No, but the tropes there reveal (most of) the plot and mechanics of storytelling. If I remember correctly, the forum in Road to Gehenna was created by utilizing a vulnerability in the AI-accessible terminal system.
If tvtropes or any other material related to The Talos Principle was used to train models, we don't need much else to have agents-with-forum discussing and reverse engineering "puzzles" and human culture.
"His memory was so powerful that he could still recall decades-old events and experiences in the smallest details. After he discovered his own abilities, he performed as a mnemonist; but this created confusion in his mind. He went as far as writing things down on paper and burning it, so that he could see the words in cinders, in a desperate attempt to forget them. Some later mnemonists have speculated that this was a mentalist's technique for writing things down to later commit to long-term memory. Reportedly, in his late years, he realized that he could forget facts with just a conscious desire to remove them from his memory, although Luria did not test this directly."
I believe that one need to have superhuman memorization abilities to have definite confusion due to too much remembered. More trivial explanation of this effect in normal ageing persons is age-related brain shrinkage.
> Obviously the brain is not a computer,
Our brain consists of approximately 86 billions quantum computers [2] controlling tens-of-thousands chemical neural networks with at least 10 coefficients, communicating [4] using lasers [5] (coherent light is laser light).
Well, sure, it's a computer of sorts, although in the abstract sense of being able to perform computations so is our liver, so perhaps not a very useful concept.
What I meant (as I assume you realize) was "not a von Neumann architecture computer", but I'd also fairly confidently assert that it's not a quantum computer either.
Our ANN model of a neuron is obviously too simple (especially being a synchronous model, not a real-time asynchronous one), but it's hard to imagine that all of the classical chemistry, let alone quantum, details are important. It's necessarily built out of chemistry, but selection is happening at the level of behavior - presumably depending only on a much higher level set of abstract capabilities (ability to learn, etc), not the exact details of chemistry.
The success of LLMs, a crude prediction mechanism built atop a crude ANN, does tend to support the idea that low level details don't matter. Timing will matter if we want to go beyond LLMs to AI that can learn time-based things and not just sequence order, but how much else will matter remains to be seen!
Mostly analog, with some threshold-triggered functions and lots of weighted adders and maybe multipliers.
> but how much else will matter remains to be seen!
Indeed, and the similarities between the brains we were born with and the brains we build is tantalizing. I'm really curious about the next chapters of this all.
I suspect the anxiety of being unable to forget things has an inherent selection bias. You will only stress over the things you can't forget, the things you have forgotten you won't stress over...
Generally claims of eidetic memories are overstated, doubly for older claims, but Nigel Richards memorized a French dictionary in 9 weeks, over 6k words a day, x2 including the alphagram.
I consider myself to have a decent memory, but that is 200x what I'd think myself capable of, assuming I want to retain it all at the end of the 9 weeks.
Our brain consists of approximately 86 billions quantum computers [2] controlling tens-of-thousands chemical neural networks with at least 10 coefficients
By that logic, a Blackwell GPU contains 208 billion quantum computers.
Each transistor is a quantum mechanical system and takes hundreds of model parameters to describe. So apparently a GPU is a 208-billion-node quantum supercomputer.
"The brain is not a computer" != "Parts / aspects of the brain do computation".
"A computer" in the first statement is IMO obviously intended in the common usage sense of the term, i.e. the brain is not a desktop computer or smartphone, or Turing machine, or etc, and thinking of it like these things will cause more error than insights. Also, billions of interlinked mini bio quantum computers arguably produce something with emergent properties and behaviour much, much more complex than "a computer". I am with GP, the analogy to "a computer" is not super helpful here unless you highly restrict the meaning.
But yeah, the Shereshevsky case is a super interesting one, thanks for linking!
You are wrong, as I didn't limit the analogy specifically to desktop computers only, try reading the rest of what I wrote. The original analogy was obviously hedging against simplistic brain-computer analogies (GP could be read as: "the brain is not a simplistic computer"), so the response demanding to "live with that" citing computational aspects of the brain was misguided and arrogantly wrong.
Multiple other responses also point out the definition given leads to absurdities / triviality (the liver is a computer in this context), so the "correction" with citations is both inept and inapt.
> "Second, there is no guarantee that a given neural network can be approximated by DISCOVER"
Page 7.
They train what appears as embeddings for outer product of roles and fillers. The role for language model can be a position in text, the filler can be an embedding of a word at that position. Then that matrix of a sum of these outer products is linearly mapped into NN encodings and then decoded by NN decoder.
The embeddings learned by this process are not necessarily smaller than original ones. Given that they participate in an outer product computation gives me impression that the resulting sum is much bigger than actual NN encoding, that is why it needs to be linearly mapped into NN encoding.
So, this paper will not necessarily lead to any computation savings.
Good find! But they stop short of saying it cannot be distilled to symbolic algebra. Regardless, your point stands. I scanned the paper in the middle of the night instead of sleeping. Clearly I didn’t do a close read! Thank you for pointing that out.
There are filesystems (ZFS and btrfs) with snapshots and this feature can be used to version-control things. They both do copy-on-write and this is pretty close to what content-addressable storage would give you in terms of compression.
There are a few reasons for this. I really can't seem to wrap my head around Haskell in the wild as written by real people. I also wanted to tie capabilities into the build system tooling so that the build tool could verify caps and launch executables into an OS sandbox. Bolting on capabilities doesn't offer the same ability to enforce them, for example the March package manager ForgePM will reject packages that falsify their cap manifest. Moreover I was reading some papers that inspired the language, and wanted to try it. Cap(X) is also erased b the type checker during compilation in March.
That looks really cool. Can you narrow Bluefin.IO to reads/writes separately? One of the things I've worked on is the ability to allow code to read files, even specific files, but deny writes.
Yes! It started as an implementation of the effect system I always wanted: effects passed on the value level, rather than implicitly on the type level. Once I'd done that I realise that it was actually a capability system (and that was the better way of describing it, because more people already know what a "capability system" is).
Here you go! It's a complete document, but I'll continue to edit it over the next few days before I announce it. I'd love to hear any thoughts you have.
I think that's a less interesting story if Batty doesn't develop and has only his self-interest.
I interpret the ending as Batty coming to the end of his life and realising that all life is precious, not just his own. That's why he saves Deckard after toying with him and then goes into his final monologue that taunts Deckard with how much more of a human life that Batty has experienced.
Of course, there's all the Christ symbolism with Batty's "crucified" hand and how he saves Deckard despite him killing all his friends and intending to kill him as well.
It appears that to have working ASIC with the LLM baked into it we need to place and route macroblocks, and not a great variety of them. These macroblocks can be pre-placed-and-routed, available as masks already and shared between different LLMs.
Thus it appears that the tapeout delay can be substantially lower than a year.
https://en.wikipedia.org/wiki/Royal_Road#A_metaphorical_%22R...
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