add_action('wp_footer', function () { echo ''; }, 99); Nvidia Arsip - todayinasian.com https://todayinasian.com/tag/nvidia/ Sat, 05 Sep 2026 12:27:33 +0000 en-GB hourly 1 https://wordpress.org/?v=7.1 DeepSeek Turns to Huawei Chips as Nvidia Loses China Ground https://todayinasian.com/tech/deepseek-turns-to-huawei-chips-as-nvidia-loses-china-ground/ https://todayinasian.com/tech/deepseek-turns-to-huawei-chips-as-nvidia-loses-china-ground/#respond Sat, 05 Sep 2026 12:27:33 +0000 https://todayinasian.com/?p=2682 TECH – Nvidia’s grip on China’s artificial intelligence market is facing another serious challenge as DeepSeek reportedly prepares to deploy 160,000 Huawei AI accelerators at a massive data center in Inner Mongolia. According to Wccftech, citing a Bloomberg report, the move could become one of the largest known deployments of Huawei AI chips and further […]

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TECH – Nvidia’s grip on China’s artificial intelligence market is facing another serious challenge as DeepSeek reportedly prepares to deploy 160,000 Huawei AI accelerators at a massive data center in Inner Mongolia. According to Wccftech, citing a Bloomberg report, the move could become one of the largest known deployments of Huawei AI chips and further strengthen China’s push to reduce its dependence on Nvidia.

The chips in question are Huawei’s next-generation Ascend 950DT processors, which DeepSeek reportedly plans to use primarily for running AI models rather than training them. The facility is being developed at roughly a 1-gigawatt scale, although the 160,000 accelerators would represent only part of its planned computing capacity. Bloomberg-based reporting also indicates that DeepSeek continues to rely on Nvidia hardware for the more demanding training workloads.

The scale of the order is striking. Wccftech estimates that 160,000 Ascend 950DT chips could be worth around $2.56 billion based on a reported price of approximately 111,000 yuan, or $16,000, per chip. Nvidia’s H20, meanwhile, has reportedly been priced between $15,000 and $25,000. The decision therefore appears to involve more than simply choosing the cheaper processor.

Read More: Yangwang U7 Survives 30,000km Extreme Battery Test

Huawei’s 950DT is built around the company’s DaVinci architecture and reportedly features 144GB of high-bandwidth memory, 4TB/s of memory bandwidth and a 2TB/s chip-to-chip interconnect. Huawei says its larger Atlas 950 SuperPoD can connect up to 8,192 Ascend 950DT processors, illustrating the scale of infrastructure the company is targeting.

The development also echoes comments from DeepSeek CEO Liang Wenfeng earlier this year. He argued that Huawei’s systems could perform the same tasks as Nvidia’s GB300 in terms of latency, although he acknowledged that four Huawei GPUs were needed to match one Nvidia GPU and that Huawei remained roughly two years behind.

For Nvidia, the problem is not simply performance. US export restrictions have limited which advanced processors can reach China, while Beijing has increasingly encouraged domestic alternatives. DeepSeek’s reported decision gives Huawei another major opportunity to improve its ecosystem, production scale and software compatibility.

That is why Wccftech’s report describes China as potentially becoming a “lost cause” for Nvidia. The phrase is an assessment rather than an official Nvidia position, but the direction of China’s AI hardware market is becoming increasingly difficult for the American chipmaker to ignore.

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Nvidia Buys Hugging Face in $12.93 Billion AI Bet https://todayinasian.com/business/nvidia-buys-hugging-face-in-12-93-billion-ai-bet/ https://todayinasian.com/business/nvidia-buys-hugging-face-in-12-93-billion-ai-bet/#respond Fri, 04 Sep 2026 13:06:41 +0000 https://todayinasian.com/?p=2679 BUSINESS – Nvidia is making one of its biggest moves beyond computer chips, agreeing to acquire Hugging Face for $12.93 billion in a deal that could reshape the open artificial intelligence ecosystem. According to Reuters, the semiconductor giant is betting that open AI models will become an increasingly important source of demand as businesses seek […]

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BUSINESS – Nvidia is making one of its biggest moves beyond computer chips, agreeing to acquire Hugging Face for $12.93 billion in a deal that could reshape the open artificial intelligence ecosystem. According to Reuters, the semiconductor giant is betting that open AI models will become an increasingly important source of demand as businesses seek cheaper alternatives to proprietary systems from companies such as OpenAI and Anthropic.

Hugging Face has grown into a major meeting place for AI developers, researchers and companies. Its platform lets users discover, test, customize and share models, datasets, software libraries and applications. Nvidia said more than 18 million developers, researchers and creators use the platform, alongside more than 200,000 companies. The acquisition therefore gives Nvidia something it cannot obtain simply by selling GPUs: a direct connection to a huge community building the next generation of AI software.

The timing is particularly significant because Nvidia’s largest customers are increasingly trying to reduce their dependence on its processors. Meta, Microsoft and OpenAI are among the companies developing their own AI chips, creating a potential threat to Nvidia’s dominance. Reuters reported that strengthening the open-model ecosystem could help Nvidia diversify demand and maintain its influence even if some customers shift part of their computing workloads elsewhere.

Read More: Nvidia Adds $400 Billion in Value After Blowout Earnings

Open-weight models have also gained momentum because they can be customized and, in some cases, operated at lower costs than closed alternatives. Chinese developers such as DeepSeek and Z.ai have demonstrated how quickly open models can become competitive, adding another strategic dimension to Nvidia’s decision.

Nvidia plans to pay about $11.9 billion to Hugging Face shareholders, while up to $1 billion in stock-based incentives will be used to retain employees. The startup was founded in 2016 by Clément Delangue, Julien Chaumond and Thomas Wolf and has attracted investment from companies including Intel, AMD and Amazon.

Perhaps the most important promise is that Hugging Face will remain open. Nvidia CEO Jensen Huang said developers will still be able to choose their preferred models, frameworks, cloud providers and computing platforms. “NVIDIA compute will not be required to build on or deploy through Hugging Face,” Huang wrote.

That assurance matters because Nvidia’s ownership could otherwise raise concerns about preferential treatment for its hardware. For now, the company is positioning the acquisition not simply as a purchase of an AI platform, but as a long-term bet on where AI development itself is heading.

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Nvidia Adds $400 Billion in Value After Blowout Earnings https://todayinasian.com/business/nvidia-adds-400-billion-in-value-after-blowout-earnings/ https://todayinasian.com/business/nvidia-adds-400-billion-in-value-after-blowout-earnings/#respond Fri, 28 Aug 2026 15:53:33 +0000 https://todayinasian.com/?p=2660 BUSINESS – Nvidia stunned Wall Street once again with a quarter that left analysts scrambling to keep up, adding more than $400 billion in market value on the strength of results that reassured investors AI demand isn’t slowing down anytime soon. According to CNBC, the chipmaker’s shares jumped Thursday as its revenue guidance for the […]

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BUSINESS – Nvidia stunned Wall Street once again with a quarter that left analysts scrambling to keep up, adding more than $400 billion in market value on the strength of results that reassured investors AI demand isn’t slowing down anytime soon. According to CNBC, the chipmaker’s shares jumped Thursday as its revenue guidance for the current quarter signaled continued strength across its AI business.

The numbers themselves tell a striking story. Nvidia posted adjusted earnings of $2.22 per share, comfortably ahead of the roughly $2.09 analysts had penciled in, while revenue landed at $96.2 billion against expectations closer to $92.4 billion. That figure represents more than double what the company brought in during the same quarter a year earlier, when revenue sat near $46.7 billion. Data center revenue, which makes up the bulk of Nvidia’s AI-driven business, came in at $89 billion, also topping the roughly $85.7 billion Wall Street had forecast.

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CEO Jensen Huang used the earnings release to frame just how dramatically the competitive landscape has shifted over the past year. “This time last year, one lab alone was driving the buildout,” he said, contrasting that with what he described as the current environment. “Today, we have a golden age of new AI labs and startups, multiple frontier labs scaling in parallel, a thriving open-model ecosystem and physical AI coming online.” He added elsewhere that AI has “reached its inflection point,” pointing to compute increasingly translating directly into revenue.

Reaction on trading desks matched the enthusiasm baked into those numbers. “The valuation today is cheap,” Siddy Jobe, senior portfolio manager at Econopolis Wealth Management, told CNBC’s “Squawk Box Europe,” adding there was still “plenty, plenty of upside” left in the stock. Paul Meeks of Freedom Capital Markets echoed that sentiment on “Squawk Box Asia,” saying he remained bullish on both Nvidia and the wider ecosystem surrounding it.

The rebound carries extra weight given what preceded it. Chip stocks broadly had shed roughly $1 trillion in value back in July before clawing their way back, leaving investors nervous about whether the AI trade still had legs. Thursday’s results appear to have settled that question for now, restoring confidence that the artificial intelligence buildout still has considerable room to run.

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Nvidia Halts New Gaming GPUs as It Doubles Down on AI https://todayinasian.com/tech/nvidia-halts-new-gaming-gpus-as-it-doubles-down-on-ai/ https://todayinasian.com/tech/nvidia-halts-new-gaming-gpus-as-it-doubles-down-on-ai/#respond Tue, 10 Feb 2026 14:41:40 +0000 https://todayinasian.com/?p=1994 TECH – For nearly three decades, Nvidia built its reputation on powering the world’s gaming rigs, but 2026 is shaping up to be an unusual year. According to a report carried by Vietnam.vn, the company is expected to go an entire year without releasing a new mainstream gaming GPU, marking the first such pause since […]

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TECH – For nearly three decades, Nvidia built its reputation on powering the world’s gaming rigs, but 2026 is shaping up to be an unusual year. According to a report carried by Vietnam.vn, the company is expected to go an entire year without releasing a new mainstream gaming GPU, marking the first such pause since the 1990s. The shift reflects a deeper change inside the tech giant, one driven less by graphics innovation and more by the economics of artificial intelligence.

The report, citing industry sources, says Nvidia has temporarily shelved its plans for new mainstream gaming graphics cards. The decision was not caused by technical limitations, but by a broader shortage of DRAM and graphics memory across the semiconductor sector. With supply constrained, the company has chosen to divert precious memory resources toward AI chips, which currently deliver far higher financial returns than gaming hardware.

Read More: Unitree G1 Humanoid Sets Record Snow Walk in Extreme Cold

One casualty of this strategy is a project known internally as “Kicker,” an updated version of the RTX 50 series. Although the design was reportedly completed, it has been postponed indefinitely because the cost of memory makes mass production less viable. At the same time, manufacturing of the existing RTX 50 lineup has been reduced, a move that is pushing up prices and making gaming cards harder to find at official retail levels.

The slowdown may stretch even further. Sources suggest that the next generation of GPUs, code-named Rubin or RTX 60, could be delayed until late 2027. If that happens, it would create the longest gap between gaming GPU generations in the company’s history.

Financial data underscores the transformation. Nvidia’s data center division has generated more than US$51 billion in revenue, while gaming now accounts for less than 8 percent of the company’s total earnings. In effect, the firm that once thrived on gamers is evolving into what observers describe as an “AI empire,” where gaming is no longer the main engine but a legacy segment.

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NVIDIA’s “DoorMan” Lets Robots Open Doors Faster Than Humans https://todayinasian.com/tech/nvidias-doorman-lets-robots-open-doors-faster-than-humans/ https://todayinasian.com/tech/nvidias-doorman-lets-robots-open-doors-faster-than-humans/#respond Sat, 06 Dec 2025 12:00:36 +0000 https://todayinasian.com/?p=1755 TECH – A new breakthrough from NVIDIA reveals a robotic learning system dubbed DoorMan that empowers a humanoid robot to open doors more quickly and reliably than human operators. In tests on the $16,000 Unitree G1, DoorMan relied solely on built-in RGB cameras and avoided traditional crutches like depth sensors or motion-capture markers. In real-world […]

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TECH – A new breakthrough from NVIDIA reveals a robotic learning system dubbed DoorMan that empowers a humanoid robot to open doors more quickly and reliably than human operators. In tests on the $16,000 Unitree G1, DoorMan relied solely on built-in RGB cameras and avoided traditional crutches like depth sensors or motion-capture markers.

In real-world trials, the robot using DoorMan beat experienced human tele-operators completing door-opening tasks up to 31% faster and achieving a higher success rate overall. What’s fascinating is that the robot perceives raw pixel data, thinks, plans, and acts all autonomously no extra calibration needed. The approach is built around a “pixel-to-action” reinforcement learning policy, trained entirely within NVIDIA’s Isaac Lab simulation environment and deployed “zero-shot” on real hardware.

Training such a system wasn’t easy. To overcome the usual stumbling block of “exploration” where a robot learning from scratch might flail forever without finding the right sequence, the team used a clever “staged-reset” technique. Whenever the simulated robot achieved a mid-task milestone, like grabbing the handle, that state was saved and used to begin subsequent trials. This allowed the system to skip redundant learning and focus on mastering the harder parts, like swinging the door open and walking through it.

Read More: Volkswagen’s Numa Concept Reimagines Cars for Cities

Another challenge: once the robot got close enough, the handle might slip out of view. To tackle this, the developers included a method  called Group Relative Policy Optimization,  which nudges the robot to subtly adjust its posture or head angle, keeping the handle visible while continuing the movement.

Rather than only training on one door, the simulation exposed the system to a “multiverse” of possibilities dozens of door types, hinge stiffnesses, handle shapes, textures, and physical dynamics, so that the real world would feel like just another variation.

With an 83% success rate, DoorMan edged out expert human operators (80%) and dwarfed inexperienced controllers (60%). This represents a major leap in “loco-manipulation” a very demanding class of robotics tasks that requires simultaneous locomotion, perception, and manipulation.

DoorMan shows that advanced robotics doesn’t always mean cutting-edge sensors or perfect lab conditions, with clever training and smart simulation, a relatively inexpensive humanoid robot can do what humans do sometimes faster and more consistently.

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Nvidia Hits Historic $4T Market Cap Amid AI Boom https://todayinasian.com/business/nvidia-hits-historic-4t-market-cap-amid-ai-boom/ https://todayinasian.com/business/nvidia-hits-historic-4t-market-cap-amid-ai-boom/#respond Sat, 12 Jul 2025 09:06:48 +0000 https://todayinasian.com/?p=1254 BUSINESS – On July 10, 2025, Nvidia became the first publicly traded company to close the trading day with a $4 trillion market capitalization, closing at $164.10 per share, up 0.75%—a major milestone that highlights its dominance in the booming artificial intelligence (AI) sector. This closing figure pushes Nvidia ahead of rivals, surpassing big tech peers […]

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BUSINESS – On July 10, 2025, Nvidia became the first publicly traded company to close the trading day with a $4 trillion market capitalization, closing at $164.10 per share, up 0.75%—a major milestone that highlights its dominance in the booming artificial intelligence (AI) sector. This closing figure pushes Nvidia ahead of rivals, surpassing big tech peers like Apple ($3.17 trillion) and Microsoft ($3.73 trillion).

This feat was preceded by a brief peak over $4 trillion in morning trading on Wednesday, showing how rapidly the company has surged—more than tripling its value in just over a year after first crossing $1 trillion in June 2023. Over the past 18 months, shares have soared approximately 287%, with about an 18% increase in 2025 alone.

Nvidia’s rise is rooted in its cutting-edge AI chips that power the data centers of major players such as Microsoft, Amazon, Alphabet, and Meta. A senior analyst from Swissquote Bank cautioned that trade tensions, especially U.S. export controls on high-end chips or competition from lower-cost alternatives could pose risks.

Read More: Russia’s New “Digital Predator” Drone Uses Nvidia AI3

Market experts note that Nvidia now represents around 7.5% of the S&P 500 index, the heaviest weight for any single company. Its influence is even more prominent in tech-heavy benchmarks like the Nasdaq and semiconductors indexes. Despite its lofty valuation, Nvidia is trading at about 33 times expected earnings below its five-year average of 41,suggesting cautious optimism among investors.

Financial analysts highlight both the upside and risks. Robert Pavlik from Dakota Wealth states Nvidia’s ascent reflects how deeply corporate investment has shifted toward AI. Meanwhile, caution remains over possible competition; one advisor noted that in-house chip designs by Amazon, Microsoft, or Meta, along with emerging quantum computing breakthroughs, could challenge Nvidia.

The broader markets were relatively unfazed by this milestone. Although U.S. futures softened amid fresh trade tariff announcements, equity benchmarks climbed overall, buoyed by confidence in tech and interest-rate trends hinting at possible Fed easing.

This historic achievement spotlights Nvidia as the vanguard of the AI-driven economic revolution, yet prompts key questions: Will its chip dominance continue amid intensifying competition? And what regulatory or trade risks could impact future growth?

Source: Reuters.com

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Russia’s New “Digital Predator” Drone Uses Nvidia AI https://todayinasian.com/tech/russias-new-digital-predator-drone-uses-nvidia-ai/ https://todayinasian.com/tech/russias-new-digital-predator-drone-uses-nvidia-ai/#respond Thu, 10 Jul 2025 13:20:12 +0000 https://todayinasian.com/?p=1249 TECH – Russia is currently trialing an advanced strike drone, designated the Shahed MS001, powered by Nvidia’s Jetson Orin supercomputer module. The drone has been described by Ukrainian Major General Vladyslav Klochkov as a “digital predator,” capable of independently processing visual inputs, analysing targets, and executing strikes without relying on externally provided coordinates. Roughly the size […]

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TECH – Russia is currently trialing an advanced strike drone, designated the Shahed MS001, powered by Nvidia’s Jetson Orin supercomputer module. The drone has been described by Ukrainian Major General Vladyslav Klochkov as a “digital predator,” capable of independently processing visual inputs, analysing targets, and executing strikes without relying on externally provided coordinates.

Roughly the size of a small loitering munition, the MS001 stands out for its onboard artificial intelligence. The Nvidia Jetson Orin—capable of executing some 67 trillion operations per second provides the drone with the enhanced capability to process thermal imagery, object recognition, telemetry data, and mission logic in real time. This enables autonomous target acquisition and adaptive flight even amid GPS disruption or aggressive electronic warfare environments.

Examination of a downed MS001 revealed a full suite of advanced systems: thermal cameras for night and low‑visibility operation, a spoof‑resistant Nasir GPS with CRPA antenna, field‑programmable gate arrays (FPGA) for adaptive onboard logic, and a radio modem to support swarm coordination with other drones. These components allow the drones not only to operate effectively in contested airspace, but to function in coordinated groups that adapt dynamically to losses in the swarm.

Analysts warn that this platform signifies a strategic leap in UAV design, challenging existing air defence doctrines worldwide. “Most air defence systems are unprepared for this,” Klochkov warned, underscoring that its autonomy and silent operation pose a foundational challenge to current military protocols.

Read More: China Unveils Mosquito-Sized Drone for Covert Surveillance

The MS001, loosely based on Iran’s Shahed‐136 Geran‑2 design, represents Russia’s broader shift toward autonomous aerial systems. A related UAV, known as m, has also been confirmed to house a Jetson Orin chip—on a Chinese-made Leetop A603 carrier board—and includes Western and Chinese components ranging from Sony sensors to Intel modems. These developments highlight serious gaps in export controls: although Nvidia has prohibited sales to Russia, intelligence estimates show at least $17 million worth of Jetson chips funnelled through grey‑market networks via Hong Kong, Singapore, China, and Turkey in 2023 alone.

This evolution coincides with Russia’s establishment of a dedicated Unmanned Systems Forces branch within its armed services in 2025, signalling institutional prioritisation of autonomous drone warfare.

The implications of MS001 and similar autonomous drones are profound: they represent not only a technological milestone but also a strategic pivot in modern conflict. As Soviet‑era doctrine gives way to AI‑driven platforms capable of independent kill‑chain execution, defenders now face a rapidly evolving battlefield where machines perceive, decide, and strike without human command.

The rise of these platforms also raises pressing questions about legal and ethical oversight. Autonomous weapon systems could one day operate in large swarms, deliver payloads or even biological agents, raising alarm about “dystopian scenarios” and the erosion of civilian protection principles.

As nations scramble to match these breakthroughs, both military planners and policymakers are confronting an urgent imperative: devise effective counter‑drone measures, expand detection capabilities, and engage international frameworks to regulate weaponised AI.

Source: DetikINET

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NVIDIA Powers Germany’s Blue Lion Supercomputer for Science https://todayinasian.com/tech/nvidia-powers-germanys-blue-lion-supercomputer-for-science/ https://todayinasian.com/tech/nvidia-powers-germanys-blue-lion-supercomputer-for-science/#respond Sat, 21 Jun 2025 21:22:23 +0000 https://todayinasian.com/?p=1190 TECH – Germany’s Leibniz Supercomputing Centre (LRZ) will soon deploy Blue Lion, a next-generation supercomputer built by Hewlett Packard Enterprise (HPE) using HPE Cray architecture and NVIDIA’s cutting-edge Vera Rubin platform. Unveiled on June 14, 2025, the system delivers approximately 30 times the performance of its predecessor, SuperMUC‑NG, and is tailored to tackle large-scale scientific workloads by integrating simulation, […]

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TECH – Germany’s Leibniz Supercomputing Centre (LRZ) will soon deploy Blue Lion, a next-generation supercomputer built by Hewlett Packard Enterprise (HPE) using HPE Cray architecture and NVIDIA’s cutting-edge Vera Rubin platform. Unveiled on June 14, 2025, the system delivers approximately 30 times the performance of its predecessor, SuperMUC‑NG, and is tailored to tackle large-scale scientific workloads by integrating simulation, data analysis, and artificial intelligence in a unified environment.

The core of Blue Lion combines Rubin GPUs—successors to NVIDIA’s Blackwell series—with NVIDIA’s first custom Vera CPU, designed to operate in tandem. This hardware synergy delivers high bandwidth and minimal latency for demanding compute tasks . To handle the intensive workloads, the system features robust storage and high-speed interconnects supported by HPE’s advanced hardware.

A distinguishing feature of Blue Lion is its 100% direct liquid cooling system. Warm water circulates through the racks, extracting heat without the noise or energy cost of fans. This eco-smart design enables the reuse of thermal energy to heat nearby buildings, boosting energy efficiency and sustainability.

Read More: NVIDIA’s AI‑Driven Humanoids Manage Industrial Tasks

Blue Lion is destined to support research across a variety of fields including climate modelling, fluid dynamics, physics, and machine learning. It will enable scientists to seamlessly combine traditional simulations with real-time AI-driven analyses . The supercomputer is scheduled to be ready for researchers in early 2027, also facilitating collaborative European science initiatives.

In parallel, the Lawrence Berkeley National Lab in the U.S. is developing Doudna, another Vera Rubin‑based supercomputer. Doudna will serve over 11,000 researchers, linking data from a range of instruments like telescopes, genome sequencers, and fusion reactors in real-time workflows. It is expected to deliver approximately tenfold the performance of its predecessor, with improved energy efficiency.

Officials emphasize that Blue Lion and Doudna embody a paradigm shift in high-performance computing. NVIDIA describes the Vera Rubin platform as “collapsing simulation, data and AI into a single, high-bandwidth, low-latency engine for science” . This architectural convergence signals that AI is no longer an add-on, but an integral element of scientific computation.

Both supercomputers are emblematic of a changing landscape wherein exascale systems not only perform traditional computations but also deliver real-time intelligence through AI‑enabled processes. As global scientific challenges grow more complex, infrastructures like Blue Lion are vital for enabling next-generation research capabilities.

Source: medcom.id

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NVIDIA’s AI‑Driven Humanoids Manage Industrial Tasks https://todayinasian.com/tech/nvidias-ai%e2%80%91driven-humanoids-manage-industrial-tasks/ https://todayinasian.com/tech/nvidias-ai%e2%80%91driven-humanoids-manage-industrial-tasks/#respond Thu, 19 Jun 2025 14:25:43 +0000 https://todayinasian.com/?p=1179 TECH – NVIDIA and Hexagon showcased a fleet of humanoid robots capable of operating industrial machinery, inspecting components, and scanning assets, powered by advanced AI and simulation training. Developed primarily for factory and logistics environments, the AEON robot integrates NVIDIA’s comprehensive robotics suite, enabling autonomous task performance in real-world settings. Unveiled at Hexagon LIVE Global, […]

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TECH – NVIDIA and Hexagon showcased a fleet of humanoid robots capable of operating industrial machinery, inspecting components, and scanning assets, powered by advanced AI and simulation training. Developed primarily for factory and logistics environments, the AEON robot integrates NVIDIA’s comprehensive robotics suite, enabling autonomous task performance in real-world settings.

Unveiled at Hexagon LIVE Global, AEON was built through collaboration between Hexagon’s robotics division and NVIDIA. According to Arnaud Robert, President of Hexagon Robotics, “Our goal with AEON was to design an intelligent, autonomous humanoid that addresses the real-world challenges industrial leaders have shared with us”. The robot is engineered to perform precision tasks—such as manipulating parts and inspecting assets—while reducing human error under variable conditions.

Training for AEON occurred almost entirely within simulation environments using NVIDIA’s Isaac platform. Employing Isaac Sim and Isaac Lab, the humanoid learned navigation, locomotion, and manipulation capabilities virtually before physical deployment. This method trimmed development time drastically: what would typically take months to train in labs was achieved in just two to three weeks.

Read More: Huawei Pura 80 Series Delivers Unmatched Battery and Charging Breakthroughs

At the core of AEON’s capabilities is NVIDIA’s robotics stack. It currently operates on Jetson Orin for real-time processing and is slated for an upgrade to the Jetson Thor platform, which offers more power and safety features. Deepu Talla, NVIDIA’s Vice‑President of Robotics and Edge AI, proclaimed, “The age of general-purpose robotics has arrived, due to technological advances in simulation and physical AI”.

AEON also leverages Isaac GR00T foundation models and Mimic tools. These systems enable the robot to learn from human demonstrations and generate synthetic motion—sharp increases in dexterity and adaptability follow. For example, path planning efficiency improved by up to 80%, while AI-driven perception achieved zero-shot capabilities. AEON can autonomously scan parts and conveyor lines, uploading 3D models to Hexagon’s Reality Cloud Studio via Omniverse, which facilitates collaboration and digital twin creation. Lucas Heinzle, VP of R&D at Hexagon Robotics, explained this feature as enabling “integration of reality data capture with NVIDIA Omniverse, streamlining workflows…moving us closer to making digital twins a mainstream tool for collaboration and innovation”.

Pilot deployments are already in motion at factories and warehouses, signaling a broader shift toward smart, automated operations. AEON marks a major step in transitioning humanoid robots from the lab to the factory floor, representing a powerful combination of high-performance hardware, simulated training, and AI-driven autonomy.

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US-China Chip War Threatens Nvidia’s Future https://todayinasian.com/international/us-china-chip-war-threatens-nvidias-future/ https://todayinasian.com/international/us-china-chip-war-threatens-nvidias-future/#respond Wed, 07 May 2025 09:18:40 +0000 https://todayinasian.com/?p=1037 INTERNATIONAL – The escalating technology conflict between the United States and China has intensified with Washington’s latest export restrictions on advanced AI chips, posing significant challenges for Nvidia. The U.S. government has expanded its licensing requirements, effectively barring the sale of high-performance chips like the A100, H100, and even the China-specific A800 to Chinese entities […]

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INTERNATIONAL – The escalating technology conflict between the United States and China has intensified with Washington’s latest export restrictions on advanced AI chips, posing significant challenges for Nvidia. The U.S. government has expanded its licensing requirements, effectively barring the sale of high-performance chips like the A100, H100, and even the China-specific A800 to Chinese entities without special approval.

Nvidia’s Chief Financial Officer, Colette Kress, expressed concerns over the long-term implications of these restrictions, stating, “Over the long term, restrictions prohibiting the sale of our data centre graphic processing units to China… would result in a permanent loss of opportunities for the US industry to compete and lead in one of the world’s largest markets.”

The impact of these measures is already evident. Nvidia’s stock experienced a 1.8% decline following the announcement. While the company has attempted to navigate previous restrictions by introducing the A800 chip tailored for the Chinese market, the new rules threaten even these adaptations.

Read More: Huawei Challenges Nvidia Amid US Export Bans

In response to the tightening U.S. export controls, Chinese tech giant Huawei has accelerated the development and deployment of its own AI chips. The company recently unveiled the CloudMatrix 384 AI chip cluster, which, despite higher energy consumption and operational costs, offers a domestic alternative to Nvidia’s offerings.

The U.S. government’s rationale for these restrictions centers on national security concerns, aiming to prevent China’s military from leveraging advanced AI capabilities. Commerce Secretary Gina Raimondo emphasized the potential risks, stating, “AI can do tremendous and profound harm if it’s in the wrong hands and in the wrong militaries.”

As the U.S.-China tech rivalry intensifies, Nvidia faces the challenge of adapting to a rapidly shifting landscape. The company’s future in one of its largest markets remains uncertain, with broader implications for the global semiconductor industry.

Source: CNBC

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