Everything as a Service or rather Everything as a hype is today’s biggest problem now to separate the blockchain hype from the reality is the biggest challenge and second is to provide this most recent and innovative solution as a service to every small/big business to benefit end user. What is the reality when it comes to actual implementation of blockchain in business? who can separate real business from all the hype or can pull real values out of these fascinating PHD case studies or study materials.
Anatomy of Blockchain – Its very simple and interesting – Open book on internet – A cryptographic linked list data structure which is replicated across the network with consensus mechanism which is based on secured information transfer between 2 people (P2P). As its distributed with no central authority. Where each block is constructed with key elements like identity information, information sent across or if this is financial then financial transaction details.
So what is blockchain; Blockchain is protocol like any other to send information, track information, pass on the information and secure information mainly in financial world. So blockchain probably is the only technology or tech toy which has gone from being an obscure tech that backed cryptocurrencies to being considered as an answer for some of the greatest modern questions in technology.
Each block is the core of the blockchain and is where information is kept. If we compare with financial ledger book then each block is simply a page in physical edger in bank. Only difference is in blockchain its page (block) is maintained by every one in blockchain and in bank its maintained by banks and kept in bank, block chain is an open book on internet.
What is interesting to see is how distributed deeplearning will work or should we even thing about it in first place. Deeplearning works much better on GPU and on internet it may completely stop or fail as the bottleneck is almost always the communication speed between layers in a neural net. In a modern GPU you have about 300 GB/s bandwidth. Compare that to the current internet speed and you see it almost makes no sense.
Merger of artificial intelligence and blockchain’s unique and most advanced techniques could be the most disruptive idea of the year, perhaps the idea of year 2018. AI blockchain technology should be aimed to distribute access to a wide range of AI algorithms. Blockchain can also be called as a tool which is tamper-resistant or a distributed ledger software underlying mainly cryptocurrencies such as Bitcoin, for recording and transferring data and assets such as financial transactions and real estate titles.
A blockchain is essentially a type of database–a way to store information. What makes it different from a traditional database is that it’s designed to be a store of information that is shared and owned by the entire network. That means every one can read, write and no one owns the data–it belongs to everyone on the network. Blockchain system may looks simple but matter of fact is that the entire blockchain ecosystem is extremely complex, plagued by infrastructure and developmental challenges in integrating functions and components.
Industry leaders should aims to prevent control of advanced AI from being entirely in the hands of Silicon Valley or few handful big companies who control 80% of the market share but are 20% or less in numbers of total industry players in numbers. Now, an ambitious artificial intelligence startup is using the funding strategy as a means of gathering the cash needed to jumpstart the development of a project. Building blockchain solutions should be very easy endeavor to follow (though as on date practically this is a convoluted labyrinth).
AI has started delivering values. Using the contemporary view of computing exemplified by recent models and results from non-uniform complexity theory has proven the fact. Blockchain technology is being used to distribute the financial market, rather than keep it in the control of a few major companies. How about the same concept with Artificial Intelligence so that it can deliver the values in a plug and play mode i.e As a Service technique. Any new startup if require or wants can just plug and play this service to get benefits rather then leaving it in just few big hands.
I don’t know if its correct to compare artificial intelligence with a frog, but let me try AI is like a frog who might be given many different descriptions but it does not change the fact that it is a frog i.e AI. Intelligent business intelligence might still be the de-jure industry leader, but de facto control secrete of success of any business now rests with the artificial intelligence and its techniques around so why not to exploit it and make best use of it to benefit every stake holder in a business, society or a common user of any service. With BaaS i.e Blockchain a a Service, the journey may be smoother, practical, and also more profitable and complex for some time.
Blockchain is the largest distributed (Blue ocean player) database of digital records users seeking blockchain to be available as service which is easy to be integrated in applications for their businesses. The potential market for these “as a service” technologies is immeasurable, and now is the right time to showcase. BaaS product to prospective clients and investors likely to be available from big players soon though.
How AI will be transforming the future of finTech to elaborate items from the above list in African markets and opportunities are even more dramatic – In just the past five years. One needs to sort federation of AIs emerge from the spontaneous interaction among the nodes and demystify it self without human guidance or intervention. Recently, big banks in collaborations with giant technology partners proudly announced their upcoming ability in near future to transform trade finance transactions with the use of BaaS.
Creating strong partnership between AIs neural network’s capsule neurons whose activity vector represents the instantiation parameters of a specific type of entity such as an object or object part now assume the blockchain working model of creating blocks. Active capsules at one level make predictions, via transformation matrices, for the instantiation parameters of higher-level capsules. When multiple predictions agree, a higher level capsule becomes active. Similarly in blockchain when block is about to get added it gets verified and agreed from many sources.
We show that a discriminatively trained, approved and accepted systems achieves state-of-art status and confidence in users. Blockchain is one of them. What effect will be brought in with the adoption of Blockchain AI on our businesses and organisations offerings and processes in next five years; will interesting to watch and enjoy. Dedicated system for the “As a Service” business and specially BaaS might become principle provider of IT services with focus on development and operations with no time and money.
The blockchain is what enables cryptocurrencies like Bitcoin and PascalCoin. Ethereum is a framework that makes it easier to build decentralized applications using blockchain technology. Consensus systems and the verification of data used in learning algorithms could be one of the possible application of a blockchain with machine learning could be the use but what would be the use case though.
I am getting tempted to say — this time is really different. AI DAOs – AI that can accumulate wealth, that you can’t turn off. Artificial intelligence is set to transform the financial services industry. Blockchain AI will create a system that learns on its own how to reinvent current solutions metaheuristicaly to carry out different jobs and functions.
Conclusion – At end allow me to say AI is a friendly technology that is here to be accepted without fail and all future products will be based on AI. Artificial intelligence is the craze in silicon valley, but on Wall Street, well, there’s a lot of skepticism. Unfortunately so far only intelligence got artificial but risk still remains for real and natural. Natural language generation can create, write and tell your business stories but still raise hands when risk over takes. An example of capsule networks under deep learning where lower-level capsule prefers to send its output to higher level capsules whose activity vectors have a big scalar product with the prediction coming from the lower-level capsule
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