Joscha Bach

“The fuzzy idea is the one of continuous existence. We don't have continuous existence... because it's not computable. There is no continuous process. The only thing that binds you together with the last week and from yesterday is the illusion that you have memories about them. So if you want to upload, it is very easy. You make a machine that thinks it's you. ...It's the same thing that you are. You are a machine that thinks it's you.”

“Minds are software states... Software doesn't have identity. Software in some sense is a physical law. ...The maintenance of the identity is not terminal. It's instrumental to something else. You maintain your identity so you can serve your meaning. So you can do the things that you are supposed to do before you die. ...For most people the fear of death is the fear of dying before they are done with the things that they feel they have to do even though they cannot quite put their finger on... what that is.”

“I don't actually have an identity beyond the identity that I construct. ...[T]he Dalai Lama... identifies as a form of government. [He] gets reborn, not because he is confused, but because he is not identifying as a human being. He runs on a human being. He's... a governmental software that is instantiated in every new generation anew. So his advisors will pick someone who does this in the next generation. So if you identify with this, you are no longer human and you don't die in this sense... only the body that you run on. To kill the Dalai Lama you'd have to kill his tradition.”

“What Gödel could show is using classical mathematical semantics you run into contradictions, and because Gödel strongly believed in these semantics... he was shocked. It... shook his world to the core, because in some sense he felt that the world has to be implemented in classical mathematics.”

“It may not have a why. This might be the wrong direction to ask... [T]here could be no relation in the "why" direction... It doesn't mean that everything has to have a purpose or a cause...”

“[T]here also seems to be a particular kind of ground truth, [e.g.,] you are confronted with the enormity of something existing at all. ...It's stunning when you realize something exists, rather than nothing. ...[T]his seems to be true. There is an absolute truth in the fact that something seems to be happening.”

“You cannot define objective truth without understanding the nature of truth... So what does the brain mean by saying that it's discovered something as truth... A model can be predictive or not... [T]here can be a sense in which a mathematical statement is true because it's defined as true under certain conditions. So it's... a particular state that a variable can have in the assembled game and then you can have a correspondence between systems and talk about truth, which is again a type of model correspondence.”

“You need to become unimportant as a subject, that is, if you are a philosopher, believe is not a verb. ...You have to submit to the things that are possibly true and... follow wherever your inquiry leads, but it's not about you, it has nothing to do with you.”

“The failure to deliver on some of the early, optimistic promises of machine intelligence, as well as cultural opposition, lead to cuts in funding for cognitive AI, and eventually the start of the new discipline of Cognitive Science. ...Cognitive Science did not develop a cohesive methodology and theoretical outlook, and became an umbrella term for neuroscience, AI, cognitive psychology, linguistics and philosophy of mind.”

“Artificial Intelligence was the attempt of thinkers like Marvin Minsky, John McCarthy and others to treat the mind as a computational system, and thereby open its study to experimental exploration by building computational machines that would attempt to replicate the functionality of minds.”

“[W]hile dynamical systems often cannot be effectively computed on a finite state machine (such as a von Neumann computer), they can often be efficiently approximated.”

“The absence of an understanding of substrate independent machines lead Leibniz to the rejection of mechanist philosophy...”

“Computational systems are machines that can be described apriori and systematically, and implemented on every substrate that elicits the causal properties that are necessary to capture the respective states and transition functions.”

“Whereas mathematics is the realm of specification, computation is the realm of implementation; it captures all those systems that can actually be realized.”

“Mathematics is the domain of all formal languages, and allows the expression of arbitrary statements (most of which are uncomputable). Computation may be understood in terms of computational systems, for instance via defining states (which are sets of discernible differences, i.e. bits), and transition functions that let us derive new states.”

“[T]he genome defines the rule book by which our brain is built. The brain boots itself, in a development process, and this booting takes some time... formation learning in which some connections are formed, basic models are built of the world so we can operate in it. How long does this booting take... about 80 megaseconds. That's the time a child is awake until it's 3 1/2 years old. By this age you understand Star Wars, and I think everything after Star Wars is cosmetics.”

“[I]f you look at the progression of AI models, it... went the opposite direction. ...AI started with linguistic protocols, which were expressed in formal grammars, and then it got to concept spaces, and now it's about to address percepts. ...At some point in the near future it's going to get better at mental simulations and at some point after that we'll get to attention directed and motivationally connected systems that make sense of the world, that are in some sense able to address meaning. This is the hardware that we have...”

“[T]here is another type of mental representation that is linguistic protocols, which is... a form of grammar and a vocabulary. ...[W]e need these ...protocols to transfer mental representations between people ...by scannning our ...representations, disassembling them ...and ...we use a discrete set of symbols to get this to somebody else... [who] trains an assembler that reverses this process and builds something that is... similar to what we intended to convey.”

“With this vector space you can do amazing things, [e.g.,] if you take the vector from king to queen, it's pretty much the same vector as between man and woman. ...[B]ecause [these concept spaces are] really a high dimension manifold, we can do interesting things like machine translation without understanding what it means, that is, without doing any proper mental representation that predicts the world. ...[T]his is [a] type of mental representation that is somewhat incomplete, but it captures the landscape that we share in a culture.”

“[W]e saw that mental representation is about percepts, mental simulations, conceptual representations... [C]onceptual representations give us concept spaces, and... these concept spaces... give us an interface for our mental representations we can use to address and manipulate them, and we can share them in cultures. [T]hese concepts are compositional. We can put them together to create new concepts. ...[T]hey can be described using higher dimensional vector spaces. They [vectors] don't do mental simulation and prediction, and so on, but we can capture regularity in our concepts with them.”