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Tesla cars will be smarter than humans by 2033 Tesla cars will be smarter than humans by 2033

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Tesla cars will be smarter than humans by 2033

Credit: Vanarama

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Tesla cars will be smarter than humans by 2033, according to a new study by car and van leasing company, Vanarama. Vanarama performed an analysis of the processing power of Tesla’s microchips to forecast how many years it will take to be on par with the human brain.

The study looked into the processing power of Tesla’s “own AI brain” and compared it with its predecessors and the human brain. Some of the key findings include:

  • Tesla’s microchips will top the human brain (one quadrillion operations per second) in only 11 years (10.94), by 2033.

  • Tesla’s microchip capability is increasing at a rate of 486% per year.

  • Tesla would take 17 years to reach the level of a mature human brain – eight years quicker than we manage (25 years for human brain maturity).

  • Tesla’s D1 chip is 30 times more powerful than the chip they used only six years ago.

Credit: Vanarama

Vanarama found that Tesla’s microchip capability is increasing at a rate of 486% per year. The first chip it looked at was a 2016  NVIDIA component that managed 12 trillion operations per second, which is the measure of a computer’s processing power. Tesla’s latest D1 chip managed 362 trillion.

“At that rate, Tesla’s self-driving AI chip will top the human brain (one quadrillion operations per second) in only 11 years (10.94), by 2033,” Vanaram noted.

The company further explained that if you were to look at the growth rate from the first NVIDIA chip it analyzed, it shows that Tesla would take 17 years to reach the level of a mature human brain. This is eight years faster than humans reach brain maturity which is typically 25 years of age.

Credit: Vanarama

Tesla D1 chip 3X more powerful than a chip they used 6 years ago

Tesla’s D1 chip was unveiled during AI Day last year and was designed for the Dojo supercomputer. Tesla recently shared a fresh look at the microarchitecture of the Dojo supercomputer when it gave a presentation in New Orleans.

This year, Tesla will hold another AI Day event and it’s expected to release the new D1 chip and other interesting things such as a working prototype of the Optimus Bot. Vanarama took note of the D1 chip’s processing power and said that it was a “considerable increase in computing intelligence from the previous chip, Hardwar 3, which performed 144 trillion operations per second in 2019. Before that, it was the Hardware 2 on 72 trillion, and the Nvidia chip on 12 trillion.”

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The Dojo ExaPOD supercomputer will use a total of 24 D1 chips which will make the system capable of just over one quintillion operations per second. For perspective, that number is written out as 1,086,000,000,000,000,000.

A glimpse of the future for AI chips

Take a look at the graphic above. Comparing the processing power of Tesla’s microchips. Vanarama said that in the time it has taken one to read it, Tesla’s microchips would have completed up to 7.6 quadrillion operations each.

“It wouldn’t be crazy to believe that tech will become significantly smarter than humans in our lifetime. Microchips are currently capable of working the way brain synapses do, with researchers developing chips that are inspired by the way the brain operates.”

You can learn more about Vanarama’s research here.

Note: Johnna is a Tesla shareholder and supports its mission. 

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Your feedback is important. If you have any comments, or concerns, or see a typo, you can email me at johnna@teslarati.com. You can also reach me on Twitter @JohnnaCrider1

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Tesla Full Self-Driving v14.1 first impressions: Robotaxi-like features arrive

Tesla Full Self-Driving v14.1 is here, and we got to experience it for ourselves.

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Tesla rolled out its Full Self-Driving v14.1 yesterday, its first public launch of its most robust and accurate FSD iteration yet. Luckily, I was able to get my hands on it through the Early Access Program.

The major changes in FSD v14.1 were revealed in the release notes, which outline several notable improvements in areas such as driving styles, parking, and overall navigation. Here’s what Tesla outlined fully in its release notes:

  • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
  • Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
  • Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
  • Added additional Speed Profile to further customize driving style preference.
  • Improved handling for static and dynamic gates.
  • Improved offsetting for road debris (e.g. tires, tree branches, boxes).
  • Improve handling of several scenarios including: unprotected turns, lane changes, vehicle cut-ins, and school busses.
  • Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
  • Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!

I wanted to try it for myself. My big must-dos were my complaints with v13.2.9, which included parking when arriving at a destination, Navigation when leaving a destination, and definitely a general improvement in the car traveling at an acceptable rate of speed, even when using the “Hurry” driving style.

Here’s what I noticed with the new Full Self-Driving v14.1:

Speed Profiles are More Realistic

I am driving on “Hurry” about 95% of the time when utilizing Full Self-Driving. In past versions, most notably v13.2.9, my Tesla would slowly reach the speed limit, and it would tend to hang out at about 1-2 MPH either above or below it.

My first observation with v14.1 was the vehicle’s tendency to get right up to speed and, since I was still on Hurry, drive slightly above the speed limit. It never got out of line; it traveled at speeds I would typically drive at manually.

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I think this is a big improvement on its own, because I felt that I was pressing the accelerator too frequently in past FSD versions. Oftentimes, it just wasn’t going fast enough to justify the “Hurry” label; it felt more conservative and more like a student driver than anything.

Check it out:

This was among my favorite improvements, and it was the first thing I noticed as the car navigated me to the Supercharger, where my next positive is.

Navigating into parking lots, self-parking at Supercharger

One of the changes noted in the Release Notes was the addition of Arrival Options, which allows the car to select the appropriate parking situation. Since I was going to charge, the car had already chosen “Charger” as the parking option.

Pulling into a gas station or convenience store, especially during work days, can be stressful, as they are usually congested and full of foot and vehicle traffic. In past FSD versions, I have noticed the car being slightly “jumpy” and even hesitant to proceed through the lot.

Driving through parking lots was a noticeable improvement. It seems as if the car is much more confident in making its way through, while still being aware and cautious enough to safely navigate to the Supercharger.

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It then backed straight into a Supercharger stall, which was recently repaired and is once again active. I was actually upset it chose this specific stall because it had been inactive for a while. However, Tesla got this stall back up and running, the car chose it, and backed into the spot flawlessly:

This was super cool to experience, and I think it is a testament to how hard the Tesla AI team has worked. CEO Elon Musk recently stated that FSD would enable automatic parking at Superchargers, which was really awesome to experience firsthand.

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I decided to leave the Supercharger and go to an auto parts store to pick up some interior cleaner and some microfiber towels. I love keeping my Tesla clean!

I also thought it would be a great opportunity to see how it would react to another parking lot, how it would navigate it, and let it choose a parking spot. It did it all flawlessly:

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I had zero complaints about everything here. All of it was done really well.

Making a choice after being caught in the middle of an intersection

I arrived at a tight intersection in Dallastown, PA, and what my car did next has catalyzed quite a conversation on X.

It proceeded out into the middle of the intersection as the light was green. It had to yield to oncoming traffic, and while waiting, the light turned yellow, then red.

Most people, including myself, would have turned right and proceeded through the intersection since the car was already past the line. However, FSD chose to back up and wait for the next light cycle, which I felt was also a more than acceptable option:

There are some conflicting perspectives on what it chose to do here. Some said they would have proceeded and would want FSD to also proceed. I can agree with that perspective, but I also think it is not the worst thing in the world to back up. In Pennsylvania, I couldn’t find the exact law that says what is right or wrong. Instead, I did see that a left turn on red is only feasible when you’re going from a One-Way street to another One-Way.

I’m not totally sure what is “correct” here, but I think either option is fine. I have personally done both, and I’ve seen other drivers do both. I was more than fine with the car doing this, and I was honestly impressed that it did.

Navigated a busy grocery store lot, found suitable parking

This is not the busiest my local grocery store gets, but it was still congested enough for me to be impressed.

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FSD decided to do one loop in the parking lot before it found a spot that it felt was good enough for me. I was perfectly fine with where it chose to park, and I thought it did a really great job. I was impressed with how stress-free I felt, as I have noted in the past that parking lots are definitely an area where Tesla needs to improve.

I was happy with its performance:

Strange right turn signal as if it saw an emergency vehicle

This was the first bug I noticed with FSD v14.1. While traveling on a local road, it put the right turn signal on and approached the curb as if it was pulling over for an emergency vehicle or as if it was going to park on the street.

It then realized its mistake and proceeded:

I’m not super sure what caused this, but I was a tad bit confused. There were no police cars, ambulances, or anyone with flashing lights to my rear. There was a dump truck on the other side of the road, and I almost felt like the way it navigated “around” that was probably what triggered it.

Navigation is still making strange decisions

I’ve written about navigation and my discontent with some of its decisions. It seems v14.1 didn’t resolve much of anything with navigation, and it did a couple of things wrong.

The first was that it tried to take the illogical and pointless path out of the Supercharger. I wrote about this a few days ago, as FSD tried to take my car the wrong way.

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It did it again, but I overrode the decision, and it was all okay:

This is a minor issue, but it is still pretty frustrating. Hopefully, the navigation will learn after performing this adjustment after enough times.

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The next navigation issue was more frustrating than the Supercharger one, especially considering it completely ignored the route. The navigation had the vehicle very clearly heading straight, but out of nowhere, the right turn signal went on. I overrode it, but the car still turned right, ignoring the navigation completely:

I ended up taking over here and driving until I could get to a stop sign.

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Final Thoughts

I am really impressed with all of the changes Tesla made with FSD v14.1, and while there were a handful of bugs, things were tremendously better than v13.2.9.

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Nvidia CEO Jensen Huang regrets not investing more in Elon Musk’s xAI

The CEO stated that Nvidia is already an investor in xAI, but he wished he had given the artificial intelligence startup more money.

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Credit: Elon Musk/X

Nvidia CEO Jensen Huang revealed that one of his investment regrets is not putting more money into Elon Musk’s artificial intelligence startup, xAI. 

Speaking in a CNBC interview, Huang said Nvidia is already an investor in xAI but wished he had given the artificial intelligence startup more money. This was due to Musk’s record of building transformative companies such as Tesla and SpaceX.

A new wave of transformative AI firms

Huang said he’s very excited about xAI’s latest financing round. He described Musk’s company as part of a powerful new generation of AI developers, alongside OpenAI and Anthropic. that are reshaping the computing landscape.

“I’m super excited about the financing opportunity they’re doing. The only regret I have about xAI, we’re an investor already, is that I didn’t give him more money. You know almost everything that Elon’s pat of, you really want to be part of as well,” the Nvidia CEO stated.

The CEO also clarified Nvidia’s investment in xAI, revealing that Elon Musk had offered the investment opportunity to the chipmaker. “He (Musk) gave us the opportunity to invest in xAI. I’m just delighted by that,” Huang stated.

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AI investment boom

Huang contrasted today’s AI-driven economy with the early days of the internet. “Back then, all the internet companies combined were maybe $30 or $40 billion in size,” he said. “If you look at the hyperscalers now, that’s about $2.5 trillion of business already operating today.”

He also stated that the ongoing shift from CPU-based computing to GPU-powered generative AI represents a “multi-trillion-dollar buildout” that Nvidia is looking to support. Huang added that every Nvidia engineer now works with AI coding assistants such as Cursor, which he called his “favorite enterprise AI service,” and it has led to a major productivity boost across the company.

Watch Nvidia CEO Jensen Huang’s CNBC interview in the video below.

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Investor's Corner

Stifel raises Tesla price target by 9.8% over FSD, Robotaxi advancements

Stifel also maintained a “Buy” rating for the electric vehicle maker.

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Credit: Tesla China

Investment firm Stifel has raised its price target for Tesla (NASDAQ:TSLA) shares to $483 from $440 over increased confidence in the company’s self-driving and Robotaxi programs. The new price target suggests an 11.5% upside from Tesla’s closing price on Tuesday.

Stifel also maintained a “Buy” rating despite acknowledging that Tesla’s timeline for fully unsupervised driving may be ambitious.

Building confidence

In a note to clients, Stifel stated that it believes “Tesla is making progress with modest advancements in its Robotaxi network and FSD,” as noted in a report from Investing.com. The firm expects unsupervised FSD to become available for personal use in the U.S. by the end of 2025, with a wider ride-hailing rollout potentially covering half of the U.S. population by year-end.

Stifel also noted that Tesla’s Robotaxi fleet could expand from “tiny to gigantic” within a short time frame, possibly making a material financial impact to the company by late 2026. The firm views Tesla’s vision-based approach to autonomy as central to this long-term growth, suggesting that continued advancements could unlock new revenue streams across both consumer and mobility sectors.

https://twitter.com/AIStockSavvy/status/1975893527344345556

Tesla’s FSD goals still ambitious

While Stifel’s tone remains optimistic, the firm’s analysts acknowledged that Tesla’s aggressive autonomy timeline may face execution challenges. The note described the 2025 unsupervised FSD target as “a stretch,” though still achievable in the medium term.

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“We believe Tesla is making progress with modest advancements in its Robotaxi network and FSD. The company has high expectations for its camera-based approach including; 1) Unsupervised FSD to be available for personal use in the United States by year-end 2025, which appears to be a stretch but seems more likely in the medium term; 2) that it will ‘probably have ride hailing in probably half of the populations of the U.S. by the end of the year’,” the firm noted.

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