Neuko

neuko

This article is the second in a three part series. If you want to read the first one you can do here . Spending Christmas on the beach in Australia was the perfect way to celebrate surviving a year of together. traveling James’ childhood friend emigrated to Australia a few years ago and had been badgering us to visit ever since. We kept telling him it was too expensive, but since our Estonian e-residency cards were there we ended up with no choice but to hop on the cheapest flight we could find. I guess he was pretty happy that we’d finally made it halfway around the world as he surprised us at the airport! Living and working in a campervan We were unsure if we could afford to travel Australia and weren’t particularly interested in doing so if it was going to cost a fortune. The original plan was to spend a couple of weeks with our friend Dale, visit Canberra to collect our identity cards, and then leave. At some point in the first two weeks, the constant sunshine and beach life changed our minds and we decided to buy a campervan in which we would live and work while we travelled some of the East coast. I guess it was easy to fall in love with this lifestyle! Almost as soon as we decided this we were lucky enough to land our second freelance job. We were recommended as reputable developers by a mutual friend which resulted in a contract for three months work. This contract was another perfect fit for us; the client had an idea and wanted us to architect, , and build the product. Another job meant we would need to have power and internet available (despite still living like hippies)! design We found a van with solar power so we could charge our laptops (and a fridge to keep the beer cold) and solved the internet problem by splashing out on a SIM card with 40GB of data. Our first coffee in our home on wheels! We drove and worked our way from Sydney to Adelaide, back to Sydney, up to Brisbane, and back to Sydney again. The route was a little weird, but we didn’t want to drive all the way to Perth and our visa meant we could only stay for 3 months at a time. The wifi in Australia was not great. Outside of the big cities we struggled to find places to work but our SIM cards were fantastic. With the sun charging everything for us we were able to work from our van most days using our 4G. With the exception of the terrible wifi, the public services in Australia are incredible. Every beach and park has clean toilets and showers (some of them even have hot water but a cold shower is often welcome), BBQ’s, seating areas, and drinking water stations. I despise camping so I was surprised how much I loved living in a van — I think the facilities and weather were huge factors in this! Gotta work where you can We worked when and where we could, often sitting outside the van or using picnic tables at campsites. On long drives whoever wasn’t driving would usually try and get some work done, at least until our laptops overheated in the non air conditioned cab! Living and working in a car After 3 months our visa was up and we had to leave Australia. As we were so close to New Zealand we decided it would be the perfect time to visit. With our new found love for van life we hired a campervan. However, we didn’t have an equally amazing time… The internet was practically non-existent even with expensive local SIM cards we were without signal for days at a time. This was frustrating as we were trying to work, but luckily the project was coming to an end and we were able to put on the finishing touches without good wifi. Our van, (which was basically a family car with a mattress in the back) was one of the cheapest rentals we could find. Despite this it still put us way over budget — at the time of writing NZ is the most expensive country we’ve visited. Even though we were trying to save money our daily expenditure doubled our budget to €100 a day. A bit colder than we’d like | Queenstown was beautiful We really enjoyed visiting New Zealand and we did some amazing things; took our first helicopter ride to hike a glacier, white water rafted the highest waterfall, bathed in hot springs, and visited the wettest place on the planet. However, though the landscapes were absolutely breathtaking at every turn, we visited at the wrong time of year — it was cold and the days were short. Van life is no fun when you’re freezing, damp, and in the dark! First time in a helicopter! | First time hiking a glacier! Back to Europe Whilst we had been away our friends had been busy. We were invited to four weddings in the summer! I would never have missed my two best friends’ weddings, and luckily for us they were only a week apart (though unfortunately 850km apart too). We were also seriously starting to miss Europe after 18 months away and decided this was a perfect chance to spend the whole summer there. We spent one more month in Australia which we ended with a scuba diving liveaboard in Cairns on the Great Barrier Reef, and then started our journey back West. To round off our time in the east we spent a few last days in Bangkok, where it all began. It also meant we could avoid spending an entire 24 hours on a flight back from Sydney 😅 Berlin is one of our favourite European cities, and we have visited several times but only in winter — and Berlin winters are brutal! We wanted a travel break had some client work to finish off so we decided to spend a couple of months there. We spent a month in Neukölln and a month in Wedding — two of our favourite districts. For the first time working on the road we tried out a co-working space. It was a novelty for the first few days, but we found it too much like getting up and going to an office — we even brought our own lunch a couple of times! We confirmed our suspicions that we prefer a constant change of environment to stay productive. We have a couple of friends from the UK who live in Berlin and when we weren’t working we did a lot of eating and drinking! Berlin has a reputation for fantastic all night (or all weekend), parties, but there is also an incredible bar scene if you’re not a club person. I love the music in Berlin (mostly techno and deep house) but in our 2 months we only went to one club and I am still not sure if I felt cool for getting home at 10am, or like an idiot. Especially after suffering through the 3-day hangover. Park BBQs, lots of kicker, and touristing! Four weddings and no funerals Our journey back to the UK for the first time in 18 months was less than smooth. Our flight was delayed by long enough that when we landed in London the car rental shop was closed and we had to sleep on the floor of their office until they opened! It took us longer to get from Germany to the UK than our flight from Bangkok to Berlin. A typical Ryanair experience, but we just can’t resist the prices! Thankfully we had finished all our client work and were free for the summer. This was perfect because it required meticulous planning (obviously by me) to ensure we could see all of our family and friends and attend all the weddings without backtracking and covering the same ground. Finding the maker community Even travelling and working as a couple can be a lonely experience. Hostels always look so amazing with a beautiful pool and cheap bar etc, but they are almost always more expensive than an entire apartment on or a local hotel. Plus, when you have to work the next day you don’t want to sleep in a bunk bed and drink shots until 5am. Airbnb Sometimes it’s difficult to find people who share the same interests as us. We are never short of backpacker friends and drinking buddies but it’s rare to find long term travellers and fellow developers. James had seen a new community on Twitter called Makerlog. He wanted to be more accountable for development tasks and needed help seeing a product through to the end rather than continually jumping between new ideas. Makerlog looked like the perfect place to do this, so he joined the Slack and our journey into the maker community had begun! Lacking fellow female developer support and communication I joined a community on Telegram I had just discovered called Women Make. Both of us found everyone super friendly and supportive and we joked that we had our own groups of online friends now. Joining these groups made us both realise how much we relied solely on each other for emotional support, encouragement, and feedback. It was suddenly really obvious that if we could get some of that support elsewhere it would benefit our business, and potentially our relationship. Being held accountable and having friends ask how we were getting on was a big motivator for building our products. It was also great to be a part of such a diverse community of people, with experience in a wide range of topics, all helping each other. James already used Twitter but we both started to become more active. I thought there were some barriers — such as unwritten rules and expected etiquette, but I soon realised that I just needed to be myself. 24 hour startup challenge There was this crazy idea circulating Twitter called the 24 hour startup challenge. was the man behind it. After he decided to encourage some other makers to do the same thing. Pat Walls building and launching a product live on stream in 24 hours As something completely out of our comfort zones we immediately . Disclaimer, I took a LOT of encouragement and secretly hoped our internet would not be good enough for me to take part. signed up Committing to the 24 hour startup challenge was a really big deal for both of us. I regularly struggle with imposter syndrome. The idea that everyone would see how little I really know and how terrible I am at coding, live on stream, was my idea of hell. James was not as stressed as me, but as an introvert, he was concerned about how he would talk through his problems and explain what he was doing while streaming to keep it interesting for viewers. Most of the time I am an extrovert, so babbling about my code was one thing I was not worried about! Our biggest challenge for the streaming was finding a good enough internet connection. We would be taking part from Salta, Argentina. We had been staying in a shared house but thought it would be best to have our own apartment and internet connection. I booked an Airbnb but I failed to notice that the property didn’t list wifi as one of the facilities… The day before the stream we went to our new place for all of 30 minutes before realising there was no wifi. Panicking about not being able to participate we spoke to our previous host and luckily we were able stay there another couple of nights. The accommodation shenanigans meant we had wasted a good chunk of our day for preparation and I was even more stressed. Stream day was incredible. There was no reason for weeks of nerves as it wasn’t at all scary and was actually really fun! With a couple of hundred other people taking part I wasn’t sure if we would get any viewers but the audience was super supportive. It was incredible to have people watch us build our product and provide help and encouragement. I am a developer who needs to talk through code problems, often known as “rubber duck debugging”, which is often frustrating for James when he’s trying to focus. Coding on stream was a perfect solution as the audience (or just the camera) made excellent rubber ducks! Our internet was not stable enough to support us two streams so we used just one laptop and sat next to each other so any viewers would be able to hear us both. We also switched laptops a few times so everyone would get to chance to see each of our faces! We managed about 18 hours of coding before our eyes started giving up on us and we crashed. Unfortunately, we didn’t manage to finish or launch our startup, our idea was incredibly ambitious to build in 24 hours, but we were very happy with the results! Imposter syndrome Taking part in that challenge was so far out of my comfort zone it could have been on another planet. I attempted to lower my stress levels by preparing as much as I could (as much as was allowed in the rules). I researched the tools we would be using, estimated the core tasks, and planned what we would be doing each hour. In the first few hours the app took shape relatively quickly which helped push the imposter syndrome out of the way as I was able to see results. This is a theme I see in my everyday coding — if I am unable to complete a task within my time estimate then this is when the doubt about my abilities starts creeping in. I am attempting to solve this by measuring how much I get done in a larger period of time, such as a week, rather than agonising over a 2 hour task taking 4 hours — I’ll let you know how this goes! James managed to talk a lot more than he expected while coding, but this contributed a lot to his tiredness and fatigue. If there was a particularly difficult problem he did tend to go quiet for an hour or so while he worked through it. I don’t think this is necessarily an introvert issue, but something which would become easier to do with more live streaming practice. Self-improvement cannot be made without action. A lot has changed in a year and I am continuously working on pushing myself out of my comfort zone every day. Currently, I am trying to say yes to podcasts and interviews, because “doing it live” is something which scares me. Participating in the 24 hour startup challenge would not have happened if we hadn’t found the maker community. We are incredibly thankful to have discovered a group of such friendly, supportive, and wonderful friends all around the world. Making our first $5 After the failure of our first startup, we had been sustaining our travels with client work but we hadn’t given up making stuff! We launched our first native Mac app — a menu bar app to get notifications when your websites go down. People bought it! When we made that first $5 it was such an incredible feeling. We felt like we were finally on the right path. UptimeBar UptimeBar wasn’t super successful but we made a couple of hundred dollars and learned a lot of important lessons; build products which solve your own problems, build and ship an MVP for validation, and be open. This was the first of our products to be an open startup with a super basic and we got a lot of positive feedback about sharing these stats. open page This small success gave us the motivation to keep on building and we decided we wanted to be even more open and share more stats than just revenue (if we had any!) for our next startup. A possible winner Sticking to solving our own problems our next project was — a service to easily unsubscribe from spam emails with a focus on privacy. We were both spending so much time sorting through our emails we went searching for a service which would help us find and unsubscribe from ones we didn’t want. Leave Me Alone We found a few which would help us for free, but a closer look revealed that they didn’t charge for their service because they were selling all of your data for marketing. Faced with the dilemma of a messy inbox or all of our data being exploited, we decided to build our own solution, and Leave Me Alone was born! We took a new approach to building this startup by and were delighted to start seeing some success. We released to beta users first, who gave us lots of great feedback and within a few iterations, we had something ready for the wild. being completely open Just before Christmas we soft launched Leave Me Alone on social media and to the maker community. The feedback was incredibly positive. It had taken us nearly 2 years but we hoped we had finally built something that people wanted and were willing to pay for. Side project side projects With a long stay booked in Cusco for Christmas and New Year we had a bunch of free time. James built — an unobtrusive ad network for makers. There were discussions in the maker community about wanting to monetise their products with advertising, but not wanting to show visitors irrelevant or ugly ads served from big bad corporations. MakerAds MakerAds is a network of adverts by makers, and free for makers. James offers sponsored ad spots and plans to add categories in the future to allow sites to further specify what type of advert they want to show. Inspired by a I built my first Chrome extension — to fix accidental clicks on #hashtags in the Twitter search results. I had a great evening learning something new and I even added support for Firefox! Tweet from Ben Tossell Twitter Search Fixer Sadly Twitter recently updated their web app and my extension no longer works on the new version. They are slowly inviting people to try it but neither of us have been able to yet so I can’t fix it. Twitter Search Fixer is completely free and so if you have the new Twitter and want to help out please feel free! open source A new client for the New Year We were starting to run low on money. When we flew to South America in October we agreed that if we dipped below €5,000 without having client work we would fly have to back to Europe and contract or find a job. Obviously, we didn’t want to do this but historically neither of us has had much success finding work on freelance websites such as Freelancer and Upwork. Applying is a big time investment and the competition for job postings is too high and the quality of clients is too low. We looked for better places to find work and found . The quality of developers and clients is much higher. The platform is built by two nomads Emma and Philip who encountered the same problems as us when they were trying to find work while travelling. We love their approach of getting to know their customers and they have reached out to us several times for feedback or to recommend jobs specific to our skills. Moonlight It was a dream to apply to jobs with proper specifications and upfront expectations. It wasn’t long before we found a great client and project which set us up with 3 months work and meant we could keep travelling for a while longer yet — phew! After spending Christmas in the cold and at altitude we were in desperate need of sun, sea, and sand… Onwards to the equator! Merry Christmas… and a Happy New year from Cusco! Our 2018 in review Disclaimer: Some of the links are affiliate links, meaning at no additional cost to you, I might earn commission if you click through and signup or make a purchase. This article is the second in a three part series. Find the first one . The final part will be linked here when published. here Originally published at makermag.com on February 19, 2019.

A Couple of Nomad Makers: finding friends and side project profits

If an individual is sleep deprived, at what minimum can certain functions continue without getting any sleep? If someone sees something from a distance, but it is just clear enough to be roughly interpreted by the mind in terms of kind, but not specificity, is there an input configuration requirement to guarantee an optimum interpretation of the external world by the human mind? If functions are continuously operating at minimums, could there be a likelihood that some of the factors responsible for optimum outputs may start getting the message that they are no longer necessary? If this is the case, could it cascade into a serious condition? Neurons are known to have around 50 billion proteins. Protein misfolding has been established as a major cause of some neurodegenerative diseases. A possible reason for protein misfolding has been identified as [cellular] environmental stress. A theoretical basis for why environmental stress may be responsible could be to look at working minimums and maximums, for functions, over certain intervals. Theorizing protein folding requires a top-down approach, which means that there is a source for which problems might arise, resulting--eventually--in misfolding and degenerative diseases. The closest destination for the top option is the electrical and chemical signals of neurons. It is theorized that the human mind is responsible for all functions that the brain is said to do. The human mind is the collection of all the electrical and chemical signals, with their interactions and features, in sets, in clusters of neurons, across the central and peripheral nervous system. This means that the human mind is the signals with their interactions and features. All the configurations for which representations and interpretations are based, for interoception and exteroception, have just one possible option in the brain, the signals, not genes, proteins, neurons, or other types of cells. This means that whatever is interpreted, accurately or not, or seems represented, accurately or not, is a result of the signals, such that with signals, interpretations, and features, in sets, are at the top, though their work has implications for other cells in the body, and several other molecules, especially proteins, abundant in neurons. Why? Exercise, for example, is an activity where electrical and chemical signals are interacting actively, with varying features applying. This top activity results in relays of electrical signals that, conceptually, for interactions with chemical signals, in sets, have an effect on other parts of the body. Simply, electrical and chemical signals are involved in every function. The consequences of those functions can also be seen elsewhere. Proteins, Neurons, and Signals Since neurons are not the human mind, or their proteins, because they do not organize information, it can be theorized that as neurons are involved in clusters, with sets of signals, their proteins assist several interactive processes between electrical and chemical signals. This indicates that when there are extended minimums or maximums, in sets of signals, there are ways that they come to have an effect on some of the proteins of the neurons involved in respective clusters [hence environmental stress]. Simply, neurons have proteins, and these proteins contribute to the primary role of signals, but as signals carry out their roles, depending on the pace or direction, they come to also have effects on the protein of some neurons, which may work more or work less, over an interval, which may, for some cases lead to misfolding, and then accumulations and disease, conceptually. It means that the mechanisms of signals can have an effect, conceptually, on the misfolding of proteins, then possibly developing into a degenerative disease for some. Tracking Possible Paths for Protein Misfolding From Signals It is possible to develop a number of minimums, maximums, and interactive-feature stretches of signals, with an exploration of how, for some people with Amyloidosis, that may have resulted from cellular [environmental] stress, to look at the roles that signals played. The interaction of signals is the way electrical signals strike at chemical signals, while the features are some of the states of the signals, in sets, at the times of the interactions. If a person drinks cold water but does not feel it as cold, why did the signals not give the experience of cold? There are several examples like this, but what can be looked at is the intensity of certain experiences or the longevity of others, which may have caused the larger protein folding error. Theorizing why proteins misfold may have to center around the major functional operators the electrical and chemical signals, which can then be sought, as the source toward reversal or prevention. There is a recent story in Nature, AI protein-prediction tool AlphaFold3 is now open source, stating that, "AlphaFold3, unlike its predecessors, is capable of modelling proteins in concert with other molecules. But instead of releasing its underlying code — as was done with AlphaFold2 — DeepMind provided access via a web server that restricted the number and types of predictions scientists could make. Crucially, the AlphaFold3 server prevented scientists from predicting how proteins behave in the presence of potential drugs. But now, DeepMind’s decision to release the code means academic scientists can predict such interactions by running the model themselves. The company initially said that making AlphaFold3 available only through a web server struck the right balance between enabling access for research and protecting commercial ambitions. Isomorphic Labs, a DeepMind spinoff company in London, is applying AlphaFold3 to drug discovery." There is a recent press release, Argonne team breaks new ground in AI-driven protein design, stating that, "Harnessing the power of artificial intelligence (AI) and the world’s fastest supercomputers, a research team led by the U.S. Department of Energy’s (DOE) Argonne National Laboratory has developed an innovative computing framework to speed up the design of new proteins. On the heels of this year’s Nobel Prize in Chemistry, which recognized advances in computational protein design, Argonne’s AI-driven approach has been selected as a finalist for the prestigious Gordon Bell Prize. Presented by the Association of Computing Machinery, the annual prize recognizes breakthroughs in using high performance computing to solve complex science problems. Mapping a protein’s amino acid sequence to its structure and function is a long-standing research challenge. Each unique arrangement of amino acids — the building blocks of proteins — can yield different properties and behaviors. The sheer volume of potential variations makes it impractical to test them all through experiments alone. To put this in perspective, modifying just three amino acids in a sequence of 20 creates 8,000 possible combinations. But most proteins are far more complex, with some research targets containing hundreds to thousands of amino acids." If an individual is sleep deprived, at what minimum can certain functions continue without getting any sleep? If someone sees something from a distance, but it is just clear enough to be roughly interpreted by the mind in terms of kind, but not specificity, is there an input configuration requirement to guarantee an optimum interpretation of the external world by the human mind? If functions are continuously operating at minimums, could there be a likelihood that some of the factors responsible for optimum outputs may start getting the message that they are no longer necessary? If this is the case, could it cascade into a serious condition? Neurons are known to have around 50 billion proteins . Protein misfolding has been established as a major cause of some neurodegenerative diseases . A possible reason for protein misfolding has been identified as [cellular] environmental stress . A theoretical basis for why environmental stress may be responsible could be to look at working minimums and maximums, for functions, over certain intervals. have around 50 billion proteins major cause of some neurodegenerative diseases as [cellular] environmental stress Theorizing protein folding requires a top-down approach, which means that there is a source for which problems might arise, resulting--eventually--in misfolding and degenerative diseases. The closest destination for the top option is the electrical and chemical signals of neurons. It is theorized that the human mind is responsible for all functions that the brain is said to do. The human mind is the collection of all the electrical and chemical signals, with their interactions and features, in sets, in clusters of neurons, across the central and peripheral nervous system. This means that the human mind is the signals with their interactions and features. All the configurations for which representations and interpretations are based, for interoception and exteroception, have just one possible option in the brain, the signals, not genes, proteins, neurons, or other types of cells. This means that whatever is interpreted, accurately or not, or seems represented, accurately or not, is a result of the signals, such that with signals, interpretations, and features, in sets, are at the top, though their work has implications for other cells in the body, and several other molecules, especially proteins, abundant in neurons. Why? Exercise, for example, is an activity where electrical and chemical signals are interacting actively, with varying features applying. This top activity results in relays of electrical signals that, conceptually, for interactions with chemical signals, in sets, have an effect on other parts of the body. Simply, electrical and chemical signals are involved in every function. The consequences of those functions can also be seen elsewhere. Proteins, Neurons, and Signals Since neurons are not the human mind, or their proteins, because they do not organize information, it can be theorized that as neurons are involved in clusters, with sets of signals, their proteins assist several interactive processes between electrical and chemical signals. This indicates that when there are extended minimums or maximums, in sets of signals, there are ways that they come to have an effect on some of the proteins of the neurons involved in respective clusters [hence environmental stress]. Simply, neurons have proteins, and these proteins contribute to the primary role of signals, but as signals carry out their roles, depending on the pace or direction, they come to also have effects on the protein of some neurons, which may work more or work less, over an interval, which may, for some cases lead to misfolding, and then accumulations and disease, conceptually. It means that the mechanisms of signals can have an effect, conceptually, on the misfolding of proteins, then possibly developing into a degenerative disease for some. Tracking Possible Paths for Protein Misfolding From Signals It is possible to develop a number of minimums, maximums, and interactive-feature stretches of signals, with an exploration of how, for some people with Amyloidosis, that may have resulted from cellular [environmental] stress, to look at the roles that signals played. The interaction of signals is the way electrical signals strike at chemical signals , while the features are some of the states of the signals, in sets, at the times of the interactions. If a person drinks cold water but does not feel it as cold, why did the signals not give the experience of cold? There are several examples like this, but what can be looked at is the intensity of certain experiences or the longevity of others, which may have caused the larger protein folding error. The interaction of signals is the way electrical signals strike at chemical signals Theorizing why proteins misfold may have to center around the major functional operators the electrical and chemical signals, which can then be sought, as the source toward reversal or prevention. There is a recent story in Nature , AI protein-prediction tool AlphaFold3 is now open source , stating that, "AlphaFold3, unlike its predecessors, is capable of modelling proteins in concert with other molecules. But instead of releasing its underlying code — as was done with AlphaFold2 — DeepMind provided access via a web server that restricted the number and types of predictions scientists could make. Crucially, the AlphaFold3 server prevented scientists from predicting how proteins behave in the presence of potential drugs. But now, DeepMind’s decision to release the code means academic scientists can predict such interactions by running the model themselves. The company initially said that making AlphaFold3 available only through a web server struck the right balance between enabling access for research and protecting commercial ambitions. Isomorphic Labs, a DeepMind spinoff company in London, is applying AlphaFold3 to drug discovery." Nature AI protein-prediction tool AlphaFold3 is now open source There is a recent press release, Argonne team breaks new ground in AI-driven protein design , stating that, "Harnessing the power of artificial intelligence (AI) and the world’s fastest supercomputers, a research team led by the U.S. Department of Energy’s (DOE) Argonne National Laboratory has developed an innovative computing framework to speed up the design of new proteins. On the heels of this year’s Nobel Prize in Chemistry, which recognized advances in computational protein design, Argonne’s AI-driven approach has been selected as a finalist for the prestigious Gordon Bell Prize. Presented by the Association of Computing Machinery, the annual prize recognizes breakthroughs in using high performance computing to solve complex science problems. Mapping a protein’s amino acid sequence to its structure and function is a long-standing research challenge. Each unique arrangement of amino acids — the building blocks of proteins — can yield different properties and behaviors. The sheer volume of potential variations makes it impractical to test them all through experiments alone. To put this in perspective, modifying just three amino acids in a sequence of 20 creates 8,000 possible combinations. But most proteins are far more complex, with some research targets containing hundreds to thousands of amino acids." Argonne team breaks new ground in AI-driven protein design

AlphaFold 3: How Does Proteins Misfolding Cause Neurodegenerative Diseases?

If the purpose is to understand how the the brain works, where in the brain is physicalism? Or, where in the brain is dualism? What part of the brain is materialism? How has the philosophy of mind defined the human mind, exactly for components within the cranium? There would have been eras that physicalism, dualism, materialism, panpsychism and several other philosophical takes may have held court with descriptions of how the mind or body worked, but with advances in neuroscience, there is little to no fit for their expressions. There are currently difficult problems of the mind like substance abuse, gambling addiction, mental disorders, and more. These are not problems that need more labels, but problems that, at minimum, any theory should state how the mind is operational while they are in effect and what could be done against their tides. Even within neuroscience, how the brain works is simply not neurons, neural circuits, or a population of neuronsbecause if a cluster of neurons mechanizes a function, what exactly is the cluster doing that another cluster is not? If it is stated that it is yet to be understood, then what theory of neural circuit has expressed why a [neurons] group specializes in a function? Neurons are not like changing. Neurons are close to solid [physical] forms, so it is unlikely that they are getting shaped in one direction that would indicate why they interpret a smell differently from the next, or a smell from a sound. Simply, neurons are not having direct anatomic changes to ensure a function, in contrast to another function. Even with synapses, when strong or weak, what must be definitive in every synapse? Assuming the philosophy of mind had looked closely at clusters of neurons in the last century to base many of its takes, maybe it would have been ahead of science. So far, philosophy of mind is no longer ahead of neuroscience and may not even be much linked anymore, since the philosophy chooses what it wants but the science is vacant for an advance within the cranium. The closest options to what the mind is and how the mind works is theorized to be the electrical and chemical signals of nerve cells, in sets, in clusters of neurons. It is the configuration of the signals, their interactions, and features that could be zeroed in on for how the human mind works. There is no function of neurons—for the mind—that signals are not involved in. There is no synapse—chemical or electrical—that is absent of signals. Genes are not the human mind. The environment is not the human mind. Neurons are not the human mind. Elementary particles of physics are not the human mind. Neuroglia are not the human mind as well. To answer questions about the human mind is to seek out what the mind might be in the cranium, not stray juxtapositions that, no matter how cutely described, cannot even answer for mental disorders, in the same mind for which several consciousness or philosophical stretches should define. To properly evaluate any consciousness theory or philosophical theory of mind, questions—on what the mind is [in the cranium, not the mind of the universe], how it works distinctively and how it may explain or suggest solutions to mind problems—should be sought, not generalized neuroimaging, adversarial collaboration or vague correlates. It is like trying to understand how human memory works, with mentions of long-term, short-term and others, without naming relays across memory destinations or if the configuration of any memory is different from an emotion or a feeling, or the exact forms for which memories are associated. There is a new book featured on The Transmitter, How did consciousness evolve? An excerpt from ‘A History of Bodies, Brains, and Minds: The Evolution of Life and Consciousness’, stating that, "However, life is a scientifically observable phenomenon, while our subjective experiences are not accessible to third parties. Furthermore, for conscious subjects, their own life is an experiential phenomenon as well. One alternative to get away from the mind-body conundrum has been pan-psychism, which is an extension of the identity hypothesis, proposing that some degree of consciousness is a feature of the universe like energy or gravity are. Some other researchers, particularly physicists, have moved much farther, proposing that the source of consciousness relies on quantum mechanics. In this view, quantal superpositions of states in elementary particles would collapse wave functions into (proto-) moments of experience composed of basic qualia, the fundamental ‘particles’ of consciousness. However, despite the apparent relation between consciousness and complexity, how material mechanisms become transformed into a first-person qualitative experience poses a major problem for neuroscientific research, which is conceived to deal with second-person observable phenomena. Because the unobservable nature of subjective states by second parties severely limits their scientific study, some have decided to downplay them as an irrelevant illusion generated by our complex brain networks. Whether consciousness is or is not relevant for our decisions and behavior is a debatable issue, but the illusion argument does not really explain to me how subjectivity is in fact produced." There is a recent paper in Nature, Neural populations in the language network differ in the size of their temporal receptive windows, stating that, "Despite long knowing what brain areas support language comprehension, our knowledge of the neural computations that these frontal and temporal regions implement remains limited. One important unresolved question concerns functional differences among the neural populations that comprise the language network. Neural populations exhibiting these profiles are interleaved across the language network, which suggests that all language regions have direct access to distinct, multiscale representations of linguistic input—a property that may be critical for the efficiency and robustness of language processing." If the purpose is to understand how the the brain works, where in the brain is physicalism? Or, where in the brain is dualism? What part of the brain is materialism? How has the philosophy of mind defined the human mind, exactly for components within the cranium? There would have been eras that physicalism, dualism, materialism, panpsychism and several other philosophical takes may have held court with descriptions of how the mind or body worked, but with advances in neuroscience, there is little to no fit for their expressions. There are currently difficult problems of the mind like substance abuse, gambling addiction, mental disorders, and more. These are not problems that need more labels, but problems that, at minimum, any theory should state how the mind is operational while they are in effect and what could be done against their tides. Even within neuroscience, how the brain works is simply not neurons, neural circuits, or a population of neurons because if a cluster of neurons mechanizes a function, what exactly is the cluster doing that another cluster is not? how the brain works is simply not neurons, neural circuits, or a population of neurons If it is stated that it is yet to be understood, then what theory of neural circuit has expressed why a [neurons] group specializes in a function? Neurons are not like changing. Neurons are close to solid [physical] forms, so it is unlikely that they are getting shaped in one direction that would indicate why they interpret a smell differently from the next, or a smell from a sound. Simply, neurons are not having direct anatomic changes to ensure a function, in contrast to another function. Even with synapses, when strong or weak, what must be definitive in every synapse? Assuming the philosophy of mind had looked closely at clusters of neurons in the last century to base many of its takes, maybe it would have been ahead of science. So far, philosophy of mind is no longer ahead of neuroscience and may not even be much linked anymore, since the philosophy chooses what it wants but the science is vacant for an advance within the cranium. The closest options to what the mind is and how the mind works is theorized to be the electrical and chemical signals of nerve cells, in sets, in clusters of neurons. It is the configuration of the signals, their interactions, and features that could be zeroed in on for how the human mind works. There is no function of neurons—for the mind—that signals are not involved in. There is no synapse—chemical or electrical—that is absent of signals. Genes are not the human mind . The environment is not the human mind. Neurons are not the human mind. Elementary particles of physics are not the human mind. Neuroglia are not the human mind as well. Genes are not the human mind To answer questions about the human mind is to seek out what the mind might be in the cranium, not stray juxtapositions that, no matter how cutely described, cannot even answer for mental disorders, in the same mind for which several consciousness or philosophical stretches should define. To properly evaluate any consciousness theory or philosophical theory of mind, questions—on what the mind is [in the cranium, not the mind of the universe], how it works distinctively and how it may explain or suggest solutions to mind problems—should be sought, not generalized neuroimaging, adversarial collaboration or vague correlates. It is like trying to understand how human memory works, with mentions of long-term, short-term and others, without naming relays across memory destinations or if the configuration of any memory is different from an emotion or a feeling, or the exact forms for which memories are associated. There is a new book featured on The Transmitter , How did consciousness evolve? An excerpt from ‘A History of Bodies, Brains, and Minds: The Evolution of Life and Consciousness’ , stating that, "However, life is a scientifically observable phenomenon, while our subjective experiences are not accessible to third parties. Furthermore, for conscious subjects, their own life is an experiential phenomenon as well. One alternative to get away from the mind-body conundrum has been pan-psychism, which is an extension of the identity hypothesis, proposing that some degree of consciousness is a feature of the universe like energy or gravity are. Some other researchers, particularly physicists, have moved much farther, proposing that the source of consciousness relies on quantum mechanics. In this view, quantal superpositions of states in elementary particles would collapse wave functions into (proto-) moments of experience composed of basic qualia, the fundamental ‘particles’ of consciousness. However, despite the apparent relation between consciousness and complexity, how material mechanisms become transformed into a first-person qualitative experience poses a major problem for neuroscientific research, which is conceived to deal with second-person observable phenomena. Because the unobservable nature of subjective states by second parties severely limits their scientific study, some have decided to downplay them as an irrelevant illusion generated by our complex brain networks. Whether consciousness is or is not relevant for our decisions and behavior is a debatable issue, but the illusion argument does not really explain to me how subjectivity is in fact produced." The Transmitter How did consciousness evolve? An excerpt from ‘A History of Bodies, Brains, and Minds: The Evolution of Life and Consciousness’ There is a recent paper in Nature , Neural populations in the language network differ in the size of their temporal receptive windows , stating that, "Despite long knowing what brain areas support language comprehension, our knowledge of the neural computations that these frontal and temporal regions implement remains limited. One important unresolved question concerns functional differences among the neural populations that comprise the language network. Neural populations exhibiting these profiles are interleaved across the language network, which suggests that all language regions have direct access to distinct, multiscale representations of linguistic input—a property that may be critical for the efficiency and robustness of language processing." Nature Neural populations in the language network differ in the size of their temporal receptive windows

Consciousness: Why Philosophy of Mind May No Longer Be Relevant to Neuroscience

**LONDON, United Kingdom, August 9th, 2024/Chainwire/--**NeurochainAI, a decentralized AI-as-a-Service (DeAIAS) network, today launched its Token Generation Event (TGE) with its $NCN token becoming available for trading at 12 pm UTC on two centralized exchanges, Gate.io  and WhiteBIT, with listings on additional CEXs to be announced in the near future. With over 150,000 users already onboard and more than 80,000 wallets connected to the platform, NeurochainAI is swiftly establishing itself as a leader in the DeAIAS space that also covers a reliable DePIN for AI Inference. To further enhance user experience and accessibility, NeurochainAI has rolled out a beta version of its mobile app for AI inference. The beta app is already being tested by over 3,000 users across 183 countries, reflecting the global demand and anticipation for NeurochainAI's innovative solutions. The TGE marks the official launch of NeurochainAI’s $NCN token, with the project committed to a fair launch strategy by listing directly on centralized exchanges (CEXs), ensuring equal access and better terms for everyone. As a part of the strategy, the community also has the opportunity to earn NCN by connecting GPUs and participating in data tasks for extended periods of time. With a strong reputation in the industry and over 10 million users, Gate.io boasts a daily trading volume that exceeds $12 billion. WhiteBIT stands out as a top choice for crypto enthusiasts with impressive trading volumes and over 4 million users from 150 countries. The token launch will be immediately followed by the introduction of node staking, an initiative aimed at fostering network decentralization with a fair way to grow a validator network. The approach mirrors industry best practices, ensuring transparency with rewards known upfront, decentralization as the same stake applies to all nodes, and a fair chance for all to participate on a first come, first serve basis. “We're focused on creating a TGE and node staking that makes fairness and transparency a central goal, ” said Julius Serenas, CEO of NeurochainAI. “Our fair launch approach ensures all participants have the opportunity to partake in the NeurochainAI ecosystem, promoting network decentralization and community-driven growth in the AI-as-a-Service space." Operating a Neuron Validator not only contributes to the ecosystem’s decentralization but also rewards participants with daily $NCN compensation, where a stable amount of native coins must be staked to become a validator. 40% of the $NCN supply will be allocated to Neuron Validator NFTs, with a structured vesting plan designed to incentivize long-term engagement. To learn more about NeurochainAI’s node staking opportunities and becoming a Neuron Validator, visit their guide here. About NeurochainAI NeurochainAI is a decentralized AI-as-a-Service (DeAIAS) network that streamlines the process of building, launching, and use of AI-powered decentralized applications (dApps). Providing a ready-to-use AI infrastructure, the network enables developers to create AI dApps up to 24 times faster and 5 times more cost-effectively compared to traditional methods. The platform is focused on advancing the field of AI application development, offering unparalleled ease of use and affordability. Website | x | Telegram | Discord | Linkedin | Medium Contact COO Odeta Iseviciute odeta@neurochain.ai This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **LONDON, United Kingdom, August 9th, 2024/Chainwire/--**NeurochainAI, a decentralized AI-as-a-Service (DeAIAS) network, today launched its Token Generation Event (TGE) with its $NCN token becoming available for trading at 12 pm UTC on two centralized exchanges, Gate.io  and WhiteBIT, with listings on additional CEXs to be announced in the near future. With over 150,000 users already onboard and more than 80,000 wallets connected to the platform, NeurochainAI is swiftly establishing itself as a leader in the DeAIAS space that also covers a reliable DePIN for AI Inference. To further enhance user experience and accessibility, NeurochainAI has rolled out a beta version of its mobile app for AI inference. The beta app is already being tested by over 3,000 users across 183 countries, reflecting the global demand and anticipation for NeurochainAI's innovative solutions. The TGE marks the official launch of NeurochainAI’s $NCN token, with the project committed to a fair launch strategy by listing directly on centralized exchanges (CEXs), ensuring equal access and better terms for everyone. As a part of the strategy, the community also has the opportunity to earn NCN by connecting GPUs and participating in data tasks for extended periods of time. With a strong reputation in the industry and over 10 million users, Gate.io boasts a daily trading volume that exceeds $12 billion. WhiteBIT stands out as a top choice for crypto enthusiasts with impressive trading volumes and over 4 million users from 150 countries. The token launch will be immediately followed by the introduction of node staking, an initiative aimed at fostering network decentralization with a fair way to grow a validator network. The approach mirrors industry best practices, ensuring transparency with rewards known upfront, decentralization as the same stake applies to all nodes, and a fair chance for all to participate on a first come, first serve basis. “We're focused on creating a TGE and node staking that makes fairness and transparency a central goal, ” said Julius Serenas, CEO of NeurochainAI. “Our fair launch approach ensures all participants have the opportunity to partake in the NeurochainAI ecosystem, promoting network decentralization and community-driven growth in the AI-as-a-Service space." “We're focused on creating a TGE and node staking that makes fairness and transparency a central goal, ” said Julius Serenas, CEO of NeurochainAI. “Our fair launch approach ensures all participants have the opportunity to partake in the NeurochainAI ecosystem, promoting network decentralization and community-driven growth in the AI-as-a-Service space." Operating a Neuron Validator not only contributes to the ecosystem’s decentralization but also rewards participants with daily $NCN compensation, where a stable amount of native coins must be staked to become a validator. 40% of the $NCN supply will be allocated to Neuron Validator NFTs, with a structured vesting plan designed to incentivize long-term engagement. To learn more about NeurochainAI’s node staking opportunities and becoming a Neuron Validator, visit their guide here . here here About NeurochainAI NeurochainAI is a decentralized AI-as-a-Service (DeAIAS) network that streamlines the process of building, launching, and use of AI-powered decentralized applications (dApps). Providing a ready-to-use AI infrastructure, the network enables developers to create AI dApps up to 24 times faster and 5 times more cost-effectively compared to traditional methods. The platform is focused on advancing the field of AI application development, offering unparalleled ease of use and affordability. Website | x | Telegram | Discord | Linkedin | Medium Website Website x x Telegram Telegram Discord Discord Linkedin Linkedin Medium Medium Contact COO Odeta Iseviciute odeta@neurochain.ai This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

NeurochainAI Launches $NCN Token Ahead Of Node Staking

NeurochainAI নোড স্টেকিংয়ের আগে $NCN টোকেন চালু করেছে

NeurochainAI führt $NCN-Token vor Node-Staking ein

NeurochainAI lanza el token $NCN antes del staking de nodos

NeurochainAI lance le jeton $NCN avant le jalonnement des nœuds

न्यूरोचैनएआई ने नोड स्टेकिंग से पहले $NCN टोकन लॉन्च किया

NeurochainAI、ノードステーキングに先立ち$NCNトークンをリリース

NeurochainAI, 노드 스테이킹에 앞서 $NCN 토큰 출시

NeurochainAI lança token $NCN antes do staking de nós

NeurochainAI запускает токен $NCN перед стейкингом узлов

NeurochainAI, Node Staking'den Önce $NCN Token'ını Piyasaya Sürüyor

NeurochainAI ra mắt $NCN Token trước Node Staking

NeurochainAI 在节点质押之前推出 $NCN 代币

If an individual were temporarily infirm, it is possible to assume that most of the memory the individual has might be intact, but the relays to make the memories available may have dipped. This means that memories are not just important, but the relays to make them available. It is possible to define human memory not just by types but by specifications of relays for availability, such that those for reasoning at some point may be different from those from planning or those for learning from those from doing. Simply, outputs from human memory are sometimes a result of reach or relays, not just by the memory present. Relays can also be used to explain how Large language models [LLMs] work. LLMs were trained on vast amounts of internet data. This training can be assumed to be relays. Prompts to and outputs from LLMs can also be assumed to be relays across data. Simply put, LLMs work because they are able to relay predictively, with correct matches for several use cases. Though there are still weaknesses of these relays—like confabulations, hallucinations, slops in generated videos and images, and so forth—the better the relays or math functions that are developed for digital memory, the closer they might come to human intelligence. Artificial general intelligence [AGI] or artificial superintelligence [ASI] could get closer with improved relays across digital memory, in parallel to relays that result in intelligence in the human mind. AGI can be defined as relay equivalents to those in the human mind that define human intelligence. Relays may also make and specify extensions like—levels of control and base subjectivity. The internet already has more information than any individual’s brain. However, AGI may be as good as relays that use the information for similarities to human intelligence, not just the presence of information. This is similar to the human mind, where presence [of memory] does not mean available [in an instance]. The human mind is theorized to have functions and features. Though functions are shaped by relays, features are dominated by relays. Functions can be categorized into memory, feeling, emotion, and modulation of internal senses. Functions have several subcategories including—intelligence, planning, reasoning and so forth. Functional instances are determined by how they are graded or qualified by features. Features are types of relays that bring those functions to use, including their intensities. The human mind is theorized to be the collection of all the electrical and chemical signals with their interactions and features in sets, in clusters of neurons, across the central and peripheral nervous systems. Features [or relays] include pre-/prioritization, old and new sequences, early splits, principal spots, thick/thin sets, volume changes, diameter constant spaces, and others. These relays are postulated to directly mechanize what is learned and experienced. Ranking how close to human intelligence AGI or ASI may come may depend on their parallel relays. AGI would not be a measure of outcomes but a measure of relays since outcomes may be great yet deficient. For example, LLMs are excellent at predictions but lack correction skills and knowledge of consequences. They are cool at several types of pattern-matching but seem to be unidirectional in several outputs, which is not the case for the human mind. Two of several questions about AGI are: Can it have control and subjectivity? In the human mind, control, free will, or intent can be defined as functions that can be intentionally adjusted, like chewing, sitting, turning the neck, and so forth. There are functions that cannot be controlled, like the bronchioles and so forth, at least directly, like speaking, waving, and so on. Subjectivity is attachment, personalization, or self-association, away from detachment, depersonalization, or dissociation. Control [or intent] and subjectivity [or self] are postulated to be mechanized in the same sets of signals that mechanize functions. While control and subjectivity may not be described as standalone functions or information—such that something must often be controlled and there has to be an experience for the self to present—they are also subcategories where relays get to and determine their intensities. It could be possible that rows within high-dimensional vectors become aspects of control, and some columns become aspects of subjectivity. For AGI, control and subjectivity would be data that can be used alone and has to be relayed for availability, unlike with humans. Simply, AGI would use data to control data and use data to have subjectivity, conceptually. Conceptual brain science could be useful in grading LLMs to AGI, becoming another direction for computational and theoretical neuroscience to shape progress in AI. There is a recent editorial in Nature, The new NeuroAI, stating that, "Overall, the extent of the role of neuroscience in AI research, and that of AI in neuroscience research, remain open questions for the future. However, these two fields are deeply linked, and the exchange of ideas between them continues to evolve. The pursuit of more powerful artificial neural systems in leading AI research labs, particularly those affiliated with tech companies, is currently focused on engineering. This pursuit emphasizes further scaling up of complex architectures such as transformers, rather than integrating insights from neuroscience." There is a recent paper in Nature, Reservoir-computing based associative memory and itinerancy for complex dynamical attractors, stating that, "A neural network capable of memorizing and retrieving multiple memory states is also a multifunctional neural network. When different states are recalled, the neural network exhibits distinct dynamical behaviors. The idea of multifunctional RNNs has been discussed previously, along with different forms of implementation. In particular, in the index-based approach, an index parameter is introduced to modulate the functionality of the neural networks and store different states with different index values, but recalling the memorized states was a challenge, for which control may be necessary." If an individual were temporarily infirm, it is possible to assume that most of the memory the individual has might be intact, but the relays to make the memories available may have dipped. This means that memories are not just important, but the relays to make them available. It is possible to define human memory not just by types but by specifications of relays for availability, such that those for reasoning at some point may be different from those from planning or those for learning from those from doing. Simply, outputs from human memory are sometimes a result of reach or relays, not just by the memory present. Relays can also be used to explain how Large language models [LLMs] work. LLMs were trained on vast amounts of internet data. This training can be assumed to be relays. Prompts to and outputs from LLMs can also be assumed to be relays across data. Simply put, LLMs work because they are able to relay predictively, with correct matches for several use cases. Though there are still weaknesses of these relays—like confabulations, hallucinations, slops in generated videos and images, and so forth—the better the relays or math functions that are developed for digital memory, the closer they might come to human intelligence. might come Artificial general intelligence [AGI] or artificial superintelligence [ASI] could get closer with improved relays across digital memory, in parallel to relays that result in intelligence in the human mind. AGI can be defined as relay equivalents to those in the human mind that define human intelligence. Relays may also make and specify extensions like—levels of control and base subjectivity. The internet already has more information than any individual’s brain. However, AGI may be as good as relays that use the information for similarities to human intelligence, not just the presence of information. This is similar to the human mind, where presence [of memory] does not mean available [in an instance]. The human mind is theorized to have functions and features . Though functions are shaped by relays, features are dominated by relays. Functions can be categorized into memory, feeling, emotion, and modulation of internal senses. Functions have several subcategories including—intelligence, planning, reasoning and so forth. Functional instances are determined by how they are graded or qualified by features. Features are types of relays that bring those functions to use, including their intensities. The human mind is theorized to be the collection of all the electrical and chemical signals with their interactions and features in sets, in clusters of neurons, across the central and peripheral nervous systems. theorized to have functions and features electrical and chemical signals with their interactions and features Features [or relays] include pre-/prioritization, old and new sequences, early splits, principal spots, thick/thin sets, volume changes, diameter constant spaces, and others. These relays are postulated to directly mechanize what is learned and experienced. Ranking how close to human intelligence AGI or ASI may come may depend on their parallel relays. AGI would not be a measure of outcomes but a measure of relays since outcomes may be great yet deficient. For example, LLMs are excellent at predictions but lack correction skills and knowledge of consequences. They are cool at several types of pattern-matching but seem to be unidirectional in several outputs, which is not the case for the human mind. Two of several questions about AGI are: Can it have control and subjectivity? In the human mind, control, free will, or intent can be defined as functions that can be intentionally adjusted, like chewing, sitting, turning the neck, and so forth. There are functions that cannot be controlled, like the bronchioles and so forth, at least directly, like speaking, waving, and so on. Subjectivity is attachment, personalization, or self-association, away from detachment, depersonalization, or dissociation. Control [or intent] and subjectivity [or self] are postulated to be mechanized in the same sets of signals that mechanize functions. While control and subjectivity may not be described as standalone functions or information—such that something must often be controlled and there has to be an experience for the self to present—they are also subcategories where relays get to and determine their intensities. It could be possible that rows within high-dimensional vectors become aspects of control, and some columns become aspects of subjectivity. For AGI, control and subjectivity would be data that can be used alone and has to be relayed for availability, unlike with humans. Simply, AGI would use data to control data and use data to have subjectivity, conceptually. Conceptual brain science could be useful in grading LLMs to AGI, becoming another direction for computational and theoretical neuroscience to shape progress in AI. There is a recent editorial in Nature , The new NeuroAI , stating that, "Overall, the extent of the role of neuroscience in AI research, and that of AI in neuroscience research, remain open questions for the future. However, these two fields are deeply linked, and the exchange of ideas between them continues to evolve. The pursuit of more powerful artificial neural systems in leading AI research labs, particularly those affiliated with tech companies, is currently focused on engineering. This pursuit emphasizes further scaling up of complex architectures such as transformers, rather than integrating insights from neuroscience." Nature The new NeuroAI There is a recent paper in Nature , Reservoir-computing based associative memory and itinerancy for complex dynamical attractors , stating that, "A neural network capable of memorizing and retrieving multiple memory states is also a multifunctional neural network. When different states are recalled, the neural network exhibits distinct dynamical behaviors. The idea of multifunctional RNNs has been discussed previously, along with different forms of implementation. In particular, in the index-based approach, an index parameter is introduced to modulate the functionality of the neural networks and store different states with different index values, but recalling the memorized states was a challenge, for which control may be necessary." Nature Reservoir-computing based associative memory and itinerancy for complex dynamical attractors

Evaluation: What is the Neuroscience of Superintelligence, AGI—and LLMs?

What's Next in the Journey of AI? Neuro-Symbolic AI

Mass can give energy and energy can give mass—only in the presence of the speed of light, squared—is a principle of fusion in particle physics. Or, simply, energy and mass are interchangeable. However, can this be remotely used to explain an aspect of the human mind, for rough similarities, towards how the brain works? Although the human brain does not have [anything moving at] the speed of light, electrical signals have conduction velocity. While both are not equivalent, might a parallel partly apply, to explaining a mechanism of the human mind? In the brain, there are two common elements, electrical and chemical signals. Electrical signals are in relay and chemical signals are mostly stationed at synapses. Though chemical signals are in transport as well, they often move within a smaller perimeter in comparison to electrical signals that span the axonal length. It can, therefore, be assumed that given these differences, electrical signals are in an extensive motion, while chemical signals are in marginal motion. However, because chemical signals are mostly confined around synapses—which can be near stationary while active, at times—chemical signals can be said to be a comparatively slower mass, with some velocity as well, such that their total momentum [sets of electrical and chemical signals] is conserved, normally, without [say] a traumatic brain injury or something else. Neurons are often in clusters across circuits in the brain. It is theorized that these clusters allow electrical and chemical signals to work in loops or as sets. This means that when a function is mechanized in a certain cluster of neurons, it is the enterprise of the signals. The chemical signals [in set] are postulated to provide rations that make up a configuration or formation for the specificity of that function. Simply, because smells are different and smell is different from touch or vision, it means that the configuration of a set of chemical signals that specifies one is different from the other. These chemical signals are located within the range of the synapse, from the vesicles to the cleft to the receptors. Their configuration [in a set] for a function, conceptually, may be due [as established in brain science] to their volumes in the cleft or their exit sequence—through receptors, or getting taken back up, or cleared out by enzymes. Simply, chemical signals in a set, provide rations that make up the specificity of functions. Chemical signals are molecules, mostly dominated by neurotransmitters, though others like neurohormones and so forth are involved. Electrical signals are established in neuroscience to be ions, moving through the length of the axon, due to action potentials, from the voltage-gated channels. It is also established that ions have mass and molecules have mass. It is theorized that in a set, these ions carry the summaries of functions and features, from one destination—or set of chemical signals—to the next. Electrical signals deliver what they bear [to sets of electrical signals] and access what is available there, then proceed again, conceptually. A Human Mind Phase of Matter It is theorized that in a set, electrical signals strike to fuse briefly with chemical signals, to access the configuration in that set. Simply, chemical signals have rations that make up configurations, but in order to have those rations provided, they have to be struck by the mass of incoming ions. It is postulated that when [a set of] electrical signals strike, they fuse briefly, resulting in a mix that is partly ions, partly molecules, and a third transient phase, which is different from both. It is this phase, postulated to be a new state of matter, that keeps some of the configuration information and gives off the volumes of chemical signals needed. It is also what collects—or contains—some of the energy that is given off, preventing several concurrent interactions in the brain from causing disturbing experiences. Simply, for functions of the mind, it is postulated that [sets of] electrical and chemical signals have to interact. This interaction is the strike and fusion of both, giving off a new mix, with a part of it, as a different phase from both, which holds some configuration and collects the energy, conceptually. Sets of electrical and chemical signals both have mass and velocity. When they strike and fuse, they give off energy. Electrical signals have their conduction velocity, which is enough to produce a new phase of matter—within the biological environment. There are grades to the interaction or how they are qualified, resulting in features like attention, awareness, self and intent, or free will. Though the speed of light is necessary for energy and mass interchange, the interactions of [sets of] electrical and chemical signals of the mind let the conduction velocity act as a conversion factor of sorts. The velocity of [sets of] chemical signals may also play a role—or be a tad negligible in other instances. This implies that a parallel of the energy-momentum relation could be developed for sets of electrical and chemical signals, in a theoretical neurobiophysics equation. Sets of electrical signals with mass, incoming, striking to fuse with [sets of] chemical signals, which are masses too—near static—giving off energy which is collected in another phase and used also to access configurations for functions and features of the human mind, conceptually. The human mind is theorized to be the collection of all the electrical and chemical signals with their interactions and features, in sets, in clusters of neurons, across the central and peripheral nervous systems. There is a recent paper in Nature Communications Physics, Unveiling universal aspects of the cellular anatomy of the brain, where the authors wrote, "Here, we propose that statistical physics can provide a guiding framework for determining and quantifying additional structural features in the cellular complexity of the brain. By analyzing properties related to cell size, as well as pairwise and higher-order correlations in cellular-level volumetric partial brain reconstructions from multiple organisms, we show that the cellular structure of the brain displays signatures associated with collective phenomena close to criticality. Our results indicate that the cellular structure of the brains of multiple organisms show signatures of being at or close to a structural phase transition and that the corresponding critical exponents are consistent between organisms. If these structural properties of the brain are indeed critical and universal between organisms, we would expect to observe consistent exponents in the cellular structures of other organisms and brain regions." There is a recent article in The Conversation, Could quantum physics be the key that unlocks the secrets of human behaviour?, stating that, "Yet research has shown that human behaviour can’t be fully captured by these traditional or “classical” laws of probability. Could it instead be explained by the way probability works in the more mysterious world of quantum mechanics? Mathematical probability is also a vital component of quantum mechanics, the branch of physics that describes how nature behaves at the scale of atoms or sub-atomic particles. However, as we’ll see, in the quantum world, probabilities follow very different rules." Mass can give energy and energy can give mass—only in the presence of the speed of light, squared—is a principle of fusion in particle physics. Or, simply, energy and mass are interchangeable. However, can this be remotely used to explain an aspect of the human mind, for rough similarities, towards how the brain works? Although the human brain does not have [anything moving at] the speed of light, electrical signals have conduction velocity. While both are not equivalent, might a parallel partly apply, to explaining a mechanism of the human mind? In the brain, there are two common elements, electrical and chemical signals. Electrical signals are in relay and chemical signals are mostly stationed at synapses. Though chemical signals are in transport as well, they often move within a smaller perimeter in comparison to electrical signals that span the axonal length. It can, therefore, be assumed that given these differences, electrical signals are in an extensive motion, while chemical signals are in marginal motion. However, because chemical signals are mostly confined around synapses—which can be near stationary while active, at times —chemical signals can be said to be a comparatively slower mass, with some velocity as well, such that their total momentum [sets of electrical and chemical signals] is conserved, normally, without [say] a traumatic brain injury or something else. near stationary while active, at times Neurons are often in clusters across circuits in the brain. It is theorized that these clusters allow electrical and chemical signals to work in loops or as sets. This means that when a function is mechanized in a certain cluster of neurons, it is the enterprise of the signals . it is the enterprise of the signals The chemical signals [in set] are postulated to provide rations that make up a configuration or formation for the specificity of that function. Simply, because smells are different and smell is different from touch or vision, it means that the configuration of a set of chemical signals that specifies one is different from the other. These chemical signals are located within the range of the synapse, from the vesicles to the cleft to the receptors. Their configuration [in a set] for a function, conceptually, may be due [as established in brain science] to their volumes in the cleft or their exit sequence— through receptors, or getting taken back up, or cleared out by enzymes . through receptors, or getting taken back up, or cleared out by enzymes Simply, chemical signals in a set, provide rations that make up the specificity of functions. Chemical signals are molecules, mostly dominated by neurotransmitters, though others like neurohormones and so forth are involved. Electrical signals are established in neuroscience to be ions, moving through the length of the axon, due to action potentials, from the voltage-gated channels. It is also established that ions have mass and molecules have mass. It is theorized that in a set , these ions carry the summaries of functions and features, from one destination—or set of chemical signals—to the next. Electrical signals deliver what they bear [to sets of electrical signals] and access what is available there, then proceed again, conceptually. It is theorized that in a set A Human Mind Phase of Matter A Human Mind Phase of Matter It is theorized that in a set, electrical signals strike to fuse briefly with chemical signals, to access the configuration in that set. Simply, chemical signals have rations that make up configurations, but in order to have those rations provided, they have to be struck by the mass of incoming ions. It is postulated that when [a set of] electrical signals strike, they fuse briefly, resulting in a mix that is partly ions, partly molecules, and a third transient phase, which is different from both. It is this phase, postulated to be a new state of matter , that keeps some of the configuration information and gives off the volumes of chemical signals needed. It is also what collects—or contains—some of the energy that is given off, preventing several concurrent interactions in the brain from causing disturbing experiences. postulated to be a new state of matter Simply, for functions of the mind, it is postulated that [sets of] electrical and chemical signals have to interact. This interaction is the strike and fusion of both, giving off a new mix, with a part of it, as a different phase from both, which holds some configuration and collects the energy, conceptually. Sets of electrical and chemical signals both have mass and velocity. When they strike and fuse, they give off energy. Electrical signals have their conduction velocity, which is enough to produce a new phase of matter—within the biological environment. There are grades to the interaction or how they are qualified, resulting in features like attention, awareness , self and intent, or free will. attention, awareness Though the speed of light is necessary for energy and mass interchange, the interactions of [sets of] electrical and chemical signals of the mind let the conduction velocity act as a conversion factor of sorts. The velocity of [sets of] chemical signals may also play a role—or be a tad negligible in other instances. This implies that a parallel of the energy-momentum relation could be developed for sets of electrical and chemical signals, in a theoretical neurobiophysics equation. tad Sets of electrical signals with mass, incoming, striking to fuse with [sets of] chemical signals, which are masses too—near static—giving off energy which is collected in another phase and used also to access configurations for functions and features of the human mind, conceptually. The human mind is theorized to be the collection of all the electrical and chemical signals with their interactions and features, in sets , in clusters of neurons, across the central and peripheral nervous systems. their interactions and features, in sets There is a recent paper in Nature Communications Physics , Unveiling universal aspects of the cellular anatomy of the brain , where the authors wrote, "Here, we propose that statistical physics can provide a guiding framework for determining and quantifying additional structural features in the cellular complexity of the brain. By analyzing properties related to cell size, as well as pairwise and higher-order correlations in cellular-level volumetric partial brain reconstructions from multiple organisms, we show that the cellular structure of the brain displays signatures associated with collective phenomena close to criticality. Our results indicate that the cellular structure of the brains of multiple organisms show signatures of being at or close to a structural phase transition and that the corresponding critical exponents are consistent between organisms. If these structural properties of the brain are indeed critical and universal between organisms, we would expect to observe consistent exponents in the cellular structures of other organisms and brain regions." Nature Communications Physics Unveiling universal aspects of the cellular anatomy of the brain There is a recent article in The Conversation , Could quantum physics be the key that unlocks the secrets of human behaviour? , stating that, "Yet research has shown that human behaviour can’t be fully captured by these traditional or “classical” laws of probability. Could it instead be explained by the way probability works in the more mysterious world of quantum mechanics? Mathematical probability is also a vital component of quantum mechanics, the branch of physics that describes how nature behaves at the scale of atoms or sub-atomic particles. However, as we’ll see, in the quantum world, probabilities follow very different rules." The Conversation Could quantum physics be the key that unlocks the secrets of human behaviour?

Neuroscience, Particle Physics: Does e = mc^2 Have a Parallel in the Human Mind?

In this exclusive interview, Josh shares his journey into blockchain, discusses the challenges and opportunities facing QuickNode, and offers valuable insights into the latest trends in blockchain technology. From the potential of rollups to advice for emerging talent, Josh provides a comprehensive look at the current state and future direction of blockchain infrastructure. Join us as we delve into the world of blockchain development, exploring how QuickNode is working to make Web3 more accessible and efficient for developers and businesses alike. Ishan Pandey: Hello Josh Neuroth, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you share your journey into the blockchain space and what drew you to QuickNode? Josh Neuroth: I’ve spent most of my career working on internet infrastructure, scaling networks, clouds, and data centers for leading technology companies. Web3 seemed the natural evolution: decentralized computing, allowing anyone anywhere to build applications and communities on chain! I started working on web3 stuff in 2019 and went full-time in early 2021. I joined QuickNode in 2023 because it was best positioned to help onboard traditional businesses into web3. The first place builders look at is getting access to the blockchain —which is QuickNode’s core product. Ishan Pandey: With your extensive experience in scaling infrastructure, what do you see as the biggest challenges and opportunities for QuickNode in the current blockchain ecosystem? Josh Neuroth: The amount of blockchains has exploded.. and now with rollup infrastructure, anyone can launch their own blockchain. One opportunity at QuickNode we’re focusing on is building the best place for businesses to build applications on blockchain tech. Developers need reliable infrastructure that just works. The biggest challenge currently facing us and the rest of the space is the lack of a regulatory framework. While we offer infrastructure and cloud services which are well understood by regulators, our customers need regulatory certainty. Ishan Pandey: How does QuickNode’s advanced infrastructure differentiate it from other blockchain node providers in the market? Josh Neuroth: QuickNode differentiates itself through its reliable, scalable, and user-friendly infrastructure. Our platform offers top-tier RPC access, node hosting, and API services that ensure high performance and reliability. What sets us apart is our focus on developer experience. We provide comprehensive tools like faucet services, marketplace add-ons, and advanced analytics, simplifying the development and deployment process. Additionally, our support for a wide range of blockchain protocols and our ability to handle high transaction volumes make us a preferred choice for enterprise customers and smaller development teams. QuickNode’s commitment to continuous innovation and customer satisfaction further strengthens our position in the market. Ishan Pandey: Can you elaborate on the benefits of QuickNode’s Rollups-as-a-Service platform for developers, particularly in terms of flexibility and performance? Josh Neuroth: QuickNode’s Rollups-as-a-Service (RaaS) platform offers significant benefits in terms of flexibility and performance. For developers, our RaaS platform provides essential tools such as high-quality RPC access, sequencer support, faucet services, and marketplace add-ons. These tools eliminate the need for extensive infrastructure management, allowing developers to focus on building and scaling their applications. The flexibility of our platform enables developers to customize and deploy rollups according to their specific needs, while our robust infrastructure ensures high performance and reliability. By handling the complexity of setting up and maintaining nodes, QuickNode significantly reduces development time and costs, helping developers accelerate their project timelines and bring their innovations to market faster. Ishan Pandey: What new trends in technology are you particularly interested in, and how is your business leveraging these trends to enhance its services? Josh Neuroth: I’m particularly interested in rollups, because it offers a new use case for web3 and the overall crypto ecosystem. Blockchain rollups —building a blockchain on top of another chain like Ethereum —  allow organizations and communities to monetize their block space by offering their chain as a form of serverless compute. In effect, it represents a new paradigm for computing. Think of a rollup as several technologies in one: Cloudflare Workers, Stripe Payments, and Reddit all in one. I think this opens many doors… imagine building an app for a gaming community in the Philippines and not having to think about credit card payments. Ishan Pandey: What advice do you have for up-and-coming talent in the blockchain space, especially those looking to innovate in blockchain infrastructure and Web3 services? Josh Neuroth: My advice for up-and-coming talent is to try to build something —even if it's just a side project. The blockchain industry is rapidly evolving, and staying updated with the latest developments and technologies is crucial. Use the tech, experiment, and try to understand what’s happening behind the interface. Many of my last hires stood out because they built something. Some of the projects were just proof of concepts. I’ve looked through thousands of resumes, and every person who built something got an interview. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. In this exclusive interview, Josh shares his journey into blockchain, discusses the challenges and opportunities facing QuickNode, and offers valuable insights into the latest trends in blockchain technology. From the potential of rollups to advice for emerging talent, Josh provides a comprehensive look at the current state and future direction of blockchain infrastructure. QuickNode, Join us as we delve into the world of blockchain development, exploring how QuickNode is working to make Web3 more accessible and efficient for developers and businesses alike. Ishan Pandey: Hello Josh Neuroth, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you share your journey into the blockchain space and what drew you to QuickNode? Ishan Pandey: Hello Josh Neuroth, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you share your journey into the blockchain space and what drew you to QuickNode? Ishan Pandey: Hello Josh Neuroth, It's a pleasure to welcome you to our 'Behind the Startup' series. Can you share your journey into the blockchain space and what drew you to QuickNode? Josh Neuroth: I’ve spent most of my career working on internet infrastructure, scaling networks, clouds, and data centers for leading technology companies. Web3 seemed the natural evolution: decentralized computing, allowing anyone anywhere to build applications and communities on chain! I started working on web3 stuff in 2019 and went full-time in early 2021. I joined QuickNode in 2023 because it was best positioned to help onboard traditional businesses into web3. The first place builders look at is getting access to the blockchain —which is QuickNode’s core product. Josh Neuroth: Ishan Pandey: With your extensive experience in scaling infrastructure, what do you see as the biggest challenges and opportunities for QuickNode in the current blockchain ecosystem? Ishan Pandey: With your extensive experience in scaling infrastructure, what do you see as the biggest challenges and opportunities for QuickNode in the current blockchain ecosystem? Ishan Pandey: With your extensive experience in scaling infrastructure, what do you see as the biggest challenges and opportunities for QuickNode in the current blockchain ecosystem? Josh Neuroth: The amount of blockchains has exploded.. and now with rollup infrastructure, anyone can launch their own blockchain. One opportunity at QuickNode we’re focusing on is building the best place for businesses to build applications on blockchain tech. Developers need reliable infrastructure that just works. The biggest challenge currently facing us and the rest of the space is the lack of a regulatory framework. While we offer infrastructure and cloud services which are well understood by regulators, our customers need regulatory certainty. Ishan Pandey: How does QuickNode’s advanced infrastructure differentiate it from other blockchain node providers in the market? Ishan Pandey: How does QuickNode’s advanced infrastructure differentiate it from other blockchain node providers in the market? Ishan Pandey: How does QuickNode’s advanced infrastructure differentiate it from other blockchain node providers in the market? Josh Neuroth: QuickNode differentiates itself through its reliable, scalable, and user-friendly infrastructure. Our platform offers top-tier RPC access, node hosting, and API services that ensure high performance and reliability. What sets us apart is our focus on developer experience. We provide comprehensive tools like faucet services, marketplace add-ons, and advanced analytics, simplifying the development and deployment process. Additionally, our support for a wide range of blockchain protocols and our ability to handle high transaction volumes make us a preferred choice for enterprise customers and smaller development teams. QuickNode’s commitment to continuous innovation and customer satisfaction further strengthens our position in the market. Josh Neuroth: Ishan Pandey: Can you elaborate on the benefits of QuickNode’s Rollups-as-a-Service platform for developers, particularly in terms of flexibility and performance? Ishan Pandey: Can you elaborate on the benefits of QuickNode’s Rollups-as-a-Service platform for developers, particularly in terms of flexibility and performance? Ishan Pandey: Can you elaborate on the benefits of QuickNode’s Rollups-as-a-Service platform for developers, particularly in terms of flexibility and performance? Josh Neuroth: QuickNode’s Rollups-as-a-Service (RaaS) platform offers significant benefits in terms of flexibility and performance. For developers, our RaaS platform provides essential tools such as high-quality RPC access, sequencer support, faucet services, and marketplace add-ons. These tools eliminate the need for extensive infrastructure management, allowing developers to focus on building and scaling their applications. The flexibility of our platform enables developers to customize and deploy rollups according to their specific needs, while our robust infrastructure ensures high performance and reliability. By handling the complexity of setting up and maintaining nodes, QuickNode significantly reduces development time and costs, helping developers accelerate their project timelines and bring their innovations to market faster. Josh Neuroth: Ishan Pandey: What new trends in technology are you particularly interested in, and how is your business leveraging these trends to enhance its services? Ishan Pandey: What new trends in technology are you particularly interested in, and how is your business leveraging these trends to enhance its services? Ishan Pandey: What new trends in technology are you particularly interested in, and how is your business leveraging these trends to enhance its services? Josh Neuroth: I’m particularly interested in rollups, because it offers a new use case for web3 and the overall crypto ecosystem. Blockchain rollups —building a blockchain on top of another chain like Ethereum —  allow organizations and communities to monetize their block space by offering their chain as a form of serverless compute. In effect, it represents a new paradigm for computing. Think of a rollup as several technologies in one: Cloudflare Workers, Stripe Payments, and Reddit all in one. I think this opens many doors… imagine building an app for a gaming community in the Philippines and not having to think about credit card payments. Josh Neuroth: Ishan Pandey: What advice do you have for up-and-coming talent in the blockchain space, especially those looking to innovate in blockchain infrastructure and Web3 services? Ishan Pandey: What advice do you have for up-and-coming talent in the blockchain space, especially those looking to innovate in blockchain infrastructure and Web3 services? Ishan Pandey: What advice do you have for up-and-coming talent in the blockchain space, especially those looking to innovate in blockchain infrastructure and Web3 services? Josh Neuroth: My advice for up-and-coming talent is to try to build something —even if it's just a side project. The blockchain industry is rapidly evolving, and staying updated with the latest developments and technologies is crucial. Use the tech, experiment, and try to understand what’s happening behind the interface. Many of my last hires stood out because they built something. Some of the projects were just proof of concepts. I’ve looked through thousands of resumes, and every person who built something got an interview. Josh Neuroth: Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: business blogging program business blogging program

QuickNode VP of Product Josh Neuroth on Blockchain Infrastructure, Rollups, and Web3 Innovation

ব্লকচেইন পরিকাঠামো, রোলআপস এবং ওয়েব3 উদ্ভাবনে প্রোডাক্ট জোশ নিউরোথের কুইকনোড ভিপি

Josh Neuroth, VP of Product bei QuickNode, über Blockchain-Infrastruktur, Rollups und Web3-Innovation

Josh Neuroth, vicepresidente de producto de QuickNode, sobre infraestructura Blockchain, paquetes acumulativos e innovación Web3

Josh Neuroth, vice-président du produit QuickNode, sur l'infrastructure Blockchain, les rollups et l'innovation Web3

क्विकनोड के उत्पाद उपाध्यक्ष जोश न्यूरोथ ने ब्लॉकचेन इंफ्रास्ट्रक्चर, रोलअप और वेब3 इनोवेशन पर बात की

QuickNode のプロダクト担当副社長 Josh Neuroth がブロックチェーン インフラストラクチャ、ロールアップ、Web3 イノベーションについて語る

블록체인 인프라, 롤업 및 Web3 혁신 부문 Josh Neuroth 제품 부문 QuickNode 부사장

Vice-presidente de produto da QuickNode, Josh Neuroth, sobre infraestrutura Blockchain, rollups e inovação Web3

Вице-президент QuickNode по продуктам Джош Нейрот по инфраструктуре блокчейна, накопительным пакетам и инновациям Web3

QuickNode Ürün Başkan Yardımcısı Josh Neuroth'un Blockchain Altyapısı, Toplamalar ve Web3 İnovasyonu

Phó chủ tịch sản phẩm QuickNode Josh Neuroth về Cơ sở hạ tầng Blockchain, Bản tổng hợp và Đổi mới Web3

QuickNode 产品副总裁 Josh Neuroth 谈区块链基础设施、Rollups 和 Web3 创新

AI: Sleep Computational Neuroscience, Dreams, Loneliness, and Predictive Coding

Nucleoid is a Declarative (Logic) Runtime Environment, which is a type of Symbolic AI used for reasoning engine in Neuro-Symbolic AI. Nucleoid runtime that tracks given statements in JavaScript syntax and creates relationships between variables, objects, functions, etc. in the logic graph. In brief, the runtime translates your business logic to a fully working application by managing the JavaScript state as well as storing in the built-in data store, so that your application doesn't require an external database or anything else. Neural Networks: The Learning Component Neural networks in Neuro-Symbolic AI are adept at learning patterns, relationships, and features from large datasets. These networks excel in tasks that involve classification, prediction, and pattern recognition, making them invaluable for processing unstructured data, such as images, text, and audio. Neural networks, through their learning capabilities, can generalize from examples to understand complex data structures and nuances in the data. Symbolic AI: The Reasoning Component The symbolic component of Neuro-Symbolic AI focuses on logic, rules, and symbolic representations of knowledge. Unlike neural networks that learn from data, symbolic AI uses predefined rules and knowledge bases to perform reasoning, make inferences, and understand relationships between entities. This aspect of AI is transparent, interpretable, and capable of explaining its decisions and reasoning processes in a way that humans can understand. Declarative Logic in Symbolic Reasoning Declarative logic is a subset of declarative programming, a style of building programs that expresses the logic of a computation without describing its control flow. In declarative logic, you state the facts and rules that define the problem domain. The runtime environment or the system itself figures out how to satisfy those conditions or how to apply those rules to reach a conclusion. This contrasts with imperative programming, where the developer writes code that describes the exact steps to achieve a goal. Symbolic reasoning refers to the process of using symbols to represent problems and applying logical rules to manipulate these symbols and derive conclusions or solutions. In AI and computer science, it involves using symbolic representations for entities and actions, enabling the system to perform logical inferences, decision-making, and problem-solving based on the rules and knowledge encoded in the symbols. By integrating Nucleoid into Neuro-Symbolic AI, the system benefits from enhanced interpretability and reliability. The declarative logic and rules defined in Nucleoid provide clear explanations for the AI's decisions, making it easier for users to understand and trust the system's outputs. Furthermore, the explicit reasoning capabilities help ensure that decisions are made based on logical principles, adding a layer of reliability and consistency to the AI's behavior. Hello World ⚡ User:
> 'Define human with name'

Assistant:
> 'The user requested to define a human with a name using a declarative class'

---

// Ubiquitous Code:
'use declarative';

class Human {
  name: string;
  constructor(name: string) {
    this.name = name;
  }
} User:
> 'All humans are mortal'

Assistant: All humans are mortal
> 'All humans were declared as mortal.'

---

// Ubiquitous Code:
'use declarative';

$Human.mortal = true; User:
> 'Create a human with name "Socrates"'

Assistant:
> 'A human named 'Socrates' was successfully created.'

---

// Ubiquitous Code:
'use imperative';

var human1 = new Human('Socrates');

// Result: {"id":"human1","name":"Socrates","mortal":true} User:
> 'Is human with name 'Socrates' mortal?'

Assistant:
> 'The human named 'Socrates' was determined to be mortal.'

---

// Ubiquitous Code:
`use imperative`;

var human1 = new Human('Socrates');
human1.mortal;
// Result: true 💡 This executes the business logic and stores the state in the data store. const app = nucleoid() manages internal data store without requiring an external database. Learn more at nucleoid.com/docs/get-started Under the Hood: Declarative (Logic) Runtime Environment Nucleoid is an implementation of symbolic AI for declarative (logic) programming at the runtime. As mentioned, the declarative runtime environment manages the JavaScript state and stores each transaction in the built-in data store by declaratively rerendering JavaScript statements and building the knowledge graph (base) as well as an execution plan. The declarative runtime isolates a behavior definition of a program from its technical instructions and executes declarative statements, which represent logical intention without carrying any technical detail. In this paradigm, there is no segregation regarding what data is or not, instead, it approaches how data (declarative statement) is related to others so that any type of data including business rules can be added without requiring any additional actions such as compiling, configuring, restarting as a result of plasticity. This approach also opens possibilities of storing data in the same box with the programming runtime. In short, the main objective of the project is to manage both data and logic under the same runtime. The declarative programming paradigm used by Nucleoid allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help distribute the load across multiple instances, which can further improve the performance of the system. Benchmark This is the comparison of our sample order app in Nucleoid IDE against MySQL and Postgres with using Express.js and Sequelize libraries. Performance benchmark happened in t2.micro of AWS EC2 instance and both databases had dedicated servers with no indexes and default configurations. This does not necessarily mean Nucleoid runtime is faster than MySQL or Postgres, instead, databases require constant maintenance by DBA teams with indexing, caching, purging, etc. However, Nucleoid tries to solve this problem by managing logic and data internally. As seen in the chart, for applications with average complexity, Nucleoid's performance is close to linear because of the on-chain data store and in-memory computing model as well as limiting the IO process. ⭐️ Star us on GitHub for the support Thanks to declarative logic programming, we have a brand-new approach to Neuro-Symbolic AI. As we continue to explore the potential of this AI architecture, we welcome all kinds of contributions! GitHub: https://github.com/NucleoidAI/Nucleoid Nucleoid is a Declarative (Logic) Runtime Environment, which is a type of Symbolic AI used for reasoning engine in Neuro-Symbolic AI. Nucleoid runtime that tracks given statements in JavaScript syntax and creates relationships between variables, objects, functions, etc. in the logic graph. In brief, the runtime translates your business logic to a fully working application by managing the JavaScript state as well as storing in the built-in data store, so that your application doesn't require an external database or anything else. Neural Networks: The Learning Component Neural networks in Neuro-Symbolic AI are adept at learning patterns, relationships, and features from large datasets. These networks excel in tasks that involve classification, prediction, and pattern recognition, making them invaluable for processing unstructured data, such as images, text, and audio. Neural networks, through their learning capabilities, can generalize from examples to understand complex data structures and nuances in the data. Symbolic AI: The Reasoning Component The symbolic component of Neuro-Symbolic AI focuses on logic, rules, and symbolic representations of knowledge. Unlike neural networks that learn from data, symbolic AI uses predefined rules and knowledge bases to perform reasoning, make inferences, and understand relationships between entities. This aspect of AI is transparent, interpretable, and capable of explaining its decisions and reasoning processes in a way that humans can understand. Declarative Logic in Symbolic Reasoning Declarative logic is a subset of declarative programming, a style of building programs that expresses the logic of a computation without describing its control flow. In declarative logic, you state the facts and rules that define the problem domain. The runtime environment or the system itself figures out how to satisfy those conditions or how to apply those rules to reach a conclusion. This contrasts with imperative programming, where the developer writes code that describes the exact steps to achieve a goal. Symbolic reasoning refers to the process of using symbols to represent problems and applying logical rules to manipulate these symbols and derive conclusions or solutions. In AI and computer science, it involves using symbolic representations for entities and actions, enabling the system to perform logical inferences, decision-making, and problem-solving based on the rules and knowledge encoded in the symbols. By integrating Nucleoid into Neuro-Symbolic AI, the system benefits from enhanced interpretability and reliability. The declarative logic and rules defined in Nucleoid provide clear explanations for the AI's decisions, making it easier for users to understand and trust the system's outputs. Furthermore, the explicit reasoning capabilities help ensure that decisions are made based on logical principles, adding a layer of reliability and consistency to the AI's behavior. Hello World ⚡ User:
> 'Define human with name'

Assistant:
> 'The user requested to define a human with a name using a declarative class'

---

// Ubiquitous Code:
'use declarative';

class Human {
  name: string;
  constructor(name: string) {
    this.name = name;
  }
} User:
> 'Define human with name'

Assistant:
> 'The user requested to define a human with a name using a declarative class'

---

// Ubiquitous Code:
'use declarative';

class Human {
  name: string;
  constructor(name: string) {
    this.name = name;
  }
} User:
> 'All humans are mortal'

Assistant: All humans are mortal
> 'All humans were declared as mortal.'

---

// Ubiquitous Code:
'use declarative';

$Human.mortal = true; User:
> 'All humans are mortal'

Assistant: All humans are mortal
> 'All humans were declared as mortal.'

---

// Ubiquitous Code:
'use declarative';

$Human.mortal = true; User:
> 'Create a human with name "Socrates"'

Assistant:
> 'A human named 'Socrates' was successfully created.'

---

// Ubiquitous Code:
'use imperative';

var human1 = new Human('Socrates');

// Result: {"id":"human1","name":"Socrates","mortal":true} User:
> 'Create a human with name "Socrates"'

Assistant:
> 'A human named 'Socrates' was successfully created.'

---

// Ubiquitous Code:
'use imperative';

var human1 = new Human('Socrates');

// Result: {"id":"human1","name":"Socrates","mortal":true} User:
> 'Is human with name 'Socrates' mortal?'

Assistant:
> 'The human named 'Socrates' was determined to be mortal.'

---

// Ubiquitous Code:
`use imperative`;

var human1 = new Human('Socrates');
human1.mortal;
// Result: true User:
> 'Is human with name 'Socrates' mortal?'

Assistant:
> 'The human named 'Socrates' was determined to be mortal.'

---

// Ubiquitous Code:
`use imperative`;

var human1 = new Human('Socrates');
human1.mortal;
// Result: true 💡 This executes the business logic and stores the state in the data store. const app = nucleoid() manages internal data store without requiring an external database. 💡 This executes the business logic and stores the state in the data store. const app = nucleoid() manages internal data store without requiring an external database. const app = nucleoid() Learn more at nucleoid.com/docs/get-started nucleoid.com/docs/get-started nucleoid.com/docs/get-started Under the Hood: Declarative (Logic) Runtime Environment Nucleoid is an implementation of symbolic AI for declarative (logic) programming at the runtime. As mentioned, the declarative runtime environment manages the JavaScript state and stores each transaction in the built-in data store by declaratively rerendering JavaScript statements and building the knowledge graph (base) as well as an execution plan. The declarative runtime isolates a behavior definition of a program from its technical instructions and executes declarative statements, which represent logical intention without carrying any technical detail. In this paradigm, there is no segregation regarding what data is or not, instead, it approaches how data (declarative statement) is related to others so that any type of data including business rules can be added without requiring any additional actions such as compiling, configuring, restarting as a result of plasticity. This approach also opens possibilities of storing data in the same box with the programming runtime. In short, the main objective of the project is to manage both data and logic under the same runtime. The declarative programming paradigm used by Nucleoid allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help distribute the load across multiple instances, which can further improve the performance of the system. Benchmark This is the comparison of our sample order app in Nucleoid IDE against MySQL and Postgres with using Express.js and Sequelize libraries. Performance benchmark happened in t2.micro of AWS EC2 instance and both databases had dedicated servers with no indexes and default configurations. Performance benchmark happened in t2.micro of AWS EC2 instance and both databases had dedicated servers with no indexes and default configurations. This does not necessarily mean Nucleoid runtime is faster than MySQL or Postgres, instead, databases require constant maintenance by DBA teams with indexing, caching, purging, etc. However, Nucleoid tries to solve this problem by managing logic and data internally. As seen in the chart, for applications with average complexity, Nucleoid's performance is close to linear because of the on-chain data store and in-memory computing model as well as limiting the IO process. ⭐️ Star us on GitHub for the support ⭐️ Star us on GitHub for the support Thanks to declarative logic programming, we have a brand-new approach to Neuro-Symbolic AI. As we continue to explore the potential of this AI architecture, we welcome all kinds of contributions! GitHub: https://github.com/NucleoidAI/Nucleoid GitHub: https://github.com/NucleoidAI/Nucleoid https://github.com/NucleoidAI/Nucleoid

Nucleoid: Neuro-Symbolic AI With Declarative Logic - What You Need to Know

Stories, News & Mentions about NEUKO

Neuko’s Stories on HackerNoon