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Tesla FSD’s vision-based approach critiqued by Waymo CEO: ‘Our sensors are orders of magnitude better’
Tesla’s Full Self-Driving Beta may be improving at a rapid pace since its first iteration was released back in October, but Waymo CEO John Krafcik seems to be under the impression that there is a ceiling for the electric car maker’s current autonomous driving efforts. In an interview with German business publication manager magazin, Krafcik stated that Tesla is not a competitor to Waymo, as the EV maker’s tech is just a “really good driver assistance system.”
Waymo’s vehicles, which are equipped with a variety of sensors including LiDAR, are designed to be operated without a human driver. The company has even requested its passengers to not touch its autonomous cars’ steering wheel while the vehicles are operating. In comparison, Tesla’s Full Self-Driving Beta, as well as the company’s tech Navigate on Autopilot, still requires drivers to keep their hands on the steering wheel to prepare for manual intervention.
Tesla aims to develop a full self-driving suite through a vision-based system that relies on incremental improvements that are rolled out over time. Through constant updates that are built on real-world driving data gathered from its fleet, Tesla hopes to roll out a version of its FSD suite that would truly be a hands-off system. Once this is achieved, the EV maker aims to launch its own ride-hailing service, dubbed by Elon Musk as the Robotaxi Network.
This, according to the Waymo CEO, is a misconception. He also remarked that between Tesla’s camera-based approach and Waymo’s more robust sensor suite, his company’s sensors hold a massive advantage over Tesla’s electric cars. “It is a misconception that you can just keep developing a driver assistance system until one day you can magically leap to a fully autonomous driving system. In terms of robustness and accuracy, for example, our sensors are orders of magnitude better than what we see on the road from other manufacturers,” Krafcik said.
One of the notable arguments against Waymo’s autonomous vehicles is their cost, especially considering that their sensor suite includes expensive components. The CEO, however, notes that the cost of its vehicles is actually overestimated, especially as the price of sensors such as LiDAR has gotten significantly lower over the years. Today, Krafcik notes that the cost of a Waymo autonomous car is on the same ballpark as a moderately-equipped Mercedes-Benz S-Class.
“Let me paraphrase it like this: If we equip a Chrysler Pacifica Van or a Jaguar I-Pace with our sensors and computers, it costs no more than a moderately equipped Mercedes S-Class. So for the entire package, including the car – today. The costs for the technology are greatly overestimated – at least in our case” he said.
Krafcik noted that he expects the hardware cost per mile of Waymo’s autonomous vehicles to come in at around $0.30 per mile before maintenance and service costs, including fleet technicians and customer support representatives. In comparison, ride-hailing services today such as Uber and Lyft operate at around $2-$3 per mile. Tesla, on the other hand, expects an $0.18 per mile operating cost for its Robotaxi Network, as per the company’s estimates during its Autonomy Day presentation in 2019.
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News
Tesla seen as early winner as Canada reopens door to China-made EVs
Tesla had already prepared for Chinese exports to Canada in 2023 by equipping its Shanghai Gigafactory to produce a Canada-specific version of the Model Y.
Tesla seems poised to be an early beneficiary of Canada’s decision to reopen imports of Chinese-made electric vehicles, following the removal of a 100% tariff that halted shipments last year.
Thanks to Giga Shanghai’s capability to produce Canadian-spec vehicles, it might only be a matter of time before Tesla is able to export vehicles to Canada from China once more.
Under the new U.S.–Canada trade agreement, Canada will allow up to 49,000 vehicles per year to be imported from China at a 6.1% tariff, with the quota potentially rising to 70,000 units within five years, according to Prime Minister Mark Carney.
Half of the initial quota is reserved for vehicles priced under CAD 35,000, a threshold above current Tesla models, though the electric vehicle maker could still benefit from the rule change, as noted in a Reuters report.
Tesla had already prepared for Chinese exports to Canada in 2023 by equipping its Shanghai Gigafactory to produce a Canada-specific version of the Model Y. That year, Tesla began shipping vehicles from Shanghai to Canada, contributing to a sharp 460% year-over-year increase in China-built vehicle imports through Vancouver.
When Ottawa imposed a 100% tariff in 2024, however, Tesla halted those shipments and shifted Canadian supply to its U.S. and Berlin factories. With tariffs now reduced, Tesla could quickly resume China-to-Canada exports.
Beyond manufacturing flexibility, Tesla could also benefit from its established retail presence in Canada. The automaker operates 39 stores across Canada, while Chinese brands like BYD and Nio have yet to enter the Canadian market directly. Tesla’s relatively small lineup, which is comprised of four core models plus the Cybertruck, allows it to move faster on marketing and logistics than competitors with broader portfolios.
Elon Musk
Tesla confirms that work on Dojo 3 has officially resumed
“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo 3,” Elon Musk wrote in a post on X.
Tesla has restarted work on its Dojo 3 initiative, its in-house AI training supercomputer, now that its AI5 chip design has reached a stable stage.
Tesla CEO Elon Musk confirmed the update in a recent post on X.
Tesla’s Dojo 3 initiative restarted
In a post on X, Musk said that with the AI5 chip design now “in good shape,” Tesla will resume work on Dojo 3. He added that Tesla is hiring engineers interested in working on what he expects will become the highest-volume AI chips in the world.
“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo3. If you’re interested in working on what will be the highest volume chips in the world, send a note to AI_Chips@Tesla.com with 3 bullet points on the toughest technical problems you’ve solved,” Musk wrote in his post on X.
Musk’s comment followed a series of recent posts outlining Tesla’s broader AI chip roadmap. In another update, he stated that Tesla’s AI4 chip alone would achieve self-driving safety levels well above human drivers, AI5 would make vehicles “almost perfect” while significantly enhancing Optimus, and AI6 would be focused on Optimus and data center applications.
Musk then highlighted that AI7/Dojo 3 will be designed to support space-based AI compute.
Tesla’s AI roadmap
Musk’s latest comments helped resolve some confusion that emerged last year about Project Dojo’s future. At the time, Musk stated on X that Tesla was stepping back from Dojo because it did not make sense to split resources across multiple AI chip architectures.
He suggested that clustering large numbers of Tesla AI5 and AI6 chips for training could effectively serve the same purpose as a dedicated Dojo successor. “In a supercomputer cluster, it would make sense to put many AI5/AI6 chips on a board, whether for inference or training, simply to reduce network cabling complexity & cost by a few orders of magnitude,” Musk wrote at the time.
Musk later reinforced that idea by responding positively to an X post stating that Tesla’s AI6 chip would effectively be the new Dojo. Considering his recent updates on X, however, it appears that Tesla will be using AI7, not AI6, as its dedicated Dojo successor. The CEO did state that Tesla’s AI7, AI8, and AI9 chips will be developed in short, nine-month cycles, so Dojo’s deployment might actually be sooner than expected.
Elon Musk
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Elon Musk shared his update in a recent post on social media platform X.
xAI has brought its Colossus 2 supercomputer online, making it the first gigawatt-scale AI training cluster in the world, and it’s about to get even bigger in a few months.
Elon Musk shared his update in a recent post on social media platform X.
Colossus 2 goes live
The Colossus 2 supercomputer, together with its predecessor, Colossus 1, are used by xAI to primarily train and refine the company’s Grok large language model. In a post on X, Musk stated that Colossus 2 is already operational, making it the first gigawatt training cluster in the world.
But what’s even more remarkable is that it would be upgraded to 1.5 GW of power in April. Even in its current iteration, however, the Colossus 2 supercomputer already exceeds the peak demand of San Francisco.
Commentary from users of the social media platform highlighted the speed of execution behind the project. Colossus 1 went from site preparation to full operation in 122 days, while Colossus 2 went live by crossing the 1-GW barrier and is targeting a total capacity of roughly 2 GW. This far exceeds the speed of xAI’s primary rivals.
Funding fuels rapid expansion
xAI’s Colossus 2 launch follows xAI’s recently closed, upsized $20 billion Series E funding round, which exceeded its initial $15 billion target. The company said the capital will be used to accelerate infrastructure scaling and AI product development.
The round attracted a broad group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group. Strategic partners NVIDIA and Cisco also continued their support, helping xAI build what it describes as the world’s largest GPU clusters.
xAI said the funding will accelerate its infrastructure buildout, enable rapid deployment of AI products to billions of users, and support research tied to its mission of understanding the universe. The company noted that its Colossus 1 and 2 systems now represent more than one million H100 GPU equivalents, alongside recent releases including the Grok 4 series, Grok Voice, and Grok Imagine. Training is also already underway for its next flagship model, Grok 5.