Perry Marshall Explains The $10 Million Code Problem

I sat down with John Maddox who has a keen interest in information, computing, biology and evolution. John cuts right to the chase and hammers on the central issues that make biology a non-materialistic science…along with stories of numerous conflicts we’ve had along the way.

Podcast link:

Perry Marshall Explains The $10 Million Code Problem

Download The First 3 Chapters of Evolution 2.0 For Free, Here – https://evo2.org/evolution/

Where Did Life And The Genetic Code Come From? Can The Answer Build Superior AI? The #1 Mystery In Science Now Has A $10 Million Prize. Learn More About It, Here – https://www.herox.com/evolution2.0

14 Responses

  1. Justin Fine says:

    I don’t know if it’s against the rules, but I need help from some specific scientists in your circle. I have 95% of the code completed but I need a meeting with Henry Heng I have the answer. However, I have no formal education come again I know the answer and just need a little help sure, but I am a bail bondsman and I don’t know a single scientist

    I developed this code that is three dimensional omnidirectional 360° to 360 degrees of freedom. Actually developed it eight years ago when I wrote my book.

    I had a zoom with Ed Wong from herox and he offered , after my 2-minute pitch oh, you go ahead and put my project right up next to yours so, he offered to put me put next to your project on hero X next to NASA. .

    give Ezra 3 million for the cancer Evolution, and then I want to do a continuation contest on 0x for another $500,000 million dollars to have other people help develop this code because your little encoder decoder thing is ridiculous. It is a code at 8 on the galaxies movement and I can’t even begin to show you with an encoder decoder table because I don’t know how but I know God in nature has seen everywhere and I will prove it to you with one phone call for two minutes. This isn’t a request, I really need to speak with the fate of the world important. I’m having a lot of trouble finding mathematicians and scientists because I’m freaking bail bondsman most of my friends are military do two cops felonies and now we are trying to bring the world into the future but I’m dealing with a box decoder. I don’t want to insult you but I don’t think you understand what’s going on here. You think Bruce Willis and associates in Armageddon was a band of Misfits oh, my guys are bunch of military veterans and we hunt around the country, you’re not mentally equipped to handle this on your own and you never will be.” That was one of my favorite lines from the movie The Edge of Tomorrow.” This is a massive project it’s going to take millions of people I don’t know a single geneticist, oncologist, so I would like to talk to you in person, Henry is Perry there , and I will have my team with me, Henry can have his team with him. The only thing is, I am in charge this project. And it’s Henry and I can presented together, that would be the most amazing experience of my life. But my theory is mine. God gave it to me. I have spoken with my advisors and family members high up in government throughout the country, and what I have come to realize is that and this is a job for the dod with our help.

    This is not a request . So, this is High level security so, we have no time, imperative that we get this done. I need oh, that’s not once or Shuffle it into an email box, but I need this message passed to mr. Marshall in March urgent, please make sure to get it into his inbox as soon as possible so he sees it first thing Monday morning please thank you. That’s as fast as humanly possible. And also please send him a text message Square an email direct to him letting him know that it’s in his and also please send him a text message or an email direct to him letting in him know that it’s in his inbox, to MR. MARSHALL AND HENRY HENG !

    Alhough I might sound brash and that fact that I am a bondsman, I know for a fact and I have the answers to lack. I know that I am worth more than ten billion dollars honestly, 10 trillion dollars. I need a little more communication please. I’m running four businesses while working on this project, im akmost done, and supporting eight different Mouths. I am launching this adwords campaign tomorrow oh, but I will be free as early as Monday if we can get this message there that quickly? I think was in technology today is going to be a problem hahaha my name is Justin fine but direct line is 719-722-0851. So as long if you want to verify that I need this app and now like yesterday please. I know you might be an answering call cats and their service, God bless you I love you I started out there in the trenches with you. But I need this to happen as soon as possible and I really appreciate. Thank you so much have a great week.

    • Send us a video describing in detail what you are proposing to explain on the phone. [email protected]

      • Justin Fine says:

        Perry,

        Thank you for the reply. I am finishing the paper this week. I apologize for my brashness but this is my dream and I have been extremely emotional and frustrated, considering I have been working on this for 10+ years, and I keep getting shot-down because I have less than half a year of community college. All I want to do is help save the world. I know the earth better than anyone on the planet, inside and out, but I had to teach myself the chemistry, biology & quantum mechanics in the last 5.5 months when I walked away from my career of 14 years to pursue this project (and my dreams).

        I was having so much trouble understanding the basic encode and decode because I am not a programmer and did not realize what this code could actually do at full throttle, but then I realized that this is MY code and I can make it however I want. As long as it is an encode-message-decode based on cause and effect, math, my proprietary knowledge for emergences, and that it only contains 2-way-logic – – – which made it a lot easier. This is the most complex and diverse code ever written in human history, especially from a guy who 100% LITERALLY learned how to code ANYTHING AT ALL in the last 2 days!!!

        You can imagine how frustrated I have been… I hit a brick wall when I sent that message because I have the answers and am SO passionate about this. I have never cried so much since I was 13. This is my purpose.

        I decided to take a breath and reverse-engineered all of my own thoughts, all of my processes. I meditated on the Universe and my brain cracked WIDE OPEN. So, I kept going, researching advanced code now, and designed an ontological engineering language that is a modularized-articulation model with optimal partition in-mind due to the mathematical and multi-field nature of my new science’s theoretic and semantic informatics interoperability. Besides the fields of scientific inquiry I designed 10 years ago to supersede -Darwin’s Unpunctuated Gradual Evolution Theory (-D.U.GET.), supersede Super Continental Drift, and update plate tectonics, I realized this code does kill cancer, frames AI better, and helps IoT + more. I realized I needed a redundancy system so my method could be used for more than genomics and that I also needed to optimize the end-user ease–of-use and UX/UI for lay-persons (like myself) so the software could be used in worldwide collective crowdsourcing projects as well. I needed to to look at it from the ontological experience so I could just “be”. I will still need help to program it or we can also put a series of contests on HeroX. I am wire-framing and outlining it with all the heuristics and most of the informatics and semantics I can, now. I ended up having to design a new arithmetic logic unit as well because the sheer amount of information, we can go a lot faster with this calculator.

        I have no clue about analyzing gene expression signatures except for the few examples I have in emergence but I know how to apply them in my code, but Henry knows the genome. I appreciate you replying back to me, Perry. You can see in my project cover image what I would explain to you over video, my same theory I explained to Ed Wong. but I think i found the answer and will submit ASAP. We can get those patents and spot cancer and other diseases before they hit, I believe. I have thoroughly enjoyed your podcasts and you have given me hope.

        I am proposing Debunking Darwinism with mathematical truths (image), Setting the stage for laboratory experiments to solve the OOL with mathematical truths, Killing Cancer, Explaining Consciousness, and Bridging the Gap between Creation and Evolution… With Math. All with math and verifiable facts. Let me keep hacking away at it or email me through HeroX or let’s just have a phone call. I am most comfortable on the phone, having started my career as a cold caller. I don’t do solo videos but Zoom maybe? I am so close, I need a another 5 days but contact me if you like or you can just wait for the submission. I just want to do right by you, your investors, God, and anyone else this can help, but I need to win this contest. That is my purpose. Thank you for the reply and, again, thank you for this opportunity. I will meet you – – – somewhere in the middle…

  2. Egor Bezrukov says:

    Hello, Mr. Marshall.

    We have sent you a solution to the evolution 2.0 challenge (actually it’s like half-solution, it is not complete at the moment) titled “Autoencoders as solutions for this Challenge”. Our point is that autoencoders (see https://en.wikipedia.org/wiki/Autoencoder) look exactly like the required solution for the Challenge. Also, in general, artificial neural networks work the similar way to how chemical reactions work. So now we need find some type of a chemical autoencoder. (this is mostly my colleague idea, not my, but I agree with it)

    Our file also included several questions about the Challenge and about your claims in general (because the forum https://www.herox.com/evolution2.0/forum does not work).

    For example exactly my question is about chapter 9 of your book. You claim that a purely random noise on a useful information encoded in some kind of a computer code will always be harmful and there’s no actual way for it to be beneficial even in combination with the natural selection. Am I understanding it correctly? If so, can you provide any sort of a mathematical prove for your claim? I think that your claim is wrong. I wrote a computer simulation of evolution with simple digital-like square microbes (credits to foo52ru for the original idea https://www.youtube.com/foo52ru). Each microbe has a genome that works exactly like a computer program (so it’s definitely a type of code). Also purely random mutations are used. And it definitely do work, as you can see in this video – https://youtu.be/Y9ZDeV398BA . How would you explain that? If you are interested in, I will provide full English description of my program (which does not exist at the moment) and instruction on how to run the program.

    Our file have been sent around a year ago, but we still haven’t got any feedback. We would be very grateful if you provided at least some information on what happened to our solution.

    ========
    With respect from Busy beaver (me) and Outer Limits (my colleague) to Perry Marshall.

    • Egor,

      If you read my book Evolution 2.0 I think it will make very clear what we are and are not looking for.

      Yes, I would fully expect autoencoders to resemble what we are looking for in the challenge. But to win, you can’t “cheat,” and writing code is cheating. The question is, how do you get from chemicals to code without a human writing the code. You would have to get chemical reactions to produce encoders and decoders. No one knows of a physical principle that makes such a thing possible. If this is discovered, it is as big as Tesla or Einstein.

      It is certainly possible for a very small string of code, maybe 10-20 bytes to be improved with random changes especially when closely monitored for a predefined desired result. That is what Richard Dawkins “methinks it is like a weasel” program did. But notice that the desired outcomes were inherently pre-programmed in, so none of this solves the design problem in biology. All it does is demonstrate that it remains unsolved.

      If your string of code is 1 million bytes (like DNA of bacteria) or a gigabyte (human genome), the prospects of randomly mutating some random location with some random change and actually getting something useful is unimaginably, vanishingly small. The best one might hope for is a very very occasional, trivial improvement. But the sun would burn out long before you would get anything like an eye.

      So far as anyone knows, cognition is required to generate more than 50 bytes of coded information. To do so randomly would require more permutations than there are particles in the universe. More about this at https://www.sciencedirect.com/science/article/pii/S0079610721000365

      My team responded to your prize submission some months ago. My assistant is re-sending an email to you. Our response is in the HeroX interface.

      • Egor Bezrukov says:

        Thanks for answering.

        We know that our solution is not complete. At least we glad that you agree that a chemical autoencoder would be the Solution. What I do not understand is why do you think that it would be “as big as Tesla or Einstein”. Let’s imagine that it is found (an actual chemical autoencoder that produces a digital code). Then how can it possibly be useful? I can only agree that it would be scientifically interesting.

        “It is certainly possible for a very small string of code, maybe 10-20 bytes to be improved with random changes especially when closely monitored for a predefined desired result.”
        In my program each microbe has a genome with length 80 consisting of integer numbers from 0 to 79. So in bits it is equal to around log₂(80⁸⁰)≈506 bits or 63.2 bytes.

        I read about Richard Dawkins’s program in his book “Blind watchmaker”. In his program he used artificial selection (by his program) instead of truly natural selection. There’s also another program with fractal trees, it also uses artificial selection (by human). However in that time computers were much more limited than now. My program is completely different. The difference is that it uses truly natural selection so the result is not pre-programmed. All what I did was to define for microbes a purpose – to gain energy trough a couple possible ways (like photosynthesis, eating organics and attacking other microbes) and to replicate – when the energy of a microbe reaches it’s maximum level, the microbe replicates with some probability of mutation – that’s all “pre-programming” in my program. What strategy a microbe will use to survive and to replicate is not pre-programmed. I even didn’t know how will it go after I run the program. As it turns out microbes can develop many interesting strategies. After the simulation is started microbes start to use photosynthesis to replicate (because the 1-st microbe was pre-programmed with just 1 command – photosynthesis, just not to die instantly) and form something like a colony (this isn’t a true colony yet). Then, after some amount of time and some mutations, walking microbes do appear and start to occupy empty world much faster. Then, after some more time, they start to move very fast while attacking each other and all passive microbes left in the world. Often, after some more time, when the entire population of passive microbes is destroyed, true colonies do appear. In colonies, microbes check if a microbe is relative to them (if it has similar genome) before attacking it, not to attack relatives. So they use at least 2 commands together in their code, to check a microbe and to attack it (in reality they use a lot more commands than 2 and their behaviour is much more complicated). Colonies often occupy the entire world. And this is only a small part of all possible life forms that appear in this program. Some of them, like “ghosts” (srange crowds whith blurry edges of fast moving microbes that appear and disappear very fast), are not even well-explained by cyberbiologists at the moment. Nobody knows how exactly they work, but they appear in different programs like my “Replicators” and foo52ru’s “Artificial life” (if I translated it correctly). I have my own hypothesis on the “ghosts”, if you are interested. Even more different life forms can be found in other similar programs. And non of them are pre-programmed. I think that this is a perfect example of natural selection developing something entirely new. Or do you still think that it’s pre-programmed or too simple?

        “If your string of code is 1 million bytes (like DNA of bacteria) or a gigabyte (human genome), the prospects of randomly mutating some random location with some random change and actually getting something useful is unimaginably, vanishingly small.”
        I think that you don’t actually understand how the natural selection works. I have a mathematical prove that your statement is wrong. Probability of a small improvement after a small mutation is much bigger than for a big mutation. That’s the reason why in the fruit fly experiment flies did’n get any improvement. Increasing mutation rate is not equal to increasing evolution speed. For the speed of evolution by natural selection there’s a limit that you can’t overcome just by increasing mutation rate. Here is the prove:

        Let’s pick, for example, a bacteria’s genome. Now let’s assume that there’s N different chemicals that may possibly be produced after transcription and translation of the genome (even those that aren’t produced at the moment). N would definitely be a large number. Now let’s count the concentration of each of those chemicals so that we get N numbers representing the current genome’s state. Instead of N chemicals I could have chosen, for example, M external properties of the bacteria or something like that. That does not change anything. My point is just to represent the current state of a genome in numbers so that a slight mutation would change those numbers slightly in a random direction. Now, when we found those N numbers, we can assume them as an N-dimensional vector in the N-dimensional space. This is the “State” vector. Now let’s call the slight change of the State vector after a mutation the “Mutation” (new State – State = Mutation). For each State vector we can define how good it is for the bacteria. Let’s call it the Fitness function. If Fitness(State) is a differentiable function (this should definitely be true), then it means that in some little area around the State point in the N-dimensional space Fitness function should be close to being linear. And for a linear function we can represent the change of Fitness after a mutation as Fitness(State + Mutation) – Fitness(State) = dot(grad(Fitness(State)), Mutation), where grad(Fitness(State)) is the gradient of Fitness function and dot() is the dot product of 2 vectors. It is obvious that dot(grad(Fitness(State)), Mutation) product would have 50% chance of being positive if Mutation is a random vector. However as the Fitness function is not exactly linear and Mutation is not purely random, the chance would be less than 50% in the most cases. But the smaller the Mutation, the closer the chance for that mutation of being beneficial is to 50%. That’s the reason why only slight mutations often are beneficial. Big mutations or some great amounts of small mutations have much smaller chance of being beneficial.

        “So far as anyone knows, cognition is required to generate more than 50 bytes of coded information.”
        I can’t understand what do you mean by “cognition”, but my program works with 63 byte genome as mentioned above. However, in reality, not all genome is used by microbes at any point (which looks exactly like with real life genomes). If I had more computation power or somehow improved my program it would be definitely possible to get microbes to use more than 50 bytes of their genomes.

        “My team responded to your prize submission some months ago. My assistant is re-sending an email to you. Our response is in the HeroX interface.”
        That message does not seem to be the official response. We were looking for your own view on our solution. But now probably we can contact you here in the comments.

        • Egor,

          As far as I can tell, all software programs that simulate evolution have:

          -Operating systems, hardware platforms and programming environments created by humans (which are not subject to random mutations)
          -Fitness functions defined by humans
          -Parts of the “environment” that the replicating organisms “live in” that are not subject to random mutations
          -Parts of the replicating organisms that are NOT subject to random mutations
          -Parts of the replicating organisms and environment that ARE subject to random mutations

          If I look at the totality of all the code required to run your programs, most of it is invariant and only a small number of variables are permitted to vary.

          In this case a human has made a CHOICE as to what part is allowed to be a variable and what is fixed. Furthermore, these choices are typically made by very smart people after considerable experimentation.

          I acknowledge that if you allow only strategic parts of a program to vary, you can get very very interesting results. This has been demonstrated for many years by programs like Conway’s Game of Life, Avida, etc, and more recently DeepMind etc. None of these programs work without numerous pre-programmed constraints.

          I also acknowledge that machine learning programs and genetic algorithms find solutions that their programmers could not have anticipated and may not even understand. (I wrote the world’s best selling book on Google and Facebook’s advertising programs so I am well aware of how powerful AI is.)

          I do not interpret this as “the power of natural selection.” Natural selection can only select what has already evolved. Natural selection is an outcome, not an explanation. I see this as the power of permutational computation, given appropriate constraints selected by the programmer.

          We also need to turn our attention to real biology as opposed to simulations, where we notice a number of very interesting things:

          -Organisms re-write their genomes in response to inputs from hundreds of inputs from the environment. They do this non-randomly. The changes only occur in specific genome “hot spots.”

          -Organisms generate many novel innovations even when there is a very low or nonexistent amount of natural selection. Barbara McClintock’s corn plants yielded a very high percentage of successful mutations and few of them died. The adaptation of her plants was not attributable to Natural Selection, but rather Natural Genetic Engineering. Michael Levin found that cells exposed to barium will die but those exposed to a small amount will immediately generate a defense mechanism against it, in real time – despite the fact that probably no organism of that kind in history had been exposed to barium before. This is not attributable to natural selection. Rather we need to recognize that the organism is ANTICIPATING natural selection and trying to avoid it.

          -In this sense, the organisms choose constraints and choose variables, much the same way you do when you write programs that mimic Darwinian evolution. Organisms do this because they are intelligent (REF Shapiro 2021 “All living cells are cognitive”)

          The response of my team to you is our official response. We get too many submissions for me to personally look at all of them. Still, every submission gets reviewed by qualified personnel and the better ones we receive also get examined by a world class origin of life researcher. My team forwards the most promising ones to me.

          A submission that is a computer program and not a chemical experiment cannot qualify because a computer program is by definition programmed. We are searching for the origin of programming, so anything like that is automatically disqualified. The rules make this very clear.

          The fact that codes and programs only come from biology (Yockey 2005; Cronin and Walker 2016; Marshall 2021) and the fact that the non-living world is so far not known to produce codes, indicates that there are either laws of physics or principles of cognition that nobody currently understands.

          If someone can get pure chemicals to encode, transmit and decode symbolic information, then we have a major clue to not only the origin of life and the genetic code but also cellular cognition.

          A new discovery that uncovers these principles is at the level of Tesla and Einstein. Our prize is a search for the next world class prodigy.

          Perry

          • Egor Bezrukov says:

            Sorry for delaying the response.

            “-Operating systems, hardware platforms and programming environments created by humans (which are not subject to random mutations)”
            Microbes in my program are subjects to random mutation, not my computer.

            “-Fitness functions defined by humans”
            My program do not contain fitness function. There’s only a rule that defines that when the level of the energy of a microbe reaches it’s maximum, then microbe replicates. It’s not a fitness function. This is what defferes my program from the others.

            “-Parts of the replicating organisms that are NOT subject to random mutations”
            Why do you think so? I implemented it so that each part of the genome have some slight chance of changing to a random value after replication.

            “If I look at the totality of all the code required to run your programs, most of it is invariant and only a small number of variables are permitted to vary.”
            Does that make a difference from the real life? In reality there are also lots of pre-defined values that affect living organisms.

            “In this case a human has made a CHOICE as to what part is allowed to be a variable and what is fixed. Furthermore, these choices are typically made by very smart people after considerable experimentation.”
            But still the observable evolution in my program is the result of changes only in the variable parts of my microbes.

            “I acknowledge that if you allow only strategic parts of a program to vary, you can get very very interesting results. This has been demonstrated for many years by programs like Conway’s Game of Life, Avida, etc, and more recently DeepMind etc. None of these programs work without numerous pre-programmed constraints.”
            Conway’s Game of Life is not an evolution simulation. It does not contain natural selection at all. I still can’t understand why do you think that pre-programmed values are bad. There are lots of constant values and constraints in reality (for example see https://en.wikipedia.org/wiki/Physical_constant)

            “We also need to turn our attention to real biology as opposed to simulations, where we notice a number of very interesting things:”
            I am trying to prove that evolution by natural selection of random mutation is possible. I’m not trying to simulate real life. My opinion on this is that all those mechanisms do exist, but they are not the main engine of the evolution. It’s like the human’s technology. It does make it easier to produce new technologies, but as soon as we haven’t reached the technological singularity, it can’t survive and progress without humans. And like that the evolution of living organisms is also impossible without natural selection.

            “A submission that is a computer program and not a chemical experiment cannot qualify because a computer program is by definition programmed.”
            I don’t mean my program as the solution. I’m just trying to argue that the evolution by natural selection of random mutations is possible. If you don’t want to argue with me, I’ll stop.

      • Ego Bezrukov says:

        Thanks for answering! I have sent here a long comment 2 days ago, but I still can’t see it. Was it a bug and I should resend it, or does it mean that it haven’t passed the moderation?

        • All comments are moderated and it sometimes takes time to respond.

          • Egor Bezrukov says:

            Perry,

            Thanks for the discussion on my program and the possibility of evolution by natural selection of random mutations. I think it’s closed right now.

            Now I want to ask you a question that was in our solution file. It’s about the relationship between your scheme of how code works (message -> encoder -> code (signal) -> decoder -> original message [url]https://d253pvgap36xx8.cloudfront.net/editor_uploads/22073/2017/09/07/Encoding-Graphic.jpg[/url]) and the genetic code. We think that the genetic code does not approach your scheme. Your scheme consists of 3 parts (states of information flow) separated by encoder and decoder. 1 – Input (message), 2 – Encoded message, 3 – Output (should be the same as Input as stated in your scheme).

            But we can’t find any kind of information flow that would have matched those 3 states in the genetics of living organisms. So we have suggested 2 possible ways of splitting the genetic information flow into 3 states that you may have supposed to be matching your scheme:

            1. The “imagination” of a living cell (the input message) -> DNA code -> protein (the output message).
            For this scheme I want to point that you can’t really check if the input message actually existed or not. So it’s impossible to check if the code transfer succeed.
            We have provided several examples to explain that in our solution file. Here’s my colleague’s text about those examples:
            In the example when the person who is thinking of the letter A, he presses the corresponding key and that key sends a binary code from which then the letter A is recreated on the computer screen. But since we are not able to read minds, there’s no way to prove what he conceived this particular letter A. for example, if we vivisect the brain of a person who conceived the letter A, we cannot find it there, since this conceived letter A in the human brain does not exist physically (in the Michael Talbot’s book “The Holographic Universe” this question understands). Therefore, we actually cannot compare it with the letter A at the output (i.e., on a computer screen), while your scheme states just that.
            In the example with DNA, the same thing occurs. When a bacteria “makes a decision” to synthesize a new protein – this conceived protein does not yet exist in reality, it exists only in “imagination” of the bacteria. Then this “imagined protein” is translated into the DNA code, from which the real protein is synthesized. And again, there is also no way to compare the “imagined protein” at the input and the real protein at the output.

            2. DNA code (the input message) -> RNA code -> protein (the output message).
            For this scheme I want to point that the input message is not actually the same as the output. The input message is already encoded using the genetic code. So the encoder in this scheme is more like a “re-coder”. And for that reason it also does not match your scheme. That’s also stated in the central dogma of molecular biology (see [url]https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology[/url]). There’s no way that information is transferred backwards from protein to the genetic code.

            We also suggested an example which works according to this scheme – some organisms (octopuses, chameleons etc.) are able to change their color depending on the color of surrounding environment. If someone creates a mixture of chemicals which works by this way, can it be considered as a successful solution of Evo2.0 Challenge?

            • Egor,

              Hubert Yockey’s book “Information theory, evolution and the origin of life” (Cambridge Press 2005) shows that DNA transcription and translation is isomorphic with Shannon communication. I have a graphic taken from his book at https://evo2.org/dna-atheists/dna-code/

              https://evo2.org/wp-content/uploads/2011/01/dna_isomorphic.jpg

              When you press an “A” key and a letter A appears on the computer screen, the plastic keyboard key is not identical to the image on the screen. But it does 1:1 correspond to it. Similarly, DNA codons are not identical to amino acids or RNA intermediates but do correspond to them (with redundancy, 64 possible codons -> map to 20 amino acids and start / stop signals).

              The prize does not intend to solve qualia problems, i.e. it doesn’t try to figure out what an organism or conscious entity intended. It is much simpler than that. It asks how accurately a fixed communication system transmits digital information, just as a communication engineer would evaluate the fidelity of a phone or video or audio signal.

              It’s not possible to answer your final question because it doesn’t contain enough detail. The way a person can win the prize is by creating an emergent chemical system which both encodes and decodes at least 32 states.

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