News
Tesla FSD Beta 10.13’s improvements to be (especially) evident for non-CA users
Elon Musk recently provided some updates on the wide rollout of FSD Beta 10.13. The latest iteration of the company’s advanced driver-assist system began its initial release earlier this month, but its wide release has not been initiated yet.
In a recent post on Twitter, Elon Musk admitted that while Tesla is working extremely hard on FSD Beta 10.13, the system itself is not ready for wide release just yet. He estimated that FSD Beta 10.13’s wide release would likely be a week or so away, but when it does, drivers outside California will experience some very notable improvements.
As noted by the Tesla CEO, users “outside of California will notice improvements the most.” This is an interesting comment, especially considering that Musk has admitted in the past that FSD Beta “seems to work better in California” than in other areas such as Rhode Island. Musk admitted to this last year, noting that FSD Beta has been overfitted to the Bay Area.
As noted in a Benzinga report, overfitting in statistics suggests that a model relates to a specific set of data points far too closely, which may not translate well with different data points. In the case of FSD Beta, this could result in the advanced driver assist system working very well in areas like San Francisco but not as well in other areas of the United States.
Release notes of FSD Beta 10.13 leaked earlier this month have revealed that the update includes a number of key performance improvements.
Following are the partial release notes of FSD Beta 10.13 that have been shared thus far:
- Improved decision making for unprotected left turns using better estimation of ego’s interaction with other objects through the maneuver.
- Improved stopping pose while yielding for crossing objects at “Chuck Cook style” unprotected left turns by utilizing the median safety regions.
- Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
- Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
- Improved lane position error by 5% and lane recall by 12%…
- Improved lane position error of crossing and merging lanes by 22% by adding long-range skip connections and a more powerful trunk to the network architecture.
- Improved pedestrian and bicyclist velocity error by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
- Improved animal detection recall by 34% and decreased false positives by 8% by doubling the size of the auto-labeled training set.
- Improved detection recall of far away crossing vehicles by 4% by tuning the loss function used during training and improving label quality.
- Improved the “is parked” attribute for vehicles by 5% by adding 20% more examples to the training set.
- Upgraded the occupancy network to detect dynamic objects and improved performance by adding a video module, tuning the loss function, and adding 37k new clips to the training set.
- Reduced false slowdowns around crosswalks by better classification of pedestrians and bicyclists as not intending to interact with ego.
- Reduced false lane changes for cones or blockages by preferring gentle offsetting in-lane where appropriate.
- Improved in-lane positioning on wide residential roads.
- Improved object future path prediction in scenarios with high yaw rate.
- Improved speed limit sign accuracy on digital speed limits by 29%, on signs with difficult relevance by 23%, on 3-digit speeds by 39%, and on speed limit end signs by 62%. Neural network was trained with 84% more examples in the training set and with architectural changes which allocated more compute in the network head.
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Investor's Corner
Tesla has its answer to auto growth, it just has to bring it to the U.S.: analyst
Tesla has its answer to grow its automotive sales over the next few years, TD Cowen analyst Itay Michaeli says, but it just has to bring it to the U.S.
On Thursday, Michaeli reiterated his $490 price target and the ‘Buy’ rating he already held on Tesla stock (NASDAQ: TSLA). However, its automotive division has struggled to show sequential growth over the past few years, mostly due to its focus on AI and Full Self-Driving. Tesla already axed two of its lower-volume vehicles with the Model S and Model X earlier this year.
However, Tesla does not need to engineer an entire new vehicle to trigger an upward tick in sales; it just has to bring it from China to the U.S., Michaeli said.
He is talking about the Model Y L, a slightly larger version of the all-electric crossover that is already available in China. U.S. customers have been pleading with CEO Elon Musk to bring it to the country since its launch in Asia last year, but he’s not convinced of it because of the advent of self-driving and its importance in this particular market.
The problem is that Tesla owners have been requesting something larger that could fit a typical American family. The Model Y L is slightly larger than the standard Model Y, but some are concerned that it could still be too small to fit what most people might need.
Instead, they have asked for a full-size SUV from Tesla.
Tesla gives big hint that it will build Cyber SUV, smaller Cybertruck
Nevertheless, the Model Y L still presents a great opportunity for Tesla in the U.S., and Michaeli says that there is an additional sales opportunity of about 100,000 units, with demand potential falling somewhere between 60,000 and 135,000 units.
TD Cowen’s note to investors also analyzed that Tesla’s growth could come from a stock perspective as well, positively impacting the stock price, as it has been widely reliant on vehicle sales, even though Tesla has truly phased itself away from that being an important metric.
Tesla stands to gain greatly from the introduction of the Model Y L in the U.S., but only if Elon Musk sees it as a viable fit for the market. Families may need to see Tesla bring something larger to the U.S., or they might be forced to buy from another automaker that offers something that fits is needs for more interior space to haul around the kids.
Elon Musk
Tesla Hardware 3 owners could be made whole this month
Tesla Hardware 3 owners are set to get a new Full Self-Driving version this month as the company plans to release what it is referring to as v14 Lite.
The rollout is not yet confirmed for June, but Tesla executives have stated on several occasions that this more refined FSD iteration will work with their cars and increase its capabilities.
This comes after Tesla admitted during its last Earnings Call that these Hardware 3 vehicles would not be able to achieve Full Self-Driving, something that they did not know when they bought these cars. We regularly receive messages from Hardware 3 owners asking when v14 Lite will come out, what they should expect, and whether it is worth it to upgrade the self-driving computer or buy a new car altogether.
Following future rollout of FSD V14 Lite for HW3 vehicles in the US, we plan on expanding V14 Lite to additional international markets.
This update ensures that HW3 vehicle owners will continue to benefit from ongoing software updates.
Since international rollout is subject to…
— Tesla (@Tesla) April 29, 2026
It is hard not to feel for them; Tesla CEO Elon Musk said at the company’s 2019 Autonomy Day that all vehicles produced at the time, including Hardware 3 cars, had “all the hardware necessary, compute and otherwise, for Full Self-Driving.”
Musk also said in March of that year that, “Anyone who purchased Full Self-Driving will get FSD computer upgrade for free.”
Anyone who purchased full self-driving will get FSD computer upgrade for free. This is the only change between Autopilot HW2.5 & HW3. Going forward “HW3” will just be called FSD Computer, which is accurate. No change to vehicle sensors or wire harness needed. This is v important. https://t.co/lICMpT7xnX
— Elon Musk (@elonmusk) March 29, 2019
However, during the Q1 2026 Earnings Call, Musk admitted that Hardware 3 vehicles would not be capable of FSD, as “It has only 1/8th the memory bandwidth of Hardware 4, and memory bandwidth is one of the key elements needed for unsupervised FSD.”
Tesla has made some effort to remedy these Hardware 3 owners by offering:
- Discounted trade-ins toward AI4 cars
- Hardware retrofits, which would replace the self-driving computer and upgrade all cameras
- Full Self-Driving v14 Lite
The issue is that many of these owners were led to believe their cars would be capable of unsupervised self-driving. Now, they’re left scrambling for options, and while there are several, they will all require more money out of their pockets.
Expectations for Tesla v14 Lite for Hardware 3 Owners
The big differences between the AI4 v14 and v14 Lite for Hardware 3 owners will stem primarily from hardware constraints. Tesla developed v14 Lite with an optimized frame of mind; the v14 neural nets are toned down to run on an HW3 computer.
Tesla v14 will use the same behavior, but its limits will be hardware-related, especially given that the cameras on HW3 vehicles are lower-resolution.
Tesla reveals its plans for Hardware 3 owners who are eager for updates
This will result in potentially more edge cases due to the lower quality perception and less long-range detection, but reaction time and overall confidence should be more refined.
There should also be a handful of additional features that are available on AI4 cars, such as:
- Starting Full Self-Driving from Park
- Auto Shift
- Streaks
- Speed Profiles
- Improved Dynamics, like Pulling Over for Emergency Vehicles
Tesla plans to release v14 Lite this month, but we are all familiar with how the company can be with timelines. Additionally, if v14 Lite has not proven to be ready for a wide release, Tesla will slam the brakes on the rollout.
We would anticipate that Tesla is testing v14 Lite internally, and likely has been for several months.
Elon Musk
SpaceXAI just launched into your kitchen with their new app
SpaceXAI just powered its first consumer app and it predicts what you want to buy.
SpaceXAI just made its first move into consumer AI, and it involves your grocery cart. On June 3, 2026, Gopuff and SpaceXAI announced the launch of Go, a Grok-powered shopping assistant built directly into the Gopuff app that predicts what you need before you even start searching for it.
Gopuff is an instant delivery platform that operates more than 400 micro-fulfillment centers across the U.S., delivering everyday essentials, snacks, drinks, and household items in as little as 15 minutes. It is not a restaurant delivery app or a marketplace. It owns its inventory, controls its warehouses, and handles its own logistics, which means it has built one of the most detailed consumer behavior datasets in retail over its 13-year history.
Go combines SpaceXAI’s advanced reasoning, voice, and image generation models with Gopuff’s dataset of hundreds of millions of orders and real-time cultural signals from X to prepare a suggested cart the moment a customer opens the app. It learns each shopper’s habits and automatically builds a personalized cart based on time of day, location, order history, and real-time indicators. Returning customers can check out with a single tap.
Rather than searching for specific items, users can describe a situation like a game-day party or the desire for a healthy breakfast and Go will assemble a cart automatically. It can also predict when shoppers are running low on items like coffee or paper towels and have them packed and delivered in under 15 minutes. Grok voice integration lets users talk to the app in plain conversational language and check out completely hands-free.
Gopuff co-founder and co-CEO Yakir Gola said: “Today, we believe the greatest friction left in commerce is not delivery or instantaneous access to the essentials customers need. It’s the moment before: the thinking, the deciding, the remembering. We’re combining Gopuff’s demand intelligence with xAI’s frontier reasoning to create an everyday shopping experience that feels like a true extension of you.”
Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO
The timing carries context beyond the product launch. SpaceXAI was formed after SpaceX completed an all-stock merger with Elon Musk’s xAI earlier this year, folding one of the most advanced AI labs in the world into the same corporate structure as the company preparing what could be the largest IPO in history. SpaceXAI is dipping into consumer-focused AI just as it prepares for its public debut, and while Musk has openly discussed building an everything app, this launch uses Grok to power another company’s product rather than launching a standalone consumer platform. Every consumer-facing deployment of Grok ahead of the IPO roadshow adds tangible evidence that SpaceXAI is not just an infrastructure play but a direct competitor in the AI application layer where OpenAI and Google are already fighting for dominance.