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Miner HPC Mullets Keep Growing + BTC-Backed Financing IS BACK!!!

W42 ’24 | 10.14-10.20.24 | Issue CII | Block Height 866575 Welcome to the latest issue of the Vibe Check, your weekly source at the intersection of Bitcoin, Energy, and Bitcoin Mining. Grab a ☕ and start the week with all the metrics and stories that shake and bake the Bitcoin Mining industry. Subscribe and […]

W42 ’24 | 10.14-10.20.24 | Issue CII | Block Height 866575

Welcome to the latest issue of the Vibe Check, your weekly source at the intersection of Bitcoin, Energy, and Bitcoin Mining.

Grab a ☕ and start the week with all the metrics and stories that shake and bake the Bitcoin Mining industry.

Subscribe and share with your friends, colleagues, and family!


W42 ‘24 Vibe Check

  • The Overview Vibe

  • Weekly Industry Metrics

  • Headlines & News

  • The Media Vibe

  • Energy Corner

  • The Meme Vibe


The Overview Vibe

Bitcoin said WE UP as it rose steadily, tagging ~$69K. Hashprice tracked BTC price during the inter-epoch week, popping over $50/PH/Day mid-week thanks to a spike in transaction fees. Hashrate did a u-turn back towards ~680 EH/s as a lagged response to ASICs energizing with the upward lift from hashprice. Might we see economically marginal ASICs contribute to EOY network hashrate growth if BTC goes on a run?

The pureplay and mullet miners continue to diverge in strategy and operations this week. Cipher Mining tripled down on their ERCOT greenfield pipeline with their 3-site – 1.5 GW option agreement with Juvo Energy. While not immediately available, it compounds fundamental land+power value that can be monetized with BTC or HPC.

In an effort to integrate vertically their HPC business, Bit Digital acquired a Canadian tier 3 data center company for $46M. With an HPC pipeline of over 200 MW and no plans for BTC infrastructure ownership, Bit Digital sharpens up the back of its mullet towards AI. Silicon Valley’s bet in the space Crusoe Energy entered in a YUGE $3.4B JV agreement with Blue Owl Capital and Prime Digital Infrastructure to fund 200+ MW of HPC infrastructure at the Lancium Energy Campus in Abilene, Texas. It is rumored that the JV’s 100,000+ GPUs will be leveraged by OpenAI as the end customer.

On the other side of the market, MARA is bringing back Bitcoin-backed loans with their announced $200M credit line collateralized by ~4000 BTC. While there are not many details about the arrangement, it does add to MARA’s push to build a $$$ war chest of BTC and USD on their balance sheet. OG Bitcoin tech and mining services company Blockstream raised $210M to go hard in the paint on L2s and buy Bitcoin. It seems like raising capital to pick up sats is a growing preference across both private and public capital markets.

I’ll be drowning in my Longhorn tears after the loss to Georiga yesterday…SAD! lol! I hope everyone had a great weekend. Remember to call your mom, stay hydrated, and SHARE THIS ISSUE WITH ALL YOUR FRIENDS AND COLLEGUES!


Bitcoin/Mining Metrics

  • BTC price2: ~$68,490.00 @ EOW. +9.19% WOW.

  • Hash price1: $47.9 PH/Day @ EOW. +5.14% WOW.

  • Network Hashrate (SMA 7 Day)1: ~689 EH/s @ EOW. +1.17% WOW. 

  • Difficulty1: 92.05 T @ EOW. 0.00% WOW.

  • ASIC Retail Price (s19/m30 family)1: $4.24/TH/s @ EOW. +42.76% WOW.

Sources: Hashrate Index1, Bitbo2

Weekly Hashprice – Block Height 866575 – Hashrate Index

Weekly Hashrate – Block Height 866575 – Hashrate Index

Mempool Stats – Block Height 866575 – mempool.space

Mining Stats – Block Height 866575 – mempool.space

Headlines & News

Featured

  • Crusoe, Blue Owl Capital and Primary Digital Infrastructure Enter $3.4 billion Joint Venture for AI Data Center Development – Press Release.

  • Bit Digital, Inc. Vertically Integrates, Acquiring Tier 3 HPC Datacenter Company; 280+ MW Pipeline in Major Metropolitan Areas – Press Release.

  • Bitcoin miner MARA warns AI mirrors 2000s internet boom, firms risk overbuilding infrastructure: Bernstein – The Block.

  • Energy-hungry cryptocurrency mining is growing in Iowa. Will it help or hurt the state? – Des Moines Registerr.

General PubCo Updates

Capital Markets & M&A

  • Cathedra Bitcoin Announces Cancellation of Previously Announced Non-Brokered Offering – Press Release.

  • Blockstream Secures $210M Led by Fulgur Ventures to Drive Layer-2 Growth and Expand Bitcoin Treasury – Press Release.

  • MARA Secures $200M Credit Line with Bitcoin Collateral – TheMinerMag.

Regulatory/Legal Updates

  • OG Miner Sues Local Council to Retrieve 8,000 Bitcoin Buried in Landfill – TheMinerMag.

Research/Reports/Newsletters


The Media Vibe


The Energy Corner


The Meme Vibe


Subscribe and keep your eye out for the development of the Vibe Check throughout 2024!

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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.

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IBM expands professional services for Cisco firewalls

With the expanded Cisco partnership, IBM TLS can now support the lifecycle of these Cisco firewalls, whether physical, cloud or virtual, by planning, designing, purchasing, installing, de-installing, and supporting them, helping clients to optimize their core or AI infrastructure, according to Atul Dhall, vice president of product management and global

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Nvidia looks to power AI factory networks

Nvidia also introduced BlueField 4, a next-generation processor that acts as the operating system for AI factories. It delivers 800Gbit/sec of throughput, double the throughput of its predecessor BlueField 3, and six times more compute than BlueField 3. BlueField 4 combines Arm-based CPUs with the ConnectX-9 SuperNIC to accelerate storage,

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Noble Quarterly Revenue Falls

Noble Corp on Monday reported $798 million in revenue for the third quarter, down from $849 million for the prior three-month period as lower rig utilization offset lower contract drilling services costs. “Utilization of the 35 marketed rigs was 65 percent in the third quarter of 2025 compared to 73

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Google Cloud targets enterprise AI builders with upgraded Vertex AI Training

Enterprises can quickly set up managed Slurm environments with automated resiliency and cost optimization through the Dynamic Workload Scheduler. The platform also includes hyperparameter tuning, data optimization, and built-in recipes with frameworks like NVIDIA NeMo to streamline model development. Enterprises weigh AI training gains Building and scaling generative AI models

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USA Upstream Mergers and Acquisitions Slump

After a hot start to the year, U.S. upstream mergers and acquisitions slid into a slump in the third quarter, with deal value dropping to $9.7 billion, marking the third straight quarterly decline. That’s what Enverus Intelligence Research (EIR), a subsidiary of Enverus, said in a statement sent to Rigzone recently, adding that “persistently low crude prices have kept many buyers on the bench, particularly for oil-weighted private equity-backed oil and gas exits that fueled much of the activity in the recent past”. A table included in the statement highlighted that the top five U.S. upstream deals of the third quarter comprised a deal between Crescent Energy and Vital Energy for $3.049 billion, a deal between Stone Ridge Holdings and ConocoPhillips for $1.3 billion, a deal between Mach Natural Resources and IKAV for $787 million, a deal between California Resources and Berry Corp for $717 million, and a deal between Diversified Energy and Canvas Energy for $550 million. Andrew Dittmar, principal analyst at EIR, noted in the statement that “crude prices in the mid-$60s or worse have made it tough for sellers” and said “most remaining shale M&A opportunities need stronger pricing to justify public companies paying for the undeveloped locations”. Only about 1,800 shale locations held by private equity can deliver a 10 percent return at $50 per barrel West Texas Intermediate, according to Dittmar, who added that 6,700 require higher prices to hit that benchmark. “Many firms are holding off on exits, anticipating a more favorable market in 2027 or later,” he noted. EIR went on to highlight in the statement that the quarter “wasn’t a complete shutout”. “SMID-cap corporate combinations and gas-weighted deals provided some action,” EIR said. “Notable transactions include Crescent Energy’s (CRGY) acquisition of Vital Energy (VTLE) for more than $3 billion in stock and

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Oil Giants Join OPEC in Boosting Output

The world’s biggest oil companies are expected to press ahead with plans to accelerate production growth when they report earnings this week, despite weak crude prices and higher supplies from OPEC and its allies.  Exxon Mobil Corp., Chevron Corp., Shell Plc, BP Plc and TotalEnergies SE will likely grow output 3.9% this year and 4.7% in 2026, according to analysts’ estimates compiled by Bloomberg. The increases — which include new projects as well as acquisitions — appear designed to capitalize on an expected oil-price upturn in the latter half of next year.  But they could add to the supply glut in the short term. “They’re taking the long view that oil demand is going to be a lot more resilient post-2030,” Noah Barrett, a research analyst at Janus Henderson, which manages about $457 billion. “If they’re not making the investments today, then their portfolios will be really disadvantaged when prices move higher.” After years of outsized profits as oil demand roared back following the pandemic, the world’s largest energy companies are feeling the pinch of crude prices that have dropped about 14% this year near to a four-year low. In response, they’re cutting jobs, reducing low-carbon investments and trimming share buybacks to channel funds toward the most valuable part of their business: oil and gas production. “All the supply coming to the market is shrinking OPEC’s spare capacity — so there’s a light at end of the tunnel, Betty Jiang, an analyst at Barclays Plc. “Whether that’s second half of 2026 or 2027, the balance is going to tighten. It’s just a matter of when.” Recent US sanctions on key Russian giants Rosneft PJSC and Lukoil PJSC provided respite from oil’s fall this year, with Brent crude rising 7.5% last week to more than $65 a barrel. But the oil market is

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Tokyo Gas to Lift Dividend 40 Pct by Fiscal 2028 Under New Plan

Japan’s top utility gas provider Tokyo Gas Co. plans to boost its dividend by the fiscal year that ends March 2029 as part of a wider strategy to deliver 200 billion yen ($1.3 billion) in shareholder returns.  The company on Wednesday announced a new midterm management plan spanning fiscal years 2026 and 2028, with the goal for dividends to reach 140 yen ($0.92) per share by the end of the period. That compares with its 100 yen dividend for the current fiscal year. Tokyo Gas shares briefly jumped after the announcement, rising as much as 7%, before reversing those gains gains to trade 0.8% lower at 2:30 p.m. in Tokyo. The company also said it plans to invest as much as 1.3 trillion yen by the end of fiscal year 2028, including 350 billion yen overseas. The move comes as Tokyo Gas is under pressure to improve capital efficiency, after activist Elliott Investment Management disclosed last year that it acquired a 5% stake in the firm. Bloomberg reported in August that Tokyo Gas decided to sell a commercial building in Ginza as shareholders push the company to unload assets that aren’t essential for its core business. In total, Tokyo Gas said it plans 200 billion yen of total shareholder returns over the three-year period. Tokyo Gas also announced earnings for the second quarter, and boosted its fiscal year guidance. The company increased its annual operating income forecast by 4.4% to 166 billion yen, and dividend to 100 yen a share versus 80 yen in prior guidance. WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed.

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Macquarie Strategists Forecast USA Crude Stock Drop

In an oil and gas report sent to Rigzone by the Macquarie team late Monday, Macquarie strategists, including Walt Chancellor, revealed that they are forecasting that U.S. crude inventories will be down by 2.4 million barrels for the week ending October 24. “This follows a 1.0 million barrel draw in the prior week, with the crude balance realizing modestly looser than our expectations,” the strategists said in the report. “For this week’s balance, from refineries, we model a minimal reduction in crude runs. Among net imports, we model a large reduction, with exports higher (+0.7 million barrels per day) and imports lower (-0.2 million barrels per day) on a nominal basis,” they added. “Likewise, timing of cargoes remains a source of potential volatility in this week’s crude balance. From implied domestic supply (prod.+adj.+transfers), we look for a bounce (+0.6 million barrels per day) on a nominal basis this week,” they continued. The strategists went on to state in the report that they “anticipate a smaller increase (+0.5 million barrels) in SPR [Strategic Petroleum Reserve] stocks this week”. Also in the report, the strategists noted that, “among products” they “look for draws in gasoline (-4.2 million barrels) and distillate (-1.3 million barrels), with jet stocks also slightly lower (-0.2 million barrels)”. “We model implied demand for these three products at 14.6 million barrels per day for the week ending October 24,” the strategists added in the report. In its latest weekly petroleum status report at the time of writing, which was released on October 22 and included data for the week ending October 17, the U.S. Energy Information Administration (EIA) highlighted that U.S. commercial crude oil inventories, excluding those in the SPR, decreased by one million barrels from the week ending October 10 to the week ending October 17. In that

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Oil Rally Fades on Oversupply Fears

Oil declined as mounting signs of oversupply quelled a bumper rally triggered by US sanctions on key Russian producers last week. West Texas Intermediate fell 1.9% to again settle close to $60 a barrel, the steepest daily drop in more than two weeks. Investors are better positioned to renew bets now that a looming surplus will push prices down after a massive liquidation of speculative wagers. The amount of oil being shipped across the world’s oceans hit a record high, indicating that excess supplies continue to rise. In addition, OPEC+ may agree to add more production at a meeting this weekend. Last week, US President Donald Trump’s administration imposed sanctions on Russia’s two biggest oil producers — Lukoil and state-controlled Rosneft PJSC — to pressure the Kremlin to end the war in Ukraine. The move spurred the biggest unwinding of crude futures positions on record, with bearish wagers held by hedge funds at an all-time high before the sanctions were announced. The ensuing price spike left cleaner positioning for those looking to bet on a drop. Price swings are also set to be exacerbated by the expiry of tens of thousands of Brent options contracts still held near $65 a barrel. The impact of the sanctions is still unclear, with traders closely following actions taken by Chinese and Indian energy companies, top buyers of Russian crude. “The market is now questioning the actual effectiveness of the sanctions,” said Ole Hvalbye, an analyst at SEB AB. “While a full blacklisting sounds dramatic, the mechanisms for enforcement remain unclear, and so far, there are no signs of disrupted Russian flows.” One Indian refiner plans to seek non-Russian barrels, while others are considering whether they can continue to take some discounted Russian oil cargoes by leaning on small suppliers, instead of Lukoil and

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Eni, Egypt Sign Agreement for Potential Biogas Projects

Eni SpA and Egypt’s Bioenergy Association for Sustainable Development, affiliated with the Environment Ministry, signed Monday an agreement for a feasibility study on biogas production in the North African country using animal and agricultural waste. “The joint study will assess the feasibility of building a biodigestion plant capable of treating agricultural and animal waste, particularly from livestock farming”, Italy’s state-controlled energy major Eni said in a press release. “The biogas produced by biodigestion can generate renewable electricity and heat, while also producing higher-value organic fertilizers for use in agriculture, further contributing to the circular economy. The initiative would also reduce greenhouse gas emissions from agricultural waste and byproducts, while generating high-quality carbon credits.  “The agreement is in line with the Ministry of Environment’s objective to promote the dissemination of biogas technology across Egyptian governorates and to develop innovative and sustainable energy solutions that contribute to emission reduction and sustainable development. “It also fits in Eni’s long-term strategy to achieve carbon neutrality by 2050 through a multi-faceted approach that includes developing integrated solutions to reduce emissions and enhance resource efficiency”. Elsewhere in Africa Eni earlier this year inaugurated its first vegetable oil extraction plant in the Republic of the Congo, unlocking new feedstock capacity for its biorefineries. The facility in Loudima, in the southern part of the Central African country, can produce up to 30,000 million metric tons per annum (MMtpa) of vegetable oil. The plant will use crops grown on “degraded and underutilized land or through intercropping systems, as part of an innovative regenerative agriculture project developed in collaboration with local stakeholders”, Eni said in a statement June 28. On May 28 Eni said it had signed an agreement with Cote d’Ivoire’s Agriculture Ministry to explore the potential of cultivating biofuel crops in the West African country. The memorandum of understanding “aims to enhance the rubber

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IT shortcuts curb AI returns

Organizations must ensure the infrastructure is AI ready Infrastructure is another area where Cisco found a major difference. Pacesetters are designing their networks for future demands. Seventy-one percent say their networks can scale instantly for new AI projects. Roughly three-quarters of pacesetters are investing in new data center capacity over the next year. Currently, about two-thirds say their infrastructure can accommodate AI workloads. Most pacesetters (93%) also have data systems that are fully prepared for AI, compared with 34% of other companies. About 76% have fully centralized their in-house data, while only 19% of other companies have done the same. Eighty-four percent report strong governance readiness, while 95% have mature processes to measure the impact of AI. If ever there was a technological shift that requires the right infrastructure, it’s AI. AI generates a significant amount of data, needs large amounts of processes and low latency, high-capacity networks. Historically, businesses could operate with networks that operated on the premise of “best effort,” but that’s no longer the case. From the data center to campus to branch offices, in most companies, the network will require a refresh. Scaling AI requires the right processes When it comes to being disciplined, 62% of pacesetters have an established process for generating, piloting, and scaling AI use cases. Only 13% of other organizations (non-pacesetters) have reached this level of maturity. Most pacesetters say their AI models achieve at least 75% accuracy. Almost half also expect a 50% to 100% return on investment (ROI) within a year, far above the average. Cisco notes that over the past six months, pressure has been building for companies to show tangible ROI. Executives and IT leaders are pushing for results, and so are competitors. By contrast, most other companies are in early stages of readiness. Although 83% plan to

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Qualcomm goes all-in on inferencing with purpose-built cards and racks

From a strategy perspective, there is a longer term enterprise play here, noted Moor’s Kimball; Humain is Qualcomm’s first customer, and a cloud service provider (CSP) or hyperscaler will likely be customer number two. However, at some point, these rack-scale systems will find their way into the enterprise. “If I were the AI200 product marketing lead, I would be thinking about how I demonstrate this as a viable platform for those enterprise workloads that will be getting ‘agentified’ over the next several years,” said Kimball. It seems a natural step, as Qualcomm saw success with its AI100 accelerator, a strong inference chip, he noted. Right now, Nvidia and AMD dominate the training market, with CUDA and ROCm enjoying a “stickiness” with customers. “If I am a semiconductor giant like Qualcomm that is so good at understanding the performance-power balance, this inference market makes perfect sense to really lean in on,” said Kimball. He also pointed to the company’s plans to re-enter the datacenter CPU space with its Oryon CPU, which is featured in Snapdragon and loosely based on technology it acquired with its $1.4 billion Nuvia acquisition. Ultimately, Qualcomm’s move demonstrates how wide open the inference market is, said Kimball. The company, he noted, has been very good at choosing target markets and has seen success when entering those markets. “That the company would decide to go more ‘in’ on the inference market makes sense,” said Kimball. He added that, from an ROI perspective, inferencing will “dwarf” training in terms of volume and dollars.

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AI data center building boom risks fueling future debt bust, bank warns

However, that’s only one part of the problem. Meeting the power demands of AI data centers will require the energy sector to make large investments. Then there’s data center demand for microprocessors, rare earth elements, and other valuable metals such as copper, which could, in a bust, make data centers the most expensively-assembled unwanted assets in history. “Financial stability consequences of an AI-related asset price fall could arise through multiple channels. If forecasted debt-financed AI infrastructure growth materializes, the potential financial stability consequences of such an event are likely to grow,” warned the BoE blog post. “For companies who depend on the continued demand for massive computational capacity to train and run inference on AI models, an algorithmic breakthrough or other event which challenges that paradigm could cause a significant re-evaluation of asset prices,” it continued. According to Matt Hasan, CEO of AI consultancy aiRESULTS, the underlying problem is the speed with which AI has emerged. “What we’re witnessing isn’t just an incremental expansion, it’s a rush to construct power-hungry, mega-scale data centers,” he told Network World. The dot.com reversal might be the wrong comparison; it dented the NASDAQ and hurt tech investment, but the damage to organizations investing in e-commerce was relatively limited. AI, by contrast, might have wider effects for large enterprises because so many have pinned their business prospects on its potential. “Your reliance on these large providers means you are indirectly exposed to the stability of their debt. If a correction occurs, the fallout can impact the services you rely on,” said Hasan.

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Intel sees supply shortage, will prioritize data center technology

“Capacity constraints, especially on Intel 10 and Intel 7 [Intel’s semiconductor manufacturing process], limited our ability to fully meet demand in Q3 for both data center and client products,” said Zinsner, adding that Intel isn’t about to add capacity to Intel 10 and 7 when it has moved beyond those nodes. “Given the current tight capacity environment, which we expect to persist into 2026, we are working closely with customers to maximize our available output, including adjusting pricing and mix to shift demand towards products where we have supply and they have demand,” said Zinsner. For that reason, Zinzner projects that the fourth quarter will be roughly flat versus the third quarter in terms of revenue. “We expect Intel products up modestly sequentially but below customer demand as we continue to navigate supply environment,” said Zinsner. “We expect CCG to be down modestly and PC AI to be up strongly sequentially as we prioritize wafer capacity for server shipments over entry-level client parts.”

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How to set up an AI data center in 90 days

“Personally, I think that a brownfield is very creative way to deal with what I think is the biggest problem that we’ve got right now, which is time and speed to market,” he said. “On a brownfield, I can go into a building that’s already got power coming into the building. Sometimes they’ve already got chiller plants, like what we’ve got with the building I’m in right now.” Patmos certainly made the most of the liquid facilities in the old printing press building. The facility is built to handle anywhere from 50 to over 140 kilowatts per cabinet, a leap far beyond the 1–2 kW densities typical of legacy data centers. The chips used in the servers are Nvidia’s Grace Blackwell processors, which run extraordinarily hot. To manage this heat load, Patmos employs a multi-loop liquid cooling system. The design separates water sources into distinct, closed loops, each serving a specific function and ensuring that municipal water never directly contacts sensitive IT equipment. “We have five different, completely separated water loops in this building,” said Morgan. “The cooling tower uses city water for evaporation, but that water never mixes with the closed loops serving the data hall. Everything is designed to maximize efficiency and protect the hardware.” The building taps into Kansas City’s district chilled water supply, which is sourced from a nearby utility plant. This provides the primary cooling resource for the facility. Inside the data center, a dedicated loop circulates a specialized glycol-based fluid, filtered to extremely low micron levels and formulated to be electronically safe. Heat exchangers transfer heat from the data hall fluid to the district chilled water, keeping the two fluids separate and preventing corrosion or contamination. Liquid-to-chip and rear-door heat exchangers are used for immediate heat removal.

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INNIO and VoltaGrid: Landmark 2.3 GW Modular Power Deal Signals New Phase for AI Data Centers

Why This Project Marks a Landmark Shift The deployment of 2.3 GW of modular generation represents utility-scale capacity, but what makes it distinct is the delivery model. Instead of a centralized plant, the project uses modular gas-reciprocating “power packs” that can be phased in step with data-hall readiness. This approach allows staged energization and limits the bottlenecks that often stall AI campuses as they outgrow grid timelines or wait in interconnection queues. AI training loads fluctuate sharply, placing exceptional stress on grid stability and voltage quality. The INNIO/VoltaGrid platform was engineered specifically for these GPU-driven dynamics, emphasizing high transient performance (rapid load acceptance) and grid-grade power quality, all without dependence on batteries. Each power pack is also designed for maximum permitting efficiency and sustainability. Compared with diesel generation, modern gas-reciprocating systems materially reduce both criteria pollutants and CO₂ emissions. VoltaGrid markets the configuration as near-zero criteria air emissions and hydrogen-ready, extending allowable runtimes under air permits and making “prime-as-a-service” viable even in constrained or non-attainment markets. 2025: Momentum for Modular Prime Power INNIO has spent 2025 positioning its Jenbacher platform as a next-generation power solution for data centers: combining fast start, high transient performance, and lower emissions compared with diesel. While the 3 MW J620 fast-start lineage dates back to 2019, this year the company sharpened its data center narrative and booked grid stability and peaking projects in markets where rapid data center growth is stressing local grids. This momentum was exemplified by an 80 MW deployment in Indonesia announced earlier in October. The same year saw surging AI-driven demand and INNIO’s growing push into North American data-center markets. Specifications for the 2.3 GW VoltaGrid package highlight the platform’s heat tolerance, efficiency, and transient response, all key attributes for powering modern AI campuses. VoltaGrid’s 2025 Milestones VoltaGrid’s announcements across 2025 reflect

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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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