Latest news with #ProjectDojo
Time of India
6 days ago
- Automotive
- Time of India
Tesla Pulls the Plug: The End of Dojo and a Pivot in the Self-Driving Race
The Reality Check: Talent and Tech Turbulence The Shift: From 'Build' to 'Buy' Live Events In 2019, the world watched as Elon Musk unveiled Project Dojo : a new breed of AI supercomputer , powered by custom Tesla-designed D1 chips, that promised to devour mountains of driving video and train neural networks poised to revolutionize autonomous vehicles . Dojo's technical ambitions dazzled more than an exaflop of power, a dense fabric of interconnected processing units, and the hope of rendering the supply constraints and architectural limits of external chips Street and tech forums alike caught the fever: analysts speculated Dojo could add hundreds of billions to Tesla's worth thanks to its first-mover lead in self-driving and the robotaxi revolution. It was Musk at his storytelling best. Dojo would be the digital cortex underpinning a fleet of Tesla cars learning and improving together on the open mid-2025, the dream began to unravel. Key leaders, including Dojo's own head, Peter Bannon, departed. A mass exodus saw around 20 top engineers bolt to form Density AI, a stealth startup helmed by former Dojo chief Ganesh Venkataramanan. Internal momentum faltered just as cracks began to show in Tesla's robotaxi rollout: limited launches, driving hiccups, and investor Musk, ever pragmatic in the face of market tides, changed tack. According to Musk, maintaining two divergent chip lines. Dojo's custom training chips and Tesla's new inference-focused AI5 and AI6 processors no longer made business sense. Dojo's mission, powering FSD (Full Self-Driving) through brute-force on in-house hardware, lost out to a strategy leveraging external chip partnerships with Nvidia , AMD, and Samsung The end of Project Dojo doesn't mark a retreat from autonomy or AI, just a strategic pivot. Tesla has inked a $16.5 billion deal with Samsung to supply next-generation AI chips for its vehicles and humanoid robots, a clear sign that it believes the path forward runs faster on Nvidia's and Samsung's silicon than on furrowed brows in Tesla's own confirmed on X (formerly Twitter) that the company will now focus exclusively on AI5 and AI6 chips, which, while not exclusively designed for training, will be 'excellent for inference and at least pretty good for training.' The plan: integrate these chips into Tesla products like the Optimus robot and Cybercab while outsourcing vast data crunching and AI training horsepower to industry Dojo once symbolized a Silicon Valley ethos: solve the world's hardest problems with audacity and your own hardware. Its end is a reminder that, sometimes, winning the future means knowing when to build—and when to buy.
Business Insider
7 days ago
- Automotive
- Business Insider
Tesla's Musk Says ‘All Effort Is Focused on AI5/AI6 Chips' After Ending Dojo Project
Shares of electric vehicle maker Tesla (TSLA) gained 2.3% on August 8, despite news of the disbanding of the entire Dojo supercomputer team. The team was built to focus on developing Tesla's in-house artificial intelligence (AI) chips to power its self-driving technology and Optimus humanoid robot. The closure of the Dojo project means Tesla will now have to rely on sourcing chips from tech companies, such as Nvidia (NVDA), AMD (AMD), and Samsung (SSNLF). Elevate Your Investing Strategy: Take advantage of TipRanks Premium at 50% off! Unlock powerful investing tools, advanced data, and expert analyst insights to help you invest with confidence. However, the news was not all bad, since CEO Elon Musk quickly clarified that Tesla's AI5 and AI6 chips will take over the role of the Dojo team. Investors reacted positively, driving TSLA stock higher on Friday. Musk explained the shift in an X post, saying, 'It doesn't make sense for Tesla to divide its resources and scale two quite different AI chip designs.' AI6 Is the New Dojo Following Musk's post, a Tesla enthusiast cheered the shift, saying, 'AI6 is the new Dojo.' Tesla has stopped its separate Project Dojo supercomputer initiative to focus entirely on its in-house AI5 and AI6 chips. Musk stated that, instead of maintaining two different AI chip designs, Tesla will use its AI5 and AI6 chips both for training and inference of its autonomous driving systems, such as Full Self-Driving (FSD) and Autopilot. These chips will also be used in Tesla's consumer products, including Optimus robots, the Cybercab, and the next-generation Roadster. Project Dojo was originally designed to train Tesla's autonomous driving AI using custom D1 chips arranged in a unique 5×5 system-on-wafer design. However, Musk now sees the AI6 chip as the natural successor to Dojo, combining and improving many of its features. He confirmed that all Tesla AI chip efforts will now focus on AI6, which will be produced at Samsung's new Texas fabrication facility. Musk added that he will be personally involved in speeding up AI6 production. Is TSLA Stock a Buy, Hold, or Sell? Analysts remain cautious about Tesla's long-term outlook due to ongoing declines in EV sales and the ending of EV tax incentives on September 30. On TipRanks, TSLA stock has a Hold consensus rating based on 13 Buys, 15 Holds, and eight Sell ratings. The average Tesla price target of $305.37 implies 7.4% downside potential from current levels. Year-to-date, TSLA stock has lost 18.4%.
Indian Express
10-08-2025
- Automotive
- Indian Express
Tesla scraps Project Dojo: What it means for full self-driving and future of AI
Earlier this week, Tesla ended Project Dojo, which was a partnership between Tesla and Dojo computers. This brought an end to the automaker's efforts to build in-house chips for its driverless technology goals. Tesla has been focused on building driverless cars for almost a decade now. So why did Tesla end its attempts to produce chips in-house for its autonomous vehicles? The decision came because Tesla CEO Elon Musk shifted to relying on Nvidia and AMD for compute chips, along with Samsung for manufacturing. According to Musk, Tesla was closing Project Dojo because it would be inefficient for the business to split its resources and scale two distinct AI chip designs. Dojo would not be included in Tesla's consumer goods because it was intended to train the company's autonomous driving programme. Dojo was the automaker's effort to build custom supercomputers designed to train Tesla's neural network for driverless cars. A neural network functions like a simulated brain, supporting Tesla's goal of launching Robotaxi and Full Self-Driving (FSD) cars. This network is installed across a large fleet of Tesla cars today, enabling some automated driving functions that still require a human to be attentive behind the wheel. Tesla's decision to shut down Dojo, which Musk had been talking about since 2019, marks a major strategic shift. Musk had previously described Dojo as the cornerstone of Tesla's AI ambitions and its push for full self-driving, thanks to its ability to 'process truly vast amounts of video data.' He even mentioned it briefly during the company's second-quarter earnings call. The primary reason is Tesla's vision-only philosophy. For FSD to work, its neural networks must identify and categorise objects in the environment, then make driving decisions in real time. This requires training on enormous volumes of driving data so that, when activated, FSD can continuously gather and process visual data at speeds comparable to human depth and motion detection. In essence, Tesla wants to build a digital model of how the human brain and visual cortex function. To achieve this, Tesla must store, process, and run millions of simulations on video data gathered from vehicles worldwide. Although Tesla depended on Nvidia to run its Dojo training computer, the aim was to reduce reliance on a single supplier and improve performance by boosting bandwidth and lowering latency. Tesla's Dojo system was intended to serve as an AI training platform for FSD. A supercomputer consists of thousands of smaller computers, or nodes. Each node has a central processing unit (CPU) and a graphics processing unit (GPU). While the CPU manages the node overall, the GPU handles more complex tasks, such as splitting workloads into many parts and processing them in parallel. GPUs are critical for machine learning tasks like FSD training in simulation. Musk's broader vision is for Tesla to become an AI company capable of making self-driving cars by mimicking human vision. Most other companies in the autonomous driving sector use a combination of sensors—lidar, radar, cameras—and high-definition maps. Tesla believes it can achieve full autonomy with cameras alone, paired with advanced neural networks to analyse data and make instant driving decisions. In August 2024, Musk began promoting Cortex, Tesla's new AI training supercluster being built at its Austin headquarters to tackle real-world AI challenges. This shifted focus away from Dojo. Bloomberg reports that Tesla will now rely more on Nvidia and other partners such as AMD for computing and Samsung for chip fabrication. On 28 July 2025, Tesla and Samsung signed a $16.5 billion agreement to produce AI6 inference processors for high-performance AI training, FSD, and Tesla's Optimus humanoid robots. Meanwhile, Dojo's lead, Peter Bannon, is leaving the company, and the remaining team members will be reassigned to other data centre and compute projects within Tesla.
