lyapunova

Thank you for your rebuttal. It is good to think about the "just a stochastic parrot" thing. In many ways this is true, but it might not be bad. I'm not against replay. I'm just pointing out that I would not start with an _affordable_ 20k robot with fairly undeveloped engineering fundamentals. It's kind of like trying to dig a foundation to your house with a plastic beach shovel. Could you do it? Maybe, if you tried hard enough. Is it the best bet for success? doubtful.

Thanks for maintaining benchmarks here. Is there a github repo that might accompany the benchmarks that I could take a look at / reproduce?

So, a couple things here.

It is true that replay in the world frame will not handle initial position changes for the shirt. But if the commands are in the frame of the end-effector and the data is object-centric, replay will somewhat generalize.(Please also consider the fact that you are watching the videos that have survived the "should I upload this?" filter.)

The second thing is that large-scale behavior cloning (which is the technique used here), is essentially replay with a little smoothing. Not bad inherently, but just a fact.

My point is that there was an academic contribution made back when the first aloha paper came out and they showed doing BC on low-quality hardware could work, but this is like the 4th paper in a row of sort of the same stuff.

Since this is YC, I'll add - As an academic (physics) turned investor, I would like to see more focus on systems engineering and first-principles thinking. Less PR for the sake of PR. I love robotics and really want to see this stuff take off, but for the right reasons.

To be honest, I actually really like the visual delivery here. It's especially helpful for understanding what's going on with computer vision problems. Please make more!

I can appreciate that, but also they are recording and replaying motor signals from specific teleoperation demonstrations. Something that _was_ possible in the 1950s. You might say that it is challenging to replay demonstrations well on lower-quality hardware. And so there is academic value in trying to make it work on worse hardware, but it would not be my goto solution for real industry problems. E.g. this is not a route I would fund for a startup, for example.

Sorry, but this is a lot of marketing for the same thing over and over again. I'm not against Aloha as an _affordable_ platform, but skimping on hardware is kind of a bug not a feature. Moreover it's not even _lowcost_, its BoM is still like 20k and collecting all the data is labor intensive and not cheap.

And if we're focusing on the idea, it has existed since the 1950s and they were doing it relatively well then:

https://www.youtube.com/watch?v=LcIKaKsf4cM

To be honest, most researchers in applied ML in the bay say the opposite. If you are trying to be nimble and prototype, use pytorch. If you're trying to gain some optimizations as you near deployment, rewrite in Jax.

Let me say, he's a great teacher! I took a CV class with him. He should teach more, and take it seriously.

Being a popular AI influencer is not necessarily correlated with being a good researcher though. And I would argue there is a strong indication that it is negatively correlated with being a good business leader / founder.

Here's to hoping he chills out and goes back to the sorely needed lost art of explaining complicated things in elegant ways, and doesn't stray too far back into wasting time with all the top sheisters of the valley.

Edit: the more I think about it, the more I realize that it probably screws with a person to have their tweets get b-lined to the front page of hackernews. It makes you a target for offers and opportunities because of your name/influence, but not necessarily because of your underlying "best fit"

The headline, the picture, the article --- it would be easier to take them seriously if they just made the tools work and stopped posing for band pictures.

I am happy to have the tools, but the hype, the valuation, the "we have solved everything" mentality. It's just so offputting.

I think the problem with stuff like this is that in many cases the authors have an idea like "LLMS + ???? = Operating System !"

which is not that hard of an idea to come up with. Generally in each instance of LLM + ???? = "thing", the first papers that come out to fill the ???? with an answer do that in a rush to get on arxiv and so naturally the work is lackluster (since they have barely had time to think about an actual good solution for the ????).

I am really impressed by this work. If only Disney needed an empirical physicist...

I appreciate the conciseness of this article. Thank you for sharing. I agree. The kitchen sink data strategy appears to be fairly inefficient with current model architectures.

Twitter is just embarrassing now. I haven't used it in over a year now. Turns out it's absolutely unnecessary for a normal, well-informed lifestyle.

The word on the street among the researchers I know from my grad school days is that this is basically a bunch of datasets that were created earlier on for specific papers, and the subset of researchers are repackaging them as a kind of weird academia twitter winnertakeall thing.

The author list also reminds me of the embarrassing practices of the physics community…

Nothing wrong with releasing a webpage with a list of datasets, but the press and need for a whole big announcement that claims it will change robotics makes them seem desperate.

Why is it so painfully obvious that people with position piece blog posts do so to distance themselves or provide an alibi for the things they plan to directly contradict in the future?

Why is it that tech brand names (including people like Altman) have just become so cursed?

I feel like society at large is tired.

Everyone buys the thing but basically does it because it's required to continue to play the game - not because it brings them joy.

I'm sorry but this is just a depressing article...

Seems like it offers no upside.

You are completely right about this being a shallow treatment of a complicated subject.

There are many different functions the concept of the "growth mindset" serve. Unfortunately, we do not differentiate between them, which as you pointed out can make quite challenging to even discuss.

For example, the OpEd by Hattie you linked is also a fairly undeveloped exploration of what we are really getting at when we discuss the growth mindset. On one hand, for example, it is a way to help children cope with psychological struggle. On the other hand, it is a paradigm by which we live and fit into societal hierarchical structures.

I would argue that although having a fixed mindset might be a "tool" to use so that you don't "try too hard and hurt yourself" (which is more or less what Hattie argues), it is a terrible general paradigm to live by as it is fundamentally, a self-fulfilling prophecy. If you are born "dumb" and unable to read, that will always be the case. Obviously this is not how brains work. The reasonable conclusion here is that the growth-mindset is the closer model to reality and the fixed-mindset is a tool to help handle "moments in time".

I also really like the instructor for this course!

Seems like he really cares. I looked him up and I guess he was a student of Andrew Ng (the legendary ML lecturer!!) so it makes sense.

I have stayed in SF for almost a decade and have no plans to leave.

Many of my younger friends have moved to NYC (or elsewhere) and they have told me they don't like the overwhelming tech culture that permeate the bay drowning out the rest of the culture. I could see that happening to Seattle as well, but probably not NYC.

I can kind of understand it being like competing colonies of bacteria (each sub-culture). I think its pretty valid, but I don't mind all tech all the time ;D.

A fair response. I agree, I would rather see thoughtful technical insights than vanilla advertisements on reddit or whatever. That being said, the quality of these MLOps websites blog posts (excluding the one from OP) on average tend to leave a lot to be desired, seemingly trying to say _anything_ rather than _something_. Because of this, I tend to click the link, but back out when I see its true purpose is to be an ad.

This is a great and fairly accessible project. I'd like to give this a shot at my local hackerspace!

No disrespect. This article isn't terrible (and I did learn something practical), but isn't the underlying purpose of this post to advertise whatever service assemblyai.com provides?

Why is it necessary for MLOps product websites to have blogs? This content could also be posted on Medium or the author's personal project website and serve the same purpose (arguably helping the author's brand more effectively). The only downside would be that this startup would not get the indirect advertising.

It's almost as if governments are actually serving their constituencies...

Something that large corporations (or otherwise masquerading as NGOs) will most certainly never do unless it magically aligns with making them filthy rich in the process.

One more for the list is that a lot of people don't know what "Karpathy" means unless they are in the field and have been reading papers.

It might be good to include context like "the science communicator/researcher, Andrej Karpathy" so that it is clearer that it is referring to a useful person to look at posts from.

Possibly dumb question, but why does gemini have to be difficult to use? Why not just serve simple renders of Markdown+inline media?

Why not just use something like Obsidian for this purpose?

I love hacker news. I did really appreciate getting a serious answer.

Serious question - not trying to be cute or funny - is Xitter pronounced like "sitter", "ksitter", or "shitter"?

I have never let the existence of Elon swing my decision making too much one way or the other.

As others have pointed out, he has some qualities that making him a major asset and some that make him a liability.

Since you asked specifically about Elon, I think he is best at launching companies via the SV playbook, but not as well-suited for sustaining mid-to-latestage companies that aim to serve as industry cornerstones (with some exception allotted for SpaceX). The pattern I have seen is the underlying layers of the companies he spearheads early on typically erode due to rapid accumulation of both technical and cultural debt.

Whether the CFO leaving is a "canary" or not, I think there is ample evidence that Tesla's overall value proposition is grossly misaligned with its current valuation (futures priced-in). I would not blame people for using this as an excuse to weaken their positions on Tesla.

I am invested and have been for almost a decade, for the record.