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New open-source math model Light-R1-32B surpasses equivalent DeepSeek performance with only $1000 in training costs

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A team of researchers has introduced Light-R1-32B, a new open-source AI model optimized for solving advanced math problems, making it available on Hugging Face under a permissive Apache 2.0 license — free for enterprises and researchers […]

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A team of researchers has introduced Light-R1-32B, a new open-source AI model optimized for solving advanced math problems, making it available on Hugging Face under a permissive Apache 2.0 license — free for enterprises and researchers to take, deploy, fine-tune or modify as they wish, even for commercial purposes.

The 32-billion parameter (number of model settings) model surpasses the performance of similarly sized (and even larger) open source models such as DeepSeek-R1-Distill-Llama-70B and DeepSeek-R1-Distill-Qwen-32B on third-party benchmark the American Invitational Mathematics Examination (AIME), which contains 15 math problems designed for extremely advanced students and has an allotted time limit of 3 hours for human users.

Developed by Liang Wen, Fenrui Xiao, Xin He, Yunke Cai, Qi An, Zhenyu Duan, Yimin Du, Junchen Liu, Lifu Tang, Xiaowei Lv, Haosheng Zou, Yongchao Deng, Shousheng Jia, and Xiangzheng Zhang, the model surpasses previous open-source alternatives on competitive math benchmarks.

Incredibly, the researchers completed the model’s training in fewer than six hours on 12 Nvidia H800 GPUs at an estimated total cost of $1,000. This makes Light-R1-32B one of the most accessible and practical approaches for developing high-performing math-specialized AI models. However, it’s important to remember the model was trained on a variant of Alibaba’s open source Qwen 2.5-32B-Instruct, which itself is presumed to have had much higher upfront training costs.

Alongside the model, the team has released its training datasets, training scripts, and evaluation tools, providing a transparent and accessible framework for building math-focused AI models.

The arrival of Light-R1-32B follows other similar efforts from rivals such as Microsoft with its Orca-Math series.

A new math king emerges

Light-R1-32B is designed to tackle complex mathematical reasoning, particularly on the AIME (American Invitational Mathematics Examination) benchmarks.

It was trained from Qwen2.5-32B-Instruct, starting from a model without long-chain-of-thought (COT) reasoning. The team applied curriculum-based supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) to refine its problem-solving capabilities.

When evaluated, Light-R1-32B achieved 76.6 on AIME24 and 64.6 on AIME25, surpassing DeepSeek-R1-Distill-Qwen-32B, which scored 72.6 and 54.9, respectively.

This improvement suggests that the curriculum-based training approach effectively enhances mathematical reasoning, even when training from models that initially lack long COT.

Fair benchmarking

To ensure fair benchmarking, the team decontaminated training data against common reasoning benchmarks, including AIME24/25, MATH-500, and GPQA Diamond, preventing data leakage.

They also implemented difficulty-based response filtering using DeepScaleR-1.5B-Preview, ultimately forming a 76,000-example dataset for the first stage of supervised fine-tuning. A second, more challenging dataset of 3,000 examples further improved performance.

After training, the team merged multiple trained versions of Light-R1-32B, leading to additional gains. Notably, the model maintains strong generalization abilities on scientific reasoning tasks (GPQA), despite being math-specialized.

How enterprises can benefit

Light-R1-32B is released under the Apache License 2.0, a permissive open-source license that allows free use, modification, and commercial deployment without requiring derivative works to be open-sourced. T

his makes it an attractive option for enterprises, AI developers, and software engineers looking to integrate or customize the model for proprietary applications.

The license also includes a royalty-free, worldwide patent grant, reducing legal risks for businesses while discouraging patent disputes. Companies can freely deploy Light-R1-32B in commercial products, maintaining full control over their innovations while benefiting from an open and transparent AI ecosystem.

For CEOs, CTOs, and IT leaders, Apache 2.0 ensures cost efficiency and vendor independence, eliminating licensing fees and restrictive dependencies on proprietary AI solutions. AI developers and engineers gain the flexibility to fine-tune, integrate, and extend the model without limitations, making it ideal for specialized math reasoning, research, and enterprise AI applications. However, as the license provides no warranty or liability coverage, organizations should conduct their own security, compliance, and performance assessments before deploying Light-R1-32B in critical environments.

Transparency in low-cost training and optimization for math problem solving

The researchers emphasize that Light-R1-32B provides a validated, cost-effective way to train strong long-chain-of-thought models in specialized domains.

By sharing their methodology, training data, and code, they aim to lower the cost barriers for high-performance AI development.

Future work includes exploring reinforcement learning (RL) to enhance the model’s reasoning capabilities further.

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SolarWinds buys Squadcast to speed incident response

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Basin Electric urges Congress to support clean energy tax credits

Congress should maintain Inflation Reduction Act clean energy tax credits to provide utilities with certainty about their investment decisions, Todd Brickhouse, CEO and general manager of Basin Electric Power Cooperative, said during a House hearing on Wednesday. “The immediate removal of [the production tax credit] will not allow utilities to plan for and avoid increased costs, and this will also immediately harm ratepayers,” Brickhouse said during a hearing held by the Energy and Commerce Committee’s subcommittee on energy on the challenges of responding to rising demand growth. Basin Electric, a generation and transmission wholesale cooperative based in Bismarck, North Dakota, is building 1,500 MW of solar, partly based on the assumption the capacity would be eligible for PTCs, according to Brickhouse. Congressional Republicans are looking for ways to trim federal spending to pay for their budget plans, potentially including changes to tax credits provisions contained in the Inflation Reduction Act. Rep. Mariannette Miller-Meeks, R-Iowa, said the IRA’s tax credits can help spur the buildout of energy infrastructure to meet growing electric demand.  “Tax incentives like the tech-neutral clean energy credits under [sections] 45Y and 45E, and the 45Q carbon sequestration credit, and the 45X advanced manufacturing credit aim to strengthen American manufacturing capability and reduce the engineering procurement and construction risks that have plagued major energy projects,” Miller-Meeks said. She joined 17 other House Republicans in an Aug. 6 letter to House Speaker Mike Johnson, R-La., supporting the IRA’s tax credits. Those tax credits are “incredibly helpful in ensuring that we can get those projects built and online in a manner that’s affordable for our customers,” said Noel Black, senior vice president of federal regulatory affairs for Southern Co., which owns utilities in the Southeast. Renewable energy can help meet electricity demand, in part because it can be built relatively quickly, according

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USA Crude Oil Inventories Rise WoW

U.S. commercial crude oil inventories, excluding those in the Strategic Petroleum Reserve (SPR), increased by 3.6 million barrels from the week ending February 21 to the week ending February 28, the U.S. Energy Information Administration (EIA) highlighted in its latest weekly petroleum status report. This report was released on March 5 and included data for the week ending February 28. The report showed that crude oil stocks, not including the SPR, stood at 433.8 million barrels on February 28, 430.2 million barrels on February 21, and 448.5 million barrels on March 1, 2024. Crude oil in the SPR stood at 395.3 million barrels on February 28 and February 21, and 361.0 million barrels on March 1, 2024, the report outlined. Total petroleum stocks – including crude oil, total motor gasoline, fuel ethanol, kerosene type jet fuel, distillate fuel oil, residual fuel oil, propane/propylene, and other oils – stood at 1.600 billion barrels on February 28, the report showed. Total petroleum stocks were down 4.6 million barrels week on week and up 16.8 million barrels year on year, the report revealed. “At 433.8 million barrels, U.S. crude oil inventories are about four percent below the five year average for this time of year,” the EIA stated in its latest weekly petroleum status report. “Total motor gasoline inventories decreased by 1.4 million barrels from last week and are one percent above the five year average for this time of year. Finished gasoline inventories increased, while blending components inventories decreased last week,” it added. “Distillate fuel inventories decreased by 1.3 million barrels last week and are about six percent below the five year average for this time of year. Propane/propylene inventories decreased by 2.9 million barrels from last week and are four percent below the five year average for this time of year,”

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Stranded energy assets put UK on course for $141bn loss, says study

The future global economic exposure to fossil fuel assets that could become stranded by the energy transition has doubled in the past five years from $1.4 trillion to $2.28tn by 2040. The UK is expected to be the ninth country globally to experience the heaviest losses per capita from stranded fossil fuel assets, making it more exposed than the US, Italy or France. About $141 billion (£113bn) of that total could be wiped from the UK economy from stranded fossil fuel assets, according to a new study by UK Sustainable Investment and Finance Association (UKSIF) and Transition Risk Exeter (TREX). Oil, gas or coal reserves, together with associated infrastructure and investments, are expected to lose economic viability before their operational lifetimes conclude due to climate policies, technological changes, and shifting market conditions. In a warming scenario between 2.5°C and 2.9°C, climate-intensified natural disasters may lead to $12.5tn in economic losses by 2050, the study predicts. The study estimates that the financial loss from stranded fossil fuel assets alone amounts to about $3,279 per UK adult. They warned that individual savers will shoulder the cost of the UK’s “outsized exposure” to fossil fuels. James Alexander, chief executive of UKSIF, said: “With asset stranding presenting a material risk to the long-term health of the UK economy, including the retirement savings of millions of people, it is clear that a carefully controlled transition away from fossil fuels is both an environmental and a financial imperative. “Too many oil and gas companies are betting on demand that will not materialise in a decarbonising world, and the public are at risk of paying the bill. The surest way to offset the risk of losses posed by stranded assets is to invest in industries that will thrive as fossil fuels decline.” Alexander called on the UK government to demonstrate global climate leadership by

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DOE approves LNG export permit extension for Golden Pass

Dive Brief: The U.S. Department of Energy on Wednesday approved a liquefied natural gas export permit extension for Golden Pass LNG, a project owned by QatarEnergy and ExxonMobil and currently under construction in Sabine Pass, Texas. It is the third LNG-related authorization by DOE since President Trump took office, reversing a Biden administration “pause” on export approvals. Trump has said he wants the U.S. to achieve “energy dominance” and fossil fuel exports are a part of that strategy. Consumer and environmental advocates, however, warn that unrestricted gas exports could raise domestic gas prices by more than 30%, send electricity prices higher and stymie efforts to reduce emissions. Dive Insight: Golden Pass is expected to begin exporting LNG by the end of this year, making it the ninth large-scale export terminal operating in the United States, DOE said. Exporting natural gas “supports American jobs, bolsters our national security and strengthens America’s position as a world energy leader,” Secretary of Energy Chris Wright said in a statement. DOE’s decision follows two February actions: the agency approved an export approval for Commonwealth LNG, and issued an order on rehearing that removed barriers for the use of LNG as “bunkering” fuel used by the ships transporting it. “Golden Pass was the first project approved for exports to non-free trade agreement countries by DOE during the first Trump Administration, and it is gratifying that this project is so close to being able to deliver its first LNG,” Tala Goudarzi, acting principal deputy assistant secretary of the Office of Fossil Energy and Carbon Management, said in a statement. In December, DOE published a study concluding increased exports would contribute to higher electricity and natural gas prices for U.S. consumers, as well as increased greenhouse gas emissions and other costs. Then-Energy Secretary Jennifer Granholm warned that U.S. LNG exports have tripled

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Storegga applies to build Speyside green hydrogen hub

Low-carbon solutions developer Storegga has submitted a planning application for a green hydrogen facility aimed at helping to decarbonise local distilleries. The proposed Speyside hydrogen facility at Ballindalloch, Marypark, will use a 70MW electrolyser and includes plans for associated infrastructure, water supply and a wastewater pipeline. It will use renewable electricity to split water into hydrogen and oxygen through electrolysis, and is scheduled to produce 25 tonnes of green hydrogen per day on average, running 24 hours a day, seven days a week. The company envisions signing a power purchase agreement with a low-carbon power supplier to supply electricity to the site. In addition, the facility will use up to 17,600 cubic feet (500 cubic metres) of water per day for electrolysis. This will come from groundwater boreholes, supplemented with rainwater, which will be stored in detention ponds and storage units. The planning application is now under review by Moray Council, with a decision expected in the coming months. If approved, construction is expected to begin in 2026 with commercial operations starting in 2028. Storegga envisions expanding the facility beyond its initial phase, ultimately deploying about 200MW of electrolytic hydrogen production. While hydrogen would initially be supplied to customers, such as the numerous distilleries in the area, by road haul, the company said it could be supplied through a private pipeline or by blending the hydrogen into an existing gas network at a later date. In addition, it can help reduce carbon emissions within the distilling industry. In 2022, Scottish distilleries produced over 600,000 tonnes of CO₂ in scope 1 and 2 emissions. Storegga Speyside hydrogen opportunity manager Christina Smitton said: “The development of green hydrogen is a vital component of Scotland’s energy transition, and we are thrilled to be leading the charge in bringing this important technology to the

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Alberta to Change Procurement in Retaliation Against Trump

The Canadian province of Alberta is immediately halting purchases of US alcohol and changing its procurement rules to respond to President Donald Trump’s tariffs, while focusing longer-term efforts to export more oil and gas to other markets.  Alberta Premier Danielle Smith said Wednesday that she still doesn’t support taxing or reducing oil and gas exports to the US, but that the province will work on building pipelines to Canada’s coasts to increase shipments to Asia and Europe. The province is home to the world’s third-largest crude reserves and supplies the vast majority of the 4 million barrels a day of oil the US imports from Canada.  Alberta’s resources are “significantly larger and far more accessible than the quickly declining oil and gas reserves located in the United States,” Smith said at a press conference Wednesday. “Whether the US president wishes to admit it or not, the United States not only needs our oil and gas today, they are also going to need it more and more with each passing year.” Canada’s federal and provincial governments have rolled out a series of countermeasures this week in response to Trump’s tariffs, with policies targeting US alcoholic beverages among the common options. Provincial governments in Canada have control over alcohol distribution and in some cases even run retail stores. Ontario and British Columbia have already begun pulling US products off those shelves.  Smith said she’s also pursuing longer-term measures to strengthen Canada’s economic position, including free trade and labor-mobility agreements with other provinces. Premiers of neighboring provinces have also shown some receptiveness in recent weeks to pipeline projects that would allow Canada to export energy to non-US markets, she said.  “There is a real spirit of collaboration among the premiers,” Smith said. Possibilities include a spur line off the Trans Mountain oil pipeline

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AI driving a 165% rise in data center power demand by 2030

Goldman Sachs Research estimates the power usage by the global data center market to be around 55 gigawatts, which breaks down as 54% for cloud computing workloads, 32% for traditional line of business workloads and 14% for AI. By 2027, that number jumps to 84 GW, with AI growing to 27% of the overall market, cloud dropping to 50%, and traditional workloads falling to 23%, Schneider stated. Goldman Sachs Research estimates that there will be around 122 GW of data center capacity online by the end of 2030, and the density of power use in data centers is likely to grow as well, from 162 kilowatts per square foot to 176 KW per square foot in 2027, thanks to AI, Schneider stated.  “Data center supply — specifically the rate at which incremental supply is built — has been constrained over the past 18 months,” Schneider wrote. These constraints have arisen from the inability of utilities to expand transmission capacity because of permitting delays, supply chain bottlenecks, and infrastructure that is both costly and time-intensive to upgrade. The result is that due to power demand from data centers, there will need to be additional utility investment, to the tune of about $720 billion of grid spending through 2030. And then they are subject to the pace of public utilities, which move much slower than hyperscalers. “These transmission projects can take several years to permit, and then several more to build, creating another potential bottleneck for data center growth if the regions are not proactive about this given the lead time,” Schneider wrote.

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Top data storage certifications to sharpen your skills

Organization: Hitachi Vantara Skills acquired: Knowledge of data center infrastructure management tasks automation using Hitachi Ops Center Automator. Price: $100 Exam duration: 60 minutes How to prepare: Knowledge of all storage-related operations from an end-user perspective, including planning, allocating, and managing storage and architecting storage layouts. Read more about Hitachi Vantara’s training and certification options here. Certifications that bundle cloud, networking and storage skills AWS Certified Solutions Architect – Professional The AWS Certified Solutions Architect – Professional certification from leading cloud provider Amazon Web Services (AWS) helps individuals showcase advanced knowledge and skills in optimizing security, cost, and performance, and automating manual processes. The certification is a means for organizations to identify and develop talent with these skills for implementing cloud initiatives, according to AWS. The ideal candidate has the ability to evaluate cloud application requirements, make architectural recommendations for deployment of applications on AWS, and provide expert guidance on architectural design across multiple applications and projects within a complex organization, AWS says. Certified individuals report increased credibility with technical colleagues and customers as a result of earning this certification, it says. Organization: Amazon Web Services Skills acquired: Helps individuals showcase skills in optimizing security, cost, and performance, and automating manual processes Price: $300 Exam duration: 180 minutes How to prepare: The recommended experience prior to taking the exam is two or more years of experience in using AWS services to design and implement cloud solutions Cisco Certified Internetwork Expert (CCIE) Data Center The Cisco CCIE Data Center certification enables individuals to demonstrate advanced skills to plan, design, deploy, operate, and optimize complex data center networks. They will gain comprehensive expertise in orchestrating data center infrastructure, focusing on seamless integration of networking, compute, and storage components. Other skills gained include building scalable, low-latency, high-performance networks that are optimized to support artificial intelligence (AI)

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Netskope expands SASE footprint, bolsters AI and automation

Netskope is expanding its global presence by adding multiple regions to its NewEdge carrier-grade infrastructure, which now includes more than 75 locations to ensure processing remains close to end users. The secure access service edge (SASE) provider also enhanced its digital experience monitoring (DEM) capabilities with AI-powered root-cause analysis and automated network diagnostics. “We are announcing continued expansion of our infrastructure and our continued focus on resilience. I’m a believer that nothing gets adopted if end users don’t have a great experience,” says Netskope CEO Sanjay Beri. “We monitor traffic, we have multiple carriers in every one of our more than 75 regions, and when traffic goes from us to that destination, the path is direct.” Netskope added regions including data centers in Calgary, Helsinki, Lisbon, and Prague as well as expanded existing NewEdge regions including data centers in Bogota, Jeddah, Osaka, and New York City. Each data center offers customers a range of SASE capabilities including cloud firewalls, secure web gateway (SWG), inline cloud access security broker (CASB), zero trust network access (ZTNA), SD-WAN, secure service edge (SSE), and threat protection. The additional locations enable Netskope to provide coverage for more than 220 countries and territories with 200 NewEdge Localization Zones, which deliver a local direct-to-net digital experience for users, the company says.

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Inside the Nuclear Race for Data Center Energy with Aalo Atomics CEO Matt Loszak

The latest episode of the DCF Show podcast delves into one of the most pressing challenges facing the data center industry today: the search for sustainable, high-density power solutions. And how, as hyperscale operators like Google and Meta contend with growing energy demands—and, in some cases, resistance from utilities unwilling or unable to support their expanding footprints—the conversation around nuclear energy has intensified.  Both legacy nuclear providers and innovative startups are racing to secure the future business of data center giants, each bringing unique approaches to the table. Our guest for this podcast episode is Matt Loszak, co-founder and CEO of Aalo Atomics, an Austin-based company that’s taking a fresh approach to nuclear energy. Aalo, which secured a $29.5 million Series A funding round in 2024, stands out in the nuclear sector with its 10-megawatt sodium-cooled reactor design—eliminating the need for water, a critical advantage for siting flexibility. Inspired by the Department of Energy’s MARVEL microreactor, Aalo’s technology benefits from direct expertise, as the company’s CTO was the chief architect behind MARVEL. Beyond reactor design, Aalo’s vision extends to full-scale modular plant production. Instead of just building reactors, the company aims to manufacture entire nuclear plants using prefabricated, LEGO-style components. The fully modular plants, shipped in standard containers, are designed to match the footprint of a data center while requiring no onsite water—features that could make them particularly attractive to hyperscale operators seeking localized, high-density power.  Aalo has already made significant strides, with the Department of Energy identifying land at Idaho National Laboratory (INL) as a potential site for its first nuclear facility. The company is on an accelerated timeline, expecting to complete a non-nuclear prototype within three months and break ground on its first nuclear reactor in about a year—remarkably fast progress for the nuclear industry. In our discussion,

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Does It Matter If Microsoft Is Cancelling AI Data Center Leases?

Strategic Reallocation: Microsoft is a major owner and operator of data centers and might be reallocating resources to in-house infrastructure rather than leased spaces. Supply Chain Delays: TD Cowen noted that Microsoft used power and facility delays as justifications for voiding agreements, a tactic previously employed by Meta. Oversupply Issues: Analysts at TD Cowen speculate that Microsoft may have overestimated AI demand, leading to an excess in capacity. As it is all speculation, it could simply be that the latest information has driven Microsoft to reevaluate demand and move to more closely align projected supply with projected demand. Microsoft has reiterated their commitment to spend $80 billion on AI in the coming year. Reallocating this spending internally or wit a different set of partners remains on the table. And when you put the TD Cowen report that Microsoft has cancelled leases for “a couple hundred megawatts” into context with Microsoft’s overall leased power, which is estimated at around 20 GW, you see that more than 98% of their energy commitment remains unchanged. Investment Markets Might See the Biggest Hits Microsoft’s retreat has had ripple effects on the stock market, particularly among energy and infrastructure companies. European firms like Schneider Electric and Siemens Energy experienced a decline in stock value, indicating fears that major AI companies might scale back energy-intensive data center investments. However, at press time we have not seen any other indicators that this is an issue as despite these concerns about potential AI overcapacity, major tech firms continue to invest heavily in AI infrastructure:         Amazon: Pledged $100 billion towards AI data centers.         Alphabet (Google): Committed $75 billion.         Meta (Facebook): Planning to spend up to $65 billion.         Alibaba: Announced a $53 billion investment over the next three years. If we see a rush of announcements

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Dual Feed: Vantage Data Centers, VoltaGrid, Equinix, Bloom Energy, Constellation, Calpine

Nuclear Giant Constellation Acquires Natural Gas Stalwart Calpine, Creating the Largest U.S. Clean Energy Provider On January 10, 2025, Constellation (Nasdaq: CEG) announced a definitive agreement to acquire Calpine Corp. in a $16.4 billion cash-and-stock transaction, including the assumption of $12.7 billion in net debt.  A landmark transaction, the acquisition positions Constellation as the largest clean energy provider in the United States, significantly enhancing its generation portfolio with natural gas and geothermal assets. With an expanded coast-to-coast footprint, the combined company will provide 60 GW of power, reinforcing grid reliability and offering businesses and consumers a broader array of sustainability solutions. The move strengthens Constellation’s competitive retail electricity presence, serving 2.5 million customers across key U.S. markets, including Texas, California, and the Northeast. “This acquisition will help us better serve our customers across America, from families to businesses and utilities,” said Joe Dominguez, president and CEO of Constellation. “By combining Constellation’s unmatched expertise in zero-emission nuclear energy with Calpine’s industry-leading, low-carbon natural gas and geothermal generation, we can deliver the most comprehensive clean energy portfolio in the industry.” A Strategic Move for the Data Center Industry With skyrocketing demand for AI and cloud services, data centers are under increasing pressure to secure reliable, low-carbon energy sources. The Constellation-Calpine combination is particularly relevant for large-scale hyperscale operators and colocation providers seeking flexible energy solutions.  For the data center industry, this consolidation offers several advantages: Diverse Energy Mix: The integration of nuclear, geothermal, and low-emission natural gas provides data centers with flexible and reliable energy options. Grid Stability: Calpine’s extensive natural gas fleet enhances grid reliability, crucial for data centers operating in high-demand regions. Sustainability Initiatives: The combined entity is well-positioned to invest in clean energy infrastructure, including battery storage and carbon sequestration, aligning with the sustainability goals of hyperscale operators. The

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

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

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

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

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2025 playbook for enterprise AI success, from agents to evals

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

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

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

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