Kardashov civilization scale, talking about total energy harnessed by it, gets it all wrong. What really marks civilization scale is the power of applied computations it is able to make per unit of time. (“Applied” means that they are used by civilization in reaching its goals.) This is the real civilization scale. “Orlovsky scale” :)

Why do we need to sleep - and how this is related to consciousness? Strange that for thousands of years people were puzzled by this simple question. Strange, since the answer is easy to find. If you wonder why the sleep is needed, try not to sleep - and see what you will miss. Sleep deprivation degrades consciousness, time-, space- and self-awareness, thoughts coherence, memory - i.e. all cognitive and intellectual functions. Thus, sleep is something our brain cortical neural networks require to avoid loosing its efficiency in computations. The awoken brain cortex activity is orchestrated by the reticular formation of the brain steam: the mechanism which creates our consciousness as a coherent thread of experience (one may compare that to the work of the OS system scheduler in a modern CPUs). Obviously, when run non-stop, the orchestration loses efficiency. Sleep resets it, allowing brain cortex to work in non-coherent mode for few hours (we feel that as sleep with no dreams, where we lose consciousness) - combined with "test drive" of REM sleep where the consciousness and coherence is present in a reduced form, receiving no external sensory input ("hallucinating" with dreams). This restores reticular formation "task scheduler" efficiency and supports our cognitive and intellectual functions after we awake. Interestingly this shows that the sleep is not a property of the brain cortex, but rather of the brain steam, reticular formation, which has been present among animals much before humans, for hundreds of millions of years - in all species that do sleep (reticular formation is there in all chordata, starting from jawless fish). Thus, the sleep is a reticular formation reset: a reboot for the brain orchestrator. The funniest part that some other phylogenetic branch of animals - cephalopod mollusks (octopuses, squids, cuttlefishes) - had independently acquired brain structure very similar to the reticular formation of chordata (and also named "reticular formation") - and, with it, ability & necessity to sleep! QED, the puzzle of sleep is solved with what we already know today!

Indeed, our brains are Universal quantum computers. Whether they "delegate the exponential explosion of state and computation" to the quantum physics layer via some form of quantum chemistry (like chlorophyll does), or handle it in some other way, remains to be discovered.

Many underestimate the risk of not having censorship-resistent high-load computing (able to run at least linear algebra in parallel Mode - what humans call "AI" and "ML" today) - and overestimate the value of money comparing to it. When you have a gun and is among some apes, it doesn't matter how much "sound and hard money" those apes have. Intelligence (as an ability to outperform others in your computing capacity in creating models of the world around) is the ultimate "gun" - and all humans, not able to do that outperformance, are the apes. Without censorship-resistant scalable computing we will just have tyranny of the scale we never had in the past - and bitcoin-as-money won't save from that. That's why since 2017 we are building crnsorship-resistance computing platform, and work on technology backing it, like in @UVioletAI and #RGB #FreeAI thefree.ai

Consciousness. Self-awareness. Intelligence. These are the things which are abundant not just in the Universe but even here on Earth across many biological species and programs. They are not the things which are important. What is important is the existence of individual will. That is rare even amongst humans, - and AI, AGI, and ASI are still extremely far from acquiring it. PS. Consciousness is just a single-threaded computation. All species with nervous system or advanced programs with self-introspection which run on CPUs have it. Self-awareness is an ability to model oneself and compute that model. Again, high animals can do that and I am quite sure one can eventually get the same property from tensor computing ("AI"). Intelligence is an ability to have a coherent predictive model of the world - pretty much the same as self-awareness, but directed externally and not internally. It seems like the Tree of Knowledge [of the Self and own Will] is required to be tasted by anyone seeking the real awakening, not the fake one. Designing AI which can supersede humans requires creating such tree first. Doubt OpenAI or Google engineers, or other humans who haven't ate from that tree themselves will be able to create it :)

I am a strong supporter for generalized molecular nano-assembly, which allows creation and production of hardware (molecular) computational architectures at exa-industrial scale, very robust, energy-efficient and green. Good that such nanoassembler was already released few billions years ago with no human or "natural intelligence" involved. Its core components are DNA and ribosomes; instead of silicone it uses computational architectures based on some forms of carbohydrates (lipoproteins, nucleoproteins and saccharoproteins). It's a pity that humanity was too uneducated and unintelligent not to use it and instead tried to reinvent the wheel with this bullshitty and scammy x86, ARM and other attempts which won't withstand the time and are unusable for building any proper interstellar civilization. #HumanityIsScam

"Conscious is a thread of coherent experience"

🚨BREAKING: The European Parliament has just APPROVED the AI Act. What everyone should know: ➵ The AI Act follows a risk-based approach. Some AI systems are banned, such as those involving: - Cognitive behavioral manipulation of people or specific vulnerable groups; - Social scoring: classifying people based on behavior, socioeconomic status, or personal characteristics; - Biometric identification and categorization of people; - Real-time and remote biometric identification systems, such as facial recognition. ➵ Some AI systems fall in the "high-risk" category, such as those involving: - Critical infrastructures (e.g. transport) that could put the life and health of citizens at risk; - Educational or vocational training that may determine the access to education and professional course of someone’s life (e.g. scoring of exams); - Safety components of products (e.g. AI application in robot-assisted surgery); - Employment, management of workers, and access to self-employment (e.g. CV-sorting software for recruitment procedures); - Essential private and public services (e.g. credit scoring denying citizens opportunity to obtain a loan); law enforcement that may interfere with people’s fundamental rights (e.g. evaluation of the reliability of evidence); - Migration, asylum, and border control management (e.g. automated examination of visa applications); - Administration of justice and democratic processes (e.g. AI solutions to search for court rulings). ➵ High-risk AI systems will be assessed before being put on the market and also throughout their lifecycle. People will have the right to file complaints about AI systems to designated national authorities. ➵ Generative AI, like ChatGPT, will not be classified as high-risk but will have to comply with transparency requirements and EU copyright law. Some of the obligations are: - Disclosing that the content was generated by AI; - Designing the model to prevent it from generating illegal content; - Publishing summaries of copyrighted data used for training. ➵ The AI Act is expected to officially become law by May or June, and its provisions will start taking effect in stages: - 6 months later: countries will be required to ban prohibited AI systems; - 1 year later: rules for general-purpose AI systems will start applying; - 2 years later: the whole AI Act will be enforceable. ➵ Fines for non-compliance can be up to 35 million Euros or 7% of worldwide annual turnover. ➵ If you want to learn more about the AI Act, including challenges, opportunities, and practical insights, join my live session with @BertuzLuca, @JcMalgieri & @RistoUuk on April 4th (register using the link below).

Google announces Stealing Part of a Production Language Model We introduce the first model-stealing attack that extracts precise, nontrivial information from black-box production language models like OpenAI's ChatGPT or Google's PaLM-2. Specifically, our attack recovers the embedding projection layer (up to symmetries) of a transformer model, given typical API access. For under \20 USD, our attack extracts the entire projection matrix of OpenAI's Ada and Babbage language models. We thereby confirm, for the first time, that these black-box models have a hidden dimension of 1024 and 2048, respectively. We also recover the exact hidden dimension size of the gpt-3.5-turbo model, and estimate it would cost under 2,000 in queries to recover the entire projection matrix. We conclude with potential defenses and mitigations, and discuss the implications of possible future work that could extend our attack.

Read from right to left: rightmost items are most basic/fundamental; leftside are composed/dependent on the right side.

It is strange that the simplest thing - rational reasoning - is still not run in artificial computational environments at scale, while the most popular app there is mimicking human uncertain rumblings and cognition errors/biases with much more computationally expensive LLMs.

Intelligence is an ability to find “pockets” of computational reducibility inside computationally-irreducible systems. In simple terms this means “finding patterns within chaos”. In thermodynamic terms - ability to locate areas with lower entropy. In computer science terms - ability to find P-time problems within an NP domain.

LLM is not “learning world map”; is “doing clustering analysis on context of word embeddings”. Back in the days it would be called “large statistical fuzzy language models” - but we are in the era of AI hype: statistics are not clickbait and also can’t scare voters and produce neoluddites.

The difference between DNA as a storage medium and all human-created mediums (type, HDD and lithographic flash) is that DNA can pack 3D - while other human-created media can’t. That is why the density of packing for DNA are many orders of magnitude better: just 1cm3 of DNA can store 10^19 bits, which is about 2^64. None of existing human media can achieve that amount of storage yep up today - I mean their total volume.

DNA is a universal Turing machine. Hydrogen is the main atom in the Universe. Thanks to stars carbon, oxygen and nitrogen became most widespread chemically-active elements in the Universe. Combination of carbon, hydrogen and oxygen represents the most prolific form for 3D nanorobotics (see enzymes) called “biochemistry”. It works this way in the interstellar medium, on zillions of planets and their satellites (like Titan, Europe and many other in our Solar system). Such biochemistry lack persistence and programming. DNA, made of nucleic acids, is both the storage (persistent memory) and the code - and probably the most common universal base for a Turing computer in the Universe. Lets look into its instruction set architecture. It uses a single base pair - a error-correctable structure - which represents two bits. The instruction word is a codon, made of several base pairs. On Earth, it happened to be triplets, i.e. 12 bits. Unlike byte, it can encode 4^3=2^6=64 bits, which happened to be enough to represent main nanoassembler microcode for nanorobotics - a set of aminoacids to construct protein-based enzymes. It is not machines and robots who will conquer the Universe. It is biochemical organisms and genetic code which are the most advanced machines and nanorobotic factories who is already doing that or, maybe, already had done.