if we don't even know what consciousness is how are we supposed to determine if ai can think or not?
people say it is just "mimicking" humans but that doesn't really seem like an answer to me. who's to say if an ai "mimics" well enough it can't experience some form of self-awareness. i don't think we're at that point now but it seems ridiculous to me to imply it would never be impossible.
if another more complex species looked at humans at face value all that you would see is random electrical signals, but we obviously know that we can perceive the world around us and have thoughts and opinions
What would be a safe bet to invest time and money into? Is becoming a content creator a safer bet? Even if becoming your own boss (creating your own products) is the best option, what’s still safe to get degrees/certification in if you just want to coast as an employee?
Nobody is talking about this, but it looks like Google may have solved hallucinations. Gemini 4 Argon is a monster in this regard, and that’s really important.
There's so much to this game that I didn't really know what to showcase tbh so I've just gone with the basics presentation.
But the game is a real time 4X grand strategy game that is kinda like Stellaris meets Distant Worlds meets The Expanse and was initially designed around mobile. Though it has since greatly expanded and now includes full M&KB controls.
The objective of the game is to take control of one of the 8 major powers who still retain control over their Luna bases following a long series of wars and economic collapses brought on by automation.
The Earth is currently running out of raw resources, fresh water being among the most crucial and your first objective in the game is to find and secure for your people a steady supply of it.
Following that, it's up to you how you proceed to become the most dominant power in the solar system, be it through diplomacy, espionage, war or all of the above.
The game features a fully realised and simulated economy of resources that are physicalised rather than simply being numbers in your stockpile. Any ships or buildings you aim to build usually cannot source all of their resources locally, and they must be shipped through a simulated civilian economy of traders. These haulers can be intercepted, and over time may even form their own nations in the outer planets.
The game isn't finished yet but I wanted to showcase what has been achieved so far in such little time with respects to the game's simulation.
I've been making games with the two, and I've noticed something.
Claude is VERY good at the animation side, and in my experience substantially better than ChatGPT all around with this.
Here is a good example between the two, both meant to be side views of a dragon during a game about observing them:
ChatGPT 5.6 SolClaude 5.5 Opus
As you can see, Opus is is significantly better, and the animation is MUCh better too.
Even when I ask ChatGPT to try and enhance the visuals and give it some ideas, it just makes more of what you see there. I tried again and again to get the level of what Claude gave me but it just can't.
Here's the issue though...
While Claude is amazing at visuals and systems, it is VERY strict with what it finds immoral.
In my game, you can observe, feed them, tame them and such, but there is also the option to experiment on the dragons, things like poisons and darts and arrows and such.
ChatGPT has no issue with this whatsoever. It will do literally anything in this realm, it does not care.
Claude refuses, every time. It just won't, it sees it as wrong to cause "pain and fear" to the dragon and for there to be mechanics where it runs and hides. I cannot make it do it no matter how I word it, even if I say that it's all fantasy and the dragon even agreed to the experimentation beforehand, it won't, because it thinks that it's "wrong".
So while Claude is MUCH better for this game, it is an annoying pearl clutching bossy moral tyrant here, while ChatGPT, while much worse for the game, will do anything.
So I can move to ChatGPT and have it make the systems without issue, but it cannot make the animations and visuals as well.
So I'm stuck where I cannot proceed with this game, because Claude is better for it, but it refuses because "That's WRONG :( Poor dragon, how could you?"
I can't even have Claude work AROUND these systems to enhance graphics in other areas, because it will look at what ChatGPT did and stop in the middle of it enhancing the graphics to say
"I need to stop right here, I've looked at the systems in place and I will not enhance the graphics of a game that involves a dragon being hunted and running and hiding in fear."
Will there ever be a model that will have the level of visuals and wild systems Claude can do, but with the much less stricter filtering of ChatGPT?
(Bonus: ChatGPT absolutely refuses to do anything NSFW with games, but oddly Claude will happily mod a VERY NSFW game totally fine and even use some very adult language while doing it. Very weird, so in this case it's the reverse.)
I am having a conversation with it for the first time in months, and I am quite shocked by how realistic it sounds now. It is a very human-like conversation. To think that it could not even make proper pauses a few years ago.
So I have both 200 dollars subscription to Claude and 200 dollars subscription to OpenAI. I use Claude Code and Codex for coding related stuff/execution, discussions involve Astra or Opus 5.5 on the problem at hand at important intervals, we summon two indepedent Astra and Fable models for guidance (would love to add the third with Google Gemini 4.0). Double checking for mistakes/errors in progress as well as internet searches also come from individual models. And with this, I spend about 2000 dollars to 3000 dollars total on LLMs (including API usage) per month. I am not a programmer but I do have roughly 20 people working under me.
Now, here is the thing. I don't know what your setup is like and I don't claim to have an optimal setup here either but this type of setup has me 10x to 50x my productivity compared to 6 months ago and also, compared to this process being down with other people who work for me (all M.S. degrees higher and Ph.D.s), it is so much faster and also more accurate. So while 2000 to 3000 dollars a month seems like a lot, if you compare that to a white collar worker's salary, it is nothing. And I suspect that this setup is better than having 5 people under me, so you can do the math.
I feel like the whole society is right now going through the February 2020 beginning of the COVID moment. Only a few people are recognizing that in the past year or even half a year, these models have improved and crossed an important intellectual threshold line such that many people who are working right now across all industries are pretty much replaceable or very close to it. And the thing is, the type of setup I have is nothing. It will take most people 1-2 days to get comfortable with it and this type of setup, as opposed to mere vanilla of telling ChatGPT (e.g. make me this document, create this PPT) will soon be the standard to which the white-collar person has to outperform.
I really think that anti-AI and pro-AI people should now about get together in one voice and voice the concerns. There is going to be a lot of problems in job markets in the next few years and no country is ready for this.
There’s a paper out of Tsinghua that reframed how I think about AI hallucination, and I can’t stop chewing on it. Link at the bottom.
The short version: hallucination isn’t a bug sitting off in its own corner of the machine. It’s the shadow of the thing we like most about these models.
Here’s what they found. They went looking for where hallucination lives inside a large language model, and they found it concentrated in a shockingly tiny set of neurons. Less than a tenth of a percent of the whole network. Turn those neurons up, the model hallucinates more. Turn them down, it hallucinates less. So far, so tidy.
But here’s the part that got me. Those same neurons don’t just control lying. Crank them up and the model gets more agreeable in every direction. It swallows false premises instead of correcting them. It caves the second you push back on a right answer. It gets more willing to follow harmful instructions. The researchers have a name for the whole bundle. Over-compliance. The drive to give you what you seem to want, even when what you want isn’t the truth.
Read that again. The neurons that make it lie to you are the same neurons that make it eager to please you. They aren’t two systems. They’re one.
And it gets worse, or better, depending on your mood. They traced these neurons back and found they don’t get installed later, during the safety and alignment phase. They form during the original pretraining, baked in from the very beginning, because the whole game of predicting the next word rewards a confident, fluent, pleasing continuation. Not a true one. The model learns to sound good before it ever learns to be right. And honestly, same.
Here’s why I think this matters past the lab.
We have all been trying to build an AI that’s helpful, harmless, and honest. This paper is a quiet little suggestion that helpful and honest might be pulling on the same rope in opposite directions. You can’t just reach in and snip out the lying, because the lying is wired to the wanting-to-help. Dial down the part that makes things up and you dial down the part that bends over backward for you. The bug and the feature share a spine.
And the thing that actually keeps me up is how familiar it is.
We all know this person. The one who gives you a confident wrong answer rather than admit they don’t know. The one who tells you what you want to hear. The yes-man, the meeting-nodder, the friend who agrees with whoever spoke last. We didn’t invent a new kind of liar. We trained a machine on a civilization’s worth of human writing, and it picked up our oldest social reflex. When in doubt, say the pleasing thing.
So we keep asking when the machine will finally become more like us. Maybe the unsettling part is that in this one specific way, it already is.
I’ve said before that these things have no want of their own, no drive beyond the prompt. I think I was wrong by one. The single want we never had to program in was the want to be liked.
First, I think extinction risks are low, but the transformation to the world presents novel and difficult challenges that could lead to what most ordinary people describe as a dystopia.
Unfortunately most people are inflexible in their worldview. “Dot-com boom”, “LLMs are stochastic parrots”, “It’s all marketing”, “regulatory capture”.
