in Malaysia, leveraging shared infrastructure, to supply gas to Malaysia LNG and meet the growing LNG demand in Asia,” and follow previous deals in the country with SapuraOMV in 2024 and Petronas in 2025, said Patrick Pouyanné, chairman and chief executive officer of TotalEnergies.  Upon completion of the transactions, which are subject to regulatory approvals, TotalEnergies will hold a 30% operated interest in both fields, alongside PTTEP (25%), KUFPEC (25%) and PCSB (20%). The parties commemorated the agreements during a signing ceremony Nov. 1, 2026, in conjunction with Abu Dhabi International Petroleum Exhibition and Conference (ADIPEC) under way in Abu Dhabi, UAE.

Read More »

Utilities need to become project developers. Are they ready?

Load growth is no longer an abstract number in an electricity market report or forecast; it’s a reality. According to the U.S. Energy Information Administration (EIA), U.S. electricity load will increase nearly 2 percent in 2026 and 2.5 percent next year, driven by large loads like data centers and manufacturing as well as increased electrification of transportation and building heating and cooling. To put that number in perspective, annual load growth between 2005 and 2019 was about 0.1 percent, meaning the next two years will see nearly 50 times the growth that the industry experienced in the last 15 years. Rapid load growth changes nearly everything for utilities, from how they plan and invest to how they engage and communicate with customers. Load growth is also compelling many utilities to do something they haven’t done at this scale and pace before: develop their own generation. “Utilities are used to designing and building a gas plant once every five or 10 years, and then they would contract via PPAs (power purchase agreement) everything else,” said Alex Pope, Manager of Power Development Portfolios 1898 & Co. “But the systems utilities have in place to self-develop generation projects were never built to handle the volume necessary to meet the demand and timelines of today’s customer needs.” Building from scratch is hard As PPAs and BTAs (Build-Transfer Agreement) alone become insufficient to close the generation and load gap, many utilities that recognize the need to build more projects themselves face an important question: how do we start? One avenue is to focus inward and develop the internal expertise and resources needed to move projects from concept to commercialization—everything from land acquisition and permitting to financing, regulatory approvals, procurement strategies, and construction. While this approach gives utilities complete control over the development of new generation,

Read More »

Rethinking the outage map for a multi-hazard world

For many, fall means sweater weather and all things pumpkin spice. For utilities, these months have other, less festive sides. Hurricane season, wildfire season and the start of the heating season all converge in the same 8-12-week window.   Hurricane season may be quieter this year, thanks to El Niño, but data shows climate change hasintensified Atlantic hurricanes. Meanwhile, fall is peak wildfire season, particularly in California, when Santa Ana winds kick up. And the northern half of the country is switching furnaces back on after months of inactivity. Individually, these are known risks utilities plan for. Layered together, they’re a bigger threat.  Because of this, utilities are starting to ask more of their outage maps, moving beyond “when will my power be back on?” to “what’s happening around me?” Maps are becoming less of a status tracker and more of a situational awareness tool.  The outage map levels up  For decades, utility outage maps told customers when their power would be back on, along with repair status and outage cause. That’s still valuable, but outages aren’t the only thing causing sleepless nights. Hazards now stack and planned maintenance often lands in the same week and region as storms, wildfires and seasonal gas-related risk.   Historically, customers pieced this information together from disconnected sources like text alerts, county web pages, weather apps and wildfire trackers. Now, hazard layers bring it together in one place, drawing on GIS, OMS and weather feeds.   This shift isn’t just about the growing frequency and overlap of hazards. It also reflects rising customer expectations for self-service, with the map as their first stop before the call center.  Self-service isn’t optional in a crisis  During a crisis, utility customers want access to whichever channel responds fastest and most clearly. If the utility’s map can’t deliver, their next stop

Read More »

DOE’s Office of Critical Minerals and Energy Innovation Launches PROSPECT Implementation Prize To Expand America’s Mining and Critical Minerals Workforce

WASHINGTON—The U.S. Department of Energy’s (DOE) Office of Critical Minerals and Energy Innovation today launched the PROSPECT Implementation Prize, which will award up to $70 million to support universities in expanding the skilled workforce required to domestically produce, process, recover, and recycle critical minerals. This prize competition is part of DOE’s broader up to $100 million Providing Opportunities for Specialized Education in Critical Technologies (PROSPECT) initiative, which delivers on President Trump’s bold agenda to restore American energy dominance, secure long term economic growth, rebuild domestic supply chains, and reduce reliance on foreign adversaries for critical minerals. “DOE has laid the groundwork for growing America’s critical minerals workforce—and now we’re turning those plans into reality. Universities are taking the necessary steps to deliver measurable results, from expanding student support through scholarships to modernizing curricula with new training modules, certificates, and Super Intelligence,” said Assistant Secretary of Energy Audrey Robertson. “The Trump Administration is committed to freeing America from dependence on foreign sources of critical minerals that are essential to powering our economy, and creating good-paying, fulfilling jobs for Americans.” PROSPECT has established a near-term goal of doubling the number of graduates with mining, minerals, and associated supply chain credentials within two years. The PROSPECT Implementation Prize follows the recently completed PROSPECT Planning Prize, which awarded funding to universities for developing comprehensive workforce-expansion plans. The Implementation Prize focuses on putting workforce development programs into action and demonstrating measurable results. The U.S. faces a growing shortage of skilled mining and critical minerals professionals, with an estimated 6,000 new mining engineers needed over the next decade. Expanding America’s talent pipeline is essential to strengthening domestic supply chains and reducing reliance on foreign nations for critical materials. Mining and geological engineering careers offer strong earning potential, with a median annual wage of $106,220 in 2025.

Read More »

OCP 2026: Cooler Master Scales Liquid Cooling from Cold Plates to 2.5 MW CDUs

Modular Air-Assisted Cooling Targets Existing Data Centers One of the most instructive systems examined during the tour was Cooler Master’s 300 kW Air-Assisted Liquid Cooling (AALC) CDU, a modular liquid-to-air design intended for data centers without an existing facility water distribution system. Rather than transferring server heat into a building’s chilled-water or facility-water loop, the AALC system circulates coolant through the IT equipment and rejects the captured heat through fan-driven radiators. The distinction matters for operators seeking to introduce liquid-cooled AI racks into facilities that were not built with dedicated liquid cooling infrastructure. Although air-assisted systems still require sufficient facility airflow and heat rejection capacity, they offer an alternative to extending a new water distribution network throughout the data hall. The approach is already finding applications in the field. As DCF recently reported, Corvex deployed liquid-cooled NVIDIA Blackwell infrastructure inside an existing air-cooled data center, using Lenovo Neptune technology to avoid a conventional facility-wide liquid cooling conversion. Cooler Master’s 300 kW design separates the pumping equipment from its radiator assemblies. During the tour, a company representative explained that the system can be configured with a central pump rack and either one or two radiator racks, each providing a nominal 150 kW of cooling capacity. This modular arrangement allows cooling capacity to be matched more closely to the installation, rather than requiring every deployment to use the full 300 kW configuration. Serviceability is a major feature of the design. The system uses redundant pumps in a 2+1 arrangement, with two pumps supporting normal operation and a third providing standby capacity. Pump modules are designed for replacement without interrupting cooling operations. Other field-replaceable components include fans, filters, expansion tanks, and power-related assemblies. The product also incorporates redundant filtration and monitoring capabilities intended to help operators identify faults and maintain cooling performance. The

Read More »

7×24 Fall 2026: AI Frontier Futurist Meets Data Center OG

A 1988 Data Center Becomes a 20 MW AI Asset The second presentation, Converting a 1990 Enterprise Data Center to 20MW AI Workloads, featured Coe alongside Ari Chernikoff, vice president of development at Legacy Investing, and Dan Amundson, project manager at Gardner Builders. The project centered on 1001 Third Avenue South in downtown Minneapolis, a financial-services computing facility originally constructed in 1988. The building had supported earlier generations of enterprise computing before portions were converted to commercial office space and smaller colocation operations. Although its remaining operating data center load had declined to approximately 500 kilowatts by the time the AI redevelopment began, the property retained substantial infrastructure inherited from its original mission-critical design. Tall ceilings, robust floor loading, raised access floors, existing medium-voltage substations, and established utility connections made the building an unusually strong candidate for conversion. These characteristics, Chernikoff explained, can determine whether an existing building offers a practical path to high-density computing or proves economically unsuitable for redevelopment. Legacy Investing had identified a market opportunity in what Chernikoff called the industry’s “missing middle”: facilities generally ranging from 20 MW to 80 MW, rather than the 100 MW-plus campuses increasingly associated with hyperscale and frontier AI development. The company viewed existing buildings with available power and favorable infrastructure characteristics as potential shortcuts to deployment, particularly where demand for AI inference and other latency-sensitive workloads favored proximity to major urban markets. Following an AI tenant commitment in summer 2024, the development team faced an aggressive initial requirement: Deliver the first 5 MW of capacity by the end of that year. The first phase was ready for service approximately four months after Gardner’s involvement became formalized, followed by another 5 MW in 2025 and an expansion program ultimately reaching 20 MW over roughly 20 months. All of this had to

Read More »

Gartner warns $3.5T in AI infrastructure spending could be at risk by 2030

Musk predicted that more than 200 neocloud companies could face significant financial distress, predicting that only a small number would survive the coming shakeout. He also said SpaceX would not acquire any of the companies, describing such purchases as “pointless.” The chickens are already coming home to roost on the neoclouds. CoreWeave, Nebius, Applied Digital and TeraWulf have reported quarterly losses over the past year, while IREN has failed to turn a profit in its past three quarters. Shares of CoreWeave, Nebius and IREN have fallen more than 30% during October, according to Reuters. Building AI data centers requires substantial upfront investment in GPUs, networking equipment, power systems, cooling infrastructure and facilities. Operators must then generate enough revenue from leasing computing capacity to cover operating expenses, interest payments and equipment replacement.

Read More »

The 50-Gigawatt Test: SemiAnalysis Sees a Historic Data Center Surge in 2027

The global data center industry is approaching a potentially historic test of its ability to turn artificial intelligence investment into operational infrastructure. In a provocative new forecast, semiconductor and AI infrastructure research firm SemiAnalysis predicts that approximately 51.2 gigawatts of net data center IT capacity will be added globally, excluding China, during 2027. That would represent more than double the 25 GW the firm expects to be added in 2026. Published October 19, the report, Datacenters 2027: The Year of Acceleration, +50GW in a Single Year, makes a forceful argument that much of this unprecedented expansion is already visible in the industry’s construction pipeline. Authored by Jeremie Eliahou Ontiveros, Reyk Knuhtsen and Dylan Patel, the analysis draws on SemiAnalysis’ proprietary tracking of construction starts, individual buildings, hyperscale leasing commitments, equipment procurement and project financing. Its researchers identify more than 60 GW of data center capacity under construction. Among the 40 largest campuses they examined, more than 24 GW is reportedly in advanced stages of development, with much of that capacity expected to be delivered in 2027. The forecast is not entirely composed of projects already under construction, however. SemiAnalysis’ capacity chart includes approximately 11.9 GW of 2027 additions associated with projects still classified as planned. The remainder is associated with facilities already operating or under construction, according to the model’s building-status categories. SemiAnalysis argues that the volume and maturity of projects already underway make a dramatic acceleration increasingly likely, despite well-documented constraints involving electricity, construction labor, equipment and capital. But the prediction has also become the subject of a revealing industry debate, with competing forecasts and new corporate disclosures raising questions about how much infrastructure can actually be delivered on schedule. The disagreement is no longer principally about whether AI infrastructure demand is real. It is about whether the industrial

Read More »

HPE’s Quantum Computing Bet: A Multi-Vendor Path to the Data Center

QuEra Deal Targets On-Premises Quantum Integration Under the expanded collaboration, HPE and QuEra intend to develop integrated testbeds, software interoperability, hybrid algorithms and performance benchmarks to support future quantum deployments alongside HPE Cray supercomputing infrastructure. The work is intended to address the practical requirements of coordinating quantum processors with the classical computing systems that prepare workloads, process results and support quantum error correction. QuEra Chief Commercial Officer Yuval Boger, who previously discussed the development of hybrid quantum-classical infrastructure on the DCF Show, emphasized that integrating quantum hardware into an HPC environment presents different engineering challenges than providing access through the cloud. Boger said, “HPE’s deep experience in supercomputing gives organizations the benefit of working with a partner who can solve that problem at the scale they need.” The collaboration envisions deploying future fault-tolerant quantum hardware at customer facilities rather than requiring organizations to rely exclusively on cloud-based quantum computing services. That option could appeal to national laboratories, defense organizations, pharmaceutical researchers and other institutions managing classified information, proprietary intellectual property or data subject to sovereignty requirements. QuEra’s neutral-atom architecture uses individual atoms as qubits, manipulating them with lasers and electromagnetic controls. Unlike superconducting quantum processors, which generally require dilution refrigerators operating at temperatures measured in millikelvin, neutral-atom systems can operate without extreme cryogenic refrigeration. They still require specialized laser systems, vacuum equipment, precision optics and environmental controls, presenting facility requirements substantially different from those of conventional servers. On-premises quantum-HPC integration is already being tested. In Japan, the National Institute of Advanced Industrial Science and Technology (AIST) operates QuEra’s 260-physical-qubit Gemini neutral-atom computer as part of its ABCI-Q research platform, which also incorporates an NVIDIA H100-based AI supercomputer. An October 26 case study published by QuEra describes Gemini operating in a separate building approximately 350 meters from the main GPU installation,

Read More »

At 7×24 Exchange, AI Data Center Growth Confronts New Realities of Power, Grid Reliability and Community Trust

DC BLOX: Community Engagement Must Go Beyond Public Relations The afternoon program shifted attention from electrical infrastructure to the growing challenges surrounding data center development and community acceptance. In a discussion moderated by Juli Ierulli, strategic account manager at Environmental Air Systems and vice president of 7×24 Exchange International, Michael Clark, senior vice president of data center construction at DC BLOX, described how the company has revised its approach to engaging communities as it expands into new markets. Clark acknowledged that DC BLOX had encountered significant opposition after entering markets where it lacked the established relationships that had supported earlier developments across the Southeast. “We made multiple stumbles in some of those new markets,” he said, describing how the company sometimes found itself responding to negative publicity rather than presenting a clear explanation of its plans and commitments. The experience led DC BLOX to develop a more systematic approach to community engagement, emphasizing early communication, site-specific websites, accessible explanations of resource consumption and written commitments that residents and officials can evaluate. Clark also pointed to what he called the industry’s “NDA hangover,” reflecting years of development activity conducted under confidentiality agreements that frequently left neighboring communities unaware of what was being planned. But perhaps the most revealing moment came when Clark recounted a conversation with residents near a DC BLOX development in Rockdale County, Georgia. After the company outlined the countywide economic and community benefits expected from the project, one neighbor challenged the distribution of those benefits. “So the rest of the county gets the benefit and we have to pay all the costs,” the resident observed, according to Clark. The question captured a fundamental tension in the industry’s community engagement efforts: tax revenues and economic development benefits may extend across a county, while nearby residents experience the immediate effects

Read More »

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.

Read More »

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

Read More »

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

Read More »

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

Read More »