Oh, I don't know... couldn't Drexler's "Gray Goo" be modified to incorporate Ivan's DNA and be done with it?
On Thu, Jul 13, 2023 at 12:58 PM Matt Mahoney <[email protected]> wrote: > On Thu, Jul 13, 2023 at 6:21 AM <[email protected]> wrote: > > > > On Thursday, July 13, 2023, at 4:28 AM, Matt Mahoney wrote: > > > > Organizing disorganized thoughts begins with a goal. Why build AGI? We > can group the goals into roughly 4 categories. > > > > 1. Scientific curiosity, understanding the brain and consciousness. > > 2. Automating labor. > > 3. Uploading, immortality. > > 4. World domination, launching a singularity, creating utopia. > > > > 5. Creating an artificial descendant > > Nice one. Yudkowsky was right. AI will kill us all and we won't even > put up a fight. But probably not in this century. > > Let's put a timeline on this. Assume Moore's Law continues doubling > global computing power every 2 years. This is uncertain because clock > speeds stalled at 2-3 GHz in 2010 and transistor sizes are likely to > stall this decade because we are close to the ~5 nm spacing limit > between dopant atoms in silicon. A RAM capacitor stores a bit using 8 > electrons. Further advances will require nanotechnology, moving atoms > instead of electrons, to solve the power problem. In about 60-70 years > we will stall at the Landaurer limit 4 zJ per bit operations at room > temperature, still a 10^9 improvement over transistors. > > 1. The AGI algorithm is mostly understood. LLMs pass the Turing test. > We understand how neural networks succeeded where symbolic processing > failed. Language evolved to be efficiently learnable one layer at a > time in the order of phonemes, word segmentation, semantics, and > grammar. Symbolic models, like those used for compilers, failed > because they put grammar before semantics (e.g. how to parse "I ate > pizza with Bob/olives/a fork"). Fully connected neural networks like > transformers can learn arbitrarily deep hierarchical concepts like > mathematics and world models of physics and social interaction. Human > knowledge is half inherited and half learned (about 10^9 bits each), > but LLMs can learn the inherited part, like human emotions, from an > appropriately large enough unlabeled corpus. It knows how to model > feelings without having feelings. It knows that it is an LLM. It is > self aware without being conscious, in the sense that it understands > how humans have an irrefutable sense of being conscious (as part of > our evolved fear of death), without having this sense itself. > > 2. Automating labor requires more than language. Vision and robotics > are advancing but not at human level yet. It will take about 30 years > to reduce the cost of producing a movie from $1M to $10. The value of > labor is world GDP divided by interest rates, about $1 quadrillion. We > should expect investment on this scale. Modeling 10^10 human brain > sized neural networks will require 10^26 OPS, 10^25 parameters, and > 10^17 bits of human knowledge collected no faster than 5-10 bits per > second per person at a cost of > $100 trillion. This is slow enough > for humans to adapt to the changing job market without massive > unemployment. Instead, AI will make us more productive, improve our > lives both at work and home, and increase our income. But the big > change is we will have little need or desire to interact with other > humans because AI will be far more helpful. You can have everything > you want, but this is not where happiness comes from. A state of > maximum utility is static, without feeling. > > 3. We already have the technology and enough personal data to > construct an LLM that claims to be you, happily living in a virtual > utopia. All that remains is to construct a world where nobody else > knows or cares that you exist in a human body. > > 4 and 5. To transform the world, technology has to catch up to > biology. The biosphere has 10^37 bits of DNA storage and executes > 10^29 DNA copy and 10^31 amino acid transcription operations per > second. Human evolution was the result of 10^48 operations over the > last 10^17 seconds (3 billion years). Photosynthesis generates food at > a rate of 500 TW, out of 90,000 TW available solar power. We already > have solar panels that are 30% efficient. Global computing power is > now about 10^19 OPS and 10^26 bits. At the current rate of Moore's Law > and with intelligent design, our self replicating, non DNA based > descendents will be ready to displace DNA based life around 2100. > > -- > -- Matt Mahoney, [email protected] ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T59f369fee7febd6d-M19485ddce6a542f25f2caf46 Delivery options: https://agi.topicbox.com/groups/agi/subscription
