#LIKE MICROECONOMICS AND NEURAL NETWORKS

[gojos-nightmare-box]

BRUHHHHHH I GOT LOCKED OUT OF MY STUDENT ACCT AND NEED IT FOR DOCUMENTS AND THEYRE LIKE WHAT COURSES DID U TAKE

I DONT REMEMBER????? THATS WHY I WANT MY TRANSCRIPT SOBBING

[ddamscore]

Crypto Price Prediction: Unveiling the Future of Digital Assets

The world of cryptocurrencies has captivated both investors and enthusiasts alike, with the promise of transformative technologies and substantial returns. As the crypto market continues to evolve, price predictions have become crucial for traders seeking to make informed decisions to buy, sell or trade in this highly volatile landscape. In this article, we discuss the realm of crypto price predictions, exploring how they are generated, their accuracy, and their importance for the crypto community.

The Science of Crypto Price Predictions

Cryptocurrency price predictions are based on various factors and methodologies, ranging from technical analysis and historical data to fundamental factors and market sentiment. Technical analysis involves studying price charts and patterns to identify potential trends and support and resistance levels. Traders use various indicators such as Moving Averages (MA), Relative Strength Index (RSI), and Bollinger Bands to make predictions about what will be the future of crypto. On the other hand, fundamental analysis considers the underlying value and adoption potential of a cryptocurrency, evaluating factors like technology, partnerships, and real-world use cases. Analysts often examine a project's team, community support, and its competitive advantage in the market.

Factors Affects Crypto Price Predictions

Crypto price predictions are heavily influenced by both macroeconomic and microeconomic factors. Macro factors include global economic conditions, regulatory developments, and geopolitical events that can sway the sentiment of the entire crypto market. Let me give you an example, positive news on cryptocurrency regulations from major economies like the United States or China can trigger a bullish trend, while negative news can lead to a bearish sentiment in crypto overall price. Micro factors, such as project-specific news, network upgrades, and tokenomics changes, have a more direct impact on individual cryptocurrencies. For example, the release of a new software update, the integration of a new feature, or a partnership with a major company can boost the price of a particular cryptocurrency. Additionally, tokenomics changes, such as the implementation of token burns or staking mechanisms, can alter the supply and demand dynamics of that particular crypto, influencing the price.

The Role of Data and Technology

In recent years, the advancement of machine learning and artificial intelligence has significantly enhanced the accuracy of crypto price predictions. Automated trading bots and algorithms use vast amounts of historical data to identify patterns and trends that might otherwise go unnoticed by human traders while making a decision. These technologies have brought both convenience and challenges, as predicting crypto prices accurately remains a complex and evolving task but it can be highly profitable if someone makes an informed decision. Machine learning algorithms employ techniques like recurrent neural networks (RNNs) and long short-term memory (LSTM) networks to analyze historical price data and market sentiment of crypto. By recognizing patterns and correlations, these algorithms can identify potential price movements. However, it is important to note that no prediction model is completely accurate, and the accuracy of predictions can vary depending on market conditions and the quality of data used to make predictions.

Evaluating Prediction Accuracy

Assessing the accuracy of crypto price predictions is a critical aspect of using these forecasts for investment decisions. While some predictions might be spot-on, others can miss the mark by a wide margin as I mentioned above that no prediction method so far is fully accurate till now. Traders must consider the track record and credibility of the sources providing predictions and should avoid solely relying on any single forecast to trade, buy or sell the crypto. Reputable sources for crypto price predictions often back their forecasts with comprehensive research and analysis. They take into account technical and fundamental factors, as well as the prevailing market sentiment to give a prediction. Reliable analysts and platforms regularly update their predictions to reflect changes in the market, allowing investors to stay informed and make timely decisions as per their most likely perfect prediction. . It is crucial to remember that the crypto market is highly speculative and subject to rapid fluctuations. While predictions can provide valuable insights, they should not be considered as guarantees of future price movements. A good investor always conducts their research, diversifies their portfolios, and stays informed about market developments.

Conclusion

Crypto price predictions play an indispensable role in guiding investors and traders in the ever-changing world of digital assets. As the crypto market evolves, more sophisticated tools and technologies will likely emerge to improve the accuracy of predictions. While these forecasts provide valuable insights, it is essential to remember that the crypto market remains highly speculative and subject to rapid fluctuations. Investors should exercise caution and conduct thorough research before making any financial decisions based on these forecasts.

FAQ

Q1. Are crypto price predictions reliable for investment decisions? Crypto price predictions can offer valuable insights, but they should be used as one of several factors in making investment decisions. It is crucial to conduct your research and consider various sources before investing in cryptocurrencies. Q2. Can automated trading bots guarantee profitable trades? No, automated trading bots cannot guarantee profitable trades. They rely on historical data and patterns, but the crypto market is inherently unpredictable, and no strategy can guarantee consistent profits. Q3. What role do regulatory developments play in crypto price predictions? Regulatory developments can have a significant impact on crypto prices. Positive regulations often boost market sentiment, leading to price increases, while negative regulations may lead to price declines. Traders should closely monitor regulatory news and updates. Q4. How often should I review crypto price predictions? Crypto markets are highly dynamic, and price predictions can change rapidly. Investors should review predictions regularly and stay up-to-date with market developments to make well-informed decisions.

Read More : PepeCoin (PEPE) Price Prediction

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[teshknowledgenotes]

A Lesson on Elementary Worldly Wisdom As It Relates To Investment Management & Business - Charlie Munger Notes

Charlie Munger’s famous talk at USC Business School in 1994 entitled A Lesson on Elementary Worldly Wisdom.

The carrot part of this talk is about the general subject of worldly wisdom which is a pretty good way to start. After all, the theory of modern education is that you need a general education before you specialize. And I think to some extent before you’re going to be a great stock picker, you need some general education.

What is elementary, worldly wisdom? Well, the first rule is that you can’t really know anything if you just remember isolated facts and try and bang em back. If the fact don’t hang together on a latticework of theory, you don’t have them in a usable form.

You’ve got to have models in your head. And you’ve got to array your experience both vicarious and direct on this latticework of models. You may have noticed students who just try to remember and pound back what is remembered. Well, they fail in school and in life. You’ve got to hang experience on a latticework of models in your head.

What are the models? Well, the first rule is that you’ve got to have multiple models because if you just have one or two that you’re using, the nature of human psychology is such that you’ll torture reality to that if fits your models, or at least you’ll think it does. You become the equivalent of a chiropractor who of course is great in medicine.

It’s like the old saying, “To the man with only a hammer, every problem looks like a nail.” And of course that’s the way the chiropractor goes about practicing medicine. But that’s a perfectly disastrous way to think and a perfectly disastrous way to operate in the world. So you’ve got to have multiple models.

And the models have to come from multiple disciplines because all the wisdom of the world is not to be found in one little academic department. That’s why poetry professors, by and large are so unwise in a worldly sense. They don’t have enough models in their heads. So you’ve got to have models across a fair array of disciplines.

You may say “My God, this is already getting way too tough�� But, fortunately it isn’t that tough because 80 or 90 important models will carry about 90% of the freight in making you a worldly-wise person. And of those only a mere handful really carry very heavy freight.

So let’s briefly review what kind of models and techniques constitute this basic knowledge that everybody has to have before they proceed to being really good at a narrow art like stock picking.

First there’s mathematics. Obviously you’ve got to be able to handle numbers and quantities, basic arithmetic. And the great useful model, after compound interest, is the elementary math of permutations and combinations. And that was taught in my day in the sophomore year in high school. I supposed by now in great private school, it’s probably down to the eight grade or so.

Many educational institutions although not nearly enough have realized this. At Harvard Business School, the great quantitative thing that bonds the first year class together is what they call decision tree theory. All they do is take high school algebra and apply it to real life problems. And the students love it. They’re amazed to find that high school algebra works in real life.

By and large, as it works out, people can’t naturally and automatically do this. If you understand elementary psychology, the reason they can’t is really quite simple: The basic neural network of the brain is there through broad genetic and cultural evolution. So you have to learn in a very usable way this very elementary math and routinely in life just the way if you want to become a golfer, you can’t use the natural swing that broad evolution gave you. You have to learn to have a certain grip and swing in a different way to realize your full potential as a golfer.

If you don’t get this elementary but mildly unnatural mathematics of elementary probability in to your repertoire, then you go through a long life like a one legged man in an ass kicking contest. You’re giving a huge advantage to everybody else.

One of the advantages of a fellow like Buffett whom I’ve worked with all these years is that he automatically thinks in terms of decision trees and the elementary math of permutations and combinations.

Obviously you have to know accounting. It’s the language of practice business life. It was a very useful thing to deliver to civilization. I’ve heard it came to civilization through Venice which of course was once the great commercial power in the Mediterranean. However, double entry bookkeeping was a hell of an invention.

You have to know enough about it to understand its limitations because although account is the starting place, it’s only a crude approximation. And it’s not very hard to understand its limitations. For example everyone can see that you have to  do more or less just guess at the useful life of a jet airplane or anything like that just because you express the depreciation rate in neat numbers doesn’t make it anything you really know.

Which models are the most reliable? Well, obviously the models that come from hard science and engineering are the most reliable models on this Earth. And engineering quality control at least the guts of it that matters to you and me and people who are not professional engineers is very much based on the elementary mathematics of Fermat and Pascal.

I suppose the next most reliable models are from biology and physiology because after all, all of us are programmed by our genetic makeup to be much the same.

And when you get into psychology, of course it gets very much more complicated. But it’s an ungodly important subject if you’re going to have any worldly wisdom.

The elementary part of psychology the psychology of misjudgment as I call it is a terribly important thing to learn. There are about 20 little principles. And they interact, so it gets slightly complicated. But the guts of it is unbelievably important.

Terribly smart people make totally bonkers mistakes by failing to pay heed to it. In fact, I’ve done it several times during the last two or three years in a very important way. You never get totally over making silly mistakes.

There’s another saying that comes from Pascal which I’ve always considered one of the really accurate observations in the history of thought. Pascal said in essence “The mind of man at one and the same time is both the glory and the shame of the universe.”

And that’s exactly right. It has this enormous power. However it also has these standard misfunctions that often cause it to reach wrong conclusions. It also makes man extraordinarily subject to manipulation by others. For example, roughly half of the army of Adolf Hitler was composed to believing Catholics. Given enough clever psychological manipulation, what human beings will do is quite interesting.

Personally I’ve gotten so that I now use a kind of two track analysis. First, what are the factors that really govern the interests involved, rationally considered? And second, what are the subconscious influences where the brain at a subconscious level is automatically doing these things – which by and large are useful, but which often is misfunction.

One approach is rationality they way you’d work out a bridge problem by evaluation the real interests, the real probabilities and so forth. And the other is to evaluate the psychological factors that cause subconscious conclusions many of which are wrong.

Now we come to another somewhat less reliable form of human wisdom microeconomics. And here, I find it quite useful to think of a free market economy or partly free market economy as sort of the equivalent of an ecosystem.

This is a very unfashionable way of thinking because early in the days after Darwin came along, people like the robber barons assumed that the doctrine of the survival of the fittest authenticated them as deserving power you know “I’m the richest. Therefore I’m the best. God’s in his heaven, etc.”

And that reaction of the robber barons was so irritating to people that it made it unfashionable to think of an economy as an ecosystem. But the truth is that it is a lot like an ecosystem. And you get many of the same results.

Just as in an ecosystem, people who narrowly specialize can get terribly good at occupying some little niche. Just as animals flourish in niches, similarly, people who specialize in the business world and get very good because they specialize, frequently find good economics that they wouldn’t get any other way.

And once we get into microeconomics, we get into the concept of advantages of scale. Now we’re getting closer to investment analysis because in terms of which businesses succeed and which businesses fail, advantages of scale are ungodly important.

For example, one great advantage of scale taught in all of the business school of the world is cost reductions along the so called experience curve. Just doing something complicated in more and more volume enables human beings, who are trying to improve and are motivated by incentives of capitalism to do it more efficiently.

The very nature of things is that if you get a whole lot of volume through your joint, you get better at processing that volume. That’s an enormous advantage. And it has a lot do with which businesses succeed and fail.

Let’s go through a of possible advantages of scale. Some come from simple geometry. If you’re building a great spherical tank, obviously as you build it bigger, the amount of steel you use in the surface goes up with the square and the cubic volume goes up with the cube. So as you increase the dimensions you can hold a lot more volume per unit are of steel.

And there are all kinds of things like that where the simple geometry the simple reality gives you an advantage of scale.

For example you can get advantages of scale from TV advertising. When TV advertising first arrived when talking colour pictures first came into our living rooms it was an unbelievably powerful thing. And in the early days, we had three networks that had whatever it was say 90% of the audience.

Well, if you were Procter & Gamble you could afford to use this new method of advertising. You could afford the very expensive cost of network television because you were selling so many cans and bottle. Some little guy couldn’t. And there was no way of buying it in part. Therefore, he couldn’t use it. In effect, if you didn’t have a big volume, you couldn’t use network TV advertising which was the most effective technique.

So when TV came in, the branded companies that were already big got a huge tailwind. Indeed they prospered and prospered and prospered until some of them got fat and foolish, which happens with prosperity, at least to some people.

And your advantage of scale can be an informational advantage. If I got to some remote place, I may see Wrigley chewing gum alongside Glotz’s chewing gum. Well, I know that Wrigley is a satisfactory product, whereas I don’t know anything about Glotz’s. So if one is 40 cents and the other is 30 cents, am I going to take something I don’t know and put it in my mouth, which is a pretty personal place after all, for a lousy dime?

So, in effect, Wrigley simply by being so well known, has advantages of scale what you might call an informational advantage.

Another advantage of scale comes from psychology. The psychologists use the term social proof. We are all influenced subconsciously and to some extent consciously by what we see others do and approve. Therefore, if everybody’s buying something, we think it’s better. We don’t like to be the one guy who’s out of step.

Again some of this is at a subconscious level and some of it isn’t. Sometimes, we consciously and rationally think “Gee, I don’t know much about this. They know more than I do. Therefore why shouldn’t I follow them?”

The social proof phenomenon which comes right out of psychology gives huge advantages to scale for example, with very wide distribution, which of course is hard to get. One advantage of Coca-Cola is that it’s available almost everywhere in the world.

Well, suppose you have a little soft drink. Exactly how do you make it available all over the Earth? The worldwide distribution setup which is slowly won by a big enterprise gets to be a huge advantage, and if you think about it, once you get enough advantages of that type, it can become very hard for anybody to dislodge you.

There’s another kind of advantage to scale. In some businesses, the very nature of things is to sort of cascade toward the overwhelming dominance of one firm.

The most obvious one is the daily newspapers. There’s practically no city left in the U.S. aside from a few very big ones, where there’s more than one daily newspaper.

The great defect of scale, of course which makes the game interesting so that the big people don’t always win, is that as you get big, you get the bureaucracy. And with the bureaucracy comes the territoriality which is again grounded in human nature.

They also tend to become somewhat corrupt. In other words, if I’ve got a department and you’ve got a department and we kind of share power running this thing, there’s sort of an unwritten rule: “If you don’t bother me, I won’t bother you and we’re both happy” So you get layers of management and associated costs that nobody needs. Then while people are justifying all these layers, it takes forever to get anything done. They’re too slow to make decisions and nimbler people run circles around them.

The constant curse of scale is that it leads to big, dumb bureaucracy which of course, reaches its highest and worst form in government where the incentives are really awful. That doesn’t mean we don’t need governments because we do. But it’s a terrible problem to get big bureaucracies to behave.

But bureaucracy is terrible, and as things get very powerful and very big, you can get some really dysfunctional behaviour. Look at Westinghouse. They blue billions of dollars on a bunch of dumb loans to real estate developers. They put some guy who’d come up by some career path, I don’t know exactly what it was, but it could have been refrigerators or something and all of a sudden he’s loaning money to real estate developers building hotels. It’s a very unequal contest. And in due time, they lost all those billions of dollars.

However, Berkshire Hathaway, by and large does not invest in the people that are “surfing” on complicated technology. After all we’re cranky and idiosyncratic as you may have notice.

And Warren and I don’t feel like we have any great advantage in the high tech sector. In fact, we feel like we’re at a big disadvantage in trying to understand the nature of technical developments in software, computer chips or what have you. So we tend to avoid that stuff, based on our personal inadequacies.

Again that is a very, very powerful idea. Every person is going to have a circle of competence. And it’s going to be very hard to advance that circle. If I had to make my living as a musician, I can’t even think of a level low enough to describe where I would be sorted out to if music were the measuring standard of civilization.

So you have to figure out what your own aptitudes are. If you play games where the other people have the aptitudes and you don’t, you’re going to lose. And that’s as close to certain as any prediction that you can make. You have to figure out where you’ve got an edge. And you’ve got to play within your own circle of competence.

If you want to be the best tennis player in the world, you may start out trying and soon find out that it’s hopeless, that other people blow right by you. However, if you want to become the best plumbing contractor in Bemidji, that is probable doable by two-thirds of you. It takes will, It takes intelligence. But after a while, you’d gradually know all about the plumbing business in Bemidji and master the art. That is an attainable objective, given enough discipline. And people who could never win a chess tournament or stand in centre court in a respectable tennis tournament can rise quite high in life by slowly developing a circle of competence which results partly from what they were born with and partly from what they slowly develop through work.

And yet, in investment management, practically nobody operates that way. We operate that way, I’m talking about Buffett and Munger. And we’re not alone in the world. But a huge majority of people have some other crazy construct in their heads. And instead of waiting for a near cinch and loading up, they apparently ascribe to the theory that if they work a little harder or hire more business school students, they’ll come to know everything about everything all the time.

To me that’s totally insane. The way to win is to work, work, work, work and hope to have a few insights.

How many insights do you need? Well I’d argue: that you don’t need many in a lifetime. If you look at Berkshire Hathaway and all of it’s accumulated billions, the top ten insights account for most of it. And that’s with a very brilliant man, Warren’s a lot more able than I am and very disciplined devoting his lifetime to it. I don’t mean to say that he’s only had ten insights. I’m just saying that most of the money came from ten insights.

So you can get very remarkable investment results if you think more like a winning pari-mutuel player. Just think if it as heavy odds against game full of craziness with an occasional mispriced something or other. And you’re probably not going to be smart enough to find thousands in a lifetime. And when you get a few, you really load up. It’s just that simple.

We’ve really made the money out of high-quality businesses. In some cases we bought the whole business. And in some cases, we just bought a big block of stock. But when you analyze what happened, the big money’s been made in high-quality businesses. And most of the other people who’ve made a lot of money have done so in high quality businesses.

Over the long term, it’s hard for a stock to earn a much better return than the business which underlies it earns. If the business earns 6% on capital over 40 years and you hold it for that 40 years, you’re not going to make much different than a 6% return, even if you originally buy it at a huge discount. Conversely, if a business earn 18% on capital over 20 or 30 years, even if you pay an expensive looking price, you’ll end up with a fine result.

So the trick is getting into better businesses. And that involves all of these advantages of scale that you could consider momentum effects.

How do you get into these great companies? One method is what I’d call the method of finding them small get em when they’re little. For example, buy Walmart when Sam Walton first goes public and so forth. And a lot of people try to do just that. And it’s a very beguiling idea. If I were a young man, I might actually go into it.

But it doesn’t work for Berkshire Hathaway anymore because we’ve got too much money. We can’t find anything that fits our size parameter that way. Besides, we’re set in our way. But I regard finding them small as a perfectly intelligent approach for somebody to try with discipline. It’s just not something that I’ve done.

Finding em big obviously is very hard because of the competition. So far, Berkshire’s managed to do it. But can we continue to do it? What’s the next Coca-Cola investment for us? Well the answer to that is I don’t know. I think it gets harder for us all the time.

And ideally and we’ve done a lot of this, you get in to a great business which also has a great manager because management matters. For example, it’s made a great difference to General Electric that Jack Welch can in instead of the guy who took over Westinghouse a very great difference. So management matters, too.

And some of it is predictable. I do not think it takes a genius to understand that Jack Welch was a more insightful person and a better manager than his peers in other companies. Nor do I think it took tremendous genius to understand that Disney had basic momentum in place which are very powerful and that Eisner and Wells were very unusual managers.

So you do get an occasional opportunity to get in to a wonderful business that’s being run by a wonderful manager. And of course that’s hog heaven day. If you don’t load up when you those opportunities, it’s a big mistake.

Occasionally, you’ll find a human being who’s so talented that he can do things that ordinary skilled mortals can’t. I would argue that Simon Marks who was second generation in Marks & Spencer of England was such a man. Patterson was such a man at National Cash Register. And Sam Walton was such a man.

These people do come along and in many cases, they’re not all that hard to identify. If they’ve got a reasonable hand with the fanaticism and intelligence and so on that these people generally bring to the part, then management can matter much.

However, averaged out, betting on the quality of a business is better betting on the quality of management. In other words, if you have to choose one, bet on the business momentum, not the brilliance of the manager.

But, very rarely, you find a manager who’s so good that you’re wise to follow him into what looks like a mediocre business.

[taskfarm]

Quantum computing will be key for the take off of IoT

Within the next years the biggest changes and strongest influence from IoT will be seen in the industrial sector and in critical infrastructure, with focus on Middle East and South America as legacy is of less importance there and the implementation of IoT is an opportunity for expansion. Due of the growing amount of data that IoT produces, the real take off of IoT will happen together with quantum computing as then computing and security obstacles can be solved at the same time, says Scott Amyx, IoT Strategist, CEO at Amyx+ and IBM IoT Futurist. Interview by Julia Weinzettl

Scott Amyx will be speaking at the M2M/IoT Forum on March 27th-28th in Vienna, Austria.

Source: Oil And Gas Jobs Register.

What economic sector will be most influenced by IoT within the next years?

Scott Amyx: In my opinion the primary focus near term is still the industrial side. That´s fairly a canvassing statement. IoT will have strong influence in supporting the automotive industry, the building industry and consumer electronics, but fundamentally we are really talking about a b2b in some cases a b2b2c type of situation. Now additionally we are going to see momentum around critical infrastructure - electric grid,  gas pipelines, telecommunications for example are starting to be influenced by IoT, specifically the regions we are going to see arise are the Middle East as well as South America.

Why there?

Scott Amyx: This not too surprising as in more mature markets like the EU and North America utilities or energy companies are primarily compliance and regulation driven. In order to make these types of investments cost savings and efficiency in automation has to be overwhelming. If you already have an existing set of infrastructure it´s difficult to overhaul it as it´s incremental, whereas in the case of South America and the Middle East, investment in IoT basically is an opportunity for expansion. We are talking about laying down a brand new set of fiber optics next to utilities - whether it´s gas lines or electric lines - under the ground. More importantly they are interested in getting very granular data at each point. It´s not just some data at the end mile or at the beginning and the end of the transmission but it´s actually the data in the process. One application for this data is for analytics but it´s also increasingly used for security. Which is a double sided sword, because as we start to allow these IP addressable types of connectivity, we need to make sure that there are no potential gaps opened, that leave a backdoor entry into the entire system of the grid. It´s not just a matter of economy but also a political and military defense issue.

If we look into the future within the next ten years what changes will we find in our society because of the technological advancements?

Scott Amyx: I think there will be quite some changes in the next ten years, but I wonder if this time frame is closer to the next twenty or twenty five years. At the moment there is a lot of discussion and controversy around the topics of AI, robotics and 4th industrial revolution and is it´s role in society. We all know that there is going to be a huge job loss as the world economic forum has stated it and many more. It´s a bit of a given known.

Scott Amyx, CEO Amyx+

What is your view on this matter?

Scott Amyx: One thing that people don´t really appreciate is that there is a difference between task versus job. For instance if you think about the old days when there was an actual person who would route phone calls and connected your call to where you wanted to call. That´s a task and that´s were automation comes in. I think what people have to recognise is that tasks will be automated - whatever those tasks are - but the jobs are just going to change. Moreover it´s not simple labor destruction it rather is a fluid, dynamic reconstruction of the labor economics. So the automation of tasks will lead to the loss of some jobs not needed any longer - like there is much less need for blacksmiths since the invention of the car - but it will emerge into the creation of new jobs. The way I see it is that automation helps us to increase the standard of living. If I can automate ten tasks that frees me up to have more time and resources as i don´t have to allocate money to that tasks any more. That means I can reallocate my time and effort into other things. The future of jobs is in human to human relationships in particular in empathy business models.

Do you have examples for that?

Scott Amyx: If you look into the last ten years, there has been a significant rise in empathy roles such as coaching, spiritual leaders whether it´s yogis or others, as well increasing counseling and psychotherapy. Let´s take this into the future: when we travel different parts of the world sometimes what we are looking for is connection, maybe I just want to have coffee with somebody - another human being - in a new city that I’m not familiar with or maybe I want a tour guide - not because I can´t access my map - but because I want to connect with another human. These kind of jobs will not only not vanish but increase.  

Coming back to the topic of IoT - do you think that the major breakthrough will come once we change to quantum computing?

Scott Amyx: Yes, and the reason for that is, as you are probably aware, in the internet of things, there are some pervasive and some dogmatic challenges that the industry faces. One would be the interoperability or lack of security which is one of the biggest challenges but here is a ton of other issues that prevent IoT from truly taking off. Some of the benefits of quantum computing is that it will handle computation faster as well as handle more complex computations that are fundamentally different from the classical computers. That allows for us data crunching, the ability to run all the inputs at the same time and get immediate results mainly because of the facturing aspect, the memory space and sequential processing that will not be supported real time by classical machines. With IoT the volume of data, different data types and the metadata is increasing. We are capturing data from couches and floors, walls and paints, agriculture and water. The other important part is security. Both primarily to solve difficult cryptography as well as to create security. This is hugely important and is the notion of quantum key distribution. Predictive data analytics will be able to be handled and will literally support machine learning. That will produce so much complexities whether it’s around discovery, cybersecurity, finance or health care. All these very complex optimisation problems especially in support of machine learning and deep learning of neural networks will be supported. If you developed a very complex system like a smart city IT implementation you will have an IoT system just for lighting that connects one building. This system will then connect with other lighting systems across the city, with the traffic IoT systems, the CCTV IoT systems, water systems and so forth and so forth. You have layers and layers of systems and systems. How do you verify that everything is working correctly? Well, quantum can potentially handle a lot of the verification and validation process quickly.

amyxinternetofthings.com m2m-forum.eu

About Scott Amyx:

CEO at Amyx+, IBM IoT Futurist, European Commission, United Nations, Wiley Author, TechCrunch, Voted Top IoT Expert by Inc., Postscapes & IoT Institute, Winner of the Cloud & DevOps World Innovation Award

Scott Amyx received the Gartner Cool IoT Vendor 2017, Cloud & DevOps World 2016 Award for Most Innovative and was voted Top Global IoT Influencer & Expert by Inc. Magazine, Postscapes, Top IoT Authority by the Internet of Things Institute, and Top 10 Global Speakers by Speaking.com. Scott is a thought leader, speaker, and author on the Internet of Things and the Managing Partner at Venture1st and CEO of Amyx+. Scott has been nominated to the World Economic Forum as a committee member for the Future of the Internet and has been nominated by global luminaries for TED Talk. The Republic of Korea nominated Scott to represent cutting-edge research and case studies on the Internet of Things at the ITU Telecom World, United Nations 2015 in Budapest. Gerson Lehrman Group (GLG), AlphaSights, 10EQS, and other research firms look to Scott for unrivaled insights and pulse on the changing IoT landscape.

Scott has over 19 years of large-scale strategy and implementation experience, managing double digit million dollar projects across multiple verticals. In his last corporate position as VP of Product Management, he helped the company be acquired by a Fortune 500 publicly traded company. Scott has also started numerous startups and successfully sold a company. He has a master’s degree in applied microeconomics/ public policy from the University of Chicago. Scott was a national Sloan Fellow at Carnegie Mellon University.

TED Profile: https://www.ted.com/profiles/5517138  Speech Videos: https://www.youtube.com/channel/UCNnVp5hGUCRoY-XpPDoGPMA