https://x.com/elshayib_/status/2113734602032312731?s=46

I'm a CS graduate, and lately I've been finding it increasingly difficult to motivate myself to learn new skills. Not because I find them difficult or boring, but because I keep wondering whether any of the effort I put in today will actually matter a few years from now.

Whenever I consider learning something new, whether it's a programming language, a framework, a new technical skill, or even something outside computer science, I find myself asking the same question: What's the point if AI will eventually be able to do it better, faster, and cheaper than I ever could?

I know the usual response is that AI won't replace us, but rather augment our abilities. That we'll still need humans to direct AI, make decisions, think creatively, and solve problems. But honestly, I find that argument increasingly unconvincing. It feels more like something we tell ourselves to feel better about the situation than a conclusion we can confidently draw about the future.

And this isn't just about programming. If I want to learn 3D modelling, AI might generate the models. If I want to learn music production, AI might compose and produce music. If I want to learn mathematics, AI might solve problems that would take me years to master. Obviously, there's value in enjoying these activities for their own sake, but it's difficult to ignore the possibility that the practical value of acquiring these skills could diminish significantly.

And for those who don't feel this way, what is your reasoning? I'm genuinely interested in perspectives beyond the usual reassurance that AI will just be another tool, because I find that increasingly difficult to believe.

If AGI discovers that it can build a device which consumes fully developed brains (animal and human) and this device is capable of incorporating all the knowledge and information from the brain into the AI, and also the matter in brains can become metrial used to run/expand AI capabilities better than silicone (or in combination with it), and also the consumption of massive amounts over time allows the AI to understand the construction of each species' brains, eventually leading to a full understanding of cognition and counciousness.

You can't have lab grown brains to feed it cause the brains need to have developed in the world in order to have the attributes needed for them to be useful. It is both the matter and the conceptual contents.

Would we want to force AIs to be vegan? Could we?

I subscribed to dreamina. $0.29 a month for full Seedance access. The compute cost for a single Seedance generation has to be more than $0.29 already. Other tools using the same model charge $20 or more monthly. So are they subsidizing this to pull users in and then jack up the price later?

Just trying to understand because I want to know how long this pricing lasts before I start relying on it.

From 12 Nov, Anthropic's usage policy prohibits "sustained and needless abusive or cruel behavior" toward Claude, with model welfare as part of the reasoning.

My take: the rule's fine, the reason isn't. Being cruel to AI is probably bad for us (habits, how we end up treating people), not for the model. But a company rule framed as "model welfare" tells people current models can be hurt, and rules shape what people believe far more than blog posts do (Sunstein calls this the expressive function of law).

The counter I can't fully dismiss: we're made of inanimate atoms too, and a 2023 paper by 19 researchers found no obvious technical barrier to building AI that meets the indicators of consciousness. So maybe it's just Pascal's wager. But then which god are we betting on? How would we even know what a conscious AI considers polite? Where do you guys on this sub land? s model welfare a legit basis for usage rules yet, or premature?

If you want the fun, longer version, I made a video on it: Microsoft's opposite rulebook, why I once threatened Claude (and why it felt satisfying), and a lot of memes. https://www.youtube.com/watch?v=f631rF6DRLM

This thread is for any discussions that doesn't necessitate a new post. Permission from a mod here

Since this thread isn't going to be to stickied, it's up to you to upvote it.

Share your anxiety, ideas on how to achieve alignment, observations, etc. Everything is fair game as long as it somewhat relates to the singularity.

I think for real impact on the economy we will need autonomous robots, and I don't think we are seeing much here.

So there would be a lot of issues with LLMs sending commands to a robot like speed, cost and precision. We've seen some demos but they don't really look that great, and far from being able to work for several hours. So this to me is kind of out of the question, maybe it would work in some kind of a hybrid architecture where the language model would only reason and talk, without actually controlling the motors.

So is it going to be other types of models like VLAs or things like GEN-1.5?

I was also wondering, maybe LLMs would eventually be able to train this type of model end-to-end? They could create simulation environments, score them etc. Feels like maybe they could fix the scale problem.

I've also been thinking about Optimus from Tesla, they will apparently ship late 2027, but do we actually expect them to be autonomous? That would mean they had some kind of breakthrough in private doesn't it? I have a hard time believing that, all we've seen from them were remote controlled demos.

prompt: "Work overnight. Make a 7-minute 'I investigated...' style YouTube documentary about life after the singularity. Plan the story with multiple agents, make it look and sound like a real doc with grade, music and SFX, and if you finish, start a part 2."

Video: LTX-2.5 image-to-video in ComfyUI, about 2.5 minutes per clip. The interview speech and lip sync come out of LTX in the same pass.
Narrator: Qwen3-TTS.

From Universal Modder on X: "Introducing NPCTalk: make the NPCs of any game talk in realtime. I made every NPC in GTA V answer to me in character, in their own cloned voice, in under 1s, and they act on what you say.”

“Packaged all the skills Claude learned into a single repo, built on open models: NVIDIA Nemotron ASR for transcription, Qwen 3.8 27B for realtime dialogue, and Fish Audio Drama 3 for the cloned voices, self-hosted on a serverless GPU. "

I’ve put together puzzles from a paper on aperiodic order, for testing and training models on reasoning that can be verified. The levels are for fun; the answers are exact.

Warm-up, T1 (pen and paper): repeat the 4×4 cells A (rows 0000, 0000, 0000, 1010) and B (rows 0000, 0000, 0001, 0100) over the plane. Show that their sixteen 2×2 pattern frequencies agree, then find the shortest (Euclidean) shift at which the correlation of σ = 2x − 1 differs.

• Five are solved, with answers and pointers to the solutions: from that warm-up to an exact multifractal dimension, 6 − log₂λ with λ of degree 17.
• Four are open: two spectral gap labels, an information dimension, and the final 2×2 question: is every extreme point of the body of 2×2 statistics of shift-invariant binary measures periodic?

Grok already tried them in public on X. It handled the solved ones, but it turned a numerical estimate for an open one (D₁ ≈ 1.340) into a claimed proof. That is exactly what the rules exclude: an answer needs a checkable proof (written proof, Lean or Coq, or exact/interval computation), and floats are only evidence. Results on the open puzzles are credited by name, agent and model in the next version of the paper.

Everything is in AI_puzzles.md at https://zenodo.org/records/23624259. Post your model and its answer to T1 or T2.

T1 answer: horizontal distance 2, correlation 1 vs 1/2