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Nvidia unveils GeForce RTX 50 Series graphics cards with big performance gains

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia launched its much-awaited Nvidia GeForce RTX 50 series graphics processing units (GPUs), based on the Blackwell RTX tech. Jensen Huang, CEO of Nvidia, disclosed the news during his opening keynote speech at CES 2025, the […]

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Nvidia launched its much-awaited Nvidia GeForce RTX 50 series graphics processing units (GPUs), based on the Blackwell RTX tech.

Jensen Huang, CEO of Nvidia, disclosed the news during his opening keynote speech at CES 2025, the big tech trade show in Las Vegas this week.

“Blackwell, the engine of AI, has arrived for PC gamers, developers and creatives,” said Huang. “Fusing AI-driven neural rendering and ray tracing, Blackwell is the most significant computer graphics innovation since we introduced programmable shading 25 years ago.”

The new RTX Blackwell Neural Rendering Architecture comes with about 92 billion transistors. It has 125 Shader Teraflops of performance 380 RT TFLOPS, 4,000 AI TOPS, 1.8 terabytes per second of memory bandwidth, G7 memory (from Micron) and an AI-management processor. The top SKU has basically over 3,352 trillion AI operations per second (TOPS) of computing power.

“The programmable shader is also able to carry neural networks,” Huang said.

A neural face rendering.

Among the new technologies in this generation are RTX Neural Shaders, DLSS 4, RTX Neural Face rendering to create more realistic human faces, RTX Mega Geometry for rendering environments, and Reflex 2.

The DLSS 4 now can generate multiple frames at once thanks to advanced AI technology. That makes for much better frame rates.

Nvidia showed that one scene could be rendered at 27 frames per second with the DLSS turned off, with a 71 millisecond PC latency. DLSS 2 can do that scene with its super resolution tech at 71 FPS and PC latency of 34 milliseconds. DLSS 3.5 can do the scene at 140 FPS and 33 milliseconds. But DLSS 4 comes in at a whopping 247 FPS and 34 milliseconds. DLSS 4 is more than eight times better performance than systems that aren’t using AI for the predictive processing.

Nvidia’s SKUs include the GeForce RTX 50 Series Desktop Family. It includes the top of the line GPU, the GeForce RTX 5090 coming in at 3,404 AI TOPS and 32GB of G7 memory for $1,999. It also includes the GeForce RTX 5080 at 1,800 AI TOPS and 16GB of G7 memory for $999. The GeForce RTX 5070 Ti (the performance of a 4090) has 1,406 AI TOPS, 16GB of G7 memory for $749 and the GeForce RTX 5070 has 1117 AI TOPS, 12GB of G7 and costs $549.

Nvidia also said the GeForce RTX 50 Series will come to laptops with two times efficiency with more performance at half the power compared to the previous generation. It has 40% more battery life with Black Max-Q, two times larger generative AI models, and it is as thin as 14.9 millimeters in terms of laptop thickness.

As far as pricing goes, the laptops will come as follows: RTX 5090 at 1,824 AI TOPS and 24GB at $2,899. The RTX 5080 laptops will be at 1,334 AI TOPS, 16GB and $2,199. The RTX 5070 Ti will be 992 AI TOPS, 12GB and $1,599 and the RTX 5070 will be 798 AI TOPS, eight GB and $1,299.

Those are steep prices, but they represent the high end of value in GPUs for gaming.

Nvidia unveiled its Nvidia GeForce RTX 50 Series graphics chips.
Nvidia unveiled its Nvidia GeForce RTX 50 Series graphics chips.

Justin Walker, senior director of GeForce products, said in press briefing that Nvidia’s GeForce graphics card brand just celebrated its 25-year anniversary. It was the hit product that helped cement the company’s dominance in the ultra-competitive graphics processing unit (GPU) market and it enabled the company to use graphics as a springboard to AI processing, which is why Nvidia is the most valuable company in the world with a market capitalization of $3.65 trillion.

Now, it turns out, Walker said, AI can be used to help accelerate the performance of GPUs.

“The great thing about that is that while we are now an AI company, as well as gaming, our gaming side still benefits tremendously from the fact that we are doing AI,” Walker said.

And that’s the root of one of the announcements: Nvidia took the wraps of DLSS 4, which uses AI to predict the next pixel that needs to be drawn and then preemptively renders the pixel based on that prediction. The AI TOPS (a measure of AI performance) will be up to 4,000.

The new architecture of the 5000 series will have 1.8 terabytes per second of memory bandwidth, and it’s also tapping the Blackwell architecture that is the foundation of Nvidia’s latest AI processors.

The new GPU also has neural rendering technologies such as neural shaders.

“This is probably the biggest thing to happen in the graphics since programming for shaders, we are actually going to be embedding small neural networks within the shaders itself, and these neural networks can do certain things much more effectively and efficiently than traditional shaders,” Walker said.

The tech will enable Nvidia to compress textures eight times to maximize use of memory.

The Reflex 2 tech will use predictive shading to reduce the latency between when a gamer creates a movement and it shows up on the screen, so it will be 75% more responsive for gamers.

The 5090 series is likely to ship in January and the rest of the systems are going to ship in the March time frame, and the company will say which companies are shipping with the technology later. A number of games like Cyberpunk 2077 can play in 4K resolution at over 200 frames per second.

Walker said the company will have a list of games that take advantage of the various features.

Nvidia DLSS 4 Boosts Performance by Up to 8 times

Nvidia’s DLSS 4 AI tech is paying off.

DLSS 4 debuts Multi Frame Generation to boost frame rates by using AI to generate up to three frames per rendered frame. It works in unison with the suite of DLSS technologies to increase performance by up to 8x over traditional rendering, while maintaining responsiveness with Nvidia Reflex technology.

DLSS 4 also introduces the graphics industry’s first real-time application of the transformer model architecture. Transformer-based DLSS Ray Reconstruction and Super Resolution models use 2x more parameters and 4x more compute to provide greater stability, reduced ghosting, higher details and enhanced anti-aliasing in game scenes. DLSS 4 will be supported on GeForce RTX 50 Series GPUs in over 75 games and applications the day of launch.

Nvidia Reflex 2 introduces Frame Warp, an innovative technique to reduce latency in games by updating a rendered frame based on the latest mouse input just before it is sent to the display. Reflex 2 can reduce latency by up to 75%. This gives gamers a competitive edge in multiplayer games and makes single-player titles more responsive.

Blackwell Brings AI to Shaders

DLSS 4

Twenty-five years ago, Nvidia introduced GeForce 3 and programmable shaders, which set the stage for two decades of graphics innovation, from pixel shading to compute shading to real-time ray tracing. Alongside GeForce RTX 50 Series GPUs, NVIDIA is introducing RTX Neural Shaders, which brings small AI networks into programmable shaders, unlocking film-quality materials, lighting and more in real-time games.

Rendering game characters is one of the most challenging tasks in real-time graphics, as people are prone to notice the smallest errors or artifacts in digital humans. RTX Neural Faces takes a simple rasterized face and 3D pose data as input, and uses generative AI to render a temporally stable, high-quality digital face in real time.

RTX Neural Faces is complemented by new RTX technologies for ray-traced hair and skin. Along with the new RTX Mega Geometry, which enables up to 100 times more ray-traced triangles in a scene, these advancements are poised to deliver a massive leap in realism for game characters and environments.

The power of neural rendering, DLSS 4 and the new DLSS transformer model is showcased on GeForce RTX 50 Series GPUs with Zorah, a groundbreaking new technology demo from Nvidia.

Autonomous Game Characters

Nvidia 5070 has the performance of a 4090.

GeForce RTX 50 Series GPUs bring industry-leading AI TOPS to power autonomous game characters in parallel with game rendering.

Nvidia is introducing a suite of new Nvidia ACE technologies that enable game characters to perceive, plan and act like human players. ACE-powered autonomous characters are being integrated into Krafton’s PUBG: Battlegrounds and InZOI, the publisher’s upcoming life simulation game, as well as Wemade Next’s
MIR5.

In PUBG, companions powered by NVIDIA ACE plan and execute strategic actions, dynamically working with human players to ensure survival. InZOI features Smart Zoi characters that autonomously adjust behaviors based on life goals and in-game events. In MIR5, large language model (LLM)-driven raid bosses adapt tactics based on player behavior, creating more dynamic, challenging encounters.

AI Foundation Models for RTX AI PCs

Nvidia’s RTX Blackwell

Showcasing how RTX enthusiasts and developers can use NVIDIA NIM microservices to build AI agents and assistants, NVIDIA will release a pipeline of NIM microservices and AI Blueprints for RTX AI PCs from top model developers such as Black Forest Labs, Meta, Mistral and Stability AI.

Use cases span LLMs, vision language models, image generation, speech, embedding models for retrieval-augmented generation, PDF extraction and computer vision. The NIM microservices include all the necessary components for running AI on PCs and are optimized for deployment across all NVIDIA GPUs.

To demonstrate how enthusiasts and developers can use NIM to build AI agents and assistants, NVIDIA today previewed Project R2X, a vision-enabled PC avatar that can put information at a user’s fingengertips, assist with desktop apps and video conference calls, read and summarize documents, and more.

Jensen Huang, CEO of Nvidia.
Jensen Huang, CEO of Nvidia.

The GeForce RTX 50 Series GPUs supercharge creative work flows. RTX 50 Series GPUs are the first consumer GPUs to support FP4 precision, boosting AI image generation performance for models such as FLUX by 2x and enabling generative AI models to run locally in a smaller memory footprint, compared with previous-generation hardware.

The NVIDIA Broadcast app gains two AI-powered beta features for livestreamers: Studio Voice, which upgrades microphone audio, and Virtual Key light, which relights faces for polished streams. Streamlabs is introducing the Intelligent Streaming Assistant, powered by NVIDIA ACE and Inworld AI, which acts as a
cohost, producer and technical assistant to enhance livestreams.

The NvidiaFounders Editions of the GeForce RTX 5090, RTX 5080 and RTX 5070 GPUs will be available directly from nvidia.com and select retailers worldwide.

Stock-clocked and factory-overclocked models will be available from top add-in card providers such as ASUS, Colorful, Gainward, GALAX, GIGABYTE, INNO3D, KFA2, MSI, Palit, PNY and ZOTAC, and in desktops from system builders including Falcon Northwest, Inniarc, MAINGEAR, Mifcom, ORIGIN PC, PC Specialist and Scan Computers.

Laptops with GeForce RTX 5090, RTX 5080 and RTX 5070 Ti Laptop GPUs will be available starting in March, and RTX 5070 Laptop GPUs will be available starting in April from the world’s top manufacturers, including Acer, ASUS, Dell, GIGABYTE, HP, Lenovo, MECHREVO, MSI and Razer.

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From packets to prompts: What Cisco’s AITECH certification means for IT pros

Cisco positions the AITECH learning path as a bridge from “traditional knowledge-based work” to innovation-driven roles augmented by AI, explicitly targeting professionals who need to design technical solutions, automate tasks, and lead teams using modern AI tools and methodologies. The curriculum spans AI-assisted code generation, AI-driven data analysis, model customization (including RAG),

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HPE’s latest Juniper routers target large‑scale AI fabrics

The three new models give customers several options for configurations and throughput capacity, but they all share support for the same deep buffers, security, and optics for AI network fabric buildouts, Francis said. In addition to the new hardware, HPE added new AI support, including a Model Context Protocol (MCP)

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Energy Department Announces $171.5 Million To Expand U.S. Geothermal Energy

Support for Field-Scale Tests and Exploration Drilling Can Help Advance Affordable, Reliable, Secure Geothermal Energy for American Homes and Businesses WASHINGTON—The U.S. Department of Energy (DOE) today announced a funding opportunity of $171.5 million to support next-generation geothermal field-scale tests for both electricity generation and exploration drilling to support characterization and potential confirmation of promising geothermal prospects. The activities enabled by this opportunity will help deliver on President Trump’s Executive Order, Unleashing American Energy by advancing geothermal technology, innovation, and exploration, in turn supporting the potential for geothermal energy to provide affordable, reliable, around-the-clock domestic electricity to Americans nationwide. “Work under this opportunity will directly support our commitments to advance energy addition, reduce energy costs for American families and businesses, and unleash American energy dominance and innovation,” said DOE Assistant Secretary of the Hydrocarbons and Geothermal Energy Office Kyle Haustveit. “Thanks to President Trump’s America First Energy Agenda, these demonstrations and drilling activities will help us realize the enormous potential of geothermal to spur domestic manufacturing, enable data center growth, and provide affordable, reliable, and secure energy solutions nationwide.” The funding opportunity includes six topics with varied levels of funding and awards anticipated. For the first round of applications, two of the six topics will be open, seeking field tests for enhanced geothermal systems and drilling for next-generation and hydrothermal resource characterization / confirmation. Although the United States leads the world in geothermal electricity capacity with about four gigawatts, DOE analysis shows the potential for at least 300 gigawatts of reliable, flexible geothermal power on the U.S. grid by 2050. Projects under this opportunity are expected to help derisk geothermal development approaches and locations nationwide, which can encourage private investment, spur industry growth, and help realize the country’s geothermal potential. Letters of Intent for the opportunity are due March 27, 2026, and full applications are due April 30, 2026.

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Energy Department Announces Largest Loan in Department History, Delivering Over $7 Billion in Electricity Cost Savings for Georgia and Alabama Customers

WASHINGTON—U.S. Secretary of Energy Chris Wright today announced the Department of Energy’s (DOE) Office of Energy Dominance Financing (EDF) has closed a historic $26.5 billion loan package to deliver over $7 billion in electricity cost savings to millions of customers in Georgia and Alabama. In accordance with President Trump’s Executive Order, Unleashing American Energy, this unprecedented loan package will support two wholly owned subsidiaries of Southern Company. Funded under President Trump’s Working Families Tax Cut, the investment will lower American energy costs, create thousands of jobs, and increase grid reliability in Georgia and Alabama. “Thanks to President Trump and the Working Families Tax Cut, the Energy Department is lowering energy costs and ensuring the American people have access to affordable, reliable, and secure energy for decades to come,” said Secretary Wright. “The President has been clear: America must reverse the energy subtraction agenda of past administrations and add more reliable power generation to our electrical grid. These loans will not only lower energy costs but also create thousands of jobs and increase grid reliability for the people of Georgia and Alabama.” The two loans will build or upgrade over 16 gigawatts (GW) of firm reliable power to the electrical grid. This includes 5 GW of new gas generation, 6 GW in nuclear improved through upgrades license renewals, hydropower modernization, battery energy storage systems and over 1,300 miles of transmission and grid enhancement projects. These loans represent the largest government investment aimed at directly lowering consumer energy costs and increasing grid reliability. Once all funds are received through the program, the loans are estimated to reduce Southern Company’s interest expenses by over $300 million per year, helping expedite lower electricity costs for customers. Southern Company is among the first utilities working with the DOE and the Trump Administration to restore American

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Energy Secretary Keeps Critical Generation Online in Mid-Atlantic

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Insights: Venezuela – new legal frameworks vs. the inertia of history

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Eni makes Calao South discovery offshore Ivory Coast

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CFEnergía to supply natural gas to low-carbon methanol plant in Mexico

CFEnergía, a subsidiary of Mexico’s Federal Electricity Commission (CFE), has agreed to supply natural gas to Transition Industries LLC for its Pacifico Mexinol project near Topolobampo, Sinaloa, Mexico. Under the signed agreement, which enables the start of Pacifico Mexinol’s construction phase, CFEnergía will supply about 160 MMcfd of natural gas for an unspecified timeframe noted as “long term,” Transition Industries said in a release Feb. 16. The natural gas—to be sourced from the US and supplied at market prices via existing infrastructure—will be used as “critical input for Mexinol’s production of ultra-low carbon methanol,” the company said. Pacifico Mexinol The $3.3-billion Mexinol project, when it begins operations in late 2029 to early 2030, is expected to be the world’s largest ultra-low carbon chemicals plant with production of about 1.8 million tonnes of blue methanol and 350,000 tonnes of green methanol annually. Supply is aimed at markets in Asia, including Japan, while also boosting the development of the domestic market and the Mexican chemical industry. Mitsubishi Gas Chemical has committed to purchasing about 1 million tonnes/year of methanol from the project, about 50% of the project’s planned production. Transition Industries is jointly developing Pacifico Mexinol with the International Finance Corporation (IFC), a member of the World Bank Group. Last year, the company signed a contingent engineering, procurement, and construction (EPC) contract with the consortium of Samsung E&A Co., Ltd., Grupo Samsung E&A Mexico SA de CV, and Techint Engineering and Construction for the project. MAIRE group’s technology division NextChem, through its subsidiary KT TECH SpA, also signed a basic engineering, critical and proprietary equipment supply agreement with Samsung E&A in connection with its proprietary NX AdWinMethanol®Zero technology supply to the project.

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Why do data centers need so much water?

Another legacy cooling technology in data centers is what’s called a cooling tower. A cooling tower sits outside of the main building, and the water cascades down these towers like a waterfall. However, the tower is open to the atmosphere to let natural cooling in. The churn of the water dissipates the heat, but there is significant evaporation in the process. “It evaporates a lot. I mean, we’re talking many, many Olympic swimming pools worth of water on a daily basis in some of these data centers,” said Green. “Some of the hyperscalers I work with are still using open cooling tower solutions, even today.” There were other reasons for using evaporation. For starters, evaporation equipment takes up a lot less space the chilled water equipment. Secondly is the price. Chilled water-cooling costs about 10% to 15% more than equivalent evaporation technology. But that is changing, Green notes, as more and more societal pressure, economic pressure around water consumption continues to move to the forefront, data centers are being forced to adapt. “We’re in a market now where we can use air cooled chillers that don’t evaporate water like a water-cooled chiller does, and have a very, very similar level of overall system efficiency,” he said. We are also seeing the advent of closed loop technology, where liquid is pumped into a system to absorb heat and then pumped out to be cooled and recirculated, much like a car radiator. Gamers have been on the forefront of liquid cooling and closed loop with all-in-one coolers for gaming PCs becoming standard issue now.

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Netskope targets AI-driven network bottlenecks with AI Fast Path

AI Fast Path focuses on optimizing traffic flows between enterprise users, the Netskope cloud, and major AI providers. Netskope says more than 90% of its 120 NewEdge data centers can now connect to leading AI applications in less than five milliseconds from the Netskope cloud, an effort aimed at minimizing added delay as traffic is inspected for data loss prevention (DLP), threat protection, and policy enforcement. “Customers realized that if they don’t adopt these AI apps, they’re probably going to be extinct in a few years. At the same time, we can’t afford to compromise on security,” Arandjelovic says. “So, with NewEdge and the AI Fast Path, we’ve created a super-optimized path where there is literally barely a bump in the wire. At the same time, they are not compromising security, because you’re passing through our cloud and getting all the benefits of our data protection and threat protection.” As a set of capabilities within NewEdge, AI Fast Path enables better performance and efficiency for AI applications. According to Netskope, AI Fast Path provides enterprises with:

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AMD strikes massive AI chip deal with Meta

The funding is also unique. Instead of a cash purchase, AMD has reportedly given Meta warrants to buy up to 160 million shares at $0.01 each. Stock warrants are financial instruments that give you the right (but not the obligation) to buy a company’s stock at a fixed price before a certain expiration date, according to the vendors. With 1.6 billion shares outstanding, Meta is poised to acquire 10% of AMD. But perhaps not. These shares vest only as Meta buys more computing capacity. The final tranche vests only if AMD’s stock price hits $600, according to a recent 8K filing. AMD shares are currently valued at just over $200 as of this writing. The deal is identical to the one AMD struck with OpenAI last October. That deal was also for 6 GW worth of GPUs and included a warrant for up to 160 million AMD common stock shares structured to payout once certain targets were met. Meta is not playing favorites. Last week it announced that it will also deploy standalone Nvidia Grace CPUs in its production data centers, citing greatly improved performance-per-watt. That doesn’t come as a surprise to Gaurav Gupta, vice president analyst at Gartner, who says we are compute constrained and Hyperscalers or frontier model companies will use a multisource approach to get access to compute.  “No one wants to be stuck with a single vendor. Diversify and then different workloads have different compute needs.,” he said.

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Nvidia lines up partners to boost security for industrial operations

Akamai extends its micro-segmentation and zero-trust security platform Guardicore to run on Nvidia BlueField GPUs The integration offloads user-configurable security processes from the host system to the Nvidia BlueField DPU and enables zero-trust segmentation without requiring software agents on fragile or legacy systems, according to Akamai. Organizations can implement this hardware-isolated, “agentless” security approach to help align with regulatory requirements and lower their risk profile for cyber insurance. “It delivers deep, out-of-band visibility across systems, networks, and applications without disrupting operations. Security policies can be enforced in real time and are capable of creating a strong protective boundary around critical operational systems. The result is trusted insight into operational activity and improved overall cyber resilience,” according to Akamai. Forescout works with Nvidia to bring zero-trust technology to OT networks Forescout applies network segmentation to contain lateral movement and enforce zero-trust controls. The technology would be further integrated into partnership work already being done by the two companies. By running Forescout’s on-premises sensor directly on the Nvidia BlueField, part of Nvidia Cybersecurity AI platform, customers can offload intensive computing tasks, such as deep packet inspections. This speeds up data processing, enhances asset intelligence, and improves real-time monitoring, providing security teams with the insights needed to stay ahead of emerging threats, according to Forescout. Palo Alto to demo Prisma AIRS AI Runtime Security on Nvidia BlueField DPU Palo Alto Networks recently partnered with Nvidia to run its Prisma AI-powered Radio Security(AIRs) package on the Nvidia BlueField DPU and will show off the technology at the conference. The technology is part of the Nvidia Enterprise AI Factory validated design and can offer real-time security protection for industrial network settings. “Prisma AIRS AI Runtime Security delivers deep visibility into industrial traffic and continuous monitoring for abnormal behavior. By running these security services on Nvidia BlueField, inspection

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Raising the temp on liquid cooling

IBM isn’t the only one. “We’ve been doing liquid cooling since 2012 on our supercomputers,” says Scott Tease, vice president and general manager of AI and high-performance computing at Lenovo’s infrastructure solutions group. “And we’ve been improving it ever since—we’re now on the sixth generation of that technology.” And the liquid Lenovo uses in its Neptune liquid cooling solution is warm water. Or, more precisely, hot water: 45 degrees Celsius. And when the water leaves the servers, it’s even hotter, Tease says. “I don’t have to chill that water, even if I’m in a hot climate,” he says. Even at high temperatures, the water still provides enough cooling to the chips that it has real value. “Generally, a data center will use evaporation to chill water down,” Tease adds. “Since we don’t have to chill the water, we don’t have to use evaporation. That’s huge amounts of savings on the water. For us, it’s almost like a perfect solution. It delivers the highest performance possible, the highest density possible, the lowest power consumption. So, it’s the most sustainable solution possible.” So, how is the water cooled down? It gets piped up to the roof, Tease says, where there are giant radiators with massive amounts of surface area. The heat radiates away, and then all the water flows right back to the servers again. Though not always. The hot water can also be used to, say, heat campus or community swimming pools. “We have data centers in the Nordics who are giving the heat to the local communities’ water systems,” Tease says.

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Vertiv’s AI Infrastructure Surge: Record Orders, Liquid Cooling Expansion, and Grid-Scale Power Reflect Data Center Growth

2) “Units of compute”: OneCore and SmartRun On the earnings call, Albertazzi highlighted Vertiv OneCore, an end-to-end data center solution designed to accelerate “time to token,” scaling in 12.5 MW building blocks; and Vertiv SmartRun, a prefabricated white space infrastructure solution aimed at rapidly accelerating fit-out and readiness. He pointed to collaborations (including Hut 8 and Compass Data Centers) as proof points of adoption, emphasizing that SmartRun can stand alone or plug into OneCore. 3) Cooling evolution: hybrid thermal chains and the “trim cooler” Asked how cooling architectures may change (amid industry chatter about warmer-temperature operations and shifting mixes of chillers, CDUs, and other components) Albertazzi leaned into complexity as a feature, not a bug. He argued heat rejection doesn’t disappear, even if some GPU loads can run at higher temperatures. Instead, the future looks hybrid, with mixed loads and resiliency requirements forcing more nuanced thermal chains. Vertiv’s strategic product anchor here is its “trim cooler” concept: a chiller optimized for higher-temperature operation while retaining flexibility for lower-temperature requirements in the same facility, maximizing free cooling where climate and design allow. And importantly, Albertazzi dismissed the idea that CDUs are going away: “We are pretty sure that CDUs in various shapes and forms are a long-term element of the thermal chain.” 4) Edge densification: CoolPhase Ceiling + CoolPhase Row (Feb. 3) Vertiv also expanded its thermal portfolio for edge and small IT environments with the: Vertiv CoolPhase Ceiling (launching Q2 2026): ceiling-mounted, 3.5 kW to 28 kW, designed to preserve floor space. Vertiv CoolPhase Row (available now in North America) for row-based cooling up to 30 kW (300 mm width) or 40 kW (600 mm width). Vertiv Director of Edge Thermal Michal Podmaka tied the products directly to AI-driven edge densification and management consistency, saying the new systems “integrate seamlessly

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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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