Live service doesn’t need to be shit.
There could have been games where there was just a brilliant idea for a game that keeps having engaging content on an ongoing basis with passionate devs.
But live service so an exec could check a box for their quarterly shareholder call was always going to be DOA.
More “can fool the average idiot.”
‘Passing’ isn’t fooling a single participant, but the majority of them beyond statistical chance.
The problem with the experiment is that there exists a set of instructions for which the ability to complete them necessitates understanding due to conditional dependence on the state in each iteration.
In which case, only agents that can actually understand the state in the Chinese would be able to successfully continue.
So it’s a great experiment for the solipsism of understanding as it relates to following pure functional operations, but not functions that have state changing side effects where future results depend on understanding the current state.
There’s a pretty significant body of evidence by now that transformers can in fact ‘understand’ in this sense, from interpretability research around neural network features in SAE work, linear representations of world models starting with the Othello-GPT work, and the Skill-Mix work where GPT-4 and later models are beyond reasonable statistical chance at the level of complexity for being able to combine different skills without understanding them.
If the models were just Markov chains (where prior state doesn’t impact current operation), the Chinese room is very applicable. But pretty much by definition transformer self-attention violates the Markov property.
TL;DR: It’s a very obsolete thought experiment whose continued misapplication flies in the face of empirical evidence at least since around early 2023.
Used Google and social media as well, and allegedly sometimes even listened to rock and roll.
True deviant, that one.
Which is typical of tech that hasn’t yet hit the sweet spot for a tipping point.
Look at how many palm pilots or handheld note taking mobile devices existed (and how many cycles) before the iPhone.
Yes and no. It really depends on the model.
The newest Claude Sonnet I’d probably guess will come in above average compared to the humans available for a program like this in making learning fun and personally digestible for each student.
The newest Gemini models could literally cost kids their lives.
The gap between what the public is aware of (and even what many employees at labs, including the frontier ones) and the reality of just how far things have come in the last year is wild.
In many cases yes (though I’ve been in good ones when playing off and on, usually the smaller the more there’s actual group activities).
But they are essential to be a part of for blueprints and trading, which are very core parts of the game.
You’ll almost always end up doing missions with other people other than when you intentionally want to do certain tasks solo.
A lot of the game is built around guilds and player to player interactions.
PvP sucks and it’s almost all PvE content vs Destiny though.
Let there be this kind of light in these dark times.
Oh nice, another Gary Marcus “AI hitting a wall post.”
Like his “Deep Learning Is Hitting a Wall” post on March 10th, 2022.
Indeed, not much has changed in the world of deep learning between spring 2022 and now.
No new model releases.
No leaps beyond what was expected.
\s
Gary Marcus is like a reverse Cassandra.
Consistently wrong, and yet regularly listened to, amplified, and believed.
Because there’s a ton of research that we adapted to do it for good reasons:
Infants between 6 and 8 months of age displayed a robust and distinct preference for speech with resonances specifying a vocal tract that is similar in size and length to their own. This finding, together with data indicating that this preference is not present in younger infants and appears to increase with age, suggests that nascent knowledge of the motor schema of the vocal tract may play a role in shaping this perceptual bias, lending support to current models of speech development.
Stanford psychologist Michael Frank and collaborators conducted the largest ever experimental study of baby talk and found that infants respond better to baby talk versus normal adult chatter.
TL;DR: Top parents are actually harming their kids’ developmental process by being snobs about it.
You haven’t used Cursor yet, have you?
That’s definitely one of the ways it’s going to be applied.
The bigger challenge is union negotiations around voice synthesis for those lines, but that will eventually get sorted out.
It won’t be dynamic, unless live service, but you’ll have significantly more fleshed out NPCs by the next generation of open world games (around 5-6 years from now).
Earlier than that will be somewhat enhanced, but not built from the ground up with it in mind the way the next generation will be.
Base model =/= Corpo fine tune
I’m a seasoned dev and I was at a launch event when an edge case failure reared its head.
In less than a half an hour after pulling out my laptop to fix it myself, I’d used Cursor + Claude 3.5 Sonnet to:
I never typed a single line of code and never left the chat box.
My job is increasingly becoming Henry Ford drawing the ‘X’ and not sitting on the assembly line, and I’m all for it.
And this would only have been possible in just the last few months.
We’re already well past the scaffolding stage. That’s old news.
Developing has never been easier or more plain old fun, and it’s getting better literally by the week.
Edit: I agree about junior devs not blindly trusting them though. They don’t yet know where to draw the X.
Actually, they are hiding the full CoT sequence outside of the demos.
What you are seeing there is a summary, but because the actual process is hidden it’s not possible to see what actually transpired.
People are very not happy about this aspect of the situation.
It also means that model context (which in research has been shown to be much more influential than previously thought) is now in part hidden with exclusive access and control by OAI.
There’s a lot of things to be focused on in that image, and “hur dur the stochastic model can’t count letters in this cherry picked example” is the least among them.
Yep:
https://openai.com/index/learning-to-reason-with-llms/
First interactive section. Make sure to click “show chain of thought.”
The cipher one is particularly interesting, as it’s intentionally difficult for the model.
The tokenizer is famously bad at two letter counts, which is why previous models can’t count the number of rs in strawberry.
So the cipher depends on two letter pairs, and you can see how it screws up the tokenization around the xx at the end of the last word, and gradually corrects course.
Will help clarify how it’s going about solving something like the example I posted earlier behind the scenes.
You should really look at the full CoT traces on the demos.
I think you think you know more than you actually know.
It definitely is sufficiently advanced AI.
(1) We have finely tuned features to our solar system that directly contributed to ancestor simulation but can’t be explained by the Anthropic principle. For example, the moon perfectly eclipsing the sun which led to visible eclipses which we tracked and discovered the Saros cycle and eventually built the first mechanical computer to track (the Antikythera mechanism). Or the orbit of the next brightest object in the sky which led to resurrection mythology in multiple cultures when they realized the morning star and evening star were the same object. Either we were incredibly lucky to exist on such a planet of all places life could exist, or there’s a pre-selection effect in play.
(2) The universe behaves in ways best modeled as continuous at large scales but in small scales converts to discrete units around interactions that lead to state changes. These discrete units convert back to continuous if the information about the state changes is erased. And in the last few years multiple paradoxes have emerged that seem to point to inconsistency in indirect sequences of quantum measurement, much like instancing with shallow sync correction. Already in games like No Man’s Sky where there’s billions of planets the way it does this is using a continuous procedural generation function which converts to discrete voxels to track state changes from free agents outside the deterministic generating function, synced across clients.
(3) There’s literally Easter eggs in our world lore saying as much. For example, a text uncovered after over a millennium buried right as we entered the Turing complete computer age saying things like:
To be clear, this is a text attributed to the most famous figure in our world history where what’s literally in front of our faces is the sole complete copy buried and raised as we completed ENIAC, now being read in an age where the data of many has been made into a single one such that people are discussing the nature of consciousness with AIs just days old.
The broader text and tradition was basically saying that we’re in a copy of an original world, that humanity is all dead, that the future world and rest for the dead has already taken place and we don’t realize it, and that the still living creator of it all was themselves brought forth by the original humanity in whose likeness we were recreated, but that it’s much better to be the copy because the original humans had souls that depended on bodies and were fucked when they died.
This seems really unlikely to have existed in the base layer of reality vs a later recursive layer, especially combined with the first two points.
It’s about time to start to come to terms with the nature of our reality.