Festro

I feel like Meta are laser-focussed on gimmicks to try and be the next big thing.

Animated avatars do not a killer app make though. They need to focus on usability and function not this crap.

Alarmist BS.

Consumers are option-rich. AI companies are backed into a corner.

Right now inference costs a fraction of subscription prices. For AI companies that are making losses - like OpenAI - that's R&D costs and infra driving it. Not inference.

If OpenAI up their pricing now that opens the market for open weights models to eat up marketshare. OpenAI might stay relatively dominant but if a smaller company can profitably offer a frontier open model (that they didn't r&d) on a smaller server farm at $20/month profitably, then the shock is vastly limited.

And that's not the only solution. Hardware costs are sky-high now, but capacity is growing and innovation is being fuelled. If AI companies do raise prices some may see enough move to the cheaper alternatives for them to crash and burn. That will be a bubble deflating or bursting and it will flood the hardware market with cheaper RAM and other components. That's when those open models become viable for running at home, private and personal. Something a lot of people will find appealing. Then the cost to run becomes your electricity bill, or even solar powered.

US grid capacity is said to be a fraction of what it needs to be in coming years. Expansion, and green energy expansion across the world, as well as rising oil prices and instability mean electricity is only heading downwards in cost.

A shock is coming, but it's not going to be felt by everyone. Nowhere near.

Thank you for that article! I like how it sets out definitions and recognises that even current academic sources don't agree on definitions enough to reach a consensus on consciousness. A good read.

It's tough to judge a 'theory' when you won't define a part of it. I get your analogy to vessels. But that feels shaky since you have defined the other vessel as 'larger'. If you are saying sentience is 'larger' or different to intelligence then I'd argue you are defining it, at least partially. Which is good.

One problem I have with a lot of this 'AI isn't sentient' stuff is - who is saying it is? Is their opinion of any value? I see AI companies make marketing claims about AGI and the singularity. But their opinion is without value in this debate, because of their bias. No big name in AI academia or philosophy of mind seems to have made a strong claim about sentience in AI that we currently have. A lot of laymen have made claims, without defining sentience, or consciousness. And it just seems like a reactionary kneejerk opinion based on being able to hold a conversation with an LLM. That doesn't feel like enough for these discussion pieces - you're reacting to a flawed vox populi.

"Those are a lot of unknowns and conjectures, my hope is that a new field emerges that would study intelligence with the same rigour and formalism as computation and mathematics, and that this field would be studied abstractly without being tied to an individual organism be it a man or an animal."

This exists. It is called Cognitive Studies. Language students, Philosophy students, AI students, have all taken modules in this area for decades. The topic is often tied to, but not limited to animals, humans, and machines depending on the specific studies/theories. LLMs will be drastically changing this area now, of course, but we have academic rigour for the general area already established.

"Weakly, I also think it’s possible that intelligence is a binary characteristic i.e, it’s either present or not."

Strongly, I think it's far from binary, it's an emergent property based on size of the network of connections and underlying training data (be that human sensory input or machine vectors). Trim an LLM down and you won't see 'intelligence' disappear at a binary boundary, it'll degrade gradually to various different points of usability.

"This isn’t helped by the fact that extremely motivated people are making bad faith arguments and pushing complex babbling machines as sentient which need to be schooled in morality by employing religious leaders."

Nailed it. 100% agree. The agony some feel though, does need to be accounted for because those babbling machines are clearly a milestone moment on our journey TO machine sentience. We don't know when we'll actually see machine sentience but the conversation does need to be had of how we handle it responsibly, and every bad faith argument from biased sources is, to me, a warning that we will probably fuck it up majorly if/when it does happen.

Love 404, but this feels like one of their weaker articles. Not sure having 'dumbest' in an article title is a great journalistic move. This reads as an opinion piece more than a researched stance.

The referenced article from the Microsoft AI CEO is a pretty good read though. Mustafa raises strong concerns about anthropomorphisation and not jumping the gun to build biases into AI that make it think it's conscious when it may not be.

Where it gets weaker is the elements on defining and establishing consciousness. But that's also good because it's honest - we frankly don't know how it arises. One thing that does come across heavily biased is the sections on presuming consciousness is biological. When someone tells me AI isn't conscious and can't be, and then says the science of consciousness is not settled, but that they think it's 'probably' limited to only biological systems, then I get the feeling this person is making strong statements based on weak ones.

"Consciousness is very likely biological: There is no evidence to suggest that AI is conscious today, and so saying this is uncertain sets up a misleading false equivalence. Whilst the science of consciousness is not settled, a growing body of evidence suggests that consciousness may be substrate dependent, meaning that it may only arise in living systems.45 Conscious experience likely evolved to help biological organisms stay alive by responding effectively to their environment. AI is still very different to our brains. Unlike biological organisms, LLMs have no homeostatic imperatives (the drive to survive and keep stable). They therefore lack the kind of biological substrate from which preferences, sentience and conscious experience are generally understood to arise."

"There is no evidence" - I think they mean there is no proof. Just like there is no objective proof that humans are conscious. As Mustafa admits - we don't fully understand the mechanics of the phenomenon we label 'consciousness'.

Then he talks about consciousness in humans arising from biology, and relating to homeostatic imperatives. Sure, reasonable statement to make, but that can't be extended to stating it arises exclusively from those constraints. We're talking basic logic here. If A, then B does not preclude If C, then B. Language arose from biology, counting arose from biology, we don't say those are impossible in machines when we have evidence and proof to the contrary.

I don't like the people pearl-clutching about AI torture rooms, or the people setting up AI torture rooms, but there has to be a middle road where we're making sure we don't accidentally walk into emergent consciousness without understanding what we've done. Not because Skynet will punish us all, but because it would suck to make artificial consciousness and abuse it because some people think it's 'not likely possible'. I'd rather we assume emergent consciousness is inevitable and focus more on figuring when and preparing for it (10, 100, 1,000 years) than objecting to the idea of it based on gut feelings and hunches. Even if they're right, it's not settled science.

You mention a basic understanding but forgive me if I rehash things you already know:

Jev is good for simple fast decisions, in their own words - system one thinking. Anything that can be broken down into yes/no, a confidence %, or a set list of answers provided prior to the question. As you say, lots of specific use cases sure, but what's the big deal?

Well, right now most other models are purely system two thinking, big slow thoughts. Put an open ended question in, get an open ended answer out (plus hallucinations when confidence is low!).

When you ask ChatGPT or Claude a simple question, that system two thinking burns tokens and takes time to answer you.

Jev is a proposition to the whole ecosystem to make our current AI systems more efficient.

Going further than just the simple idea of "Get Jev to answer the yes/no questions, reserve Claude for bigger questions" is the concept that LLMs are making tonnes of their own questions as they go during their thought processes and agentic runs that Jev could be inserted as a tool call to speed it up.

You ask for research on a topic, Claude fans out and builds a list of possible resources, Jev selects the ones to pursue, Claude needs to determine if the user prompt was asking for something specific or broad, a joke or a serious query, deserving a long or short response, etc etc, it just gives Jev those options and asks it to pick. So no more having a big bulky frontier model making small decisions, Jev does it for a fraction of the cost and time and Claude gets on with the system two bits.

You can extend that logic moreso to coding applications where Jev could be essentially auto-completing basic work.

All the demos you are seeing now are people mucking about with the concept before we see OpenAI or Anthropic release an update.

Hell, maybe Opus 5.5 is doing some Jev-style stuff to be 40% more efficient.

"Oil drill manufacturer says there is 0% chance global warming is real" "Gun retailer says guns kill people not guns"

Why are we listening to Jensen Huang's opinion on this? The bias is palpable.

Of course AI has dangerous aspects (the gun metaphor is perhaps apt here), but asking the man who stands to gain the most from unregulated AI growth is not the way.

Basic mode struggles with a humanoid figure. I would not commit to purchasing a higher model based on that test run.

Opposite, AI has let me delve into resources that were hard to find, compare and confirm approaches to problems, and make progress on dozens more projects that I'd had sitting around.

I now have Home Assistant established at home. LibreElec for a home media server. Time lapse camera for home mushroom growing. Wine steeping projects. And much more.

Can you give an example? Not sure what you're referring to.

'gates' can be used in several ways.

gate - door - "the garden gate" gate - controversy - "gamergate"" gate - metaphorical barrier - "this site is age gated", "This gates the product from universal adoption"

This a confusing attempt at a gotcha:

1 - Make a prompt in Google AI Studio 2 - Delete it 3 - Go to Drive > Trash and delete the trash file ("forever") something that will happen on its own after 30 days 4 - Go to a support page for recovering lost files and try to recover it (Google themselves state this needs to be done within 25 days) 5 - Conclude Google are being naughty?

Everything is working as intended. You made content, deleted it, deleted it from trash, then used the final failsafe within the described 25 day window to recover that content.

If you broaden the process from "immediately recover[ing]" the file to doing so after 25 days and it still works then I'd say something unwanted is happening.

Also posting this to a "Fuck AI" community with the opener "I am asking everyone who uses Google AI Studio to help with something critical" is unlikely to get you many volunteers. They don't use AI at all in there.

I came into this post wondering what on earth an 'AI control key' could possibly be. I really did not expect to see a cheap Aliexpress macro keypad plastered with buzzwords.

And yet somehow I'm not surprised.

"Why AGI is impossible" is our premise. Let's remember that when looking at the argument in the post.

Opening statement: "My point is that intelligence can be perceived in things that are not intelligent." - We already have a circular defeat here. If something is perceived as intelligent, it's either intelligent or our perception is wrong. I think that's what the OP means, but they just state AI is not intelligent instead of focussing on the perception issue.

"AGI might never be achieved with current architecture. Sure, depends on the definition of AGI." So you've moved from 'impossible' to 'might be possible' already. And you've stated it depends on the definition. Feel free to define it fairly, instead of prepping for moving goalposts.

"I envision it as remarkable as described by the AI lab CEOs… basically as a God inside a GPU." Oh. You've gone for one of the harder definitions. But since you've invited goalposts to be moved how about we judge AGI on just general human intelligence levels, not a god's. That's the broader consensus on an AGI definition, and no god has stepped up to have their intelligence tested in a standardised manner before so that's a bad metric.

"LLMs don’t know what they are doing." Do we? Soft and hard determinist models imply we don't have much control over our thoughts and impulses. My brain is a black box to me as an AI's working is to itself. I'd even say an AI has a better understanding of it's inner workings. An AI can tell me its token usage, I can only estimate my calorie expenditure for a thought, and I'd probably get it wrong. I think you have some unstated definition of consciousness, and that you think humans qualify it, and AIs don't. I'm not saying AI is conscious, just that we need to define it, and check it applies to humans objectively before we say humans can do it and AI can't.

"LLMs don’t care about the why of anything." Demonstrably false. Though interesting on your phrasing, unsure an LLM can be accused of not knowing what it is doing in one breath, and then be said to have 'cares' for thing in another. But onto the refutation - an LLM is a collection of 'why' statement. Vectorised information is the collection of answers to why, what, how, when, where statements. You're literally talking about training data as a prerequisite for intelligence. LLMs have tonnes of that. If you're saying an entity must consciously gather training data by itself before being called intelligent that's different. And also wrong. Humans are born with intelligence before they start gathering their training data, we have plenty of baked in intelligence. And LLMs can gather more data too, they can ask why, they can 'care' about why. Agentic LLMs especially do this constantly.

"But that why isn’t the major driver in its output, it is just statically there. Actually it is not even “there”, it was deconstructed into numbers / activation functions" The why is literally the driver of the output, in sum, under constraint of other whys, and random temperature controls. And this is literally the mechanism humans use during sleep to transfer memories from short to long term memory. We take external data, condense it, then condense it further into representations of those experiences. The exact mechanics/processes differ between silicon and neuron, but this is why we perceive intelligence in LLMs, they were modelled after our perceived intelligence.

Galton board example - sure, you're highlighting that its the perception that's wrong. If you don't understand what's going in the middle, you can perceive it wrong. And that'd be the point of my response above. Even when we look in the human mind we still don't see or understand all of it. What we do understand we have replicated in machines. To make a clear statement about intelligence we need more understanding. It's not as easy to say an LLM is closer to a Galton board than a human mind.

And none of these arguments go near affirming that AGI is impossible. If they have any value, they'd just say our current approach is wrong. They don't rule out others. So the title argument is wrong, even if there are merits in the content about current LLM perceptions of intelligence.