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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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US lets China buy semiconductor design software again

The reversal marks a dramatic shift from the aggressive stance the Trump administration took in May, when it imposed sweeping restrictions on electronic design automation (EDA) software — the critical tools needed to design advanced semiconductors.  A short-lived stoppage  The restrictions had targeted what analysts called the “upstream” of chip

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Hardcoded root credentials in Cisco Unified CM trigger max-severity alert

The affected products-Cisco Unified CM and Unified CM SME–are core components of enterprise telephony infrastructure, widely deployed across government agencies, financial institutions, and large corporations to manage voice, video, and messaging at scale. A flaw in these systems could allow attackers to compromise an organization’s communications, letting them log in

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Angola Raises Diesel Price by 33 Pct, Third Increase This Year

Angola raised the diesel price by 33%, the third increase this year as authorities press ahead with fuel-subsidy cuts that have been encouraged by the International Monetary Fund. The price will rise to 400 kwanzas ($0.43) per liter on Friday from 300 kwanza previously, the Petroleum Derivatives Regulatory Institute said in a statement late Thursday. The increase is part of a “gradual adjustment of fuel prices,” it said. Previous hikes were announced in March and April. The IRDP said prices of other fuels, including gasoline and liquefied-petroleum gas, will remain unchanged in Angola, Africa’s third-largest oil producer. The IMF said in February that Angola should do more to eliminate subsidies that cost about $3 billion last year — similar to the amount the government spent on health and education last year. The latest hike follows an IMF-World Bank review of Angola’s financial system that ended last month. 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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OPEC+ Moves Meeting to Saturday as Group Weighs Another Hike

Key OPEC+ members brought forward to Saturday an online meeting where they’re set to consider a fourth bumper oil production increase, delegates said.  Saudi Arabia and its partners have been discussing another output hike of 411,000 barrels a day for August as their base-case scenario as they seek to recoup lost market share. The video-conference was moved one day earlier because of scheduling issues, said the officials, who asked not to be identified since the change isn’t yet public.   The Organization of the Petroleum Exporting Countries has roiled markets in recent months by speeding up the return of halted output, despite faltering demand and an impending surplus. Their strategy shift is dragging crude prices lower, offering relief to consumers and playing into calls from US President Donald Trump for cheaper fuel. Eight major OPEC+ members have already agreed to restart 411,000 barrels a day in May, June and July, triple the rate they initially scheduled. Officials have said that Riyadh is eager to revive more idle production as quickly as possible to regain market share ceded to US shale drillers and other rivals. The kingdom’s pivot away from years of supply restraint aimed at shoring up crude prices has upended traders’ assumptions about what role the OPEC+ alliance will continue to play in world oil markets. Brent crude futures traded near $68 a barrel in London on Friday. The international benchmark plunged 12% last week as a tentative truce between Israel and Iran allayed fears over the threat to Middle East energy exports.    Further OPEC+ increases threaten to create a glut. Global oil inventories have been building at a brisk clip of around 1 million barrels a day in recent months as demand cools in China and supplies continue to swell across the Americas.  Markets are headed for a substantial surplus later this year,

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Methane Emission Tracking Satellite Lost in Space, EDF Says

Methane emissions tracking satellite MethaneSAT lost contact with mission operations, and it is “likely not recoverable,” the Environmental Defense Fund (EDF) said in a statement. “After pursuing all options to restore communications, we learned this morning that the satellite has lost power,” the EDF said. “The engineering team is conducting a thorough investigation into the loss of communication. This is expected to take time. We will share what we learn,” the nonprofit organization added. Launched in March 2024, MethaneSAT had been collecting methane emissions data over the past year. It was one of the most advanced methane tracking satellites in space, measuring methane emissions in oil and gas producing regions across the world, according to the statement. “The mission has been a remarkable success in terms of scientific and technological accomplishment, and for its lasting influence on both industry and regulators worldwide,” the EDF said. “Thanks to MethaneSAT, we have gained critical insight about the distribution and volume of methane being released from oil and gas production areas. We have also developed an unprecedented capability to interpret the measurements from space and translate them into volumes of methane released. This capacity will be valuable to other missions,” the organization continued. MethaneSAT had the ability to monitor both high-emitting methane sources and small sources spread over a wide area, according to the release. It is designed to measure regions at intervals under seven days, regularly monitoring roughly 50 major regions accounting for more than 80 percent of global oil and gas production, according to an earlier statement. “The advanced spectrometers developed specifically for MethaneSAT met or exceeded all expectations throughout the mission. In combination with the mission algorithms and software, we showed that the highly sensitive instrument could see total methane emissions, even at low levels, over wide areas, including both

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How Has USA Energy Use Changed Since 1776?

A new analysis piece published on the U.S. Energy Information Administration (EIA) website recently, which was penned by Mickey Francis, Program Manager and Lead Economist for the EIA’s State Energy Data System, has outlined how U.S. energy use has changed since the Declaration of Independence was signed in 1776. The piece highlighted that, according to the EIA’s monthly energy review, in 2024, the U.S. consumed about 94 quadrillion British thermal units (quads) of energy. Fossil fuels – namely petroleum, natural gas, and coal – made up 82 percent of total U.S. energy consumption last year, the piece pointed out, adding that non-fossil fuel energy accounted for the other 18 percent. Petroleum remained the most-consumed fuel in the United States, the piece stated, outlining that this has been the case for the past 75 years. It also highlighted that, last year, nuclear energy consumption exceeded coal consumption for the first time ever. The analysis piece went on to note that, when the Declaration of Independence was signed in 1776, wood was the largest source of energy in the United States. “Used for heating, cooking, and lighting, wood remained the largest U.S. energy source until the late 1800s, when coal consumption became more common,” it added. “Wood energy is still consumed, mainly by industrial lumber and paper plants that burn excess wood waste to generate electricity,” it continued. The piece went on to highlight that coal was the largest source of U.S. energy for about 65 years, from 1885 until 1950. “Early uses of coal included many purposes that are no longer common, such as in stoves for home heating and in engines for trains and ships. Since the 1960s, nearly all coal consumed in the United States has been for electricity generation,” the piece said. The analysis piece went on to state that petroleum has

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Ocean Installer Awarded EPCI Contract for Var Energi’s Balder Project

Subsea services firm Ocean Installer has been awarded a fast-track engineering, procurement, construction and installation (EPCI) contract by Var Energi for further development of the Balder Phase VI project for the further development of the Balder area in the North Sea. This project is part of Var Energi’s hub development strategy in the Balder area, which is centered around the newly installed Jotun floating production storage and offloading vessel (FPSO), Ocean Installer said in a news release. Ocean Installer said it will execute subsea umbilicals, risers, and flowlines (SURF) activities including the fabrication and installation of flexible flowlines and umbilicals. Financial details of the contract were not disclosed. The project is scheduled to deliver first oil by the end of 2026, reinforcing both companies’ shared commitment to efficient development of subsea tie-backs on the Norwegian Continental Shelf (NCS), according to the release. “Var Energi is a key customer for Ocean Installer and the wider Moreld group. It’s exciting to see that Ocean Installer signs a new contract within the same week that the Jotun FPSO starts producing first oil as part of the Balder Future project, in which Ocean Installer has played a key role,” Moreld CEO Geir Austigard said. The contract is called off under the strategic partnership contract entered into with Vår Energi in June 2022. It is also a continuation of a multi-year collaboration between Vår Energi and Ocean Installer in the Balder area, where Ocean Installer has been engaged since 2019, the release said. “We are happy that Vår Energi continues to place their trust in us. Subsea tiebacks have been the core of our business for 14 years, and as the NCS transitions to more marginal fields, our expertise is valuable in enabling faster and more cost-efficient developments. Working together with Vår Energi to utilize

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ADNOC Drilling Wins $800MM Contract for Fracking Services

ADNOC Drilling Company said it was awarded a contract valued at up to $800 million by ADNOC Onshore for the provision of integrated hydraulic fracturing services for conventional and tight reservoirs. The five-year agreement is set to begin in the third quarter, ADNOC Drilling said in a news release. The contract’s scope of work supports ADNOC’s strategic goal to accelerate the development of conventional and tight reservoirs across the United Arab Emirates (UAE) and includes the design, execution, and evaluation of multistage hydraulic fracturing treatments, which will be deployed across a wide range of assets in Abu Dhabi, according to the release. Fracturing services for conventional and tight reservoirs are used to enhance the flow of oil or gas through existing natural pathways and optimize production by improving flow rates, the company said. ADNOC Drilling said it plans to “deploy advanced technologies throughout the project to maximize efficiency and performance”. Proprietary fracturing simulation software will be used to optimize every stage of the operation, increasing flow rates and overall hydrocarbon recovery. Intelligent fluid systems will adapt dynamically in real-time to reservoir conditions, improving fracture efficiency and reducing environmental impact, while automated pumping units and blending systems will enhance safety, streamline operations and reduce the need for on-site manpower, the company stated. ADNOC Drilling’s new CEO, Abdulla Ateya Al Messabi, said, “This significant contract is a powerful endorsement of ADNOC Drilling’s expanding capabilities and our trusted partnership with ADNOC Onshore. It reflects our ability to deliver high-impact, technologically advanced fracturing services that will help unlock the UAE’s energy potential. As we continue our transformation, we are proud to support the nation’s strategic energy goals and reinforce our position as a leader in integrated drilling and completion solutions”. The award “further reinforces ADNOC Drilling’s leadership in high-tech oilfield services, combining next-generation equipment,

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CoreWeave achieves a first with Nvidia GB300 NVL72 deployment

The deployment, Kimball said, “brings Dell quality to the commodity space. Wins like this really validate what Dell has been doing in reshaping its portfolio to accommodate the needs of the market — both in the cloud and the enterprise.” Although concerns were voiced last year that Nvidia’s next-generation Blackwell data center processors had significant overheating problems when they were installed in high-capacity server racks, he said that a repeat performance is unlikely. Nvidia, said Kimball “has been very disciplined in its approach with its GPUs and not shipping silicon until it is ready. And Dell almost doubles down on this maniacal quality focus. I don’t mean to sound like I have blind faith, but I’ve watched both companies over the last several years be intentional in delivering product in volume. Especially as the competitive market starts to shape up more strongly, I expect there is an extremely high degree of confidence in quality.” CoreWeave ‘has one purpose’ He said, “like Lambda Labs, Crusoe and others, [CoreWeave] seemingly has one purpose (for now): deliver GPU capacity to the market. While I expect these cloud providers will expand in services, I think for now the type of customer employing services is on the early adopter side of AI. From an enterprise perspective, I have to think that organizations well into their AI journey are the consumers of CoreWeave.”  “CoreWeave is also being utilized by a lot of the model providers and tech vendors playing in the AI space,” Kimball pointed out. “For instance, it’s public knowledge that Microsoft, OpenAI, Meta, IBM and others use CoreWeave GPUs for model training and more. It makes sense. These are the customers that truly benefit from the performance lift that we see from generation to generation.”

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Oracle to power OpenAI’s AGI ambitions with 4.5GW expansion

“For CIOs, this shift means more competition for AI infrastructure. Over the next 12–24 months, securing capacity for AI workloads will likely get harder, not easier. Though cost is coming down but demand is increasing as well, due to which CIOs must plan earlier and build stronger partnerships to ensure availability,” said Pareekh Jain, CEO at EIIRTrend & Pareekh Consulting. He added that CIOs should expect longer wait times for AI infrastructure. To mitigate this, they should lock in capacity through reserved instances, diversify across regions and cloud providers, and work with vendors to align on long-term demand forecasts.  “Enterprises stand to benefit from more efficient and cost-effective AI infrastructure tailored to specialized AI workloads, significantly lower their overall future AI-related investments and expenses. Consequently, CIOs face a critical task: to analyze and predict the diverse AI workloads that will prevail across their organizations, business units, functions, and employee personas in the future. This foresight will be crucial in prioritizing and optimizing AI workloads for either in-house deployment or outsourced infrastructure, ensuring strategic and efficient resource allocation,” said Neil Shah, vice president at Counterpoint Research. Strategic pivot toward AI data centers The OpenAI-Oracle deal comes in stark contrast to developments earlier this year. In April, AWS was reported to be scaling back its plans for leasing new colocation capacity — a move that AWS Vice President for global data centers Kevin Miller described as routine capacity management, not a shift in long-term expansion plans. Still, these announcements raised questions around whether the hyperscale data center boom was beginning to plateau. “This isn’t a slowdown, it’s a strategic pivot. The era of building generic data center capacity is over. The new global imperative is a race for specialized, high-density, AI-ready compute. Hyperscalers are not slowing down; they are reallocating their capital to

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Arista Buys VeloCloud to reboot SD-WANs amid AI infrastructure shift

What this doesn’t answer is how Arista Networks plans to add newer, security-oriented Secure Access Service Edge (SASE) capabilities to VeloCloud’s older SD-WAN technology. Post-acquisition, it still has only some of the building blocks necessary to achieve this. Mapping AI However, in 2025 there is always more going on with networking acquisitions than simply adding another brick to the wall, and in this case it’s the way AI is changing data flows across networks. “In the new AI era, the concepts of what comprises a user and a site in a WAN have changed fundamentally. The introduction of agentic AI even changes what might be considered a user,” wrote Arista Networks CEO, Jayshree Ullal, in a blog highlighting AI’s effect on WAN architectures. “In addition to people accessing data on demand, new AI agents will be deployed to access data independently, adapting over time to solve problems and enhance user productivity,” she said. Specifically, WANs needed modernization to cope with the effect AI traffic flows are having on data center traffic. Sanjay Uppal, now VP and general manager of the new VeloCloud Division at Arista Networks, elaborated. “The next step in SD-WAN is to identify, secure and optimize agentic AI traffic across that distributed enterprise, this time from all end points across to branches, campus sites, and the different data center locations, both public and private,” he wrote. “The best way to grab this opportunity was in partnership with a networking systems leader, as customers were increasingly looking for a comprehensive solution from LAN/Campus across the WAN to the data center.”

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Data center capacity continues to shift to hyperscalers

However, even though colocation and on-premises data centers will continue to lose share, they will still continue to grow. They just won’t be growing as fast as hyperscalers. So, it creates the illusion of shrinkage when it’s actually just slower growth. In fact, after a sustained period of essentially no growth, on-premises data center capacity is receiving a boost thanks to genAI applications and GPU infrastructure. “While most enterprise workloads are gravitating towards cloud providers or to off-premise colo facilities, a substantial subset are staying on-premise, driving a substantial increase in enterprise GPU servers,” said John Dinsdale, a chief analyst at Synergy Research Group.

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Oracle inks $30 billion cloud deal, continuing its strong push into AI infrastructure.

He pointed out that, in addition to its continued growth, OCI has a remaining performance obligation (RPO) — total future revenue expected from contracts not yet reported as revenue — of $138 billion, a 41% increase, year over year. The company is benefiting from the immense demand for cloud computing largely driven by AI models. While traditionally an enterprise resource planning (ERP) company, Oracle launched OCI in 2016 and has been strategically investing in AI and data center infrastructure that can support gigawatts of capacity. Notably, it is a partner in the $500 billion SoftBank-backed Stargate project, along with OpenAI, Arm, Microsoft, and Nvidia, that will build out data center infrastructure in the US. Along with that, the company is reportedly spending about $40 billion on Nvidia chips for a massive new data center in Abilene, Texas, that will serve as Stargate’s first location in the country. Further, the company has signaled its plans to significantly increase its investment in Abu Dhabi to grow out its cloud and AI offerings in the UAE; has partnered with IBM to advance agentic AI; has launched more than 50 genAI use cases with Cohere; and is a key provider for ByteDance, which has said it plans to invest $20 billion in global cloud infrastructure this year, notably in Johor, Malaysia. Ellison’s plan: dominate the cloud world CTO and co-founder Larry Ellison announced in a recent earnings call Oracle’s intent to become No. 1 in cloud databases, cloud applications, and the construction and operation of cloud data centers. He said Oracle is uniquely positioned because it has so much enterprise data stored in its databases. He also highlighted the company’s flexible multi-cloud strategy and said that the latest version of its database, Oracle 23ai, is specifically tailored to the needs of AI workloads. Oracle

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Datacenter industry calls for investment after EU issues water consumption warning

CISPE’s response to the European Commission’s report warns that the resulting regulatory uncertainty could hurt the region’s economy. “Imposing new, standalone water regulations could increase costs, create regulatory fragmentation, and deter investment. This risks shifting infrastructure outside the EU, undermining both sustainability and sovereignty goals,” CISPE said in its latest policy recommendation, Advancing water resilience through digital innovation and responsible stewardship. “Such regulatory uncertainty could also reduce Europe’s attractiveness for climate-neutral infrastructure investment at a time when other regions offer clear and stable frameworks for green data growth,” it added. CISPE’s recommendations are a mix of regulatory harmonization, increased investment, and technological improvement. Currently, water reuse regulation is directed towards agriculture. Updated regulation across the bloc would encourage more efficient use of water in industrial settings such as datacenters, the asosciation said. At the same time, countries struggling with limited public sector budgets are not investing enough in water infrastructure. This could only be addressed by tapping new investment by encouraging formal public-private partnerships (PPPs), it suggested: “Such a framework would enable the development of sustainable financing models that harness private sector innovation and capital, while ensuring robust public oversight and accountability.” Nevertheless, better water management would also require real-time data gathered through networks of IoT sensors coupled to AI analytics and prediction systems. To that end, cloud datacenters were less a drain on water resources than part of the answer: “A cloud-based approach would allow water utilities and industrial users to centralize data collection, automate operational processes, and leverage machine learning algorithms for improved decision-making,” argued CISPE.

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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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