I think it's the same tech they use to make the "3d" background photos on the iPhone wallpaper, which is probably also the same tech used for inferring depth when converting a normal photo to a spatial photo for viewing on an AVP.
A photosensitive patch of cells could be wired directly to motor cells/muscles on the opposite side, which would allow the organism to swim toward the light (maybe useful for feeding or migrating, etc.)
They didn't need to come about at the same time. Photosensitive proteins (opsins) and cellular motility both predate multicellular life entirely. Even single-celled euglena detect light and swim toward it with no nervous system at all.
In early multicellular animals, cells were already chemically signaling their neighbors. A photosensitive cell releasing a signaling molecule near a contractile cell isn't a coordinated miracle. It is just two pre-existing cell types sitting next to each other in tissue, which is what bodies are. Natural selection then refines that crude coupling because even a tiny, noisy light response is better than none.
Each piece, light-sensitive proteins, cell-to-cell signaling, contractile cells, evolved independently and for other reasons long before being co-opted into anything resembling vision. The question "how could A and B arise simultaneously?" dissolves once neither A nor B was new.
The "wiring to muscles" is derived from the ability of adjacent cells to communicate by chemical signals.
This communication ability has evolved before the multicellular animals, in the colonies of unicellular ancestors of animals (e.g. choanoflagellates).
The intercellular communication is a prerequisite for the development of multicellularity, like a common language is a prerequisite for a group of humans to be able to work as a team.
In an unicellular organism, a part of the cell senses light and another part, like flagella or contractile filaments reacts, moving the cell. In a multicellular organism, a division of labor appears, the cells from the dorsal side of the animal sense first light and other stimuli from the environment, so some of them specialize as sensory cells. Originally, the cells from the ventral side were more effective for locomotion, by using either cilia or propulsive contraction waves, so some of them specialized for locomotion, becoming motor cells, either muscles or ciliary bands (which in many simple animals are more important than muscles).
With this division of labor, the older intercellular communication methods have been improved, resulting in synapses between the sensory cells and the motor cells, which ensure that a chemical message that is sent reaches only the intended recipient, instead of being broadcast into the neighborhood.
For better reactions to external stimuli, the behavior of the sensory cells had to be coordinated, e.g. even when light is sensed only on one end of the animal, for the entire animal to move an appropriate command must be sent to all motor cells, not only to some of them, which has lead to synapses between the sensory cells themselves, not only between sensory cells and motor cells.
Eventually, there was a further division of labor, a part of the sensory cells has specialized to be middlemen, i.e. to relay the sensory information between the cells that have actually received it and the motor cells. These third kind of cells have become neurons. Initially the neurons were in the skin, together with the sensory cells from which they had derived, but later they migrated inside the body, where eventually they formed ganglia instead of a diffuse net, because this minimizes the reaction times, by shortening the connections between neurons, leading to a centralized nervous system.
I remember Watsi being posted years ago. I was a recent graduate then and didn’t really have the funds but I do now so I just donated to Philip’s cause! Thank you!
Buy an Arduino and some hobby servos and tinker with them.
But ideally you would have a goal in mind. what do you want your robot to do? (pass butter?) Once you have a goal then you will be able to focus on just what you need to learn to achieve that goal.
I think it comes from the RLHF. If you haven't interacted with LLMs enough to get turned off by it, I think that kind of speech is seen as powerful and confident.
RLHF = Right Left Hand Foot. It's a technique in Bavarian interpretative folk dance where you jump around, artfully hitting the soles of your feet with your hands in order to court women who are busy carrying unbelievable numbers of beer Steins into the mountains.
That's what came to mind when I saw the abbreviation. Then I looked it up:
It is a staple of marketing and journalism writing. And the guys doing the HF on it most probably came from this exact background: marketing and journalism.
I know it almost sounds crass, but you should consider letting an LLM take a crack at transpiling the code. Source to source translations are one of the most widely agreed upon strengths of LLMs.
I can tell you from reading the code in the 90s, no LLM will save you. It’s well written, but it’s not structured like modern programs. IIRC he invented his own trampoline system using goto that will leave you scratching your head for days, just trying to figure out how it works. An LLM might be able to guess, but it def isn’t going to one-shot it and that means you will need to be able to understand it as well.
I do think it is possible with the advent of Claude Agent to transpile the code. First I would refactor the trampoline system to be functional and unit test everything. Then I would use those tests to validate the transpilation. It's something that I would consider doing for a Wall Street Raider 2 to overhaul the engine and deliver massive improvements to the engine itself. I do want to do this to a certain extent to implement automated e2e testing. But I don't mind BASIC at all, prefer it actually, I just want automated testing set up. But a lot of this is beyond the scope of my goals for Early Access release.
Not OP, but I am pretty sure they are using Opencode with a certain antigravity plugin. Not going to link it, since it technically allows breaking TOS. If you‘re not using Opencode yet, I wholeheartedly recommend the switch.
Getting CC to work with other models is quite straightforward -- setting a few env vars, and a thin proxy that rewrites the requests/responses to be in the expected format.
@dang with the launch of open claw I have seen so much more LLM slop comments. I know meta comments like mine aren't usually encouraged, but I think we need to do something about this as a community. Is there anything we can do? (either ban or at least requiring full disclosure for bot comments would be nice).
EDIT: I suspect the current "solution" is to just downvote (which I do!), but I think people who don't chat with LLMs daily might not recognize their telltale signs so I often see them highly upvoted.
Maybe that means people want LLM comments here, but it severely changes the tone and vibe of this site and I would like to at least have the community make that choice consciously rather than just slowly slide into the slop era.
Parent comment has the rhythm of an AI comment. Caught myself not realizing it until you mentioned it. Seems like I am more in tune with LLM slop on twitter, which is usually much worse.
But on second sight it's clear and it also shows the comment as having no stance, and very generic.
@dang I would welcome a small secondary button that one can vote on to community-driven mark a comment as AI, just so we know.
I've been thinking about this, one solution I wonder if to put a really hard problem in the sigh up flow that humans couldn't solve, if it's solve in the signup, it's a bot, not sure how tf to actually basically captchas flip, however I suspect this would only work for so long.
Yes I usually just bite my tongue and downvote, but with the launch of open claw I think the amount of slop has increased dramatically and I think we need to deal with it sooner than later.
Thank you for pointing this out. I didn't catch that the parent comment was ai either and upvoted it. Changed it to a downvote seeing your comment and realizing it the comment did indeed have many AI flags.
How much experience do you have interacting with LLM generated prose? The comment I replied to sets off so many red flags that I would be willing to stake a lot on it being completely LLM generated.
It's not just the em dashes - its the cadence, tone and structure of the whole comment.
Yeah it's really frustrating how often I see kneejerk rebuttals assuming others are solely basing it on presence of em-dashes. That's usually a secondary data point. The obvious tells are more often structure/cadence as you say and by far most importantly: a clear pattern of repeated similar "AI smell" comments in their history that make it 100% obvious.
The theories don't answer all the questions we can ask, namely questions about how gravity behaves at the quantum scale. (These questions pop up when exploring extremely dense regions of space - the very early universe and black holes).
reply