Tesla recently showed off a demo of Optimus, its humanoid robot, walking around in moderately challenging terrain—not on a flat surface but on dirt and slopes. These things can be difficult for a humanoid robot, especially during the training cycle.
Most interestingly, Milan Kovac, VP of Engineering for Optimus, clarified what it takes to get Optimus to this stage. Let’s break down what he said.
Optimus is Blind
Optimus is getting seriously good at walking now - it can keep its balance over uneven ground - even while walking blind. Tesla is currently using just the sensors, all powered by a neural net running on the embedded computer.
Essentially, Tesla is building Optimus from the ground up, relying on as much additional data as possible while it trains vision. This is similar to how they train FSD on vehicles, using LiDAR rigs to validate the vision system’s accuracy. While Optimus doesn’t have LiDAR, it relies on all those other sensors on board, many of which will likely become simplified as vision takes over as the primary sensor.
Today, Optimus is walking blind, but it’s able to react almost instantly to changes in the terrain underneath it, even if it falls or slips.
What’s Next?
Next up, Tesla AI will be adding vision to Optimus - helping complete the neural net. Remember, Optimus runs on the same overall AI stack as FSD - in fact, Optimus uses an FSD computer and an offshoot of the FSD stack for vision-based tasks.
Milan mentions they’re planning on adding vision to help the robot plan ahead and improve its walking gait. While the zombie shuffle is iconic and a little bit amusing, getting humanoid robots to walk like humans is actually difficult.
There’s plenty more, too - including better responsiveness to velocity and direction commands and learning to fall and stand back up. Falling while protecting yourself to minimize damage is something natural to humans - but not exactly natural to something like a robot. Training it to do so is essential in keeping the robot, the environment around it, and the people it is interacting with safe.
We’re excited to see what’s coming with Optimus next because it is already getting started in some fashion in Tesla’s factories.
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In a relatively surprising move, GM announced that it is realigning its autonomy strategy and prioritizing advanced driver assistance systems (ADAS) over fully autonomous vehicles.
GM is effectively closing Cruise (autonomous) and focusing on its Super Cruise (ADAS) feature. The engineering teams at Cruise will join the GM teams working on Super Cruise, effectively shuttering the fully autonomous vehicle business.
End of Cruise
GM cites that “an increasingly competitive robotaxi market” and “considerable time and resources” are required for scaling the business to a profitable level. Essentially - they’re unable to keep up with competitors at current funding and research levels, putting them further and further behind.
Cruise has been offering driverless rides in several cities, using HD mapping of cities alongside vehicles equipped with a dazzling array of over 40 sensors. That means that each cruise vehicle is essentially a massive investment and does not turn a profit while collecting data to work towards Autonomy.
Cruise has definitely been on the back burner for a while, and a quick glance at their website - since it's still up for now - shows the last time they officially released any sort of major news packet was back in 2019.
Competition is Killer
Their current direct competitor - Waymo, is funded by Google, which maintains a direct interest in ensuring they have a play in the AI and autonomy space.
Interestingly, this news comes just a month after Tesla’s We, Robot event, where they showed off the Cybercab and the Robotaxi network, as well as plans to begin deployment of the network and Unsupervised FSD sometime in 2025. Tesla is already in talks with some cities in California and Texas to launch Robotaxi in 2025.
GM Admits Tesla Has the Right Strategy
As part of the business call following the announcement, GM admitted that Tesla’s end-to-end and Vision-based approach towards autonomy is the right strategy. While they say Cruise started down that path, they’re putting aside their goals towards fully autonomous vehicles for now and focusing on introducing that tech in Super Cruise instead.
NEWS: GM just admitted that @Tesla’s end-to-end approach to autonomy is the right strategy.
“That’s where the industry is pivoting. Cruise had already started making headway down that path. We are moving to a foundation model and end-to-end approach going forward.” pic.twitter.com/ACs5SFKUc3
With GM now focusing on Super Cruise, they’ll put aside autonomy and instead focus solely on ADAS features to relieve driver stress and improve safety. While those are positive goals that will benefit all road users, full autonomy is really the key to removing the massive impact that vehicle accidents have on society today.
In addition, Super Cruise is extremely limited, cannot brake for traffic controls, and doesn’t work in adverse conditions - even rain. It can only function when lane markings are clear, there are no construction zones, and there is a functional web connection.
The final key to the picture is that the vehicle has to be on an HD-mapped and compatible highway - essentially locking Super Cruise to wherever GM has time to spend mapping, rather than being functional anywhere in a general sense, like FSD or Autopilot.
Others Impressed - Licensing FSD
Interestingly, some other manufacturers have also weighed into the demise of Cruise. BMW, in a now-deleted post, said that a demo of Tesla’s FSD is “very impressive.” There’s a distinct chance that BMW and other manufacturers are looking to see what Tesla does next.
BMW chimes in on a now-deleted post. The Internet is forever, BMW!
Not a Tesla App
It seems that FSD has caught their eyes after We, Robot - and that the demonstrations of FSD V13.2 online seem to be the pivot point. At the 2024 Shareholder Meeting earlier in the year, Elon shared the fact that several manufacturers had reached out, looking to understand what was required to license FSD from Tesla.
There is a good chance 2025 will be the year we’ll see announcements of the adoption of FSD by legacy manufacturers - similar to how we saw the surprise announcements of the adoption of the NACS charging standard.
One of the big undocumented changes in Tesla’s 2024 Holiday Update was the changes to the Energy app. While the Model S, Model X, and Cybertruck received the Consumption tab in the Energy app for the first time, the changes made for those models also carried over to Model 3 and Model Y.
The Consumption tab lets you view your vehicle’s consumption over recent trips as well as view projected range estimates based on historical usage, but it now offers different options.
Sadly, legacy Model S and Model X vehicles produced before the 2021 refresh still don’t have access to the Energy app at this time.
Energy App
Tesla’s Energy App previously let you view a lot of in-vehicle data on what is consuming energy and how to improve your energy consumption. It was previously refreshed in 2022 and brought Drive, Park, and Consumption tabs to help compare actual vehicle energy consumption versus what you’d expect from the EPA ratings.
The old Energy App's consumption page.
Not a Tesla App
Key Changes
The Energy App has seen a lot of changes - mostly in the name of simplicity and reducing confusion. Some changes reduce functionality, but others bring even more. All of these changes impact the Consumption tab - the Park and Drive sections are unchanged.
Distance
Previously, you were able to switch the graph on the Consumption tab to show the last 5, 15, or 30 miles. Instead, it is now a static display of the last 200 miles (or 300km). This means your last 200 miles of driving - whether it's a single trip or multiple trips. Your range prediction and energy usage are now based on 200 miles of driving instead of the previous selectable distance.
This allows for a more reasonable range prediction as small bursts of high-energy usage, such as time spent accelerating to highway speeds from an offramp, are now less of an impact and are instead averaged out by regular driving.
However, for those who love to take their Teslas to the track or tow regularly, this makes the consumption significantly less useful because you can no longer see your actual energy usage for the type of driving you’re doing. This could be fixed with a reset button or by adding the ability to select your distance — similar to before.
Projected Range and Average Wh/mi
Unfortunatley, the Instant Range button has been removed, and the graph is now locked on what was previously the Average Range. Essentially, you cannot view your real-time range based on current instantaneous consumption - but you can view the overall projected range.
Additionally, average Wh/mi and projected range are still displayed - but in different areas compared to before. The projected range is displayed on the center-left side of the graph, while the average Wh/mi is now displayed at the top of the screen.
Not a Tesla App
Compare Vs EPA
Another new feature is that the average range is now compared to the EPA estimated range in terms of wh/mi. You’ll be able to see whether your driving style and conditions put you over or under the EPA estimate in a pretty quick way, which is helpful.
This new comparison is located just under your average Wh/mi.
Small and minor adjustments to your driving style - like not taking off like an electric lightning bolt at every red light - will make a big difference to your range. Don’t worry - we know its hard, we love doing it too! Other things - such as driving downhill versus uphill, will have an impact that you can’t necessarily avoid unless you’re old enough that you went to school uphill both ways.
Color Changes / Regenerative Braking
In the previous Consumption view, energy used would be displayed in yellow, while energy gained through regenerative braking would be displayed in green. However, with this update, that has now changed. Anything below the vehicle’s rated range (the thicker horizontal line on the graph, will now be displayed in green, while any consumption above the vehicle’s EPA rating will now be displayed in yellow.
While this better matches the Drive tab of the Energy app, it now makes it much harder to view any energy gained via regenerative braking. Due to the long timeline (200 miles versus as short as 5 miles before), it’s now difficult to find any areas of regen since they’d be a smaller segment on the graph and are likely to be averaged out with regular driving.
The consistency of colors between the Drive and Consumption tabs is nice, but we’d still love a user-selectable distance for the x-axis and possibly a different color for regenerative braking.
Update: We’ve recently added this section to clarify that the y-axis is not mislabeled but that green now means better than expected efficiency instead of regen use.
Total Vehicle Consumption
The final new feature is a total vehicle consumption number at the bottom left, under the chart. It will tell you how much energy you’ve consumed over the distance you’ve driven so far. This is a convenient way of seeing exactly how much energy you’ve used.
Dynamic Y-Axis
The Y-axis in the Consumption tab is now dynamic—it expands and contracts automatically based on the driving data. We’ve seen it go from 400 Wh/mi to 800 Wh/mi. You likely need to be in a Model S Plaid or Cyberbeast with Launch Mode to see numbers much higher than that.
We’re sad to see the X-axis locked to 200 miles, but seeing total vehicle consumption and comparing average consumption against the rating is equally, if not even more, valuable.
Overall, the new and improved Consumption tab is simpler and doesn’t require user input. While it takes away some features, it makes it easier for drivers who may not use it regularly. The most important piece is the projected range, which is now easier to see and understand unless you're towing and need the historical usage erased because it’s now irrelevant to your current drive. Hopefully, Tesla will allow you to scrub the graph horizontally in the future, adding the ability for the user to adjust the X-axis dynamically.
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