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Comment by mrshadowgoose | Hacker News Reader

You can, today, go to Pheonix Arizona, download the Waymo One app, and summon a full self driving vehicle. This happened silently at the end of 2020, and was overshadowed by the ongoing pandemic doom and gloom. https://blog.waymo.com/2020/10/waymo-is-opening-its-fully-dr...

On the subject of danger. Literally everything we do is dangerous to some degree. Everything. Self-driving does not need to be perfect, but only better than human drivers. We're likely already at that point with Waymo vehicles.

On the subject of automation. Humanity is on track to have the computational power to perform whole brain emulation decades before 2100. Even if we don't solve the general AI problem through other pathways, we will solve it through this path. Ethical problems aside, once this is achieved, everything will be automatable at a human level of competence.

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> On the subject of danger. Literally everything we do is dangerous to some degree.

I don't disagree with your take and I'm a self driving car proponent, but I'm worried about what process we take to get there.

One thing I've taken away from the pandemic is that people seem to have no problem imposing their tolerance for risk on others. Seems like we are on a path to play this dynamic out again in how self-driving cars come to market unless that safety profile is really well controlled and understandable.

Even if at a population-level self-driving is slightly safer statistically than person-driving, there are enough edge cases to give me pause right now, and at the individual-level it may raise my risk either as a pedestrian or driver and certainly changes what is predictable behavior [1].

[1]: https://arstechnica.com/cars/2021/04/why-its-so-hard-to-prov...

> On the subject of automation. Humanity is on track to have the computational power to perform whole brain emulation decades before 2100. Even if we don't solve the general AI problem through other pathways, we will solve it through this path. Ethical problems aside, once this is achieved, everything will be automatable at a human level of competence.

Is this actually true? I haven't heard of this. You're saying we will have an AI as good as a grown educated adult before 2100? I can't believe this at all - do you have a citation?

Yes, and the methodology I've described (whole brain emulation/WBE) is the worst-case, brute-force, but guaranteed approach. The following diagram captures the expected growth rate of computing power, and contrasts it with several thresholds (in blue) for emulation fidelity ultimately required: https://en.wikipedia.org/wiki/Mind_uploading#/media/File:Who...

The human brain works, therefore this technique will work, it's just a matter of having enough computing power.

I will re-iterate though, we are pursuing various alternative pathways to artificial intelligence, and modern machine learning has already demonstrated super-human performance within constrained domains. It's my personal belief that we will achieve human-level general intelligence long before WBE becomes practical.

This sounds bonkers to me. We don't even understand fully what it would take to emulate a brain right now. I don't believe this for one second.

Emulating a brain doesn't necessarily mean you can tell it what to do. After all, you can't always tell humans what to do, and this might somehow be a necessary component of human-level intelligence.

Would it not be feasible yet for very simple organisms?

It's currently being worked on [1]. It's only recently that we've managed to capture the complete nervous system connectivity of C. Elegans, one of the simplest organisms with a nervous system. [2]

[1]https://en.wikipedia.org/wiki/OpenWorm

[2]https://www.nature.com/articles/s41586-019-1352-7

"There are more synapses in each human brain than stars in the known universe". [1]

I don't believe there is anything guaranteed about "whole [human] brain emulation" in this century.

[1] This isn't quite true, because we estimate there are around 10^22 to 10^24 stars in the universe, while estimations for number of synapses range from 10^14 to 10^15.

We have no idea what kind of "whole brain emulation" it would take to produce what we understand as intelligence, so all this seems highly speculative.

We know it only takes 20W of power for the real thing to work.

Let that sink in. We know it isn’t impossible to run a general intelligence computer on 20W because every single one of us is living proof that it is possible. There is no reason why something man made shouldn’t be able to do the same thing. How to do that is of course a different matter, but it isn’t speculative that it can be done, it’s a direct consequence of our own existence.

No, it's not remotely true. Roughly equating neurons to petaflops, counting flops, drawing the best fitting straight line, and then announcing a date where the line gets high enough is not a remotely reasonable way to estimate a "worst case guarantee" date.

It's not impossible that some sort of thing would happen, but anyone who tells you that it can't possibly fail to be achieved in the next 80 years is lying, either to your or to themselves.

Please suggest an alternative estimation technique then.

There is a certain # of calculations/s necessary to meaningfully emulate a neuron. We currently have no idea what level of fidelity is required, but we can make guesses for each of the levels of fidelity that might be required.

The estimates that assume the highest (and likely unnecessary) level of fidelity currently top out at 2100.

For the record, I never claimed that failure was impossible, I used the phrase "on track". It's totally possible that there might be some surprise quantum weirdness going on that would be intractable to emulate with classical computers, but we've found no evidence of that to date.

This is the kind of thing that is very misleadingly true. If you simply take growth in computing power and extrapolate to the end of the century, and compare it to the current best estimate of human brain computing power, then yes, we'll get there.

But 1) that is an estimate of human brain computing power, based on number of neurons and possible connections. We have no idea if that is really a valid unit of computing "power." Do brain only compute things via voltage thresholds across synapses? Then yes, maybe this is an accurate estimate. But there are a whole lot of subcellular signal cascades happening at molecular levels we can't even begin to count and we have no idea whether or not those are also computing something accessible to the rest of the brain. 2) Matching the computing power of a brain doesn't mean you can emulate it. Emulating something requires knowing the target architecture and software. It is possible we can figure out exactly what a brain is doing to an accurate enough level to emulate it by the end of the century, but we certainly don't know how to do that right now, even if we had the computing power. Remote imaging techniques are not nearly good enough (because again, so many of the processes are subcellular) and you can't open up a brain without destroying it. This is actually a much broader problem in biology and we have figured out ways to partially dissect some animals while still keeping them alive long enough to figure out how a system works in vivo, but doing that with a brain is not something we have ever come remotely close to doing and there isn't really any ethical way to even think of how we can try to figure it out.

> You can, today, go to Pheonix Arizona, download the Waymo One app, and summon a full self driving vehicle.

Consider Google's (okay, Alphabet's) standards for success though.

My guess is that a metro area with less than 0.5% of the US population does not qualify as a successful product. Maybe as a successful small beta test.

Also, given Arizona's overly cozy relationship with self-driving [1], I would not necessarily trust a program too much on the basis that it's operating there.

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[1] https://www.theguardian.com/technology/2018/mar/28/uber-ariz...

Can you really? I remember that announcement and there was a lot of fudged language. You have to be a "member of the public service". You can download the app because it's in the app store, which is not the same thing as hailing a driverless vehicle.

It's not clear that member of the general public can actually sign up for it. Has anyone done that and taken a driverless ride in Phoenix? Happy to get more updated info / be corrected.

(And if this seems like a unreasonable amount of suspicion, I invite others to go back and read their press releases from the last 3 or 4 years, and tell me if that gives you an accurate picture of where the service is today)

In that 50 sq mile Chandler area, anyone can download the app and hail a ride. I don’t live in AZ, but I’ve seen several YouTube videos and r/selfdrivingcars posts/comments that can confirm it.

>On the subject of danger. Literally everything we do is dangerous to some degree. Everything. Self-driving does not need to be perfect, but only better than human drivers.

The problem is this statement is written like a technocrat wrote it rather than someone who makes public policy. From an engineering perspective, it’s true that it would only need to be better than a human driver. To be implemented though, it needs approval in the public sphere and not just engineers. This presents a very real publicity problem.

You are correct that everything in life contains risk. Risk is defined as severity x probability. While the severity may be the same, I think humans judge the probability very different between human and autonomous drivers.

I think it’s rooted in the need for humans to understand what’s under the hood (no pun intended) to trust the decision making capability. We already have this with human drivers through the tool of empathy evolved over millions of years. We can reasonably assume we know what humans will do. (Incidentally it’s also why witnessing someone with mental illness puts us on edge). We have no such ability to decipher an autonomous car, especially for the layman. So this distorts the uncertainty in the risk assessment and any accident can disproportionately cause our assumption of risk to elevate.

For me personally, your point really resonates. I trust human drivers in part because our incentives are aligned: neither one of us wants to get into an accident. The incentives of a machine learning model are harder to introspect on, as you point out.

I think there's another issue here, too. It relates to the observation that folks have a fear of flying, but not really a fear of driving, despite driving having about a 1 in 98 chance of killing you over your lifetime, while for aircraft it's more like 1 in 7178 (2008 data from USA Today...hopefully directionally correct). It's been discussed in research extensively[0], and seems to relate to whether or not the person feels they have a sense of personal control. I think your point is well-taken that the technological risks and the publicity challenge are independent barriers to the widespread adoption of AVs.

[0]: https://oxfordre.com/communication/view/10.1093/acrefore/978...

There’s been a few downvoted without elaborating on the disagreement, so I’ll add if you think this is incorrect take some time to think about how well policy and science were received during the pandemic. Policy will never be completely data-driven because humans do no intuitively think on statistical grounds.

Is there any update on how's that truly driverless program going for Waymo?

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