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Tesla’s Elon Musk will be hosting an AI hackathon party at his house
Elon Musk announced that Tesla will be hosting an AI hackathon, together with the company’s artificial intelligence and autopilot team, at his house in four weeks’ time.
The Tesla chief announced his plans via Twitter on Sunday. Despite impressive numbers revealed during the Q4 2019 earnings call and update, Musk and his Tesla team are not resting on their laurels and remain focused on pursuing advancements to its neural network, which is in the center of Tesla’s goal of achieving a full self-driving vehicle.
During the recent Q4 earnings call, an investor asked the Tesla chief executive for updates on FSD.
“I think that’s looking like maybe it’s going to be couple of months from now. And what isn’t obvious regarding Autopilot and Full Self-Driving is just how much work has been going into improving the foundational elements of autonomy,” Musk said.
Tesla will hold a super fun AI party/hackathon at my house with the Tesla AI/autopilot team in about four weeks. Invitations going out soon.
— Elon Musk (@elonmusk) February 2, 2020
Musk continued to explain how the Tesla team is making great strides in labeling efficiency.
“…in terms of labeling, labeling with video in all eight cameras simultaneously. This is a really, I mean in terms of labeling efficiency, arguably like a three order of magnitude improvement in labeling efficiency. For those who know about this, it’s extremely fundamental, so that’s really great progress on that,” Musk said.
Tesla vehicles rely on a custom chip that boasts of 144 tera operations per second (TOPS) for its self-driving capabilities. This two-chip FSD computer works in tandem with LPDDR4 RAM modules that come with a peak bandwidth of 68 GB/s. There are also two neural network accelerators that work in tandem to process as much as 1TB of data per second. This setup is roughly three times faster, about 80%, and about 1.25 times more power-efficient than the previous hardware. It is also able to process about 2,300 frames per second compared to the 110 frames per second processed by Tesla’s Hardware 2.5.
In his series of tweets on Sunday, Musk also mentioned Tesla’s “Dojo” supercomputer, which is speculated to be capable of processing vast amounts of data to train the company’s neural network. Through active learning, Tesla curates the most useful video clips from its fleet of connected cars and train the neural net to recognize things that it did not previously know.
“Our networks learn from the most complicated and diverse scenarios in the world, iteratively sourced from our fleet of nearly 1M vehicles in real-time. A full build of Autopilot neural networks involves 48 networks that take 70,000 GPU hours to train. Together, they output 1,000 distinct tensors (predictions) at each timestep,” Tesla wrote on the Autopilot AI section of its website.
“At Tesla, using AI to solve self-driving isn’t just icing on the cake, it the cake” – @lexfridman
Join AI at Tesla! It reports directly to me & we meet/email/text almost every day. My actions, not just words, show how critically I view (benign) AI.https://t.co/iF97zvYZRz
— Elon Musk (@elonmusk) February 2, 2020
The last major software update rolled out by Tesla allowed its vehicles to visualize more things while driving in inner-city streets. Teslas now render stoplights, stop signs, traffic cones, traffic pylons, and more.
With the upcoming AI hackathon, Tesla will get together with developers to seek out more efficient algorithms and overall improvements to the core logic for its Full Self-Driving suite through a time-boxed event. With fresh eyes working with the existing AI and autopilot team of Tesla, the carmaker may be able to accelerate the timeline and rollout of its full-featured Full Self-Driving suite sooner.
Further advances in FSD and its Autopilot feature will widen the gap between Tesla and its competitors and solidify the company’s position as one of the leading automakers in the world. These improvements will also take Tesla a step closer to the possibility of Robotaxis that they can deploy at scale.
The hackathon will also allow Tesla to fish for new AI talents to join the team. On Sunday, Musk also mentioned that the electric carmaker is looking for world-class chip designers and C++/C engineers for vehicle control and other functions of Tesla vehicles.
Musk reiterated that educational attainment is not important when joining Tesla but rather a clear understanding of how AI and neural networks function and the ability to build useful applications using that knowledge.
Elon Musk
A Tesla just delivered itself to a customer autonomously, Elon Musk confirms
Tesla CEO Elon Musk says the first self-delivery occurred today, one day ahead of schedule.

Tesla CEO Elon Musk has confirmed that a vehicle has, for the first time ever, delivered itself to a customer autonomously, one day ahead of the company’s original schedule.
To date, this is the first car to ever roll off a production line at a factory and transport itself to a customer for delivery.
Late last month, Musk announced that the first-ever fully autonomous delivery of a Tesla would take place on June 28. The plan was to have the car roll off the production lines at Gigafactory Texas and drive to a local customer without the assistance of anyone on board or remotely controlling the car through teleoperation.
Teslas will self-deliver to customers, Elon Musk says: here’s when
Musk said on Friday that it has officially happened:
🚨 Elon Musk confirms the first Tesla to self-deliver to a customer has happened, one day ahead of schedule! https://t.co/Zvb9y4m0uu
— TESLARATI (@Teslarati) June 27, 2025
The vehicle traveled as fast as 72 miles per hour, according to Ashok Elluswamy, Tesla’s Head of AI and Autopilot.
Musk continued on X:
“There were no people in the car at all and no remote operators in control at any point. FULLY autonomous! To the best of our knowledge, this is the first fully autonomous drive with no people in the car or remotely operating the car on a public highway.”
He said a video of the delivery would be uploaded soon.
We have seen cars autonomously transport themselves from production line to logistics lot at Gigafactory Texas, but this is a whole new level.
Tesla’s Giga Texas vehicles now drive themselves to outbound lot
Tesla just recently launched its Robotaxi for the first time in Austin on Sunday. Opened to a limited number of people, the company rolled out an Early Access Riders Program, but has been expanding it to more people in recent days. These cars featured a Safety Monitor in the passenger’s seat to ensure safety.
This seems to be something Tesla would like to perform more frequently in the coming months, especially locally. Eventually, it seems that Tesla will plan to have every vehicle it manufactures self-deliver, as a hauler would transport it to local delivery centers, then the car would drive itself to the customer’s house.
This is likely a few years off, but Tesla has already completed one self-delivery, which is an incredible accomplishment.
Yesterday, I wrote about Tesla’s two big milestones that are still planned for launch before the end of Q2. This was one of them. One to go: unveiling of the affordable models.
News
Tesla dispels reports that it hired ex-Cruise Autonomy head Henry Kuang
Tesla has denied reports that it hired former head of GM’s Cruise Henry Kuang.

Tesla has dispelled reports that it has hired ex-Cruise Head of Autonomy Henry Kuang.
This morning, several media outlets reported that Tesla had filled the position of Director of AI and Deep Learning for Autonomous Driving with Kuang, who was the Head of Autonomy at General Motors’ failed autonomous vehicle company, Cruise.
The rumor then circulated to X, but Tesla has now denied that those reports are true.
Tesla’s Head of Autopilot and AI, Ashok Elluswamy, revealed that the reports are false:
fake news
— Ashok Elluswamy (@aelluswamy) June 27, 2025
It would be easy to see how the hire might have been construed as real. Someone appears to have created a fake LinkedIn profile for Kuang, listing the new role at Tesla as their latest career move. The account appeared legitimate and bore all the hallmarks of a genuine page for Kuang, but it has since been removed from the site.
Additionally, there has been some rather high-level turnover at Tesla in recent days. The company recently let go of Omead Afshar, who was widely recognized as CEO Elon Musk’s right-hand man. Afshar assumed the role of North American sales head and European operations head late last year. He has been relieved of his duties, according to a Bloomberg report.
Tesla’s Omead Afshar, known as Elon Musk’s right-hand man, leaves company: reports
Alongside the loss of Afshar, Tesla’s Human Resources Head in Austin, Jenna Ferrua, also left the company this week.
This past week, Tesla launched its Robotaxi platform to a handful of people, marking the first time the company has given driverless rides to members of the public.
News
JB Straubel’s Redwood launches energy business focused on second-life EV batteries
Redwood stated that many EV battery packs retain more than 50% of their capacity after being retired from vehicles.

Redwood Materials, the battery recycling firm founded by Tesla co-founder JB Straubel, has launched a new venture called Redwood Energy. The business aims to repurpose used electric vehicle batteries into large-scale, low-cost energy storage systems.
In a post on X, Redwood revealed that it has already deployed a 12 MW, 63 MWh microgrid powered entirely by second-life EV batteries. The system is currently powering a modular data center for Crusoe AI, and it already operates at a lower cost than conventional solutions.
Repurposed batteries for scalable storage
Redwood Energy is designed to bridge the gap between battery recovery and recycling by extracting value from discarded EV packs that still hold usable charge. In a blog post, Redwood stated that many EV battery packs retain more than 50% of their capacity after being retired from vehicles. That remaining energy is well suited for stationary storage applications even without recycling.
The process begins with Redwood’s collection and diagnostics system, which identifies battery packs that are still suitable for reuse. Those packs are then integrated into modular energy systems that can store energy from solar, wind, or the grid. Once the batteries reach true end-of-life, they are recycled through Redwood’s closed-loop system to recover critical minerals.
Meeting the demands of an AI-driven grid
Redwood estimates that more than 100,000 EVs will be retired this year in the United States, with millions more currently on the road. These vehicles represent hundreds of gigawatt-hours of storage potential. These resources are coming in at the right time, as electricity demand is rising rapidly amid the rise of artificial intelligence, which tends to be power-hungry.
Redwood Energy already has more than 1 GWh of second-life batteries in its deployment pipeline. That figure is expected to grow to 5 GWh in the coming year. Larger 100 MW projects are also in development.
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