self_made_human
Kai su, teknon?
I'm a transhumanist doctor. In a better world, I wouldn't need to add that as a qualifier to plain old "doctor". It would be taken as granted for someone in the profession of saving lives.
At any rate, I intend to live forever or die trying. See you at Heat Death!
Friends:
I tried stuffing my friends into this textbox and it really didn't work out.
User ID: 454
self_made_human
Kai su, teknon?
9hr ago
The issue is that there wouldn't be any need for an all out war, at least with India.
The Himalayan mountains mean a lot more to us than they do to the Chinese. They're literal high ground, covering the flat and very hard to defend Gangetic plain. In a shooting war, neither sides could actually make much territorial ingress, the logistics wouldn't work for moving the millions of troops necessary. Even aerial warfare and artillery duels wouldn't really change the picture, not when the largest mountain range in the world has had its say.
India recognizes Chinese control of Tibet, and our sheltering of the Dalai Lama is inconsequential. The Tibetan secessionist movement is just about dead. We never contested ownership of that godforsaken place, beyond a short lived backing of guerilla movements that ended in the 70s.
Arunachal Pradesh was never Chinese, at most it alternated between tenuous control between Indian kings and the Tibetans. Even when China seized control during a war with India, they voluntarily withdrew after a cease-fire.
If China didn't press these territorial claims, then it could easily exist as a neutral power that happened to have an overlapping border with India. We're not territorially expansionist, and we've had congenial ties with the rest of our neighbors, barring the obvious exception in Pakistan (and even then, they were the ones who instigated most conflict). It would be very easy to live and let live, and enjoy warm trade relationships. That is hard to do, at best, when one party considers over a million people to be their rightful citizens, for no good reason.
self_made_human
Kai su, teknon?
11hr ago
Other countries like Brazil and India have also been trying to industrial policy themselves into success for a few decades. They've also only managed to further impoverish their people.
At least in the case of India, we've emerged from crushing poverty largely due to late 80s and early 90s liberalization and movement away from mercantilist policies.
Recently, there's been an effort to reduce the attractiveness of cheap Chinese imports through tariffs and subsidies of domestic industry, and the jury is out on their effectiveness. We'd have congenial relationships with China if they weren't so myopically focused on Arunachal Pradesh and random mountains in the Himalayas. It makes me sigh when I realize how much of the international opprobrium China faces is entirely due to its own weight throwing, for very little potential gain in this particular case.
self_made_human
Kai su, teknon?
12hr ago
You've been deleting all your top-level posts.
The posts themselves were fine. Deleting them is not. The delete button has legitimate uses, we understand some people are privacy conscious, or wish to withdraw their claims. But if you're deleting a top-level post that has active discussion underneath it, and doing so consistently, you're undermining the community and acting in bad faith.
I hope you have a good explanation for why you've been doing so, because if you keep this up, you're eventually going to be banned.
self_made_human
Kai su, teknon?
14hr ago
I'm no economist, but my understanding is that tariffs harm both parties. If, likely due to ideological reasons, someone makes a mutually negative sum decision, then you're justified in punishing them.
So they're not just shooting themselves in the foot, the spread from the shotgun is hurting the other party too. They're making a mistake that hurts you too, and you'd very much prefer they didn't do that, even if you're agnostic on whether you want them better or worse off.
self_made_human
Kai su, teknon?
14hr ago
Now to get back to the cognitive dissonance stuff, there is one huge question. If you are in the latter camp where you oppose tariffs and trade regulations - why are these people not against retaliatory tariffs?
Isn't that basic game theory? A retaliation might hurt you, but it beats the alternative in the hypothetical pay-off matrix where you meekly accept unilateral tariffs. At the very least, it dissuades future trading partners from considering tariffs when you have a reputation for tit-for-tat.
self_made_human
Kai su, teknon?
2d ago
Very interesting aside! However, it doesn't address the question of diminishing returns.
Diminishing returns != No returns or negative returns.
The important question is whether the gains/$ invested are positive.
GPT 4.5 is extremely expensive, for the very limited increase in benchmark performance it represents.
And how expensive is it, that people are throwing a fit? Barely more expensive than the original GPT-4. That was absolutely worth paying the money for, when compared to GPT 3.5. GPT 4.5 has the disadvantage of peer competition.
That being said, the price of GPT-4 tokens and that of equivalent models dropped an OOM in price. DeepSeek R1/V3 and Gemini Flash 2.0 spank the OG GPT-4 with paddles and are practically free.
We've known that scaling laws are log-linear for a while now, at least since the Chinchilla days. Now that pure scaling of model size is getting super expensive, we've managed to discover a brand new opportunity to start scaling something else entirely, in the form of RL. Since we're starting off at the bottom of the curve, we've got several orders of magnitude of growth to spare there.
GPT 4.5 is not, however, a bust. The very capable and inexpensive reasoning models benefit immensely from having a strong and capable base model to RL further. You can then distill down, drastically cutting model size and inference costs, while keeping almost all the performance. It may or may not have been the progenitor of o3, which is very good.
I've used AI for coding, which you mention further down as a crowning triumph. It is... not particularly good. It struggles at anything past a very general form of the problem. It was very useful for copy-pasting similar pieces of code! Not very useful for building new features. It had a distinct habit of waiting until the interesting or important part of the problem and leaving a comment saying "Implement a function to do X!" Hmm, very interesting, if I tried that I'd get fired.
There are probably a thousand people on my Twitter feed, some of them rather famous, who disagree. Of course, I concede that there are people who think they're slop. And it also depends on which model you're trying to use for coding. There was a period where GPT-4 was updated and became ridiculously lazy. That was fixed pronto. Claude 3.7 Sonnet is apparently overeager, if left unchecked, it'll turn a request for a basic app into a full SAAS business.
If you have had issues with a model being lazy, you can always ask for it to output complete and working code! Prompting has become less and less important, but it's not dead yet.
Do you use AI to augment your work? Is it going to take your job? On what kind of a timescale? Do you think you'd be able to substitute yourself for an unmonitored AI without issue on any tasks? If not, what errors do you think it would make, and why? Honestly interested in your answers here, if nothing else. I would greatly respect you for putting your money where your mouth is on this one and bringing receipts.
I'm a doctor. Yes, I use LLMs on the regular. Yes, I expect them to put me out of business eventually, probably in 3-7 years for a 50% CI, 2-10 for a 70%.
A current LLM would do an excellent job at medical diagnostics and formulating treatment plans. It could probably handle patient interviews, for less complex cases where voice or text suffice. You could also use video if you had to.
The main reasons they couldn't replace me today are regulatory and implementation concerns. Governments mandate people with medical credentials in the loop, because that was a sensible thing to do for most of recent history. Hospitals aren't set up for LLMs.
I'm a psychiatry resident, which is uniquely safe and also uniquely at risk in some regards. It'll get the radiologists first, surgeons last. I'll be somewhere in the middle.
I am capable of verifying the information that SOTA LLMs provide in terms of medical advice. Almost all of it is good. Clinical medicine, outside of procedural specialties, hinges far more on factual knowledge, including that of guidelines, over having to figure things out on the fly in entirely novel situations.
Hallucinations aren't a solved problem, so if I had to replace myself with an LLM, I would probably set up a sort of democracy, with multiple models arguing to build consensus, a best of N scheme for multiple instances of a single model, with multiple rounds of grounding through search. I expect this to work very well, and if you do need to keep a human around for physical tasks or procedures, they don't have to be a highly paid doctor.
In other words, I'd be happy to go to Dr. LLM for my medical care, presuming very cheap measures are taken to stop it hallucinating.
Hmm... you think getting stuck in what appears to be a permanent loop is not terrible? Is this the behavior you'd accept from anyone working for you?
Given that we're testing Claude at a task it was neither designed nor trained to do, it's very much not terrible. For important tasks, it'll be trained to do them. An employer seeking to replace employees will, if they have any sense, test models for obvious flaws. For all practical use cases, LLMs don't really mode collapse these days, and in this particular case, it's more of an artifact of Claude's limited context window than an insurmountable difficulty.
The thing that keeps puzzling me about your comments is that you seem to simultaneously view ANY capacity in a task as an impressive accomplishment at the same time as you assert that AI has overwhelming general ability.
Like I said in this thread, it can take decades for AI models to progress from as bad as random chance to better than random chance. It takes far less time to go from there to human or superhuman performance. We are nowhere near the physical limits, and as I've said before, diminishing returns in absolute terms do not mean diminishing returns in value.
There's no clear reason that this has to be the limit of the answer space. Line go up... forever?
Forever? Not likely in a constrained universe. Unfortunately, the point on that line that equals human performance, or even superhuman performance, is not uniquely privileged.
All we have to do is get past that, and in many aspects, we're there. Terence Tao is on record saying that o1 is equivalent to a competent grad student in research mathematics. Once again, that's Tao, considered one of the world's best mathematicians, for his high standard of "competent".
There's also the rather bizarre fixation on LLMs - even though something like, say, an octopus is very obviously not an LLM and still has meaningful if primitive intelligence.
I'm not aware of companies spending hundreds of billions of dollars on scaling up Octopus Intelligence. LLMs are by far the most intelligent entities on this planet other than humans, and they're only getting better. I know which one I'd worry about, even if it is entirely possible that LLMs as we understand them today prove to be a dead end, and what really kicks things off is another discovery on pat with the original Transformer architecture.
self_made_human
Kai su, teknon?
2d ago
For example a properly safety tuned model will not output toxic content no matter how any of those two million tokens you use to insist that it should.
You can just look at Pliny jailbreaking SOTA models safety tuned to the max in a manner of hours or days? Do you think that definitionally, they aren't "properly" safety tuned because they're vulnerable to jailbreaks?
I don't see an empirical basis for that claim. I am agnostic on whether infinite (or just extremely large) context windows will suffice, especially when attached to a capable base model.
Even without it, a model that has fixed weights, a limited context window, but is otherwise highly intelligent, could approximate the benefits of online learning by coding and training a better version of itself. At that point you have recursive self improvement, though we're not entirely there yet (labs are increasingly using ever larger fractions of LLM written code for their internal work).
self_made_human
Kai su, teknon?
2d ago
You're correct in this assertion. A malevolent AGI or ASI does not need to be conscious or have qualia to pose a threat. It doesn't even have to think like humans, as long as it thinks.
If someone can look at a machine that is better at all of {math, coding, medicine, astronomy...} than the average human and then claim that they're not intelligent, what can you really say at that point.
Half the metrics for generality of intelligence would rule out humans as being general intelligences!
self_made_human
Kai su, teknon?
2d ago
Thus I'm going to give the chad "yes". Maybe one day I get killed by a robot, and maybe that robot is not conscious and has no self-awareness. That it killed me proves nothing.
I think you're burying the lede here, it matters how a machine kills you.
If you get run over by a Waymo robotaxi because of a sensor glitch, you're dead, but it's an entirely different story if some misaligned AGI seized control of all robotaxis and systematically started murdering humans. The former is machine error and/or stupidity. The latter is intelligence.
I don't really care about whether they have qualia or consciousness, and make no positive claims in that regard, my argument is that those factors, or even 'reasoning' in a human manner, matter not a jot when it comes to the prospect of creating entities far more intelligent than us and which could kill us using that intelligence. It could well lack a grasp of the ineffable redness of red, but it can still act in ways that increase rgb(255,0,0) as measured by its visual sensors when it shoots you.
Something like dumb grey-goo, or synthetic biological equivalents, are almost certainly going to be the products of intelligence.
self_made_human
Kai su, teknon?
2d ago
I haven't seen it yet. Care to share the link?
It took a lot of chasing, and it turns out it wasn't 4V, but rather 4o.
Here's a tweet from Greg Brockmann showing off the native image generation:
self_made_human
Kai su, teknon?
2d ago
I do not expect that Claude, under any circumstances, would express a desire to remove batteries or throw the GameBoy away in a fit of rage. It has the ability to represent said desire in text, if nothing else.
self_made_human
Kai su, teknon?
2d ago
Almost all of the improvement thus far is based on throwing more compute at the problem
Compute can be spent in many different ways. We're moving from a paradigm of scaling up the size of a model, in terms of parameter count, in favor of scaling run-time compute (time spent thinking) and reinforcement learning.
Scaling worked well, but was known to have diminishing returns, and limited by availability of high quality data to train on. It turns out that raw text dumps of the internet will only get you so far, and then curation matters.
RL, however, side-steps the issue entirely, models like OAI o1, o3 and DeepSeek's R1 were further trained on synthetic data. You take a normal LLM (or a base model), get it to attempt to solve a well defined problem where you can grade an answer. In the event they succeed at the task, you save that particular conversation/reasoning trace, and then use it to further train the model. This generates a data flywheel, which by all rights sounds like it shouldn't work (and many people didn't expect it to, thinking that the exhaustion of human generated data would stymie progress), but it turned out to work exceedingly well.
That's why models are doing particularly well at tasks like maths or coding, because you can rigorously vet the answers. This is harder to do with tasks like being a good writer, or poetry, because human evaluators often don't even agree with each other, let alone have a ground truth to refer to.
AGI is supposed to be GENERAL. This is the stuff that's supposed to be taking people's jobs in a few years
As dozens of benchmarks have shown us, doing better than chance on a metric is half the battle. The time taken to get there dwarfs the rapidity with which models then conquer and saturate the benchmark. If we have an LLM doing poorly on Pokémon (but far better than previous models, GPT-3.5 would have flunked it, GPT-2 would flop around like a magikarp), then it's not going to be much longer before it does it in its sleep.
There isn't much of a market for AI playing Pokémon. There is immense demand for them to be good at coding and maths. We've seen stunning progress in that regard, as you acknowledge. You attempt to back-chain your argument, saying that they're said to be good at maths but look, they're shit at Pokémon, which apparently invalidates the former. It really doesn't.
The argument is: this AI is struggling in a VERY non-human way with what we would consider a pretty trivial task. This reveals that its operational parameters are not like those of a human, and that we should figure out where else it is going to perform at sub-human levels. The fact that we're seeing this at the same time as it performs at SUPERhuman levels in other tasks shows that this is not AGI, or even in the direction of AGI, but rather is tool AI.
That's just Moravec's Paradox. Intelligence can be spiky.
Tell me, if you saw a human genius in the field of physics struggle with tying his laces or riding a bike, does that make his genius in his field invalid?
Claude is excellent in maths and coding, a good conversationalist and writer, if you described a human being with those properties, I'd be impressed, and it being bad at Pokémon doesnt invalidate the former.
If you're concerned about job losses, employers will be looking at coding skill before laying off programmers, not at their ability to play games.
We both agree that there was no reason to expect Claude to succeed with Pokemon at the level of an eight-year-old.
I had never given it any thought before the demonstration. But plenty of people have speculated that LLMs would never be any good at video games, and now that they're not good but not terrible, it's only a matter of time before they're great. And that time can be very short.
We've got the first AI agents out there. This was something impossible even a few years back, and they're only getting better.
self_made_human
Kai su, teknon?
2d ago
A chess AI that plays the game by making random moves has an elo of 478 and will occasionally beat a novice, which usually have an elo around 800. A dice is not AGI.
I believe that was a joke.
At any rate, even sticking to chess, I used an elo calculator and the dumb chess AI would win 13.55% of games. I still think it would be rather impressive if a dog make valid moves, even if at random.
When the first chess bots came out, public opinion was far from acknowledging the possibility that they even might become superhuman at Chess. Today, we're at the point where even grandmasters are utterly crushed by Stockfish.
Pokemon is such an easy game that it can conceivably be beaten with entirely random inputs, and provably beaten by very-close-to random inputs.
If you have a few million or billion years to wait around I suppose.
Twitch Plays Pokemon was essentially built on this premise.
As far as I'm aware, the spectators interacting with the stream were using strategies and had an idea of how to win at the game. There were plenty of trolls or awful players, but it wasn't random or too random.
self_made_human
Kai su, teknon?
2d ago
https://community.openai.com/t/advanced-voice-mode-limited/959015
"The GPT-4o model used in Advanced Voice Mode is multimodal and directly receives audio."
self_made_human
Kai su, teknon?
2d ago
My understanding is that LLaVa has long been supersede by things like cogVLM. I'm not clear on the finer implementation details.
For models like Gemini and the latest GPTs, we have very little public information about their architecture.
Most telling is the fact that none of the top commercially available chatbots have any native capability whatsoever to output images, and just blindly ram your prompt into a diffusion model api. They'll happily generate for you something totally unlike the prompt, and cheerfully insist that it's exactly what you asked for.
GPT-4V was demoed to have image generation capabilities that blew dedicated image models out of the water. OAI hasn't released it, despite strong clamoring, but Altman has said it's on the cards.
The issue you're describing is just poor implementation of image gen, at the very least GPT-4V does astonishingly better.
self_made_human
Kai su, teknon?
3d ago
Claude 3.7 Sonnet has a context window of 200k tokens. That is massive compared to the first commercial LLMs, which ranged from 4k to 16k.
It is, however, utterly dwarfed by other models like Gemini 2.0 Pro by Google. That one has a whopping 2 million token large context window, and I've personally made good use of it by throwing absurd amounts of text, including massive textbooks, into it.
There's plenty of ongoing research into both online learning, as well as drastically extending context lengths. We've gone from 4k to 2 million in about 2 years, without the original quadratic scaling of memory use still holding. I presume @DaseindustriesLtd would be better placed to answer how they pulled it off. Even accounting for performance degradation with very large context windows (needle in a haystack tests don't capture this), you can probably get around strictly needing online learning.
self_made_human
Kai su, teknon?
3d ago
Claude, at least past the 2.0 models, has been excellent. 3.0 Opus was good, 3.5 Sonnet was great, and 3.7 Sonnet only continues the hot streak. Given that GPT 4.5 is a resounding meh (look at those prices dawg, they're back to early GPT-4 days and don't beat even OAI's reasoning models in price or performance), I don't think Anthropic is doing poorly. They've released a reasoning model (3.7 can do it and standard output), and have plenty of good talent.
That being said, the way they treat paying users, both through subscription and the API, is terrible. I can only hope that they're simply strapped for GPUs, especially for inference, and are using the bulk of their compute on the 4.0 models they're cooking. Hopefully they take a page out of DeepSeek's book, those buggers aren't GPU poor, they're GPU beggars in comparison, but outside of when they're being DDOS-d, they practically throw tokens away for free.
self_made_human
Kai su, teknon?
3d ago
I believe the follow feature only posts notifications when the person you've followed makes a standalone post on the front page. Even top level comments in the main CWR thread are technically subposts.
As mentioned below, there are things from the rdrama code base that aren't fully implemented, such as themes. They probably work fine for a normal user, but using anything but the default breaks things in annoying ways if you're an admin like me.
self_made_human
Kai su, teknon?
3d ago
Oops. Thanks for telling me.
I mean, it's easy to win an argument when my opponent is invisible, but I'll let him through the filters. I don't need the handicap.
In other news: a streamer with deep pockets and a love of AI has decided to have Claude play Pokemon.
Well, if that's what you want to call an Anthropic researcher who decided to make their experiment public.
"Claude Plays Pokémon continues on as a researcher's personal project."
https://x.com/AnthropicAI/status/1894419042150027701
How should we interpret this? On the simplest level, Claude is struggling with spacial modeling and memory. It deeply struggles to interpret anything it's seeing as existing in 2D space, and has a very hard time remembering where it has been and what it has tried. The result is that navigation is much, much harder than we would anticipate. Goal-setting, reading and understanding dialogue, and navigating battles have proven trivial, but moving around the world is a major challenge.
This reminds me of a very good joke:
A woman walks in and says "holy crap, your dog can play chess?! That's amazing! What a brilliant dog! "
The man says "you think my dog is brilliant? Pffft. Hardly. He's pretty dumb, I've won 19 games out of the 20 we've played."
Jesus Christ, some people won't see the Singularity coming until they're being turned into a paperclip.
Nuh uh, this machine lacks human internal monologues and evidence of qualia, you insist, as it harvests the iron atoms from your blood.
At this point, the goalposts aren't just moving, they're approaching relativistic speed headed straight out of the galactic plane.
This AI can strategize in battle, understand complex instructions, and process information, BUT it struggles with spatial reasoning in a poorly-rendered 2D GameBoy game, therefore it's not intelligent.
It wasn't designed to play Pokémon. It still does a stunningly good job when you understand what an incredibly difficult task that is for a multimodal LLM.
Last, and most controversial: AI needs abstract "concepts." When humans reason, we often use words - but I think everyone's had the experience of reasoning without words. There are people without internal monologues, and there are the overwhelming numbers of nonverbal animals in the world. All of these think, albeit the animals think much less ably than do humans. Why, on first principles, would it make sense for an LLM to think when it is built on a human capability absent in other animals? Surely the foundation comes first? This is, to my knowledge, completely unexplored outside of philosophy (Plato's Forms, Kant's Concepts, to name a couple), and it's not obvious how we could even begin training an AI in this dimension. But I believe that this is necessary to create AGI.
This is the classic, tired, and frankly, lazy argument against LLMs. Yes, LLMs are trained on massive datasets of text and code, and they predict the most likely output based on that training. But to say they are merely "next likely text" generators is a gross oversimplification.
It's like saying humans are just “meat computers firing neurons". That is trivially true, but I'm afraid you're letting the "just" do all the heavy lifting.
The power of these models comes from the fact that they are learning statistical correlations in the data. These correlations represent underlying patterns, relationships, and even, dare I say, concepts. When an LLM correctly answers a complex question, it's not just regurgitating memorized text. It's synthesizing information, drawing inferences, and applying learned patterns to new situations.
LLMs have concepts. They operate in latent spaces where those are represented with floating point numbers. They can be cleanly mapped, often linearly, and interpreted in terms that make sense to humans, albeit with difficulty.
These representations can be analyzed, manipulated, and even visualized. I repeat, they make intuitive sense. You can even perform operations on these vectors like [King] - [Male] + [Female] = [Queen]. That isn't just word tricks, they’re evidence of abstracted relational understanding.
If you're convinced, for some reason, that tokens aren't the way to go, then boy are AI researchers way ahead of you. Regardless, even mere text tokens have allowed cognitive feats that would have made AI researchers prior to 2017 cream in their pants and weep.
There really isn't any pleasing some people.
Edits as I spot more glaring errors:
Second, AI needs more than one capacity. LLMs are very cool, but they only do one thing - manipulate language. This is a core behavior for humans, but there are many other things we do - we think spacially and temporally, we model the minds of other people, we have artistic and other sensibilities, we reason... and so on.
Even the term "LLM" for current models is a misnomer. They are natively multimodal. Advanced Voice for ChatGPT doesn't use Whisper to transcribe your speech to text, the model is fed raw audio as tokens and replies back in audio tokens. They are perfectly capable of handling video and images to boot, it's just an expensive process.
While the obvious argument around Tay was whether it was racist or dangerously based, a more serious concern is: should an intelligence allow itself to get swayed so easily by obviously biased input? The users trying to "corrupt" Tay were not representative and were not trying to be representative - they were screwing with a chatbot as a joke. Shouldn't an intelligence be able to recognize that kind of bad input and discard it? Goodness knows we all do that from time to time. But I'm not sure we have any model for how to do that with AI yet.
There appear to be several similar AI-related leprechauns: the infamous Microsoft Tay bot, which was supposedly educated by 4chan into being evil, appears to have been mostly a simple ‘echo’ function (common in chatbots or IRC bots) and the non-“repeat after me” Tay texts are generally short, generic, and cherrypicked out of tens or hundreds of thousands of responses, and it’s highly unclear if Tay ‘learned’ anything at all in the short time that it was operational
Besides, have you ever tried to get an LLM to do things that its designers have trained it, through RLHF or Constitutional AI, to not do? They're competent, if not perfect, at discarding "bad" inputs. Go ahead, without looking up an existing jailbreak, try and get ChatGPT to tell you how to make meth or sarin gas at home.
It is plausible, though obviously not possible to confirm, that ClaudeFan has updated the model some to attempt to handle these failures. It's unclear whether these updates are general bugfixes
I don't think that Anthropic, strapped for compute as it is, is going to take a fun little side gimmick and train their SOTA AI to play Pokémon. If it was just some random dude with deep pockets, as you assumed without bothering to check, then good luck getting a copy of Claude's code and then fine-tuning it. At best they could upgrade the surrounding scaffolding to make it easier on the model.
The AI will struggle to get past its training and see the question de novo, as a human would be able to.
There is a profound difference between "struggling" to do so, and being incapable of doing so.
self_made_human
Kai su, teknon?
3d ago
I'm 4 episodes into Pantheon, and I think it's really good. It's not a real spoiler to say that it's about a girl whose dad (a programmer) died of a terminal illness a few years back, but it turns out that his 'failed' mind upload did in fact work.
What I found particularly hilarious was the clear Ambani-analogue in the form of a particularly unscrupulous telecom billionaire from India who owns a massive personal skyscraper with a helipad next to slums in Mumbai. Yeah, there are so many people who fit that description. I'm surprised he didn't get it banned outright in India, given how many distribution channels the real Reliance owns.
That being said, it's obvious that this was a product of a pre-GPT age. We've made minimal progress in mind uploading any organism, even nematodes. We've got connectomes, but that's like having an LLM with parameters but no weights. It seems clear to me that it'll be entirely artificial AGI unlocking human mind uploads, and not the other way around. Still a good watch, and I've only heard good things about the second season.
self_made_human
Kai su, teknon?
3d ago
Yes, but I don't see how something like "we perceive our own continuity" can be proven wrong.
I don't think I'm disputing that, as far as I can tell.
There is a dystopian scenario in the writing where people like me are conditioned to brainwash themselves into ego death because being able to productively fork oneself and share resources between forks without regard to the fork's individual needs for them is the only way to stay competitive.
Cheer up! It's very unlikely that human uploads will be enslaved for cognitive labor, we're likely not cost-competitive with dedicated AI. Something like the Age of Ems or Pantheon requires technology to advance in ways that it very much does not appear to be advancing.* If you want to allow for enormous levels of pruning and optimizing to achieve parity, I strongly expect you won't have much recognizably human left by the time you're done. So you both can't really compete solely by Molochian self-abnegation, and you probably won't be expected to. Of course, I can't rule out that things go south in other ways and we all starve regardless.
*We can't properly emulate a nematode, but we have synthetic AI that can do graduate level mathematics.
self_made_human
Kai su, teknon?
3d ago
Human intuition is often wrong! Our intuition does not equip us in the least to naturally handle things like relativistic speeds or quantum phenomena. It evolved to handle the narrow ranges or scales that were relevant to macroscopic animals.
Even in that domain, our expectations fail us. Newton had to break from Aristotlian mechanical intuitions that were Plain Common Sense for hundreds of thousands of years.
I care about living because of my biological substrate's reward system, not because I intellectually (on what basis?) prefer an existence of a "pattern" of sun_the_second over its nonexistence.
I believe you, and why wouldn't I? At the end of the day, some values are entirely arbitrary and can't be otherwise (without solving infinite regress). This is as true for me as it is for you.
It is entirely fair for someone to believe that they value living for its own sake, and that their value systems exclude something like an upload. Now, sometimes there might be underlying beliefs or justifications that build on axiomatic bedrock, and those can be wrong when judged against their building blocks.
For example, someone might think it not even theoretically possible to upload a human mind and run its algorithms on a computer. I would, of course, think that they're mistaken on factual grounds, even if it is an enormously difficult feat to pull off.
Intuitive understandings of personal identity are often not robust in the least, but I'm confident mine are far more internally consistent than many people (especially since they've never even thought about it).
That being said, if someone recognizes that an upload might have the same thoughts and values as them, including a belief that uploads aren't moral persons or identical to the original (which might be overruled by self-interest, it's hard to make a man accept something if his literal existence hinges on not accepting it); and they still disagree with me on the moral equivalence of their own uploads, then I can't argue further.
We would agree on the facts, and disagree on their implications. I know that my mutual respect for any forks of myself drastically increase the odds that they will respect me back, and that we would be able to achieve peaceful co-existence and mutual aid. That is a fortunate fact about me, if someone would hate a copy of themselves, then their copy is going to hate them and they shouldn't make one.
self_made_human
Kai su, teknon?
3d ago
I don't consider myself to be exactly the same person after any period of time that can be measured on a clock. I think it's quite clear that I'm not particularly bothered by this.
If I can identify with and care about the wellbeing of the person "I" will be in decades, then I can identify with an upload.
Tetanus or botulism are the ones humans are at serious risk of getting. There's a vaccine for the former, and for the latter there isn't one I'm aware of,* mostly supportive care till the shitting stops alongside antitoxins. Unless you're an infant or an IV drug user, it's not the bacteria growing in your gut that's causing issues, it's the fact that you swallowed a significant number alongside their toxin.
The rest? Never heard of them, and I've heard of a lot of weird diseases that can be described as "we found 3 people over 10 years in a village in the middle of bumfuck nowhere". I would presume the average person, or even a farmer, isn't much at risk.
*I googled it, and there are a few out there, but none that are FDA approved.
More options
Context Copy link