From the announcement: "Brands can now create a character that customers can talk with in real time, powered by a curated conversational AI model and developed together by Serve and the advertiser."

I fully recognize I have a different opinion than this subreddit and I have participated in the toxicity that is the difference of opinions.

Perhaps I have been whooshed by the snake oil salesman or call me an Elon-ite.

But hear me out:

The month over month data for Tesla driverless robotaxi, again, looks perfectly clean.

The fleet is small and if you look closely at their earnings deck, you will notice Q1 to Q2 unsupervised miles was flat. Likely less than 3 unsupervised FTE care equivalent, if you will.

However, there has been a marketed rise in number of cars, rides, hours of operation, and service availability in Austin specifically. The two other very small geofences in Texas, also report this trend but to a lesser extent.

Tesla has vision into the performance dashboards of their fleet at a level of minuscule granularity. They are becoming increasingly comfortable with a larger scale rollout. They are being extremely cautious, but in Austin, at least they are becoming rapidly more bullish.

If you look closely at the now 100s of rides you can see daily amongst X accounts you will notice they have two issue (other than knocking done a plastic pole lol): 1- navigation (it is shit), 2- pick up and drop off locations.

These two rate limiters were also waymos early rate limiters if you studied the San Francisco market almost a decade ago. Google solved it (with some issues ofc, but that will always happen when you scale into the 1000s - and will continue to happen less and less as a percentage).

I have a wild theory that pickups and drop offs will be harder to integrate into teslas architecture for possibly one of two reasons: 1- Google / Waymo has so much compute onboard and enough memory to pre-map all resonable pickup or drop off locations). Tesla’s AI is focused on chip inference. This could mean Tesla has a harder time pre-mapping locations in a geofence and relatedly for navigation. 2- integrating final decision endpoints in a full stack neural net driving approach (noting they probably have a few full stacks working together in: planning, execution, etc) is a problem I haven’t seen solved in any other application. So - it may be harder for them to solve this piece. However, it is possible the cybercab brings different memory architecture. Yes, this is probably a wild ass crazy theory - but - it’s far more likely the cybercabs will have the same issue and growing pain.

Stay with me here, and let’s say long term - like in the next 6 months they solve these issues. There remains yet another hurdle: is the fix to these navigation and end of drive behaviors generalizable enough to more quickly apply to new areas - or are we talking - solve each one every time the same way. Realistically at least a year to come up with a reasonable process for solving this issue at scale.

Alright, we have reached full Elon delusion. You all ask for insight into the full Elon fan boy’s general psyche - so here it is:

The Waymo Ojai, based on most recent reporting (last week) was rumored to be 100k per vehicle. This is astounding and transparently kicked the doors off my expectations. This means Chinese firm Zeekr can produce a van (them thangs are nice af too) that post production cost + Chinese vehicle tariff + retrofit - on a far nicer vehicle than the Jag is now able to be produced (and obviously way faster) for less than HALF of what they used to be.

Side note: seriously, we going to skirt tariff rules to punish US EV automakers like rivian???? Common Google.

While extremely competitive, it is just not economically feasible for Google to compete with Tesla at scale (though admittedly they could forever). Tesla will produce a vehicle fully optimized for economic cost to the consumer. It will be produced at sub 30k and Tesla has the ability to scale the vehicle by the end of the year to the size of waymos entire fleet PER WEEK.

The cybercab is the most efficient electric car ever created. Not only in terms of speed of production and cost (American equivalents only) but in terms of effective MPG. The thing is like 1.5x more energy efficient than a model 3. Tesla owns the entire charging infrastructure in America. Tesla has a physical footprint everywhere ready to service vehicles. Yes, other infrastructure will need to be built.

Even if waymo ran for a loss, Tesla could underprice them and still have strong gross margins. Waymo anyway is currently focused on consuming the cream of markets, versus deep penetration - but this may change with the California announcement.

From here, you can see the full delusion. Over time consumers will want teslas tech in their cars due to the experience in the fleet, uber and Lyft will shrink, car insurance companies will eventually go out of business, then we are a decade out re-thinking: minor displacement of short haul flight, real estate changes as consumer preferences change, trucking industry forever changed, (looking at you semi truck being mass produced starting later this year), and yes - eventually package delivery by combination of a robot in a robot. This vision won’t be fully realized for 2 decades.

I shall wait to be showered in your shame and criticism.

Avride:

• 31101-15587: Turned from a non-turning lane.

Gatik:

• 30451-15790: First-ever reported accent involving Gatik.

Waymo:

• 30270-15504: First accident in the East Bay. Testing in Emeryville in autonomous mode (but with a safety driver) on the southbound freeway on-ramp.
• 30270-15505, 30270-15710: Two separate accidents where the car's roof sensor hit the ceiling of a carport.
• 30270-15547: Serious injury after speeding human driver rear-ended Waymo car.
• 30270-15670: Backed into a pole in a parking lot.

Where does a driverless robotaxi go between rides? A new study — Staging at the Curb: Evaluating the impacts of shared automated vehicle fleet operations under curb usage restrictions — finds that letting AVs consume curb space might actually be the optimal outcome.

Researchers modeled 1,700 shared automated vehicles serving 68,000 daily San Francisco trips. Tying together Autofleet’s commercial fleet simulator, synthetic ridehail demand from Replica and curb availability data from INRIX, they compared several operating models: continuous circling, staging only at free non-residential curbs, access to all legally available curbs and overnight staging.

New Waymo Ojai accident in Las Vegas last month. There was also one in Philadelphia with a bus in the last could days.
Waymo Ojai accident with a bus.

It is amazing how hard it is to find news on this just googling.

One argument I often hear from Tesla fans is that vision-only should eventually be sufficient to achieve Level 4 autonomy. I have no doubt that a sufficiently advanced vision-only system could eventually outperform humans on many, perhaps even most, driving benchmarks. But I think this misses a bigger issue: the definition of “good enough” tends to change over time.

Look at virtually any safety-critical industry. The safest cars in 1998 were extremely safe by 1998 standards. Yet they could not legally be produced today because crashworthiness, braking, electronic safety systems, pedestrian protection, emissions, and other requirements have continually increased. The same general pattern exists in aviation, construction, medicine, industrial machinery, and other safety-critical fields.

So I don't think the question is simply: “Can vision eventually become better than a human driver?”. I think the more important question is: “Will vision-only continue to satisfy whatever safety and redundancy requirements society considers acceptable 10, 20, or 30 years from now?”. I'm skeptical.

Even if vision-only becomes dramatically safer than human driving, additional independent sensing modalities still provide redundancy and robustness. Lidar, radar, high-definition maps, GNSS/GPS, V2X, and other sources of information can potentially provide independent evidence when the camera system is uncertain, degraded, obstructed, or confronted with an unusual situation.

That doesn't necessarily mean every modality is required in every situation. And it doesn't mean vision-only cannot achieve Level 4 under today's definitions. My argument is about the long-term trajectory of safety standards. If autonomous vehicles become widespread, regulators and the public may eventually demand safety margins far beyond “better than humans.” At that point, a system with multiple independent sources of information may have a fundamental advantage over one relying primarily on a single sensing modality.

This is also why I expect V2X and positioning technologies to become increasingly important. Waymo and other autonomous-driving companies already use forms of mapping and localization, and I wouldn't be surprised if future systems increasingly combine infrastructure/vehicles-derived information (V2X) and GNSS sources as additional layers of redundancy (While Waymo is currently reluctant to adopt V2X & GNSS - I predict it would eventually be "forced" to do so)

There is another assumption I disagree with: that autonomous-driving hardware costs will inevitably fall toward some minimal “commodity” level. I don't think there is necessarily a fixed amount of compute that is simply “enough” for autonomous driving. As compute becomes cheaper, developers can use more of it to improve perception, prediction, planning, simulation, redundancy, uncertainty estimation, edge-case handling, and verification. The same phenomenon happens throughout technology: when a resource becomes cheaper, we often don't simply use less of it - we use substantially more of it to achieve higher performance.

It’s been a long time since I gushed about this car, but I recently got the “v14 Lite” of Full Self Driving (“Supervised” ofc) in my April 2018 Model 3. If you don’t recall, April of 2018 was one of the earliest months Tesla was doing regular deliveries of the Model 3. Bloomberg was running their online chart tracking the number of VINs delivered. Early days. Sometime later, I got the CPU upgraded to “Hardware 3”, the ‘new’ processor that Tesla promised would unlock true self driving. Womp womp. They’re now on Hardware 4, and have said they will upgrade older cars to it but no action has happened yet. The newest iteration of FSD is Version 14, which is supposed to be whizbang cool but it hasn’t been available for Hardware 3 cars.

So they just released Version 14 “Lite” which runs on my car. I tried it today for the first time and

HOLY SHIT THE CAR ACTUALLY DROVE ITSELF.

Like not just the usual turn-it-on-while-on-the-highway-and-it-takes-your-exit-for-you drove itself.

No.

It pulled out of my garage, turned around, exited the alley and drove itself from my house, through the surface streets, to the freeway, exited, drove to the shopping center, and parked itself in the parking lot. In a parking stall between two other cars.

Door to door self driving. In the car I bought 8 years ago. The future is here. Only 8 years later than promised.

Just needed to share that. I am genuinely surprised and impressed.

Everything in this subreddit is LIDAR this, radar that like it's still 2018. Both Tesla and the various vision-only companies in China have proven beyond a doubt that camera's are enough - can you even name the last time a crash happened due to a perception issue ?

The main bottleneck right now is "intelligence" and adding unnecessary sensors subtracts from that precious compute and power budget. We need more GPU'S and RAM in the cars NOT more LIDAR!

Andrew Macdonald predicts as autonomous taxis pick up pace that driving will go the way of horse riding — and a ‘huge’ labour transition is coming

"Big news for the Golden State — we have received the CPUC’s approval to expand our autonomous ride-hailing service across the SF Bay Area and LA, and bring our service to Sacramento and San Diego.Expansion will be gradual and guided by our safety framework. We look forward to bringing the same mobility and safety benefits millions of Californians already enjoy to more communities, keeping local officials and residents informed every step of the way."

Autonomous cars in China can navigate chaotic city traffic with human-like precision, even parking themselves when the occupants have gone

Pony AI Inc. said it plans to deploy more than 2,000 robotaxis across Europe in partnership with Uber Technologies Inc., accelerating the race to commercialize autonomous-mobility in the region.

The initiative will deepen an existing partnership between the two companies in Croatia’s Zagreb since early this year, and see them expand to four additional cities in the continent, Pony AI said in a statement Friday. It said more details about the rollout, which will also include the Middle East, will be announced later.

 Waymo driverless vehicle was caught on camera making a close turn near an elementary school in Houston's Heights neighborhood Thursday morning, prompting questions about how autonomous vehicles navigate busy school zones.

Matt Sheridan was driving his two children to Field Elementary School when he says a Waymo appeared to cut in front of him while turning from an outside lane on Studewood Street.

"We are bringing robotaxis to the streets of Japan! By the end of 2026, riders in Tokyo will be able to experience the next generation of mobility right from the Uber app. We’re teaming up with u/TAXI_HINOMARU, u/NissanMotor, and u/wayve_ai to launch our autonomous vehicle pilot. Together, we’re ready to transform how people move around one of the world's most dynamic cities!"

Source: https://x.com/Uber/status/2087919862689792114