Anyone can use 3d mapping and geofencing. That's not a disqualifier.

As long as the remote operators and assistance teams are an order of magnitude smaller than putting a driver in every car, then it's close enough to autonomy to count as "closer" and to be useful.

"Anyone can use 3d mapping and geofencing" - that shows you their limitations and also doesn't qualify for "completely autonomous" standard. - Completely means anytime (regarding weather conditions or time of the day), anywhere (no geofencing) and completely adaptive behavior to the permanently and randomly driving conditions humans deal with while driving. Pattern recognition software alone (A.I.) would never be able to match human driving performances.

"As long as the remote operators and assistance teams are an order of magnitude smaller than putting a driver in every car" - the entire gig is way to expensive and requires "time travel" level of scientific achievements, which is 100% fiction and 0% reality.

> doesn't qualify for "completely autonomous" standard

No, but it does qualify for "closer to reality today than they were 5 years ago"

> Pattern recognition software alone (A.I.) would never be able to match human driving performances.

That's okay. A trained human can do much better than necessary, and geofenced pattern recognition software doesn't have to be as good, especially because it should have better reaction times and braking force than a human.

> "As long as the remote operators and assistance teams are an order of magnitude smaller than putting a driver in every car" - the entire gig is way to expensive and requires "time travel" level of scientific achievements, which is 100% fiction and 0% reality.

Why?

If you can run a fleet of 300 cars with 30 people, that's already enough to make tons of money once you get well-established. You don't need any scientific improvements for that, let alone the ones you're exaggerating.

"No, but it does qualify for" - please check the statement my comment was responding to. The "1 step forward, 3 steps back" way the automation sector does R&D is not moving towards reality, is moving towards confusing the public to justify their pitch to eventual investors. "That's okay." - Maybe for you, but not for investors and for the market. "Why?" - It's unsustainable, requiring resources (provided at this point by naïve investors) that commercialization can't provide. Just look at the over $100 billion wasted on this hallucination with zero actual returns. Investors expect palpable returns, not promises and delays.

> 1 step forward, 3 steps back

What are the steps back?

They're slow but they're improving. And they don't need to reach their original lofty goal.

> "Why?" - It's unsustainable

Sorry, the "Why" was directed at the level of scientific achievement you claim they need.

"What are the steps back?" - every step forward, no matter in which direction, requires more computing power from a limited computing source that gets power from a limited power source (limited because they are mobile not plugged to a network). By using more computing, the system would prioritize towards the "step forward", allocating less resources to other processes (other sensors or the new electronic system of that vehicle). More computing power (when more essential processes get to have better performance) is requiring more electricity, from a solely electric vehicle with a limited battery capacity, that ultimately would generate shorter battery range available. The more computing power and more battery power you add on any vehicle, the more you increase the vehicle manufacturing or acquiring costs.

"the level of scientific achievement" - every single step, every single minute and every single individual (the financial input), is prohibitively expensive for this R&D project, and it is not justified by any means by the results (the financial output), Companies and investors don't care about progress. They care about profits, and, in case progress would stay in their path to make profits, they'll fight against it. You should check waymo salaries, hardware prices, operations costs, and fleet management costs. From operational POV, every mile covered by those vehicles translates into a price payed by the company, money that are not recovered whatsoever at this point. Vehicle lifecycle, insurance, maintenance, cleaning and the electricity used, adds up very quickly and could go as high as half a billion dollars per year - "Argo has about 1,300 employees and is likely burning through at least $500 million a year, industry participants say." (https://www.theinformation.com/articles/argo-ai-planning-pub...). Now remember how in business, any investor usually expects to make 10 times his or her investment, in this case (the Argo.ai example) meaning that the profits (after all expenses and taxes are substracted) to be around $5 billion per year. This is the reason why Ford decided to shut down Argo, which was burning half a Billion a year with no end in sight. To directly address your statement - the scientific level needed would require way too much money to justify the road to accomplish it. Basically, all those parts interested either do not have those money, or are part of a business model that requires substantial returns on a relatively short term, and cannot afford to finance projects with constantly moving delivery dates for fictional ideas.

Does it matter? They are functional and safe enough for most sunbelt cities. We may not have FSD from day one but what we do have is leagues ahead of what's possible 5 years ago.

What these failing companies are doing for almost 15 years now is 1 step forward, 3 steps back while promising they are 6 months away from the impossible. A.I. is only pattern recognition software statistical tool, that has zero capability of learning by itself from previous experience, and that shows you how any business designed around updating the constantly changing environmental data required to make the robots operate at a decent level, is prohibitively expensive.