Latest news with #NvidiaOmniverse
Yahoo
12-06-2025
- Automotive
- Yahoo
BMW enhances production efficiency with advanced Virtual Factory
The BMW Group is advancing its Virtual Factory initiative, with production planners enhancing applications across digital twins of over 30 production facilities to streamline global production planning. The company reports that processes which previously took several weeks for real-world adjustments and testing can now be accurately simulated within the Virtual Factory framework. To prepare for upcoming vehicle launches, the BMW Group plans to integrate more than 40 new or updated models into its global production network by 2027, starting with virtual simulations to ensure stability at the manufacturing sites. The implementation of the Virtual Factory is expected to lead to a reduction in production planning costs by as much as 30%. Virtual planning is integral to the BMW Group's iFACTORY strategy, employing a variety of tools that connect building, equipment, logistics, and vehicle data, alongside 3D simulations of manual processes. This integration is said to create digital twins for all BMW Group plants globally. Using an industrial 3D metaverse application developed on Nvidia Omniverse, real-time simulations facilitate the virtual optimisation of layouts, robotics, and logistics systems. The Virtual Factory is continuously evolving, incorporating generative and agentic AI capabilities, stated the company. For each new product launch, it is critical to ensure compatibility with the production line and to prevent any potential collisions. Within the Virtual Factory, this verification process is automated, utilising construction data and 3D scans. The simulation of vehicle movement and rotation through production lines allows for automatic collision checks, reducing the time required for this process from nearly four weeks to just three days. Previously, identifying potential collisions necessitated the manual guidance of a physical vehicle body through production lines, often requiring extensive weekend work. In the paint shop, this process sometimes involved emptying and cleaning dip coating tanks, resulting in significant costs and time commitments. The BMW Group's Virtual Factory is rapidly expanding its capabilities, which now include automated collision checks, human simulations for optimising manual tasks, and automated mapping of surroundings from existing 3D scans to enhance smart transport systems. Last month, the BMW Group announced that it is enhancing its exploration of all-solid-state battery (ASSB) technology by incorporating large-format ASSB cells from Solid Power into its test vehicle, the BMW i7, which is currently being tested in the Munich area. "BMW enhances production efficiency with advanced Virtual Factory" was originally created and published by Just Auto, a GlobalData owned brand. The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
05-06-2025
- Automotive
- Yahoo
How GM + Nvidia are changing the face of the automotive industry
General Motors is making significant strides in revolutionizing its manufacturing processes through a new partnership with chipmaker Nvidia. Announced in March, the collaboration aims to harness the power of artificial intelligence to enhance automation, cut costs and improve efficiency across GM's factories. At the heart of this partnership is Nvidia's advanced computing technology, which GM is leveraging to build custom AI systems for its manufacturing operations. The automaker is using Nvidia Omniverse with Cosmos to create digital twins of its assembly lines, allowing for virtual testing and simulation of production processes before physical implementation. This is JP Hampstead, co-host with Craig Fuller of the Bring It Home podcast. Welcome to the 25th edition of our newsletter, where we go deep into one of the largest-scale tech-industrial partnerships in the automotive industry. 'Using digital twins, we simulate a running production line before it's constructed, optimizing our planning process and allowing us to scale faster while saving time and money,' explained JP Clausen, GM's executive VP of global manufacturing and sustainability. 'It also helps our team members identify and solve problems more effectively.'These digital simulations enable GM to test and refine new production processes without disrupting existing vehicle manufacturing, a critical advantage as the company balances production of both traditional combustion engines and electric vehicles. The partnership extends to training robotics platforms for operations such as material handling, transport and precision welding. Through a combination of AI and machine learning, GM has developed systems that can identify potential issues in manufacturing, such as leaks in battery packs, allowing for quick repairs and supporting quality control. The automotive industry, led by companies like GM, remains the largest user of industrial robots in America. According to Brookings Institute data, nearly half of the 233,305 industrial robots in the United States are employed in auto manufacturing. Michigan, home to GM's headquarters, accounts for nearly 28,000 robots — approximately 12% of the nation's total. Detroit, in particular, stands out as the robot capital of America, with more than three times the number of industrial robots compared to other metropolitan areas. By 2015, the Detroit-Warren-Dearborn area had 15,115 industrial robots in place, or 8.5 per 1,000 workers, a significant increase from 5,753 robots in high concentration of automation has contributed to a dramatic shift in GM's workforce composition over decades. In 1979, GM employed 468,000 American hourly workers, representing 76% of its U.S. workforce. By 2021, that number had dropped to just 45,000 American hourly workers, or 46% of the company's domestic workforce. GM's innovation hub, the Global Technical Center in Warren, Michigan, employs approximately 24,000 people with an average annual salary of $120,000. This facility has become central to developing the company's AI-driven manufacturing technologies. Using both robotics and proprietary AI tools, GM has implemented systems to inspect welds and paint coats, identifying irregularities and anomalies that might affect vehicle quality. This technology not only improves product quality but also enhances workplace safety by automating potentially hazardous tasks. 'We're using AI and advanced software to help our team minimize ergonomic stressors, enable workplace safety and enhance quality in our manufacturing plants,' notes Clausen. 'Investing in our current and future workforce with better technology helps ensure that our teams have the skills and tools needed as we continue to evolve our manufacturing footprint to meet customer demand.' GM's automation advancements come at a critical time as the company navigates challenges in electric vehicle production. In October 2023, GM announced delays in the production of electric trucks, including the Chevy Silverado EV and GMC Sierra EV, pushing the start date at its Orion Assembly plant from 2024 to late 2025. The company cited the need to 'align its capital investments with electric vehicle demand and implement vehicle engineering improvements to boost profitability' as reasons for the delay. GM's partnership with Nvidia aims to address these challenges by improving engineering efficiency and manufacturing processes. Engineers collaborate in real time on digital twins of manufacturing robotics using Nvidia's Omniverse. (Photo: Nvidia) Despite production delays, GM maintains ambitious plans, projecting to have more than 1 million units of EV capacity in North America by the end of 2025 and to convert 50% of its North American assembly capacity to EV production by automation raises concerns about job displacement, GM emphasizes that AI is being implemented to enhance, not replace, its workforce. The company describes its approach as 'people-centric,' using AI to help employees avoid ergonomic stressors and improve workplace safety. 'It's not about automating everything or building more vehicles faster — our winning formula is driven by a combination of flexible manufacturing, advanced technology, and a talented workforce,' states Clausen. Nevertheless, GM's transformation from 'automaker to platform innovator' suggests a continuing shift toward higher-skilled, technology-focused employment. In its presentation to investors titled 'From Automaker to Platform Innovator,' GM projected that software and new business ventures would grow from $2 billion to $80 billion by 2030, indicating a future in which salaried professionals may increasingly outnumber traditional manufacturing workers. The Nvidia partnership positions GM to remain competitive in an increasingly technology-driven automotive landscape. Jensen Huang, Nvidia's founder and CEO, emphasized the significance of the collaboration: 'The era of physical AI is here, and together with GM, we're transforming transportation, from vehicles to the factories where they're made.' GM plans to build next-generation vehicles on Nvidia DRIVE AGX, based on the Nvidia Blackwell architecture, delivering up to 1,000 trillion operations per second of high-performance compute. This technology will not only power manufacturing but also enhance future advanced driver-assistance systems and in-cabin safety features. As automotive manufacturing continues to advance, GM's strategic investments in AI and robotics may provide a competitive edge. The company has maintained its position as the U.S. sales leader for three consecutive years through 2024, offering what it describes as 'the broadest portfolio of electric vehicles in the industry,' with plans to expand to a dozen EV models by the end of 2025. 'The era of physical AI is here.' – Jensen Huang, Nvidia CEO (Image: Fortune Business Insights) GlobalFoundries Announces $16B U.S. Investment to Reshore Essential Chip Manufacturing and Accelerate AI Growth GlobalFoundries (NASDAQ: GFS) (GF), working with the Trump administration and with support from leading technology companies aiming to onshore critical components of their supply chain, has announced plans to invest $16 billion to expand its semiconductor manufacturing and advanced packaging capabilities across its facilities in New York and Vermont. GF's investment is a strategic response to the explosive growth in artificial intelligence, which is accelerating demand for next-generation semiconductors designed for power efficiency and high-bandwidth performance across data centers, communications infrastructure and AI-enabled devices. Kraft Heinz confirms $3B investment in US manufacturing Kraft Heinz will spend $3 billion on its U.S. manufacturing facilities, the company confirmed to Food Dive. It's the largest investment in its plants in decades. Pedro Navio, president of Kraft Heinz's North America operations, told Reuters earlier this month that planned investments could add 3,500 employees to the Lunchables producer's workforce. Rolls-Royce to invest $24 million in US manufacturing Rolls-Royce has announced a $24 million U.S. investment that will more than double production of backup power generation systems for data centers and create more than 100 new jobs in the U.S. The investment includes a new 250,000ft2 Logistics Operations Centre adjacent to the existing manufacturing facility in Mankato, Minnesota. It will enable Rolls-Royce to increase production capacity for its mtu Series 4000 generator sets, which are in high demand from the rapidly growing data center industry. The post How GM + Nvidia are changing the face of the automotive industry appeared first on FreightWaves. Fehler beim Abrufen der Daten Melden Sie sich an, um Ihr Portfolio aufzurufen. Fehler beim Abrufen der Daten Fehler beim Abrufen der Daten Fehler beim Abrufen der Daten Fehler beim Abrufen der Daten
CNBC
29-05-2025
- Business
- CNBC
We're raising our Nvidia price target after a great quarter and rosy guidance
Nvidia shares jumped in extended trading Wednesday evening after the AI chipmaker reported better-than-expected quarterly revenue and earnings. It also provided an upbeat view of its current second quarter despite restrictions on what it can sell to China. Revenue in its fiscal 2026 first quarter increased 69% year over year to $44.06 billion, beating the $43.31 billion the Street was looking for, according to estimates compiled by data provider LSEG. Adjusted earnings per share increased 57% year over year to 96 cents in the three-month period ended April 27, exceeding the consensus of 93 cents, LSEG data showed. Both EPS and the quarterly estimate excluded charges related to the H20 chip ban in China. Why we own it Nvidia's high-performance graphic processing units (GPUs) are the key driver behind the AI revolution, powering the accelerated data centers being rapidly built around the world. But Nvidia is more than just a hardware story. Through its Nvidia AI Enterprise service, Nvidia is building out its software business. Competitors : Advanced Micro Devices and Intel Most recent buy : Aug 31, 2022 Initiation : March 2019 Bottom line Nvidia's results are proof that there has been no slowdown in the buildout of AI. During the post-earnings conference call, CEO Jensen Huang pointed out four positive surprises since the company's annual GTC event in March that have driven a surge in demand. The first surprise was advancements in reasoning AI, which is included in popular large language models like ChatGPT. According to Huang, reasoning models are creating a step function surge in inference demand, which in turn increases the demand for chips because they are extremely compute-intensive. Another positive surprise was the rescinding of the so-called AI diffusion rules, which ended right at the same time that countries woke up to the importance of AI as an infrastructure, according to Huang. A third positive surprise was the development of enterprise AI agents, which he called "game-changing." The fourth and last surprise is related to industrial AI, and all the on-shoring manufacturing and the building of plants around the world, creating demand for the Nvidia Omniverse. These are important callouts, as they underscore the rapid pace of advancements in artificial intelligence, which continues to drive strong demand for Nvidia's chips. The growing integration of AI into everyday life further reinforces this trend. This is clear evidence that the AI story is still in its early innings. NVDA YTD mountain Nvidia YTD Accordingly, we're raising our price target to $170 from $165. But given Nvidia's rapid 55% stock rise from its 52-week low on April 4 through Wednesday's close of $134, we are keeping our hold-equivalent 2 rating. In after-hours trading, shares added another 5%. Commentary Heading into earnings , some of our key questions centered on the Blackwell ramp, Sovereign AI, hyperscaler demand, and developments in China. 1. Blackwell : After some early supply chain issues, the ramp of the new Blackwell superchip called GB200 has gone well. Despite the vast complexities of building it, Nvidia saw a significant improvement in manufacturing yields and an increase in rack shipments to customers. Blackwell contributed 70% of the $34.16 billion of data center compute revenue in the quarter. Overall, data center revenues, which also included networking sales, increased 73% year over year to $39.1 billion, slightly missing estimates of $39.36 billion, according to FactSet. Nvidia is always innovating its chipsets, making them more powerful and efficient with every new iteration, but also backwards compatible. The next product on its roadmap is the Blackwell Ultra or GB300. The company said samplings of these systems began earlier this month at the major cloud service providers, and it expects production shipments to start later this quarter. Nvidia is anticipating a smooth ramp of the Blackwell Ultra based on what it learned from Blackwell. 2. Sovereign AI: During the call, Huang called Sovereign AI "a new growth engine" for the company as countries around the world build out national AI factories. " Countries are racing to build national AI platforms to elevate their digital capabilities," the CEO said. Later, he likened the need for countries to invest in AI infrastructure to their past investments in electricity and the internet. Rules on how countries are purchasing AI chips from Nvidia have been dynamic lately, with President Donald Trump ending the AI diffusion rules in favor of a new policy to promote AI tech with trusted partners. One way is through trade agreements, like what we saw out of the Middle East a few weeks ago. Next up could be Europe. Huang said he will be traveling through the continent next week and " just about every country needs to build out AI infrastructure and there are umpteen AI factories being planned." 3. Hyperscalers : There's been no let-up or digestion in demand from the so-called hyperscalers, which is another term for large data center and cloud service providers like Alphabet and Oracle as well as Club names Amazon , Microsoft , and Meta Platforms . They all signaled alongside, their latest earnings reports, their intentions to keep spending aggressively on AI. Nvidia said Wednesday that on average, major hyperscalers are each deploying nearly 1,000 NVL72 racks or 72,000 Blackwell GPUs per week and are on track to further increase output this quarter. One example that CFO Colette Kress gave was that Microsoft has already deployed tens of thousands of Blackwell GPUs, but that's expected to increase to the hundreds of thousands. 4. China : As for its business in China, Nvidia shipped out $4.6 billion worth of H20s prior to the new export licensing requirement. It was unable to ship an additional $2.5 billion of H20 revenue in the quarter. The export license changes, which went into effect in mid-April, caused the company to disclose it will record a $5.5 billion charge in the quarter tied to H20 inventory, purchase commitments, and "related reserves." In a bit of good news, Nvidia said Wednesday it only had to record a $4.5 billion charge this quarter, less than originally anticipated, because it was able to reuse certain materials. Nvidia said it is still evaluating its options to supply chips to the region in compliance with the U.S. government's export control rules. Reuters reported over the weekend that Nvidia is planning mass production of a new AI chip for China that is compliant with restrictions. Huang said on the earnings call that Nvidia does not have anything right now to announce, but the company is "considering it" and "thinking about it." Losing access to the China AI accelerator market would have a material adverse impact on Nvidia's business, Kress said on the earnings call, a market she thinks will grow to nearly $50 billion. Huang echoed that sentiment in an interview with Jim Cramer for Wednesday evening's "Mad Money." Huang said that trade with China is important if the U.S. wants to be the global AI leader. "There are so many developers there [in China], and because the world is going to adopt technology from one country or another — and we prefer it to be the American technology stack," the CEO told Jim. Guidance Looking at Nvidia's fiscal 2026 second quarter outlook, the company expects revenue to be approximately $45 billion, plus or minus 2%. This view was slightly below the consensus estimate of $45.9 billion, according to LSEG. However, it reflects a loss of approximately $8 billion in H20 revenue due to the export control limitations. Moving down the line, Nvidia expects fiscal Q2 adjusted gross margins of 72%, plus or minus 50 basis points. That's roughly inline with the 72.1% expected per FactSet. According to an earnings snapshot note from Truist, Nvidia's implied fiscal second quarter EPS guidance is 98 cents at the midpoint, one penny shy of the 99-cent consensus, according to LSEG. This is pretty solid considering the loss of sales of H20 chips in China. (Jim Cramer's Charitable Trust is long NVDA, AMZN, META, MSFT. See here for a full list of the stocks.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Jim waits 45 minutes after sending a trade alert before buying or selling a stock in his charitable trust's portfolio. If Jim has talked about a stock on CNBC TV, he waits 72 hours after issuing the trade alert before executing the trade. THE ABOVE INVESTING CLUB INFORMATION IS SUBJECT TO OUR TERMS AND CONDITIONS AND PRIVACY POLICY , TOGETHER WITH OUR DISCLAIMER . NO FIDUCIARY OBLIGATION OR DUTY EXISTS, OR IS CREATED, BY VIRTUE OF YOUR RECEIPT OF ANY INFORMATION PROVIDED IN CONNECTION WITH THE INVESTING CLUB. NO SPECIFIC OUTCOME OR PROFIT IS GUARANTEED.
Yahoo
14-05-2025
- Business
- Yahoo
Nvidia and AMD partner with Humain to develop AI data centres
Nvidia and Advanced Micro Devices (AMD) have partnered with Saudi Arabian AI company Humain to supply semiconductors for a large-scale data centre project. Humain, a subsidiary of Saudi Arabia's Public Investment Fund, aims to establish the Saudi Arabia as an international AI powerhouse by combining state-of-the-art infrastructure, advanced AI models, digital platforms, and human capital development. The company plans to build AI factories with a projected capacity of up to 500MW, powered by several hundred thousand of Nvidia's most advanced GPUs over the next five years. The first phase of deployment includes an 18,000 Nvidia GB300 Grace Blackwell AI supercomputer with NVIDIA InfiniBand networking. These hyperscale AI data centres are designed to provide a secure foundation for training and deploying sovereign AI models at scale, enabling industries in Saudi Arabia and globally to accelerate innovation and digital transformation. In addition, Humain will deploy the Nvidia Omniverse platform as a multi-tenant system to enhance the development of physical AI and robotics through simulation and operation of physical environments. Humain CEO Tareq Amin said: 'Our partnership with Nvidia is a bold step forward in realizing the Kingdom's ambitions to lead in AI and advanced digital infrastructure. 'Together, we are building the capacity, capability and a new globally enabled community to shape a future powered by intelligent technology and empowered people.' Additionally, AMD has signed an agreement with Humain to develop a strong AI infrastructure. This network of AMD-based AI computing centres will extend from Saudi Arabia to the US and aims to support a wide range of AI workloads across corporate, start-up, and government markets. The open-design AI superstructure will be optimised to power AI workloads across various markets. AMD will provide its AI compute portfolio and the AMD ROCm open software ecosystem, while Humain will manage the delivery of the hyperscale data center, sustainable power systems, and global fibre interconnects. The two parties have committed up to $10bn for the deployment of 500MW of AI computing power over the next five years. The collaboration is well underway, with initial deployments across key global regions. By early 2026, the partnership is expected to activate multi-exaflop capacity, supported by next-generation AI silicon, modular data centre zones, and a software platform stack focused on developer enablement, open standards, and interoperability. "Nvidia and AMD partner with Humain to develop AI data centres" was originally created and published by Verdict, a GlobalData owned brand. The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site. Sign in to access your portfolio
Business Journals
25-04-2025
- Science
- Business Journals
Florida Atlantic University receives Department of Defense grant, will acquire Nvidia technology
The school will use Nvidia technology that could eventually be used to help the Air Force modernize its national defense and space operations. Story Highlights Florida Atlantic University receives $800,000 grant for AI research. FAU will acquire Nvidia technology for autonomous AI systems development. Research aims to modernize Air Force defense and space operations. Florida Atlantic University is poised to obtain state-of-the-art technology from the chipmaker Nvidia after receiving an $800,000 grant from the U.S. Department of Defense Air Force Office of Scientific Research. FAU's Center for Connected Autonomy and Artificial Intelligence will use the grant to develop autonomous AI systems. That technology could eventually be used to help the Air Force modernize its national defense and space operations, said Dimitris Pados, principal investigator and director of the CA-AI. 'AI has far-reaching implications for the air and space forces within the U.S. Department of the Air Force,' he said. "Ensuring these systems are rigorously tested will be critical for their integration into operations, where precision, trust and adaptability are paramount." While generative AI models are trained on enormous amounts of text and image data, enabling them to generate language and communicate abstract concepts, they are limited when it comes to understanding the physical world. To build a physical AI system, researchers need to train autonomous machines in controlled environments. That can help robots perform complex physical tasks and facilitate interactions between machines and humans, FAU reports. The university will use the DOD funding to acquire Nvidia graphics processing units, chips that can handle intensive tasks such as graphics processing, renderings and AI. It will also use Nvidia infrastructure to develop virtual environments that represent the real world and generate data to train AI for robotics and wireless networks. FAU will also use cameras, LiDAR sensors and augmented reality/virtual reality headsets to collect and render video and images that will be used in photo generation software in the Nvidia Omniverse, a platform for building 3D applications. The platform will "enable new U.S. Department of Defense-related research opportunities such as test and evaluation of AI training datasets, learning with faulty and missing data, development of a digital spectrum twin for NextG communications and networking, simulation of schools of biorobotic fish or swarms of drones, among others,' said George Sklivanitis, co-principal investigator and professor at the FAU College of Engineering and Computer Science. For more stories like this one, sign up for Miami Inno newsletters from the South Florida Business Journal and the American Inno network.
