bchege @bchege

Atlanta international terminal wait time … 2 min.

@GuntherEagleman @grok what are the top cases that get affected by this ruling?

B - For the following reasons: 1. Larger CTA button 2. Price per night is top left allowing to easy comparison when cards are in a grid based layout 3. Less visual noise - Again If there are a bunch of cards in a grid, this layout makes it easier to scan Only negative is the contrast of text is not as high as in the A version.

@SawyerMerritt Damn!

@Tesla 100% correct. I drove a 8 hour trip on FSD and can confirm that I was not exhausted when done. Total game changer.

@lawyer4SMBs I did.Not recommended at all! 😬

@Budgetdog_ Gusto. Best solution I have found after trying several other payroll providers.

AI image generation going wrong

@sarahdoody

Cybertruck and tesla bots are coming! Are you ready? $tsla!

New Tesla Model 3 - what do you think of the redesign?

👀

Tesla Asia @Tesla_Asia

3 years ago

Even better than before

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@farzyness @elonmusk Nice write up

Tesla's FSD v12 is a REALLY big deal. Last night @elonmusk livestreamed a ~45-minute video of a Model S driving itself around using Tesla's latest self-driving software, FSD v12. Self-driving is something the company has been trying to solve since Tesla Autopilot was released in 2015. Since then, Tesla has made steady progress improving the code to handle all kinds of road situations, has added cameras around the car, and removed sensors, all the while rewriting the code multiple times to solve for things the car couldn’t handle. And even though Tesla cars can drive themselves in many situations, the biggest challenge with self-driving cars is the thousands (or millions) of situations drivers face on a daily basis that are completely unexpected or difficult to solve for, like other drivers acting irrationally, inclement weather, debris on the road, weird (or lack of) lane markings, etc. Up to this point, Tesla and other companies have to spend a large amount of time running through simulated scenarios to generate code that would teach the system how to handle these situations. This code is oftentimes written by a human and needs to account for every variation of something happening on the road. And even then, there are thousands (or millions) of situations that a simulation won’t come with, since real life is so damn complicated and complex. The approach many have taken to try and solve this problem is by overfitting their self-driving cars with a ton of different sensors like LIDAR, radar, ultrasonics, cameras, and other sensors in addition to generating High-Definition maps of the areas where the cars are meant to be driven in. They’ve done this in hopes that there’s a combination of sensors and map data that would allow them to solve for the most unexpected situations. Here’s a picture of a GM Cruise vehicle that uses this approach. However, yesterday’s video has demonstrated a breakthrough in how self-driving cars can operate. Instead of using many sensors and hardware on their cars to process the world, Tesla is using 8 cameras and a computer that’s specifically built to process video data. That’s 9 total parts vs everyone else’s 30, 40, 50+ parts to process the world. Using only vision to process the world and not needing things like LIDAR, radar, and other sensors to interpret the physical objects around the car is impressive enough, but HOW the car learns to do this is what the real breakthrough is. With FSD v12, Tesla takes the video data that is collected by its fleet of ~4 million cars and runs it through an AI that is built using Neural-Nets (like ChatGPT but for the real world), and then the AI figures out what the car should do based on what it sees. What’s important to highlight here is that Tesla has done 0 work in telling the car how it should interpret the world. That means that the AI doesn’t explicitly know what a lane is, what a traffic light is, what a stop sign is, what a cone is, what a pothole is, what rain is, etc. What Tesla does is it shows the AI a metric-ton of video of a car driving around using the 8 cameras that are outfitted around the car, and the AI learns how to do the same. The more video Tesla feeds it, the better the system gets. The more unique situations that are collected from the fleet of Teslas, the better the system gets at accounting for those situations. This “AI code” will then be beamed to every Tesla in the world, and the on-board computer will be able to process its surroundings without the need to connect to Tesla’s AI server. It’s no different than you or I getting into a car and driving it. Instead of our 2 eyes collecting video around us and using our brain to process the info, the 8 camera system will collect the video and Tesla’s on-board computer will process it using the “AI code”. In other words, Tesla has moved away from humans figuring out how to write code that tells the car what to do, and instead feeds video to an AI, and the AI figures out the best way to account for every situation. The only thing Tesla needs moving forward is more video and more compute power (chips) to process videos. That’s it. This is profound. Everything that is captured on video with the 8 camera system is something the AI will be able to figure out how to navigate through. Snow. Potholes. Deer. Cyclists. Aliens. You name it. And this “code” that is generated by the AI will get better and better as Tesla’s compute capabilities grow with their purchases of NVIDIA’s H100 chips and the build-out of their in-house DOJO compute system. Not to mention the growing fleet of Teslas that will capture more and more video data around the world. Every Model S, 3, X, and Y that is sold today is a video-capturing robot that feeds the AI. And every Cybertruck and Compact Car will be the same. And believe it or not, it gets even crazier. Now that Tesla has come up with a real-world data collection and processing system with its cameras and on-board computer, this same system can be used on other physical products that can learn how to move around its surroundings. This is where Tesla’s Optimus Bot comes into play. Tesla will be able to use its 8 camera system on the Tesla Bot to collect video of its surroundings, beam it back to the AI, the AI figures out how to best do that thing that it’s collecting video for, and then beam back the “AI code” for the Bot to process with its on-board compute. We are not far away from a world where a humanoid robot watches you do the dishes, sends back the data to the mothership to process it, and then the next morning the Bot has learned how to do the dishes - not only using the video it gathered from you doing it, but from every other person in the world washing dishes. Do this process with literally anything. ChatGPT showed the masses what the potential of AI can be. NVIDIA showed the masses just how much demand there is for hardware that is used by AI systems. And now, Tesla just showed the masses what AI means for real-world physical applications. The world has changed - again.

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NEWS: Starlink Hardware Now Available at Costco Japan. teslanorth.com/2023/08/24/sta…

just called someone on X 🤯🤯🤯🤯

🚗 industry stats: Via @wholemars Q2 2023 Revenue Tesla — $25 billion GM — $44.7 billion Ford — $45 billion Net Income (Profit) Tesla — $2.7 billion GM — $2.6 billion Ford — $1.9 billion Vehicles Sold Tesla — 466,140 GM — 1,584,000 Ford — 1,119,000 Total debt Tesla - $2.67 billion GM - $114.42 billion Ford - $140.47 billion Ford CEO’s comment on the upcoming Tesla Cybertruck … “the EV (cybertruck) looks like a cool high-end product parked in front of a hotel, but his company makes trucks for real people who do real work. "If he (Elon Musk) wants to design a Cybertruck for Silicon Valley people, fine. It's like a cool high-end product parked in front of a hotel.” June 25, 2023. Netflix killed blockbuster The iPhone killed Kodak Amazon killed Sears, circuit city Uber killed the taxi industry The pickup truck market is one of the most lucrative in the US market.

"The Chevy Silverado was still on the showroom floor for reference. In front of it were three large display boards with pictures of a wide variety of vehicles, including ones from video games and sci- fi "movies. They ranged from retro to futuristic, sleek to jagged, curvaceous to jarring. With his hands casually in his pockets, von Holzhausen had the easygoing and loose- limbed manner of a surfer looking for the right wave. Musk, arms akimbo, was coiled like a bear searching for prey. As he looked at the pictures on the display boards, Musk gravitated to the ones that had a futuristic, cyber look. They had recently settled on the design for the Model Y, a crossover version of the Model 3, and Musk had been talked out of some of his more radical and unconventional suggestions. Having played it safe with the Model Y, he did not want that to happen with the design of the pickup truck. “Let’s be bold,” he said. “Let’s surprise people.” Every time someone would point to a picture that was more conventional, Musk would push back and point to the car from the video game Halo or in the trailer for the forthcoming game Cyberpunk 2077 or from Ridley Scott’s movie Blade Runner. His son Saxon, who is autistic, had recently asked an offbeat question that resonated: “Why doesn’t the future look like the future?” Musk would quote Saxon’s question repeatedly. As he said to the design team that Friday, “I want the future to look like the future.” There were a few dissenting voices suggesting that something too futuristic would not sell. After all, this was a pickup truck. “I don’t care if no one buys it,” he said at the end of the session. “We’re not doing a traditional boring truck. We can always do that later. I want to build something that’s cool. Like, don’t resist me.”"

Walter Isaacson @WalterIsaacson

3 years ago

Adding to @SawyerMerritt post: In my book, amazon.com/Elon-Musk-Walt… , I describe how on one Friday in 2017, @elonmusk decreed, “We are going to do this whole thing in stainless steel.” I note: "The use of stainless steel opened up new possibilities for the look of the truck.

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@Keviduk Right … but you have to define the save experience. That may change depending on your use case.