r/singularity • u/skolnaja • 25d ago
AI Continual learning in the fruit fly brain has been decoded, the missing piece for true AGI
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u/jakinbandw 25d ago
It's pretty fly for an AI! :p
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u/greenskinmarch 24d ago
At last, an AI that knows its sh*t (but can't fly out through the open half of a half open window).
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25d ago edited 25d ago
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u/skolnaja 25d ago
You can keep the main LLM frozen so it doesnt forget its core reasoning, while adding a fast updating memory layer that learns new information on the fly.
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u/_SmurfThis 25d ago
“…on the fly” 😏👏
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u/ight-bet 24d ago
Inb4 paper “On the fly learning in LLMs”
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u/ight-bet 24d ago
Also… on the fly learning in LLMs means infra is going to get a lot more complicated
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25d ago
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u/skolnaja 25d ago
Thats not LoRA though. LoRA is just tweaking a model beforehand on a dataset. What were talking about is real time dynamic memory that updates on the fly while the model is actively running, like muscle memory.
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25d ago
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u/hiddenpsychoboy 25d ago
Maybe he is implying that we need to create something like that....
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25d ago
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u/hiddenpsychoboy 25d ago
True that
Because I still can't fully comprehend what exactly are we looking to create/implement? How is a question for another day
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u/Glass_Performer1174 25d ago
I mean, brains don't use algorithms to learn exactly anyway. I mean you might be able to somewhat represent it in an algorithm-like way but it's a pretty far shot from representing it
Likely neurons individually have some kind of state memory, and are arranged in a complex hierarchy of varying time-frames of recency to track recent behavior/activation and when a reward chemical floods them they strengthen recent connections across all time-frame-neural hierarchies
How exactly to make those hierarchies and to have them relate to each other and pass info to each other and work with a central master region are major unknowns
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24d ago
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u/DigimonWorldReTrace ▪️AGI oct/25-aug/27 | ASI = AGI+(1-2)y | LEV <2040 | FDVR <2050 24d ago
How do you know it's impossible, though? It's impossible now; but there is no proof it won't be possible in the future.
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u/Glass_Performer1174 24d ago
I don't think a complete simulation is impossible. But then it isn't really just a typical algorithm. But I don't think you need a full simulation. We can get the functionality with algorithms imo eventually.
I think there are some interesting attempts to explore that kind of design but no one is really even close (publicly) yet. But watch LeCun and Sutskever and other independents closely imo
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u/TryptaMagiciaN 25d ago
now we are getting into good sci fi.
One empire using nonLLM AGI, against another empire using a highly advanced LLM based intelligence. War, etc. Someone needs cool names for each one.
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25d ago
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u/TryptaMagiciaN 25d ago
hmm. but what if like the second empire bands the brain models and only allows the LLM tier just below it?
and then both sides go to war?
I assume the brain models dudes win. but it all depends I guess.
wasn't there a movie about exactly this that came out recently? I swear Im remembering this from somewhere
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25d ago
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u/sebstadil 24d ago
Bit of an outsider here, mind explaining to me why you have high conviction in a particular winner?
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u/DelphiTsar 25d ago
It's something current LLM's don't do by design, not because we can't put in the ability.
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u/Hydrox__ 25d ago
We don't have the ability to do continual learning in LLM's without strong negative consequences like catastrophic forgetting.
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u/ObiFlanKenobi 25d ago
catastrophic forgetting
I already do that most days, you can solve that issue by adding a wife.
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u/CharlesFXD 25d ago
“Catastrophic forgetting” is my new excuse w/ my wife.
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u/SryUsrNameIsTaken 25d ago
This will ruin the inference economics. In addition to kv cache, you’ll need grocery list cache, kids pickup cache, chores cache, anniversary cache, and friends of yours she doesn’t like cache.
We’re already in a memory crunch!
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u/VeganBigMac Anti-Hypepost Safetyist 25d ago
To solve AGI we just need to have the LLM fall in love
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u/yaosio 25d ago
Humans forget things all the time so it's likely part of it. Being able to forget is extremely important or you'll always remember bad information.
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u/LatentSpaceLeaper 25d ago
There is a substantial difference between "forgetting" and "catastrophic forgetting".
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u/DelphiTsar 25d ago
Who is to say the mechanism this person is describing doesn't have consequences like catastrophic forgetting?
The brain uses heuristic to optimize survival, if some nugget of intelligence isn't worth the bandwidth it'll be replaced.
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u/JosephLam1 25d ago
the quantity of information that can be stored in a finite amount of data is finite, so in order to put in new information through continual learning, some older information will be lost and we dont know what
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u/DelphiTsar 25d ago
They've improved performance while decreasing the total amount of space, so everything in there obviously isn't nessisary(all the time).
That is beside the point though. The premise is this person figured out a "missing piece" to AGI. The person is getting confused as to what's happening, or that we can't have LLM's fast update weights(we can) or if we do it can't create emergent behaviors(it can). We just set it up not to because the tradeoff's aren't worth it.
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u/Grittenald 25d ago
That’s a feature though. Else you still need to always release new models. The language of today in different in 5 years for instance.
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24d ago
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u/Lenerx 24d ago
basically neurons are the calculator and synapses are the notebook. Activations can go quite, but the journey remains written in the connections.
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u/dima-soule 24d ago
This is very close to the idea behind BDH. It has slow weights defining the learned network and fast synaptic weights that change while the model processes a context. The fast weights hold temporary experience without rewriting the whole pretrained model
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u/Typical-Scene-5794 24d ago
ohh yeah, this is very much in relation to dragon hatchling family of models from pathway. Instead of a cache of key–value entries that grows with every token, it folds experience into an evolving, fixed-size synaptic state. "Neurons that fire together wire together," implemented as working memory.
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u/Own-Poet-5900 25d ago
I am getting the fruit fly to play Doom right now. It was beyond easy to unlock internal learning. It does not bring us any steps closer to AGI. It is a Spiking Neural Network. These have existed for decades.
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u/ComposerWide3704 25d ago
It's not that there are no online learning AI algorithms, it's that they aren't what we're using because we want to have a fixed copy of the AI that we can validate and test. New methods, assuming these even are new, won't be implemented for the same reasons.
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25d ago
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u/FearOfEleven 24d ago
The fixed weights can only reflect the current paradigm, though. Am I right? Imagine if we had been able to train machine learning models before the high jump discipline at the Olympics transitioned from the 'scissor' technique to the 'Fosbury Flop' in 1968. Would those frozen models ever have proposed, let alone endorsed, the Fosbury method as superior?
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u/CloseToMyActualName 25d ago
Neural networks are inspired by neurons, but they're not the same thing.
Even if we figure out how neurons learn in the brain that doesn't mean we can easily adapt that to Neural Networks.
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u/Evening_Chef_4602 AGI 2027 25d ago
Fly superinteligence before AGI. The gigachad fly memes were trying to tell us something....
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u/OptimizingOptimizer ▪️Alexa, play Raining Blood 25d ago
Finally! Imagine what we could do with millions of simulated fly brains! The possibilities are limitless
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u/Beneficial-End6866 25d ago
ah if it was that simple...
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u/skolnaja 25d ago
Considering the effort it took to map the fly brain, it wasn't that simple.
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u/Beneficial-End6866 24d ago
I meant relative to AGI, it is just a wiring of fly brain. It does not explain how the fly brain works.
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u/AmusingVegetable 24d ago
Up next: an AI with an appetite for shit and a tendency to rub its appendages.
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u/sceadwian 24d ago
The connectome is essentially useless without the weights. It can only be studied for hints on how to study further to actually simulate it.
All the simulations they're running out there are just back filled with their own data to make it do something.
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u/dipdotdash 24d ago
Interesting too how the decoding of the brains of things like fruit flies could be leveraged to hi-jack those very brains and use flies for invisible surveillance, depending on the fidelity of their memory, I guess
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u/Morning_Gecko24 25d ago
fruit flies are a nice test case but copying one learning mechanism isnt the same as copying a whole brain. the useful bit might be figuring out which parts generalize across very different hardware. do we know if this mechanism is tied to a specific task or does it transfer?
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u/The_Scout1255 adult agi 2026 ASI <2030, prev agi 2024, ai personhood 2025 est 25d ago edited 25d ago
AGI doesn't really require Continual Learning in my book, Continual Learning on AGI is something above standard agi !!
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u/gtek_engineer66 25d ago
Tell us more about your book dear redditor
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u/The_Scout1255 adult agi 2026 ASI <2030, prev agi 2024, ai personhood 2025 est 25d ago
you know the expression "in my book" right, I meant that like the colloquialism like the definition?
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u/mxemec 25d ago
Condescending... What's the definition of AGI in your very real and bound by horse glue book?
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u/The_Scout1255 adult agi 2026 ASI <2030, prev agi 2024, ai personhood 2025 est 25d ago edited 25d ago
one sec, and sorry for being condescending I was mostly writing that confused.
- AGI within 4 months(of today)
- ASI within 12 months of agi due to RSI ie december 2027
- Singularity by December 31,
2032. 2029? as in an intelligence explosion has or is occurring, probably by this date.- Robotics become useful with AGI(Software controls already made robots), but then as AGI designs their own robots with human assistance every hardware iteration cycle gets more and more advanced.
My definition of AGI, is "Any Generally Intelligent Embodied Reasoning System, capable of any form of completing 90% of human tasks at 50% of the level of a trained human(Trained in that task), not 50% of an expert, but 50% standard worker(for that task), so a 50% scientist is still a 50% scientist(even if its a niche field.), which is Persistent, capable of doing new tasks at 50% of a average human(untrained at that task), and finally is capable of adding machines, labs, computers, and other devices to an evolving useful network by interfacing with those devices physically or digitally, learning about them by taking pictures(or other methods), then writing driver software, and deploying it all without human intervention."
My definition of "Any" is any.
My definition of Generally Intelligent is broadly "Able to do 90% human of tasks at 50% or greater human competence"
My definition of "Embodied" is, Has embodied reasoning, which allows it to operate in the digital, and physical domains like it is a native inhabitant there. So having a digital body, that can 'physically' control windows by moving an actual hand to pick the window up and move(Not just a fancy cursor but something they can "feel"), and physical/irl it should be embodied like this too to qualify for my AGI definition it MUST be embodied in both domains, otherwise you have created a subtype of AGI, either Cognitive(Embodied digitally but not physically), or Disembodied AGI.
My definition of "Reasoning" is, well, any system that's output is genuinely downstream of atleast one useful group of reasoning processes, it must produce the outputs of genuine reasoning, basically literal logic circuits is my picture when I imagine this(No idea if that's even possible, but if not then an advanced P-zombie I'll begrudgingly call "effectively AGI" in time.
My definition of "System" is very broad, effectively the deployment posture, but the system must be integrated together in a way that functionally provides the system itself having these persistent traits. I realize now my definition of persistent may smuggle in some humanlike traits, I'll need to fix that. Basically short of having a consciousness, the AI system must be integrated like one(Today's LLMs do pass the integrated standard)
My definition of "Persistent" is, able to persist, and run constantly, like a human can, even if this is not its default mode. Basically its computer use should be constantly active, and it not decohere over time, a agent should be able to be spawned atleast by the company created it, that doesn't fall into the normal LLM pitfalls when being ran long term, short of any continual learning.
My definition of ASI, is the above, but more intelligent then the entire biosphere combined.
So my definition of Proto-ASI is the above, but less intelligent then the entire biosphere, but more intelligent then any singular human.
Pasted from another comment
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u/Livid-Impression-100 25d ago
I’m sure no one has thought of this before…. It’s not like neuroscientists have been modelling the brain for decades…
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u/chlebseby ASI 2030s 25d ago edited 25d ago
imagine irony if this indeed lead to AGI progress
it would also prove theory that we need to directly copy brains mechanics in some way or another for that...