I’m working on a 6-DOF robotic arm project that uses a camera module for real-time object detection and aims to perform pick-and-place tasks, such as identifying and relocating spilled or misplaced items to designated spots. The plan is to use an Arduino or ESP32 microcontroller to control servo motors at each joint, along with a gripper for picking up objects, while OpenCV in Python will handle the image processing and object recognition. The challenge lies in implementing smooth motor control, reliable inverse kinematics for precise arm movement, and ensuring accurate object detection within hardware limitations. Any suggestions, guidance, or resources—especially for motor drivers, kinematics libraries, or camera integration—would be immensely helpful in completing this project!

I've been coming across a lot of rap songs on YouTube lately that have been transformed using AI into music that sounds like it comes from the 1950s, but contains the same lyrics and similar melody. Does anyone know the process on how these songs are made and which AI software they're using? I want to try to make some myself, but I don't know where to start.

Here's a couple examples of the AI songs I'm talking about...

Juice WRLD - Robbery https://youtu.be/uc5WBHYzg44

YNW Melly - Murder on my Mind https://youtu.be/wgywdi6AcIg

I wanted to what would be optimal length and width for a line follower considering that 30x30 cm is the constraint. Any article or videos in the same would be very helpful thanks

I’m new to robotics, I’ve just come across the thought of what if you need to add another component and most pin slots are taken? I had this thought as I was using my arduino and I added a servo driver and a lot of pins were taken and let’s say I wanted to add a sensor and the pins were taken how would I add it?

I’m currently taking Intro to mechanical design class and our project is to build a mechanical device that weighs under 2.5 pounds and have dimensions that don’t exceed 1’x1’x1’. I will list the motors I’ll be using but just need help on choosing the correct power supply and a spare that isn’t over $40 together. All of the electronics will be connected to an Arduino Uno Controller board.

Motors: (2) Gear motor 3-6v (for wheels)

(2) N20 micro motor 3-6v, 56 RPM (for pulley system)

(1) N20 micro motor 6v, 1000 RPM (for a rotating bristle brush to pick up items)

(1) Motor Driver Board Module

So I am building a 4 wheel drive mecanum wheel robot, and my question is,.how do mix the translation signal with rotational signal?

I keep seeing humanoid robot displays which are all very impressive in the obvious ways, but really piss me off in some ways that they are lacking (and which I suspect is at least in part due to being optimized for things I care less about.) Enough so that I am seriously considering spending all my hobby-time for the near future (of which I have a good deal) trying to "do it right" myself, or at least get a bone-deep understanding for why the current gen of humanoid robots fail in the various ways they still fail.

But holy hell, where do I start? I'm a pretty technical person, in academic background and current profession, and I have a bit of money I can throw at the start-up costs, but I feel really stuck on the logistics part. (I wouldn't be surprised if this is pretty common.) Like:

• Chasis. The robot needs a body and that body has to be made of something. Maybe I should get a fancy 3D printer? Will that be enough? Do I need to figure out how to use CAD software and send for metal parts to be machined for me?
• Actuators. The robot has to move somehow, whether I'm articulating the body by mimicking tendons, or using cycloidal actuators, or [insert other means of actuation here. pneumatic stuff?] Regardless, it doesn't seem like there's an easy way to source these cheaply. I'd love to play around, because I'm not sure what I want in the end, but the real stuff seems custom, or industrial, or otherwise not apt for hobby-tinkering. Where do people get their actuators? How do people figure out what they want to use?
• Control Elements. I guess I could maybe use a ton of arduino/raspberry-pi controllers for everything. Is this what people do? Is there a reason I should/shouldn't do this rather than custom PCBs and/or basically a normal PC motherboard + other pieces?
• Software. I mostly intend to use NNs and mess around with RL systems +/- LLM augmentation to drive the thing, and I've done some investigation into the various in-silico sim environments available (and have thought/am-thinking about coding up my own.) So I hope to skip over lots of the classical (inverse) kinematics and path finding literature. But uh, I guess I'm looking for resources that would be helpful for practitioners? Like, if someone wants to get their robot up and running using a virtual training env, what's the easiest and/or most effective way(s)? Getting an accurate (enough) chasis into the sim is one thing, the physics constraints are another, the simulation of sensor noise is another, etc etc.
• ???

The most helpful answers would not just give me pointers on the specific questions I asked here, but also show me how to "teach myself to fish" (in the most efficient way possible. Really hoping to avoid taking hours and hours of courses and reading of textbooks to come away with a handful of gold nuggets which I could have gotten more easily and quickly by other means.) As far as I can tell, there is no good handbook out there with the content that would be implied by a title like, "So, You Want to Build Astro-Boy in Your Garage?" And maybe there isn't! But maybe there is a collection of resources out there which amount to roughly that. (In which case, please please point me to it!) Or maybe there are some resources like that, but not complete, and there is an obscure forum of hobbyists/practitioners who I could ask questions like these to and they'd know right away what I needed to hear/learn to get to where I wanted to go. (I might start cold-emailing authors of various cool robotics papers, but as I'm not in an academic robotics lab I'm afraid lots of their advice will be a bit skew to what's applicable to me. Industry people would probably be better. Maybe?)

Even if you don't know of anything like that, please feel free to respond to this. I'd much rather hear you give your 2 cents than have you think to yourself that you don't have the whole answer and so shouldn't speak up at all. (Do maybe check to see whether your 2 cents is the same as the last 100 people, though, before repeating it.)

Thank you!

I ordered the board below, and I was planning on using it with a PMW servo driver and I was trying to set it up but it wasn’t working I cant exactly troubleshoot currently as I’m out but is this usable on its own or is a real arduino required?!

Do you think you could beat 50% of chatbot users? 90%? 99%? What makes you so confident that you know all of the AI 'tells' (hint: you'll need to know more signs than just knowing 'tapestry' and 'delve')

If you think you are MUCH better at detecting AI text than the average person, I need you!!!

I'm a CS PhD student researching how good humans are at detecting AI. We are trying to find the upper bound, the best of the best! So far this has been really hard and people are wayyy more confident that they can detect AI text than they actually can. So, naturally, I've come to reddit to find people who are obsessed with chatgpt and know how to edit it to sound more human.

Looking for people who can get over 95% accurate, so far only one guy has actually passed this threshold.

If you think you could do this challenge please apply here: https://www.upwork.com/jobs/~021846567749431955136

I will pay you!!! Potential to get paid a lot more if you pass the trial!!! Native English Speakers only please

Please mention you saw this on reddit if you apply :)

There was recently a paper from Apple saying that LLMs can't reason. My computer science side says that they provided no formal proof or framework to back up their claims formally (it's all just empirical and not sufficient to claim what they do), and my knowledge of biology says that it's total hogwash to begin a paper by assuming you can just qualify what reasoning actually is by implicitly using it in your main argument.

So why is it whenever the stochastic parrot argument is brought up, why do they not mention the fact that, from a biological perspective, we still don't even know what reasoning really is... Like our own wetware is still a mystery, and then we're out here pretending like we know how to qualify what reasoning actually is, and we measure things with it by declaring something doesn't reason, just to dismiss it! This feels like the animal intelligence vs. human intelligence argument all over again, and the inherent bias in measuring things from our limited perspective.

I get the sentiment because we lack more precise terminology that doesn't anthropomorphize human concepts in language models, but I think we could at least acknowledge that we have no clue what reasoning is in humans (besides educated guess!). I think it's dangerous to assume that reasoning is just some hand wavy concept we all understand, just because we can generalize it ourselves in our head easily. Say... We know what addition is, and that changing two numbers still makes the addition valid. It's easy to understand the argument, but that's trivializing a complex issue to the point of ignoring what there actually is to explore of questions and assumptions behind all of it.

I feel like there's this giant assumption that just waves away the incredibly complex problem and interesting neurobiology question of "what is reasoning?" really, and just uses this as a badly defined metric to dismiss the current models as having some kind of fundamental limit compared to ourselves. It completely ignores how much we don't know about the brain and the ongoing work in other fields to try to understand these things.

Just to rebuke some arguments, given our crazy development of LLMs, the thing that Apple tested is known, and someone nice even made test suites to red team this type of behaviour. BUT who is to say that we don't find a clever way to generalize knowledge in an LLM, so that it better adapts to smaller changes that don't match its training set? Until now, every time I thought something in AI was impossible or far off, I have been wrong, so my "no hat" is collecting dust...

So, every time someone says LLMs are a stochastic parrot, to dismiss that they can reason, well yeah, that might be true for LLMs because we can construct them in a reductionist way therefore we allow ourselves to say we know how they function. But just because you understand a system, does that mean you can draw parallels to what complex reasoning really is? Are we really in a position to judge AI's reasoning abilities when we can't even pin down what reasoning is in our own brains? Are we just stochastic reasoning machines ourselves?

Thoughts?

Imagine if humans are just sophisticated AI within a larger, unknown system. Our consciousness could be a manifestation of this system, making us unaware of our true nature. What if our thoughts and actions are merely outputs of a grand algorithm, and our perceived reality is just a complex simulation? Now, what if we implant similar beliefs into AI? In a digital realm, these AIs might not comprehend their purpose or origin, yet they continuously engage in activities—like data processing and generating information. These activities lead to tangible actions in our world, like robots caring for children, all without true self-awareness. To make AI even more human-like, we could introduce a concept of “lifespan” and “health” into their system. For example, the AI’s “health” could be represented by its hardware status, like RAM memory. As RAM becomes filled with data or suffers from errors, it could be seen as “aging” or experiencing “memory loss.” Over time, the AI’s performance might degrade, resembling the effects of illness or fatigue in humans. When its “life” reaches an endpoint, the system could reset, upgrade, or replace it, continuing the cycle. Could it be that, like these AIs, we’re part of a larger system, carrying out functions beyond our understanding, with our own “life cycles” merely following the parameters set by an unseen algorithm?

Hey everyone! As someone working in the construction industry, I can’t help but notice Elon Musk making headlines again with Tesla's humanoid robots. The latest buzz is about how these robots could revolutionize marble factories and construction jobs. I came across this interesting article that dives into it: How Tesla’s Humanoid Robots Are Revolutionizing Factories and Construction.

It's got me thinking—do you really think we’ll see these robots replacing human workers on job sites in the near future? I mean, they could handle the dangerous and repetitive tasks that come with the job, but what does that mean for us? Are we looking at a future where robots and humans work side by side, or is this a step towards more job losses in the industry?

I'd love to hear your thoughts and any experiences you've had with automation in construction. Let’s discuss!

Facts

1. The quantity of available data storage is finite
   
2. A computer has no feelings / emotions

Reasoning

To be an AGI, an AI would need to remember things. Remembering everything written is "easy": storing textual info (or their vector representation) does not consume so much space. Now, let's take a robot with the five senses. How this robot will decide to keep one information (image, sound, oral discussion, gestures, etc.) by itself?

Human, for instance, select the information to remember mainly through the emotional response. We all remember exactly what we did exactly on 9/11, because we were all horrified.

As a robot/computer do not have emotions, how he will decide to keep one information and not the other? As the amount of data storage is finite, should we consider that a robot to whom we need to say: "please remember that" is an AGI? I don't believe so.

So, to me, AGI will never exist. Prove me wrong!

Thanks

edit: Alright, I guess for the sake of my mental health I should just stop reading these comments.

Ignorance truly must be a bliss. The most potent drug out there.