Latest news with #DensityAI
Yahoo
5 days ago
- Business
- Yahoo
Tesla 確認解散 Dojo AI 超級電腦團隊，集中火力推 AI5／AI6 晶片
L'amministratore delegato di Tesla Elon Musk sale su un'auto Tesla mentre lascia un hotel a Pechino, in Cina, il 31 maggio 2023. REUTERS/Tingshu Wang Elon Musk 在 X 發文確認 Bloomberg 早前爆料指 Tesla 已經解散內部 Dojo AI 超級電腦團隊的消息，同時解釋指因為 AI5、AI6 推理晶片的表現已經足夠好，而且易於訓練，所以不必要分散公司資源到開發設計不一樣的晶片。就如早前 Elon Musk 自己所透露，AI5 和 AI6 晶片會分別由 TSMC 和 Samsung 生產，後者更會有深度合作。 Dojo 曾被視為 Tesla 全自動駕駛（FSD）及 Optimus 人形機械人背後的關鍵運算平台，負責從海量車載影像數據中進行模型訓練。原 Dojo AI 團隊成員在離開 Tesla 後，已經有 20 名核心工程師迅速成立 DensityAI，包括帶領項目的資深工程主管 Peter Bannon，主打 AI 數據中心服務。 廣告 廣告 更多內容： Tesla Disbands Dojo Supercomputer Team, Unwinding Key AI Effort 廣告 廣告 Former Tesla Executives Create Data Center Firm DensityAI Elon Musk 帶錢解救 Samsung 晶片落後困局？Tesla 165 億美元 8 年長約是台積電不會做的讓步 緊貼最新科技資訊、網購優惠，追隨 Yahoo Tech 各大社交平台！ 🎉📱 Tech Facebook： 廣告 廣告 🎉📱 Tech Instagram： 🎉📱 Tech WhatsApp 社群： 🎉📱 Tech WhatsApp 頻道： 🎉📱 Tech Telegram 頻道：
Time of India
5 days ago
- Automotive
- Time of India
Meet Ganesh Venkataramanan, former Tesla Dojo lead building DensityAI's new all-in-one AI system for self-driving cars
Source: LinkedIn In the fast-paced realm of automotive AI , Ganesh Venkataramanan , ex-lead of Tesla's Dojo supercomputer, has launched DensityAI, a groundbreaking startup set to transform how self-driving car AI systems are developed and deployed. Backed by a team of 20 senior Tesla Dojo engineers, DensityAI focuses on creating a bespoke full-stack AI platform tailored specifically to meet the intense computational and data demands of autonomous vehicles . By combining advanced hardware and software innovation, DensityAI aims to streamline AI training and deployment for automakers, positioning itself as a pivotal player in the future of autonomous driving technology. Former Tesla's Dojo Ganesh Venkataramanan builds DensityAI to revolutionise AI technology Ganesh Venkataramanan's journey began with Tesla, where he spent seven years leading the development of Dojo, Tesla's proprietary AI supercomputer engineered to train neural networks using vast amounts of driving data. His background in chip design, sharpened during his tenure at AMD, now fuels his mission at DensityAI to deliver an end-to-end AI platform tailor-made for the automotive sector. Unlike generic AI solutions, DensityAI focuses on the unique challenges faced by carmakers — notably the enormous computational power and data handling required for autonomous driving, sensor fusion, simulation, and edge computing. The startup's platform aims to eliminate the need for automakers to build expensive and complex AI infrastructure in-house, positioning itself as a plug-and-play solution for the industry. DensityAI focuses on automotive AI challenges with plans to expand into robotics Self-driving vehicles generate and process colossal volumes of data from cameras, lidars, radars, and other sensors. The computational muscle needed to make sense of this data in real time is immense, often demanding data centers as powerful and intricate as the vehicles themselves. Currently, Nvidia holds a dominant position in the automotive AI chip market. However, DensityAI seeks to carve out its own niche by concentrating on automotive-specific AI hardware and software needs, rather than applying a broad, one-size-fits-all approach. Reports indicate DensityAI is already engaged in talks with car manufacturers and preparing for a significant funding round valued in the hundreds of millions. While cars are DensityAI's primary focus, its ambitions extend further. The company plans to target other industries reliant on real-time AI processing, including robotics and any sector that benefits from scalable data center infrastructure designed for fast, efficient AI computation. Tesla AI team changes reveal safety challenges in driverless car Venkataramanan's exit from Tesla follows a trend of high-profile departures from the company's AI division. In 2023, Andrej Karpathy, Tesla's former AI director, returned to OpenAI, and others have launched startups or raised concerns about the complexities and safety challenges in achieving full vehicle autonomy. Despite this, Tesla continues to push forward, reportedly collaborating with Samsung on next-generation AI chips. Meanwhile, startups like DensityAI benefit from the influx of top-tier talent looking to specialize in solving specific automotive AI problems — signaling a shift in the competitive landscape. Developing AI systems for self-driving cars is not merely an engineering challenge — it is also a regulatory and safety challenge. Automakers face intense scrutiny over safety, testing protocols, and deployment standards, making reliability and trustworthiness paramount. Industry experts emphasise that success in this market requires more than innovation; it demands scalable, reliable, and compliant AI solutions that can safely integrate with real-world driving conditions. DensityAI's founders bring a unique advantage here: their experience in creating one of the world's most sophisticated AI training platforms. DensityAI targets faster, smarter AI training and deployment for automakers Observers have described DensityAI as a 'full-stack AI data center company', highlighting its comprehensive strategy that combines custom hardware design with advanced software tools. This integration offers automakers a streamlined solution for training, deploying, and maintaining autonomous driving AI systems — potentially transforming the way AI data processing is handled in the automotive sector. The company's first products are expected to launch soon, targeting improvements in AI training speed, deployment efficiency, and overall cost-effectiveness. Success here could redefine the industry's approach to AI infrastructure. With a team that has already built record-breaking AI systems, DensityAI is betting it can replicate that success and accelerate the future of safe, intelligent autonomous driving. By offering tailored AI infrastructure designed specifically for automotive needs, DensityAI could help car manufacturers overcome current bottlenecks and speed up the rollout of next-generation self-driving technologies. Also Read | Intel CEO Lip-Bu Tan to meet Donald Trump in White House amid US-China semiconductor security tensions: Report AI Masterclass for Students. Upskill Young Ones Today!– Join Now
The Star
5 days ago
- Automotive
- The Star
Tesla disbands dojo supercomputer team, unwinding key AI effort
Tesla Inc. is disbanding its Dojo team and its leader will leave the company, according to people familiar with the matter, upending the automaker's effort to build an in-house supercomputer for developing driverless-vehicle technology. Peter Bannon, who was heading up Dojo, is leaving and Chief Executive Officer Elon Musk has ordered the effort to be shut down, according to the people, who asked not to be identified discussing internal matters. The team has lost about 20 workers recently to newly formed DensityAI, and remaining Dojo workers are being reassigned to other data center and compute projects within Tesla, the people said. Tesla plans to increase its reliance on external technology partners, including Nvidia Corp. and Advanced Micro Devices Inc. for compute and Samsung Electronics Co. for chip manufacturing, the people said. Musk's order marks a major shift for a program years in the making, with Dojo once positioned as central to Tesla's multibillion-dollar effort to pull ahead in the artificial intelligence race. Tesla and Bannon didn't respond to requests for comment. After Bloomberg News first reported the developments, Musk confirmed Tesla's change in approach, writing on X that the next-generation AI chips going into the company's vehicles "will be excellent for inference and at least pretty good for training. All effort is focused on that.' Tesla's shares rebounded after a slight decline overnight, rising 2.1% at 9:52am in New York on Friday. The stock had fallen 20% this year through Thursday's close. Dojo is a Tesla-designed supercomputer used to train the machine-learning models behind the electric-vehicle maker's Autopilot and Full Self-Driving systems, as well as its Optimus humanoid robot. It's based on a custom in-house chip known as D1 and was meant to be used in training AI models. The computer takes in video data captured by vehicles and rapidly processes it to improve the company's algorithms. Analysts have said Dojo could be a key competitive advantage, with Morgan Stanley estimating in 2023 that it could eventually add $500 billion to Tesla's market value. DensityAI, which is poised to come out of stealth soon, is working on chips, hardware and software that will power data centers for AI that are used in robotics, by AI agents and for automotive applications, among other sectors, Bloomberg reported this week. The company was founded by Ganesh Venkataramanan, the former head of Dojo, and ex-Tesla employees Bill Chang and Ben Floering. Talent drain Tesla has seen an exodus of key talent this year as it grapples with rising competition, falling sales and a consumer backlash to Musk's political activity. Milan Kovac, the head of engineering for Optimus, and David Lau, vice president of software engineering, left earlier this year. Bloomberg also reported in June that longtime Musk confidant Omead Afshar had parted ways with the company. The EV maker reached a US$16.5bil (RM69.8bil) deal last month with Samsung to secure AI semiconductors through 2033. The plan is for an upcoming plant in Texas to produce Tesla's next-generation AI6 chip, diversifying Tesla's sourcing beyond leading chipmaker Taiwan Semiconductor Manufacturing Co. Musk hinted at a strategic pivot during Tesla's most recent quarterly earnings call, suggesting future iterations of the company's in-house technology could converge with that of its partners. "Thinking about Dojo 3 and the AI6 inference chip, it seems like intuitively, we want to try to find convergence there, where it's basically the same chip,' Musk said on the July 23 call. Tesla's CEO also let on early last year that the company might not pursue Dojo in perpetuity, and that it may instead lean more on external partners. "We're pursuing the dual path of Nvidia and Dojo,' Musk said in January 2024. "I would think of Dojo as a long shot. It's a long shot worth taking because the payoff is potentially very high. But it's not something that is a high probability. It's not like a sure thing at all.' – Bloomberg
Time of India
6 days ago
- Automotive
- Time of India
Tesla shuts down its AI training supercomputer Dojo, loses 20 key execs to company founded by Ganesh Venkataramanan
Tesla is reportedly dissolving its Dojo supercomputer team, abandoning its in-house chip development for autonomous driving technology. According to a report by Bloomberg, - Tesla Inc. is disbanding its Dojo team and its leader will leave the company, according to people familiar with the matter, upending the automaker's effort to build an in-house supercomputer for developing driverless-vehicle technology. The Dojo shutdown coincides with Tesla's board offering Elon Musk a $29 billion compensation package to prioritize Tesla's AI goals over his other ventures, including xAI, a pure-play AI company. Meet DensityAI, AI startup founded by former Dojo head Ganesh Venkataramanan The move marks a significant pivot for the automaker, which has increasingly leaned on external partners like Nvidia, AMD, and Samsung for its AI and compute needs. Peter Bannon, the lead of the Dojo project, is leaving Tesla, and the remaining team members will reportedly be reassigned to other data center and compute initiatives within the company, the report said citing anonymous sources. The decision follows the exit of approximately 20 Dojo team members who left to form DensityAI, a new AI startup founded by former Dojo head Ganesh Venkataramanan , alongside ex-Tesla employees Bill Chang and Ben Floering. DensityAI is preparing to exit stealth mode and is focused on developing chips, hardware, and software to power AI-driven data centers for robotics, AI agents, and automotive applications. The startup aims to address high-performance computing needs with an emphasis on scalable, energy-efficient solutions for next-generation AI workloads. As Tesla recalibrates, DensityAI's emergence could reshape the AI hardware landscape, leveraging the expertise of former Dojo engineers to challenge established players in the AI data center space. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like 75% off installation and replacement for LeafFilter LeafFilter Gutter Protection Get Rates Undo What makes shutting down of Dojo important The disbanding of Dojo comes at a pivotal moment for Tesla. CEO Elon Musk has been repositioning Tesla as an AI and robotics company, despite challenges with its limited robotaxi launch in Austin in June 2025. The launch, which involved Model Y vehicles with a human co-pilot, faced criticism after reports of erratic driving behavior. Dojo, first announced in 2019, was pitched as the backbone of Tesla's AI ambitions, particularly for achieving full self-driving (FSD) by processing vast amounts of video data. Musk highlighted Dojo as recently as Tesla's Q2 2025 earnings call, though his focus shifted to Cortex, a new AI training supercluster at Tesla's Austin headquarters. Dojo combined a supercomputer with Tesla's in-house D1 chip, unveiled at AI Day 2021. Presented by Venkataramanan, the D1 was designed to work alongside Nvidia GPUs to power Dojo, with a next-gen D2 chip planned to address data flow bottlenecks. In 2023, Morgan Stanley estimated Dojo could add $500 billion to Tesla's market value by enabling robotaxi services and software revenue. However, by August 2024, Musk's rhetoric pivoted to Cortex, signaling a strategic shift. Tesla is looking externally Tesla's reliance on external partners is growing. A $16.5 billion deal with Samsung, signed last month, will produce Tesla's AI6 inference chips, designed to scale from FSD and Optimus humanoid robots to high-performance AI training. Tesla is also deepening ties with Nvidia for compute power and AMD for additional chip solutions. During the Q2 earnings call, Musk hinted at streamlining efforts, suggesting convergence between Dojo 3 and the AI6 chip to avoid redundancies. AI Masterclass for Students. Upskill Young Ones Today!– Join Now
India Today
6 days ago
- Automotive
- India Today
Meet Ganesh Venkataramanan, the ex-Tesla Dojo chief secretly building DensityAI with 20 former teammates
Ganesh Venkataramanan (Photo: LinkedIn) Ganesh Venkataramanan leads DensityAI, a startup focused on automotive AI Around 20 ex-Tesla Dojo engineers have joined DensityAI Startup aims to simplify costly AI infrastructure for carmakers A stealthy new player has just pulled into the fast lane of the automotive AI race, and it's being driven by a man who knows a thing or two about horsepower in the digital age. Ganesh Venkataramanan, the former mastermind behind Tesla's Dojo supercomputer project, has resurfaced at the wheel of DensityAI, a startup aiming to supercharge how automakers train and deploy self-driving technology. And he hasn't come alone, around 20 of his old Tesla colleagues, many senior members of the Dojo engineering squad, are riding shotgun. The mission? Build a full-stack AI platform, from chips to software, designed specifically for the unique demands of the automotive world. Unlike generic AI systems, DensityAI wants to create hardware and tools optimised for the immense data-crunching required by autonomous vehicles, covering everything from sensor fusion and simulation to edge computing. From Tesla's Dojo to DensityAI Venkataramanan left Tesla in late 2023 after a seven-year stint that saw him lead Dojo, the custom-built supercomputer used to train Tesla's neural networks on a flood of driving footage. Before that, he honed his chip-design credentials at AMD. Now, he's channelling that expertise into a new platform that could remove one of the biggest headaches for carmakers: building and maintaining costly AI infrastructure in-house. Self-driving technology demands colossal computing muscle, and the data centres needed to power it are often as complex to manage as the cars themselves. DensityAI is positioning itself as the plug-and-play solution â€' delivering high-performance, high-density computing tailored for the realities of the road. Nvidia might dominate the automotive AI chip market today. Still, several reports claim DensityAI could grab a chunk of the action by zooming in on automotive-specific needs, instead of the one-size-fits-all approach favoured by bigger players. Early whispers suggest the company is already in talks with manufacturers and eyeing a major funding round worth hundreds of millions as it emerges from stealth mode. While the startup's primary focus is on cars, its ambitions stretch further. Robotics and other industries reliant on real-time AI processing are also in its sights, with the broader aim of creating data centre infrastructure that can scale efficiently across sectors. Venkataramanan's departure is just the latest in a line of high-profile exits from Tesla's AI ranks. In 2023, Andrej Karpathy, the company's former AI director, headed back to OpenAI. Others have left to start ventures of their own or voice concerns about the complexity and safety hurdles of delivering true autonomy. Tesla itself isn't slowing down, it's reportedly teaming up with Samsung on its next-gen AI chips, but the flow of talent into new, specialised startups like DensityAI highlights shifting dynamics in the sector. Industry experts caution that breaking into this market isn't just about clever engineering. Developing reliable, scalable AI systems for vehicles is a long game, and the road is lined with regulatory speed bumps. Automakers face intense scrutiny when it comes to safety, testing, and deployment, making trust as important as raw performance. Even so, DensityAI's founders have a rare advantage: they've already built one of the most sophisticated AI training platforms on the planet. If they can apply that same focus to solving the bottlenecks facing carmakers, they could help speed up the rollout of safer, smarter autonomous systems. Observers on X have dubbed DensityAI a 'full-stack AI data centre company', meaning it plans to compete on both the hardware and the software fronts. That holistic approach could prove to be a game-changer, giving automakers a one-stop shop for training, deploying, and maintaining their AI. DensityAI's first products, expected to launch in the coming months, will aim to help carmakers train and deploy AI faster, more intelligently, and more cost-effectively. If Venkataramanan and his crew pull it off, they won't just be tweaking how cars think, they could redefine how the entire industry processes data. After all, this is a team that's already built a record-breaking AI system once. Now, they're betting they can do it again, and this time, the whole automotive world might be along for the ride. A stealthy new player has just pulled into the fast lane of the automotive AI race, and it's being driven by a man who knows a thing or two about horsepower in the digital age. Ganesh Venkataramanan, the former mastermind behind Tesla's Dojo supercomputer project, has resurfaced at the wheel of DensityAI, a startup aiming to supercharge how automakers train and deploy self-driving technology. And he hasn't come alone, around 20 of his old Tesla colleagues, many senior members of the Dojo engineering squad, are riding shotgun. The mission? Build a full-stack AI platform, from chips to software, designed specifically for the unique demands of the automotive world. Unlike generic AI systems, DensityAI wants to create hardware and tools optimised for the immense data-crunching required by autonomous vehicles, covering everything from sensor fusion and simulation to edge computing. From Tesla's Dojo to DensityAI Venkataramanan left Tesla in late 2023 after a seven-year stint that saw him lead Dojo, the custom-built supercomputer used to train Tesla's neural networks on a flood of driving footage. Before that, he honed his chip-design credentials at AMD. Now, he's channelling that expertise into a new platform that could remove one of the biggest headaches for carmakers: building and maintaining costly AI infrastructure in-house. Self-driving technology demands colossal computing muscle, and the data centres needed to power it are often as complex to manage as the cars themselves. DensityAI is positioning itself as the plug-and-play solution â€' delivering high-performance, high-density computing tailored for the realities of the road. Nvidia might dominate the automotive AI chip market today. Still, several reports claim DensityAI could grab a chunk of the action by zooming in on automotive-specific needs, instead of the one-size-fits-all approach favoured by bigger players. Early whispers suggest the company is already in talks with manufacturers and eyeing a major funding round worth hundreds of millions as it emerges from stealth mode. While the startup's primary focus is on cars, its ambitions stretch further. Robotics and other industries reliant on real-time AI processing are also in its sights, with the broader aim of creating data centre infrastructure that can scale efficiently across sectors. Venkataramanan's departure is just the latest in a line of high-profile exits from Tesla's AI ranks. In 2023, Andrej Karpathy, the company's former AI director, headed back to OpenAI. Others have left to start ventures of their own or voice concerns about the complexity and safety hurdles of delivering true autonomy. Tesla itself isn't slowing down, it's reportedly teaming up with Samsung on its next-gen AI chips, but the flow of talent into new, specialised startups like DensityAI highlights shifting dynamics in the sector. Industry experts caution that breaking into this market isn't just about clever engineering. Developing reliable, scalable AI systems for vehicles is a long game, and the road is lined with regulatory speed bumps. Automakers face intense scrutiny when it comes to safety, testing, and deployment, making trust as important as raw performance. Even so, DensityAI's founders have a rare advantage: they've already built one of the most sophisticated AI training platforms on the planet. If they can apply that same focus to solving the bottlenecks facing carmakers, they could help speed up the rollout of safer, smarter autonomous systems. Observers on X have dubbed DensityAI a 'full-stack AI data centre company', meaning it plans to compete on both the hardware and the software fronts. That holistic approach could prove to be a game-changer, giving automakers a one-stop shop for training, deploying, and maintaining their AI. DensityAI's first products, expected to launch in the coming months, will aim to help carmakers train and deploy AI faster, more intelligently, and more cost-effectively. If Venkataramanan and his crew pull it off, they won't just be tweaking how cars think, they could redefine how the entire industry processes data. After all, this is a team that's already built a record-breaking AI system once. Now, they're betting they can do it again, and this time, the whole automotive world might be along for the ride. Join our WhatsApp Channel
