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Inside China’s electric-vehicle-to-humanoid-robot pivot

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. While DOGE’s efforts to shutter federal agencies dominate news from Washington, the Trump administration is also making more global moves. Many of these center on China. Tariffs on goods from the country went into effect last week. There’s also been a minor foreign relations furor since DeepSeek’s big debut a few weeks ago. China has already displayed its dominance in electric vehicles, robotaxis, and drones, and the launch of the new model seems to add AI to the list. This caused the US president as well as some lawmakers to push for new export controls on powerful chips, and three states have now banned the use of DeepSeek on government devices.  Now our intrepid China reporter, Caiwei Chen, has identified a new trend unfolding within China’s tech scene: Companies that were dominant in electric vehicles are betting big on translating that success into developing humanoid robots. I spoke with her about what she found out and what it might mean for Trump’s policies and the rest of the globe.  James: Before we talk about robots, let’s talk about DeepSeek. The frenzy for the AI model peaked a couple of weeks ago. What are you hearing from other Chinese AI companies? How are they reacting? Caiwei: I think other Chinese AI companies are scrambling to figure out why they haven’t built a model as strong as DeepSeek’s, despite having access to as much funding and resources. DeepSeek’s success has sparked self-reflection on management styles and renewed confidence in China’s engineering talent. There’s also strong enthusiasm for building various applications on top of DeepSeek’s models. Your story looks at electric-vehicle makers in China that are starting to work on humanoid robots, but I want to ask about a crazy stat. In China, 53% of vehicles sold are either electric or hybrid, compared with 8% in the US. What explains that?  Price is a huge factor—there are countless EV brands competing at different price points, making them both affordable and high-quality. Government incentives also play a big role. In Beijing, for example, trading in an old car for an EV gets you 10,000 RMB (about $1,500), and that subsidy was recently doubled. Plus, finding public charging and battery-swapping infrastructure is much less of a hassle than in the US. You open your story noting that China’s recent New Year Gala, watched by billions of people, featured a cast of humanoid robots, dancing and twirling handkerchiefs. We’ve covered how sometimes humanoid videos can be misleading. What did you think?  I would say I was relatively impressed—the robots showed good agility and synchronization with the music, though their movements were simpler than human dancers’. The one trick that is supposed to impress the most is the part where they twirl the handkerchief with one finger, toss it into the air, and then catch it perfectly. This is the signature of the Yangko dance, and having performed it once as a child, I can attest to how difficult the trick is even for a human! There was some skepticism on the Chinese internet about how this was achieved and whether they used additional reinforcement like a magnet or a string to secure the handkerchief, and after watching the clip too many times, I tend to agree. President Trump has already imposed tariffs on China and is planning even more. What could the implications be for China’s humanoid sector?   Unitree’s H1 and G1 models are already available for purchase and were showcased at CES this year. Large-scale US deployment isn’t happening yet, but China’s lower production costs make these robots highly competitive. Given that 65% of the humanoid supply chain is in China, I wouldn’t be surprised if robotics becomes the next target in the US-China tech war. In the US, humanoid robots are getting lots of investment, but there are plenty of skeptics who say they’re too clunky, finicky, and expensive to serve much use in factory settings. Are attitudes different in China? Skepticism exists in China too, but I think there’s more confidence in deployment, especially in factories. With an aging population and a labor shortage on the horizon, there’s also growing interest in medical and caregiving applications for humanoid robots. DeepSeek revived the conversation about chips and the way the US seeks to control where the best chips end up. How do the chip wars affect humanoid-robot development in China? Training humanoid robots currently doesn’t demand as much computing power as training large language models, since there isn’t enough physical movement data to feed into models at scale. But as robots improve, they’ll need high-performance chips, and US sanctions will be a limiting factor. Chinese chipmakers are trying to catch up, but it’s a challenge. For more, read Caiwei’s story on this humanoid pivot, as well as her look at the Chinese startups worth watching beyond DeepSeek.  Deeper Learning Motor neuron diseases took their voices. AI is bringing them back. In motor neuron diseases, the neurons responsible for sending signals to the body’s muscles, including those used for speaking, are progressively destroyed. It robs people of their voices. But some, including a man in Miami named Jules Rodriguez, are now getting them back: An AI model learned to clone Rodriguez’s voice from recordings. Why it matters: ElevenLabs, the company that created the voice clone, can do a lot with just 30 minutes of recordings. That’s a huge improvement over AI voice clones from just a few years ago, and it can really boost the day-to-day lives of the people who’ve used the technology. “This is genuinely AI for good,” says Richard Cave, a speech and language therapist at the Motor Neuron Disease Association in the UK. Read more from Jessica Hamzelou. Bits and Bytes A “true crime” documentary series has millions of views, but the murders are all AI-generated A look inside the strange mind of someone who created a series of fake true-crime docs using AI, and the reactions of the many people who thought they were real. (404 Media) The AI relationship revolution is already here People are having all sorts of relationships with AI models, and these relationships run the gamut: weird, therapeutic, unhealthy, sexual, comforting, dangerous, useful. We’re living through the complexities of this in real time. Hear from some of the many people who are happy in their varied AI relationships and learn what sucked them in. (MIT Technology Review) Robots are bringing new life to extinct species A creature called Orobates pabsti waddled the planet 280 million years ago, but as with many prehistoric animals, scientists have not been able to use fossils to figure out exactly how it moved. So they’ve started building robots to help. (MIT Technology Review) Lessons from the AI Action Summit in Paris Last week, politicians and AI leaders from around the globe went to Paris for an AI Action Summit. While concerns about AI safety have dominated the event in years past, this year was more about deregulation and energy, a trend we’ve seen elsewhere. (The Guardian)   OpenAI ditches its diversity commitment and adds a statement about “intellectual freedom” Following the lead of other tech companies since the beginning of President Trump’s administration, OpenAI has removed a statement on diversity from its website. It has also updated its model spec—the document outlining the standards of its models—to say that “OpenAI believes in intellectual freedom, which includes the freedom to have, hear, and discuss ideas.” (Insider and Tech Crunch) The Musk-OpenAI battle has been heating up Part of OpenAI is structured as a nonprofit, a legacy of its early commitments to make sure its technologies benefit all. Its recent attempts to restructure that nonprofit have triggered a lawsuit from Elon Musk, who alleges that the move would violate the legal and ethical principles of its nonprofit origins. Last week, Musk offered to buy OpenAI for $97.4 billion, in a bid that few people took seriously. Sam Altman dismissed it out of hand. Musk now says he will retract that bid if OpenAI stops its conversion of the nonprofit portion of the company. (Wall Street Journal)

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

While DOGE’s efforts to shutter federal agencies dominate news from Washington, the Trump administration is also making more global moves. Many of these center on China. Tariffs on goods from the country went into effect last week. There’s also been a minor foreign relations furor since DeepSeek’s big debut a few weeks ago. China has already displayed its dominance in electric vehicles, robotaxis, and drones, and the launch of the new model seems to add AI to the list. This caused the US president as well as some lawmakers to push for new export controls on powerful chips, and three states have now banned the use of DeepSeek on government devices. 

Now our intrepid China reporter, Caiwei Chen, has identified a new trend unfolding within China’s tech scene: Companies that were dominant in electric vehicles are betting big on translating that success into developing humanoid robots. I spoke with her about what she found out and what it might mean for Trump’s policies and the rest of the globe. 

James: Before we talk about robots, let’s talk about DeepSeek. The frenzy for the AI model peaked a couple of weeks ago. What are you hearing from other Chinese AI companies? How are they reacting?

Caiwei: I think other Chinese AI companies are scrambling to figure out why they haven’t built a model as strong as DeepSeek’s, despite having access to as much funding and resources. DeepSeek’s success has sparked self-reflection on management styles and renewed confidence in China’s engineering talent. There’s also strong enthusiasm for building various applications on top of DeepSeek’s models.

Your story looks at electric-vehicle makers in China that are starting to work on humanoid robots, but I want to ask about a crazy stat. In China, 53% of vehicles sold are either electric or hybrid, compared with 8% in the US. What explains that? 

Price is a huge factor—there are countless EV brands competing at different price points, making them both affordable and high-quality. Government incentives also play a big role. In Beijing, for example, trading in an old car for an EV gets you 10,000 RMB (about $1,500), and that subsidy was recently doubled. Plus, finding public charging and battery-swapping infrastructure is much less of a hassle than in the US.

You open your story noting that China’s recent New Year Gala, watched by billions of people, featured a cast of humanoid robots, dancing and twirling handkerchiefs. We’ve covered how sometimes humanoid videos can be misleading. What did you think? 

I would say I was relatively impressed—the robots showed good agility and synchronization with the music, though their movements were simpler than human dancers’. The one trick that is supposed to impress the most is the part where they twirl the handkerchief with one finger, toss it into the air, and then catch it perfectly. This is the signature of the Yangko dance, and having performed it once as a child, I can attest to how difficult the trick is even for a human! There was some skepticism on the Chinese internet about how this was achieved and whether they used additional reinforcement like a magnet or a string to secure the handkerchief, and after watching the clip too many times, I tend to agree.

President Trump has already imposed tariffs on China and is planning even more. What could the implications be for China’s humanoid sector?  

Unitree’s H1 and G1 models are already available for purchase and were showcased at CES this year. Large-scale US deployment isn’t happening yet, but China’s lower production costs make these robots highly competitive. Given that 65% of the humanoid supply chain is in China, I wouldn’t be surprised if robotics becomes the next target in the US-China tech war.

In the US, humanoid robots are getting lots of investment, but there are plenty of skeptics who say they’re too clunky, finicky, and expensive to serve much use in factory settings. Are attitudes different in China?

Skepticism exists in China too, but I think there’s more confidence in deployment, especially in factories. With an aging population and a labor shortage on the horizon, there’s also growing interest in medical and caregiving applications for humanoid robots.

DeepSeek revived the conversation about chips and the way the US seeks to control where the best chips end up. How do the chip wars affect humanoid-robot development in China?

Training humanoid robots currently doesn’t demand as much computing power as training large language models, since there isn’t enough physical movement data to feed into models at scale. But as robots improve, they’ll need high-performance chips, and US sanctions will be a limiting factor. Chinese chipmakers are trying to catch up, but it’s a challenge.

For more, read Caiwei’s story on this humanoid pivot, as well as her look at the Chinese startups worth watching beyond DeepSeek. 

Deeper Learning

Motor neuron diseases took their voices. AI is bringing them back.

In motor neuron diseases, the neurons responsible for sending signals to the body’s muscles, including those used for speaking, are progressively destroyed. It robs people of their voices. But some, including a man in Miami named Jules Rodriguez, are now getting them back: An AI model learned to clone Rodriguez’s voice from recordings.

Why it matters: ElevenLabs, the company that created the voice clone, can do a lot with just 30 minutes of recordings. That’s a huge improvement over AI voice clones from just a few years ago, and it can really boost the day-to-day lives of the people who’ve used the technology. “This is genuinely AI for good,” says Richard Cave, a speech and language therapist at the Motor Neuron Disease Association in the UK. Read more from Jessica Hamzelou.

Bits and Bytes

A “true crime” documentary series has millions of views, but the murders are all AI-generated

A look inside the strange mind of someone who created a series of fake true-crime docs using AI, and the reactions of the many people who thought they were real. (404 Media)

The AI relationship revolution is already here

People are having all sorts of relationships with AI models, and these relationships run the gamut: weird, therapeutic, unhealthy, sexual, comforting, dangerous, useful. We’re living through the complexities of this in real time. Hear from some of the many people who are happy in their varied AI relationships and learn what sucked them in. (MIT Technology Review)

Robots are bringing new life to extinct species

A creature called Orobates pabsti waddled the planet 280 million years ago, but as with many prehistoric animals, scientists have not been able to use fossils to figure out exactly how it moved. So they’ve started building robots to help. (MIT Technology Review)

Lessons from the AI Action Summit in Paris

Last week, politicians and AI leaders from around the globe went to Paris for an AI Action Summit. While concerns about AI safety have dominated the event in years past, this year was more about deregulation and energy, a trend we’ve seen elsewhere. (The Guardian)  

OpenAI ditches its diversity commitment and adds a statement about “intellectual freedom”

Following the lead of other tech companies since the beginning of President Trump’s administration, OpenAI has removed a statement on diversity from its website. It has also updated its model spec—the document outlining the standards of its models—to say that “OpenAI believes in intellectual freedom, which includes the freedom to have, hear, and discuss ideas.” (Insider and Tech Crunch)

The Musk-OpenAI battle has been heating up

Part of OpenAI is structured as a nonprofit, a legacy of its early commitments to make sure its technologies benefit all. Its recent attempts to restructure that nonprofit have triggered a lawsuit from Elon Musk, who alleges that the move would violate the legal and ethical principles of its nonprofit origins. Last week, Musk offered to buy OpenAI for $97.4 billion, in a bid that few people took seriously. Sam Altman dismissed it out of hand. Musk now says he will retract that bid if OpenAI stops its conversion of the nonprofit portion of the company. (Wall Street Journal)

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How Cisco’s platform mindset is meeting the AI era

4. Sovereignty, trust, and the rise of sovereign AI In EMEA, trust and sovereignty were more than talk—they were central to almost every discussion. This came across loud and clear at the event and in Davos in January. Cisco emphasized four dimensions of trust: security, innovation, execution, and sovereign control.​

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SSHStalker botnet brute-forces its way onto 7,000 Linux machines

However, so far the botnet hasn’t done much other than maintaining persistence on infected machines. It has the ability to launch DDoS (distributed denial of service) attacks and conduct cryptomining, but hasn’t done anything yet to monetize its access. That, Flare says, suggests either the operator is still staging the

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ADNOC May Expand LNG Tanker Fleet

Abu Dhabi National Oil Co.’s shipping arm is evaluating the purchase of liquefied natural gas tankers as the state producer accelerates its push into global gas trading. Adnoc Logistics & Services may order four to six vessels to support the group’s expanding international business, Chief Executive Officer Abdulkareem Al Masabi said in an interview Wednesday. The order would come in addition to 14 LNG carriers already contracted to serve export projects in the United Arab Emirates. The fleet expansion underscores Adnoc’s broader effort to build a global gas portfolio. The company’s international investment arm, XRG, has been acquiring stakes in gas fields and export projects abroad while signing supply agreements, as the UAE seeks to position natural gas as a pillar of its economic growth strategy. Some of the new tankers could be ordered this year if a decision is taken to buy them, Al Masabi said without disclosing the potential cost. The company said Thursday that it continues to monitor developments in the global LNG market, but no orders for additional LNG vessels have been decided. Expanding the fleet would give Adnoc greater flexibility to market cargoes internationally rather than relying solely on long-term contracts. Separately, Adnoc L&S is adding vessels to handle rising domestic export capacity. The company will take delivery of two LNG carriers this year — adding to four already received — to transport gas from Abu Dhabi’s existing export terminal at Das Island. A further eight ships will serve the Ruwais LNG terminal under construction on the Gulf coast, which is scheduled for completion in 2028. Al Masabi also said tensions in the Red Sea have “calmed down,” though the route remains sensitive after months of attacks by Iranian-linked Houthi forces prompted many shipping companies to avoid the area. Some operators have recently resumed or

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Global Exploration Signaling ‘Early Recovery’

Global exploration is signaling an “early recovery”, according to an Enverus Intelligence Research (EIR) statement sent to Rigzone by the Enverus team recently. The statement, which highlighted that Enverus was releasing a new global exploration outlook, said EIR “finds that, while global exploration and appraisal activity in 2025 remained near historical lows, long lead indicators such as block awards, new country entries and increased seismic surveying point to a gradual recovery forming from a very low base”. “Despite depressed activity levels, exploration success rates have held steady in the 30 percent to 40 percent range, underscoring a continued focus on prospect high grading, capital discipline and risk weighted exploration strategies,” it added. EIR’s statement noted that offshore exploration accounted for more than 50 percent of total activity in 2025, “driven by infrastructure led exploration and renewed focus on higher impact opportunities”. It also said supermajors and national oil companies are leading the exploration recovery, “particularly in acquiring new acreage in regions where subsurface potential for giant discoveries is matched by above ground conditions that support faster project advancement”. Independent and junior explorers are increasing participation, according to the statement, “signaling broader industry reengagement beyond supermajors and national oil companies”. EIR noted in the statement that it expects “the slow recovery to contribute to a structural supply gap after 2030, as limited exploration today constrains future project pipelines and resource replacement”. EIR Director Patrick Rutty said in the statement, “exploration is not rebounding quickly, but the early indicators are clearly improving”. “Given recent drilling success and diminished concerns over peak demand, the industry is reprioritizing exploration, a dynamic that should drive resource capture to relatively high levels over the next five years but does not yet negate the risk of a structural supply gap later this decade,” he added. In a

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Wright Says China Bought Some VEN Oil From the USA

China has bought some Venezuelan oil that was purchased earlier by the US, according to Energy Secretary Chris Wright. “China has already bought some of the crude that’s been sold by the US government,” Wright told the media in Caracas, without giving details. “Legitimate Chinese business deals under legitimate business conditions” would be fine, he said, when asked about possible joint ventures in the country. China’s Foreign Ministry spokesman Lin Jian said he wasn’t familiar with Wright’s comments when asked at a regular briefing in Beijing on Thursday. The global oil market was jolted in January as US forces swooped into Venezuela and seized former President Nicolás Maduro, with Washington asserting control over the OPEC member’s crude industry. Since then, traders have looked for signals about how export patterns may change, and how output may be revived after years of neglect, sanctions, and underinvestment. The South American country’s so-called “oil quarantine” was essentially over, Wright said on Thursday. Ahead of the intervention, the US blockaded the country’s oil flows with a vast naval force, and seized several vessels. Refiners in China — the largest world’s oil importer — were the biggest buyers of Venezuelan crude before the US move, with the bulk of the imports bought by private processors. Given those flows were sanctioned, they were typically offered with deep discounts, making them attractive to local users. After Maduro’s seizure, President Donald Trump said that Venezuela would turn over 30 million to 50 million barrels of sanctioned oil to the US, according to a post on Truth Social. In addition, Wright told Fox News in January that the US would not cut China off from accessing Venezuelan crude. Several Indian refiners have bought Venezuela’s flagship Merey-grade crude following the US action, and the government has asked state-owned processors to consider buying more Venezuelan and US oil.

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Crude Glut Is a Boon for USA Refiners

Oil markets are awash in crude, keeping a lid on prices and squeezing drillers. For US refiners, though, the glut is proving a windfall.  The big three US refiners — Marathon Petroleum, Valero Energy Corp. and Phillips 66 — all beat estimates in fourth quarter earnings results reported in recent weeks. On calls with analysts, executives signaled a profitable outlook for 2026 and the years ahead, not least because they’re set to benefit from an influx of cheaper and more readily available heavy crudes.  The divergence reflects a growing imbalance in global fuel markets: demand for gasoline, diesel and jet fuel is rising faster than new refining capacity is growing, even as oil producers continue to pump more crude than the world needs. That dynamic allows refiners to buy cheaper feedstock while charging more for finished fuels. “We are very bullish,” Phillips 66 Chief Executive Officer Mark Lashier said on a Feb. 4 call with analysts. Fuel demand is set to grow in 2026, and global refining capacity additions will fall short, Lashier said. The upbeat tone is a far cry from early 2025, when President Donald Trump’s tariff uncertainty clouded the economic outlook and sparked concerns over fuel demand. At the time, the industry braced for a wave of plant closures. Since then, fuel consumption has remained resilient even as the supply glut drove oil prices lower. Brent crude, the global benchmark, is down about 10% over the past 12 months.  Refining margins for America’s top fuel makers, who collectively process some 8 million barrels of oil a day, ended 2025 with profits that were about $5 a barrel higher than the fourth quarter of 2024. With fuel demand forecast to stay strong, the upward momentum for margins is likely to continue. Consultant Rapidan Energy, in its refined product outlook

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Ukraine Strikes 2nd Lukoil Refinery in Russia This Week

Ukrainian drones hit another Russian refinery owned by Lukoil PJSC, as Kyiv’s attacks on its foe’s energy infrastructure resume after a lull last month. Fire crews are working to extinguish a blaze at an oil refinery in the city of Ukhta some 1,550 kilometers (965 miles) from Moscow, following a Ukrainian drone attack, Komi region Governor Rostislav Goldshtein said in a post on Telegram, without giving further details.  The fire broke out at the refinery’s primary unit and a visbreaker, a unit designed to convert heavy residue into lighter oil products, Ukraine’s General Staff said on Telegram. Lukoil didn’t respond to a Bloomberg request for comment.  Ukraine carried out multiple high-precision strikes on Russia’s energy assets last year, leading to refinery shutdowns, disruptions at oil terminals and the rerouting of some tankers. The attacks are designed to curb the Kremlin’s energy revenues and restrict fuel supplies to Russian front lines as the war is about to enter a fifth year.  The attacks slowed in January, targeting three small independent Russian refineries that together account for about 7% of the country’s typical monthly crude throughput. The lull offered temporary relief for Russia’s downstream sector, allowing refinery runs to gradually recover. As processing rates improved, the government lifted its ban on most gasoline exports, enabling producers to resume shipments in February, a month earlier than planned. On Wednesday, however, Ukraine attacked Lukoil’s oil refinery in Russia’s Volgograd region in the first major strike on the country’s oil-processing industry this year. The plant’s design capacity is about 300,000 barrels of crude a day.  The smaller Ukhta refinery has recently been processing just over 60,000 barrels per day.  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

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USA Crude Oil Stocks Rise More Than 8MM Barrels WoW

U.S. commercial crude oil inventories, excluding those in the Strategic Petroleum Reserve (SPR), increased by 8.5 million barrels from the week ending January 30 to the week ending February 6. That’s what the U.S. Energy Information Administration (EIA) highlighted in its latest weekly petroleum status report, which was released on Wednesday and included data for the week ending February 6. According to the EIA report, crude oil stocks, not including the SPR, stood at 428.8 million barrels on February 6, 420.3 million barrels on January 30, and 427.9 million barrels on February 7, 2025. Crude oil in the SPR stood at 415.2 million barrels on February 6, 415.2 million barrels on January 30, and 395.3 million barrels on February 7, 2025, the EIA report revealed. Total petroleum stocks – including crude oil, total motor gasoline, fuel ethanol, kerosene type jet fuel, distillate fuel oil, residual fuel oil, propane/propylene, and other oils – stood at 1.689 billion barrels on February 6, the report highlighted. Total petroleum stocks were down 1.7 million barrels week on week and up 81.9 million barrels year on year, the report pointed out. “At 428.8 million barrels, U.S. crude oil inventories are about three percent below the five year average for this time of year,” the EIA said in its latest weekly petroleum status report. “Total motor gasoline inventories increased by 1.2 million barrels from last week and are about four percent above the five year average for this time of year. Finished gasoline inventories decreased, while blending components inventories increased last week,” it added. “Distillate fuel inventories decreased by 2.7 million barrels last week and are about four percent below the five year average for this time of year. Propane/propylene inventories decreased 5.4 million barrels from last week and are about 36 percent above the five

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Energy providers seek flexible load strategies for data center operations

“In theory, yes, they’d have to wait a little bit longer while their queries are routed to a data center that has capacity,” said Lawrence. The one thing the industry cannot do is operate like it has in the past, where data center power was tuned and then forgotten for six months. Previously, data centers would test their power sources once or twice a year. They don’t have that luxury anymore. They need to check their power sources and loads far more regularly, according to Lawrence. “I think that for that for the data center industry to continue to survive like we all need it, there’s going to have to be some realignment on the incentives to why somebody would become flexible,” said Lawrence. The survey suggests that utilities and load operators expect to expand their demand response activities and budgets in the near term. Sixty-three percent of respondents anticipate DR program funding to grow by 50% or more over the next three years. While they remain a major source of load growth and system strain, 57% of respondents indicate that onsite power generation from data centers will be most important to improving grid stability over the next five years. One of the proposed fixes to the power shortage has been small modular nuclear reactors. These have gained a lot of traction in the marketplace even if they have nothing to sell yet. But Lawrence said that that’s not an ideal solution for existing power generators, ironically enough.

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Nokia predicts huge WAN traffic growth, but experts question assumptions

Consumer, which includes both mobile access and fixed access, including fixed wireless access. Enterprise and industrial, which covers wide-area connectivity that supports knowledge work, automation, machine vision, robotics coordination, field support, and industrial IoT. AI, including applications that people directly invoke, such as assistants, copilots, and media generation, as well as autonomous use cases in which AI systems trigger other AI systems to perform functions and move data across networks. The report outlines three scenarios: conservative, moderate, and aggressive. “Our goal is to present scenarios that fall within a realistic range of possible outcomes, encouraging stakeholders to plan across the full spectrum of high-impact demand possibilities,” the report says. Nokia’s prediction for global WAN traffic growth ranges from a 13% CAGR for the conservative scenario to 16% CAGR for moderate and 22% CAGR for aggressive. Looking more closely at the moderate scenario, it’s clear that consumer traffic dominates. Enterprise and industrial traffic make up only about 14% to 17% of overall WAN traffic, although their share is expected to grow during the 10-year forecast period. “On the consumer side, the vast majority of traffic by volume is video,” says William Webb, CEO of the consulting firm Commcisive. Asked whether any of that consumer traffic is at some point served up by enterprises, the answer is a decisive “no.” It’s mostly YouTube and streaming services like Netflix, he says. In short, that doesn’t raise enterprise concerns. Nokia predicts AI traffic boom AI is a different story. “Consumer- and enterprise-generated AI traffic imposes a substantial impact on the wide-area network (WAN) by adding AI workloads processed by data centers across the WAN. AI traffic does not stay inside one data center; it moves across edge, metro, core, and cloud infrastructure, driving dense lateral flows and new capacity demands,” the report says. An

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Cisco amps up Silicon One line, delivers new systems and optics for AI networking

Those building blocks include the new G300 as well as the G200 51.2 Tbps chip, which is aimed at spine and aggregation applications, and the G100 25.6 Tbps chip, which is aimed at leaf operations. Expanded portfolio of Silicon One P200-powered systems Cisco in October rolled out the P200 Silicon One chip and the high-end, 51.2 Tbps 8223 router aimed at distributed AI workloads. That system supports Octal Small Form-Factor Pluggable (OSFP) and Quad Small Form-Factor Pluggable Double Density (QSFP-DD) optical form factors that help the box support geographically dispersed AI clusters. Cisco grew the G200 family this week with the addition of the 8122X-64EF-O, a 64x800G switch that will run the SONiC OS and includes support for Cisco 800G Linear Pluggable Optics (LPO) connectivity. LPO components typically set up direct links between fiber optic modules, eliminating the need for traditional components such as a digital signal processor. Cisco said its P200 systems running IOS XR software now better support core routing services to allow data-center-to-data-center links and data center interconnect applications. In addition, Cisco introduced a P200-powered 88-LC2-36EF-M line card, which delivers 28.8T of capacity. “Available for both our 8-slot and 18-slot modular systems, this line card enables up to an unprecedented 518.4T of total system bandwidth, the highest in the industry,” wrote Guru Shenoy, senior vice president of the Cisco provider connectivity group, in a blog post about the news. “When paired with Cisco 800G ZR/ZR+ coherent pluggable optics, these systems can easily connect sites over 1,000 kilometers apart, providing the high-density performance needed for modern data center interconnects and core routing.”

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NetBox Labs ships AI copilot designed for network engineers, not developers

Natural language for network engineers Beevers explained that network operations teams face two fundamental barriers to automation. First, they lack accurate data about their infrastructure. Second, they aren’t software developers and shouldn’t have to become them. “These are not software developers. They are network engineers or IT infrastructure engineers,” Beevers said. “The big realization for us through the copilot journey is they will never be software developers. Let’s stop trying to make them be. Let’s let these computers that are really good at being software developers do that, and let’s let the network engineers or the data center engineers be really good at what they’re really good at.”  That vision drove the development of NetBox Copilot’s natural language interface and its capabilities. Grounding AI in infrastructure reality The challenge with deploying AI  in network operations is trust. Generic large language models hallucinate, produce inconsistent results, and lack the operational context to make reliable decisions. NetBox Copilot addresses this by grounding the AI agent in NetBox’s comprehensive infrastructure data model. NetBox serves as the system of record for network and infrastructure teams, maintaining a semantic map of devices, connections, IP addressing, rack layouts, power distribution and the relationships between these elements. Copilot has native awareness of this data structure and the context it provides. This enables queries that would be difficult or impossible with traditional interfaces. Network engineers can ask “Which devices are missing IP addresses?” to validate data completeness, “Who changed this prefix last week?” for change tracking and compliance, or “What depends on this switch?” for impact analysis before maintenance windows.

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US pushes voluntary pact to curb AI data center energy impact

Others note that cost pressure isn’t limited to the server rack. Danish Faruqui, CEO of Fab Economics, said the AI ecosystem is layered from silicon to software services, creating multiple points where infrastructure expenses eventually resurface. “Cloud service providers are likely to gradually introduce more granular pricing models across cloud, AI, and SaaS offerings, tailored by customer type, as they work to absorb the costs associated with the White House energy and grid compact,” Faruqui said.   This may not show up as explicit energy surcharges, but instead surface through reduced discounts, higher spending commitments, and premiums for guaranteed capacity or performance. “Smaller enterprises will feel the impact first, while large strategic customers remain insulated longer,” Rawat said. “Ultimately, the compact would delay and redistribute cost pressure; it does not eliminate it.” Implications for data center design The proposal is also likely to accelerate changes in how AI facilities are designed. “Data centers will evolve into localized microgrids that combine utility power with on-site generation and higher-level implementation of battery energy storage systems,” Faruqui said. “Designing for grid interaction will become imperative for AI data centers, requiring intelligent, high-speed switching gear, increased battery energy storage capacity for frequency regulation, and advanced control systems that can manage on-site resources.”

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Intel teams with SoftBank to develop new memory type

However, don’t expect anything anytime soon. Intel’s Director of Global Strategic Partnerships Sanam Masroor outlined the plans in a blog post. Operations are expected to begin in Q1 2026, with prototypes due in 2027 and commercial products by 2030. While Intel has not come out and said it, that memory design is almost identical to HBM used in GPU accelerators and AI data centers. HBM sits right on the GPU die for immediate access to the GPU, unlike standard DRAM which resides on memory sticks plugged into the motherboard. HBM is much faster than DDR memory but is also much more expensive to produce. It’s also much more profitable than standard DRAM which is why the big three memory makers – Micron, Samsung, and SK Hynix – are favoring production of it.

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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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