Cryptocurrency and artificial intelligence/machine learning seem to compliment each other quite well in theory. The effective implementation. as of today, is yet to be realized by any major projects. Creating a successful and profitable “automation” is not the same as incorporating a learning mechanism into the source code of a trading bot. If you think about other AI projects and look at the very small progress made on these after years of testing, it’s not hard to understand why. Take UC Berkeley’s “Darwin,” or Google’s DeepMind for example, which has “just now taught itself to master walking.”
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“Master” may even be a generous word. This is exciting progress none the less. The question it brings to mind is this — which is harder to learn and/or “master,” walking or executing profitable trades? Although we don’t know the exact answer it’s easy to imagine that at the very least both are extremely complicated. True profitable AI algorithmic trading is still a good ways off but it’s exciting to watch projects take up the challenge!The reason we wanted to write a whole article on this is due to a theme that keeps arising with these projects. As of current, the popular trend for AI projects is “Social media sentiment” and while it sounds fancy and savvy, it’s in reality a good deal reckless perhaps and it is a type of trading we want to avoid here at OptiToken.io. This type of indicator could in theory lead to executing trades after the fact which is not shrewd investing. It is our opinion that AI needs to go much deeper. It needs to examine blockchain(s) directly and the hash power perhaps and pickup on where the hashing is being heavily diverted to, if/when it is being diverted. This in turn, could lead to a more fruitful type of knowledge which we refer to as BPA, before public announcement. But even then, executing a trade based solely on that may be premature or somewhat baseless. The idea for now is to incorporate this type of monitoring in the form of simply notifications to the trade team. This way further research can be done to examine whether a trade is risk/reward positive. Down the road upon gathering enough data this could then potentially be automated to execute trades with a very small portion of ones portfolio to see if profitability can be created and then it must be determined if it at least outpaces Bitcoin. Bitcoin is a fair benchmark to compare against still. The idea is this, why spend time, energy and finances on developing a profitable automation if simply holding a particular coin is more fruitful?
Furthermore, where does AI come into this? The definition of Artificial Intelligence, according to Dictionary.com is, “the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” So the automation needs to be able to identify NEW patterns or opportunities and not simply execute commands it was ordered to.
At OptiToken we are trying to create a formula for identifying something we refer to as, “critical mass indicators.” A program that monitors as many facets of the blockchain and cryptocurrency infrastructure/ecosystem as possible and to identify abnormalities and then discern if they are minor or extreme. The data that can be produced and learned here has immense potential and is part of the reason we are so excited about our project.
Optitoken is the first algorithmically traded, hyperdeflationary currency, that derives its value from a carefully curated token basket. Profits from the automatic trading of the portfolio are used to regularly buy Optitoken on exchanges, creating buy pressure and volatile price action. These tokens are then destroyed, creating further value. Our ICO is open to buy the initial token basket. You can learn more about the project here at https://OptiToken.io and on Reddit at <a href="https://Reddit.com/r/OptiToken