Comment by mattlondon

>It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

Not really. If Google released all of this first instead of companies that have never made a profit and perhaps never will, the case law would simply be the copyright holders suing them for infringement and winning.

> It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

It’s not that crazy. Sometimes the rational move is to wait for a market to fully materialize before going after it. This isn’t a Xerox PARC situation, nor really the innovator’s dilemma, it’s about timing: turning research into profits when market conditions finally make it viable. Even mammoths like Google are limited in their ability to create entirely new markets.

I also think the presence of Sergey Brin has been making a difference in this.

> It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

I always thought they deliberately tried to contain the genie in the bottle as long as they could

Not true at all. I interacted with Meena[1] while I was there, and the publication was almost three years before the release of ChatGPT. It was an unsettling experience, felt very science fiction.

[1]: https://research.google/blog/towards-a-conversational-agent-...

It was a surprise to OpenAI too. ChatGPT was essentially a demo app to showcase their API, it was not meant to be a mass consumer product. When you think about it, ChatGPT is a pretty awkward product name, but they had to stick with it.

Quibi would be if someone came in 10 years from now and said "if we put a lot more money behind spitting out content using characters and settings from Hollywood IP than we'll obviously be way more popular than a tech company can be!"

I love Volvo, am considering buying one in a couple weeks actually, but they're doing nothing interesting in terms of ADAS, as far as I can tell. It seems like they're limited to adaptive cruise control and lane keeping, both of which have been solved problems for more than a decade.

It sounds like they removed Lidar due to supplier issues and availability, not because they're trying to build self-driving cars and have determined they don't need it anymore.

At first I gave him the benefit of the doubt, like that weird decision of Steve Jobs banning Adobe Flash, which ran most of the fun parts of the Internet back then, that ended up spreading HTML5. Now I just think he refused LIDAR on purely aesthetic reasons. The cost is not even that significant compared to the overall cost of a Tesla.

Yeah its absurd. As a Tesla driver, I have to say the autopilot model really does feel like what someone who's never driven a car before thinks it's like.

Using vision only is so ignorant of what driving is all about: sound, vibration, vision, heat, cold...these are all clues on road condition. If the car isn't feeling all these things as part of the model, you're handicapping it. In a brilliant way Lidar is the missing piece of information a car needs without relying on multiple sensors, it's probably superior to what a human can do, where as vision only is clearly inferior.

From the perspective of viewing FSD as an engineering problem that needs solving I tend to think Elon is on to something with the camera-only approach – although I would agree the current hardware has problems with weather, etc.

The issue with lidar is that many of the difficult edge-cases of FSD are all visible-light vision problems. Lidar might be able to tell you there's a car up front, but it can't tell you that the car has it's hazard lights on and a flat tire. Lidar might see a human shaped thing in the road, but it cannot tell whether it's a mannequin leaning against a bin or a human about to cross the road.

Lidar gets you most of the way there when it comes to spatial awareness on the road, but you need cameras for most of the edge-cases because cameras provide the color data needed to understand the world.

You could never have FSD with just lidar, but you could have FSD with just cameras if you can overcome all of the hardware and software challenges with accurate 3D perception.

Given Lidar adds cost and complexity, and most edge cases in FSD are camera problems, I think camera-only probably helps to force engineers to focus their efforts in the right place rather than hitting bottlenecks from over depending on Lidar data. This isn't an argument for camera-only FSD, but from Tesla's perspective it does down costs and allows them to continue to produce appealing cars – which is obviously important if you're coming at FSD from the perspective of an auto marker trying to sell cars.

Finally, adding lidar as a redundancy once you've "solved" FSD with cameras isn't impossible. I personally suspect Tesla will eventually do this with their robotaxis.

That said, I have no real experience with self-driving cars. I've only worked on vision problems and while lidar is great if you need to measure distances and not hit things, it's the wrong tool if you need to comprehend the world around you.

>>The biggest L of elon's career is the weird commitment to no-lidar.

I thought it was the Nazi salutes on stage and backing neo-nazi groups everywhere around the world, but you know, I guess the lidar thing too.

I have HW3, but FSD reliably disengages at this time of year with sunrise and sunset during commute hours.

Yeah, that and running Grok on a trillion GPUs in space lol

Obviously both will exist and compete with each other on the margins. The thing to appreciate is that our physical world is already built like an API for adult humans. Swinging doors, stairs, cupboards, benchtops. If you want a robot to traverse the space and be useful for more than one task, the humanoid form makes sense.

The key question is whether general purpose robots can outcompete on sheer economies of scale alone.

It's called a dishwasher, washing machine, and dryer. Plus like robomowers, vaccums etc.

I mean, I would take a robot to handle all of my housework.

Purpose built, that probably takes the form of a humanoid robot since all of tasks it needs to do were previously designed for humanoids.

Those are not "real advances in the field", which is why they are constantly abandoned for the next new buzzword.

Edit:

This just in:

https://news.ycombinator.com/item?id=46870514#46929215

The Next Big Thing™ is going to be "context learning", at least if Tencent have their way. And why do we need that?

>> Current language models do not handle context this way. They rely primarily on parametric knowledge—information compressed into their weights during massive pre-training runs. At inference time, they function largely by recalling this static, internal memory, rather than actively learning from new information provided in the moment.

>> This creates a structural mismatch. We have optimized models to excel at reasoning over what they already know yet users need them to solve tasks that depend on messy, constantly evolving context. We built models that rely on what they know from the past, but we need context learners that rely on what they can absorb from the environment in the moment.

Yep. Reasoning is so 2025.

What do you think I said that you're contradicting?

IMO the presence of safety chase vehicles is just a sensible "as low as reasonably achievable" measure during the early rollout. I'm not sure that can (fairly) be used as a point against them.

I'm comfortably with Tesla sparing no expense for safety, since I think we all (including Tesla) understand that this isn't the ultimate implementation. In fact, I think it would be a scandal if Tesla failed to do exactly that.

Damned if you do and damned if you don't, apparently.

Its irrelevant. A robot is a robot.

Dictionary def: "a machine controlled by a computer that is used to perform jobs automatically."

They couldn't even make burger flipping robots work and are paying fast food workers $20/hr in California.

If that doesn't make it obvious what they can and cannot do then I can't respect the tranche of "hackers" who blindly cheer on this unchecked corporate dystopian nightmare.

"More video" (gigabytes) is a straw man.

The key metric is more unusual situations. That scales with miles driven, not gigabytes. With onboard inference the car simply logs anything 'unusual' (low confidence) to selectively upload those needle-in-a-haystack rare events.

GPT likes to argue, and most of its arguments are straw man arguments, usually conflating priors. It's ... exhausting; akin to arguing on the internet. (What am I even saying, here!?) Claude's a lot less of that. I don't know if tracks discussion/conversation better; but, for damn sure, it's got way less verbal diarrhea than GPT.

Experiencing the same. It seems Anthropic’s human-focused design choices are becoming a differentiator.

To me ChatGPT seems smarter and knows more. That’s why I use it. Even Claude rates gpt better for knowledge answers. Not sure if that itself is any indication. Claude seems superficial unless you hammer it to generate a good answer.