[Herring]

AI is not good enough yet for anything requiring deep reasoning, mission-critical work, error detection at a human-expert level, or handling unpredictable edge cases.

It just talks like it's very smart, and humans apparently have a bias for persuasive communication skills. It's also very fast, which humans also think indicates general intelligence. But it's not, and that's why most LLM tools are author-focused, so that a human expert can catch errors.

The way you know fully autonomous driving is nowhere near ready is by noticing we don't even trust robots to do fully autonomous cooking and cleaning. Similarly, let's see it understand and refactor a massive codebase first.

[avikalp]

I have had a similar discussion with a fellow On-Deck Founder, and here is where we reached:

- More than being "good enough", it is about taking responsibility. - A human can make more mistakes than an AI, and they are still the more appropriate choice because humans can be held responsible for their actions. AI, by its very nature, cannot be 'held responsible' -- this has been agreed upon based on years of research in the field of "Responsible AI". - To completely automate anything using AI, you need a way to trivially verify whether it did the right thing or not. If the output cannot be verified trivially, you are just changing the nature of the job, and it is still a job or a human being (like the staff you mentioned who remotely control Waymos when something goes wrong). - If an action is not trivially verifiable and requires AI's output to directly reach the end-user without a human-in-the-loop, then the creator is taking a massive risk. Which usually doesn't make sense for a business when it comes to mission-critical activities.

In Waymo's case, they are taking massive risks because of Google's backing. But it is not about being 'good enough'. It is about the results of the AI being trivially verifiable - which, in the case of driving, is true. You just need three yes/no answers: Did the customer reach where they wanted? Are they safe? Did they arrive on time? Are they happy with the experience?

[Herring]

I'd be really hesitant to say anything involving humans and human judgement under uncertainty is trivial. What if the customer wants the car to drive aggressively, maybe speed a little where it "seems" safe? Should the car stop for an object that might be a plastic bag or a child's backpack? Even manual drivers are difficult to "verify" because accidents and traffic violations depend on interpretations of events, which is why we often have to go to court.

[mrshadowgoose]

> The way you know fully autonomous driving is nowhere near ready

How do you reconcile this claim with Waymo's dramatically increased rate of expansion these past few years?

[Herring]

Billions of dollars from Google, basically.

https://www.businessinsider.com/robotaxis-may-mobility-tesla...

High operational costs, low revenue potential, technical difficulties, competitors exiting the space.

[mrshadowgoose]

Sorry, that's goalpost moving.

Just reminding you of your earlier claim:

> AI is not good enough yet for anything requiring deep reasoning, mission-critical work...

Is driving a mission-critical function? Due to its safety critical nature, many would say "yes".

So have you simply pivoted to "oh it does work, but it's not as profitable as it should be"?

[Herring]

You started the business discussion, not me. You need to decide if you want to continue it or not.

When your tech is unreliable, it costs you money. The need for remote human assistance during edge cases means you have to staff that. You need really expensive sensors, so more upfront costs and maintenance. You can't run when it's rainy/snowy/etc, so more downtime. Maybe even slower rides and longer wait times so lower utilization. And of course more AI updates, more training, more data cleaning/labeling, more engineers etc etc.

[mrshadowgoose]

> You can't run when it's rainy/snowy/etc, so more downtime.

Waymo vehicles don't work in the rain? This is easily verifiable as false.

You really have a tough time with being wrong, don't you?

[llm_trw]

>AI is not good enough yet for anything requiring deep reasoning, mission-critical work, error detection at a human-expert level, or handling unpredictable edge cases.

Ai is better than humans at all those things. It's not good at those things when the context it needs to look over is more than a few thousand tokens.

Rejoice programmer, for your inability to write modular code saved your job.

[azthecx]

Apt username for such a bonkers response

[shermantanktop]

I thought my 3000 line kitchen sink function which mutates globals, uses n+1 fetching, and supports 50 feature flags was a bad idea…maybe not?