This is just the beginning. Expect to see an endless stream of Artificial Intelligence based apps aiming to solve every problem we ever had and may have. Mismatch complexity of our lives & our cognitive abilities. Other problems like too many things to keep track of, information overload, learn & remember more led AI to start helping us.Intelligence augmentations getting abandon/vanquished after almost 50 years.
Artificial intelligence is now considered as a new factor of production and has the conceivable potential to introduce new sources of growth, reinventing the business in currently in place, changing how work is done and reinforcing the role of people to drive growth in business. On the other hand i.e. thinking with machines or intelligence augmentation is serious evolutionary epistemology, and semiotic. And it has extreme potentials to take business intelligence to competitive intelligence that can infer competitive measures using augmented site-centric data.
It takes money to make money and right now a lot of that money is going into the development of artificial intelligence. Any intelligence level surpassing the human intelligence is called the superintelligence level which is still 50 years plus ahead. Machine learning, as an enabling palpable technologies, received the largest share of both internal and external investment. In Short get AI ready or ready to be swapped by AI very soon. Suddenly, artificial intelligence is everywhere.
Are you AI ready if not then be ready to be read in history books. Are we not missing the fact that artificial intelligence is about the people, not the machines. Intelligence augmentation refers to the effective use of information technology in augmenting human capabilities, and the idea has been around since 1950s. On the other hand, artificial intelligence is not well suited to situations where goals and inputs are not well defined; it’s here where intelligence augmentation will continue to play a major role.
AI is today increasingly used as a wide term to describe machines that can mimic human functions such as learning and problem solving, but was originally founded on the premise that human intelligence can be precisely described, and machines made to simulate it. Technology and non technology companies are now investing and brining out the real and materialistic values of Artificial Intelligence to the real world. Its almost after a frustrating and hard work of decade.
So where does the AI reaches its limits and IA excels? To assist the human operator in evaluating what action should to be taken next. Arguments around artificial intelligence vs intelligence augmentation are on table from last couple of decades. The term Artificial General Intelligence (AGI) is often used to represent only the latter, stricter definition. There is unprecedented hype today around AI, its incredible recent growth trajectory, myriad potential applications, and its potential emergent threats to society.
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. Are we ready to relinquish control to autonomous cars, software bots, and AI-based recommendation engines? Investment in artificial intelligence is growing fast. Tech giants like Google, Microsoft, Apple and Baidu known for their dominance in digital technologies globally are spending couple of tens of billions united state dollars on AI with 90 percent of this spent on R&D and deployment, and 10 percent on AI acquisitions.
Before getting into deeper with this black magic term i.e. Artificial Intelligence lets glance through it from the helicopter view prospective. Any thing which needs information processing in human mind is the human intelligence and if the same task is performed by machine can be (I said can be) term as artificial intelligence like looking picture and telling is this human, sad or happy, decent or nasty.
But million dollar question is “Why do we need technology to overcome cognitive limitations? Answer could many like lousy memory, humans are good at dealing with only one thing at a time, probabilities, logic non-intuitive, slow to process large amounts of information. Animal picture is a dog or cat etc. AI dont need to demystify any thing more as its metaheuristic approach has almost over shadowed going to be legacy technologies and computational power of cognitive systems techniques.
Machine Learning and Deep Learning) is not so new, have you heard of accepting selfie as authentication for your shopping bill payment, Siri on your iPhone etc. A Decentralized Autonomous Organization (DAO) is a process that manifests these characteristics. It’s code that can own stuff. Self-driving car is an excellent example for this. What if you use blockchain to store the state of machine.
In Turning test he proposed a simple test to determine whether or not a computer had achieved true artificial intelligence only by giving same question to human and a computer If the interrogator couldn’t tell which response came from the computer and which came from the person then system has attained the or have attained artificial intelligence.
AI glossary is huge and some time can also be very confusing and used interchangeable. We may not be able to define all of them here but lets try to name few terms here. Artificial Intelligence, Machine learning, Deep Learning, Supervised & Unsupervised Learning, Cognitive computing or just a prettier way to say “artificial intelligence”, Artificial neural network or Neural networks or neural net or deep neural net etc. All of them are the same thing — a computer system inspired by living brains. Bots or chat bots may may not come under AI, Data mining, Data Science, Big Data are few to name.
Separating AI as myth from reality can be tough at this time but in future it will come handy and gets easy though the hype and hyperbole that surrounds artificial intelligence. It relates to job elimination perception, great high speed northbound journey of automation and intense push for people to upgrade their skills to be in the race. We all may be looking at AI all wrong. from some time.
Artificial intelligence is everywhere in the media, its hype is not hidden. Recent comments from few billionaires about AI (some commented in favor some commented little conservatively) are all over on social media but leaders and drivers of this force must look past the hype and understand how to apply it to create real business value now.
Still most of people thinks Artificial intelligence is about robots only but reality we all know is much different. Bots, Robots, AI subsets and Agents (Siri etc) are just getting smarter with this black magic technology. Artificial intelligence is the future and will come in almost every form, every product and service we use and will use every day in our life will it be wise to ignore this uhhh may be but that does not mean we can dismiss AI as over-hyped and pay it no attention at all. The impact of AI-technologies will be significant when applied in the form of augmented intelligence.
We need to be careful of hidden risk of blind trust in AI’s ‘black box’. AI as a Service is been offered in form of ML, NLP, LUIS & DL services. For decades, the dream of creating machines that can think and learn like humans seemed like it would be perpetually out of reach, but now artificial intelligence is embedded in the phones we carry everywhere
Business and financial innovation is starting to focus on two things above all; Artificial Intelligence and Blockchain. Further, the effects that artificial intelligence and its subcategories i.e artificial neural networks, deep learning and machine learning estimates are all of a definite, palpable, empirically ascertainable quality; they are such pleasures, fascinating things, business cost reduction and pains (for some billionaires as they fight with another billionaires) as most of the industries across can feel.
All can observe presence of AI in such a strong way, so that all its technological or moral inferences are open enough at every point to the test of practical experience. Statistical inquiries the biggest enabler for machine learning as the incidence of taxation or of particular taxes, though ideal or even approximate equality of a palpable arithmetical kind is practically unattainable by governments, are not altogether to be put aside.
If we compare the older techniques or examples of intelligence augmentation with new our paper notes electronic and smarter, reminders became memory, watches became smart watches. New intelligence augmentation are like memory augmentation, “extra eyes, ears”, automation behavior patterns, information filtering, problem solving, matchmaking, transactions, introspection, self learning and coding also image, voice and text processing. Behaviour bio metrics are now changing the whole game.
In the 1940s and 1950s, a number of researchers explored the connection between neurology, information technology theory, and cybernetics. In today’s time to establish as a hub for AI development or RnD is not a difficult task as long funding for research work is available at hand.
AI promises benefits, but also poses urgent challenges (not threats, please make a note) that cut across almost all industries and business be it of any nature, i.e software development, technical support, customer care, medicines, law domain or factory / manufacturing work. The need of the hour is to upgrade our skill sets to exploit AI rather than compete with it.AI will help and do betterment for humanity. This kind of revolution tells us where we are heading.
Global competition to attract AI talent and investment; and progress will need to be made on the ethical, legal and regulatory challenges that could otherwise hold back AI. The other side of it for people involved here specifically, those with a high intellectual capacity (hyper brain) possess over excitabilities in various domains that may predispose them to certain psychological disorders as well as physiological conditions involving elevated sensory, and altered immune and inflammatory responses (hyper body).
AI at the core of business of financial-services can give better use in customer-experience functions as such business can expand AI adoption swiftly in response to the economical and industrial invasion and acquire more data, laggards will find it harder to catch up. AI adoption meeting its trepidation despite an overall acceptance of AI, nearly two-thirds of global consumers register concern about AI, although mostly at a moderate level. Top concerns revolve around security and job loss.
AI has evolved from science fiction to a real business. In 2002 during my Master of Computer application degree program I was completely in agreement that AI will always remain phd program or just for researchers only. We all know that there is no definitive single future, but instead, there are an unlimited range of possible or probable futures. AI is coming up strongly via predictive analysis letting us to equip for our future.
This is not to say however that human beings cannot anticipate and influence the future or futures, but to do so with any degree of accuracy, assumptions about future crisis, needs and consequences must be based on a realistic assessment about human nature and behavior, verifiable history, our present conditions.
This was the first serious proposal in the philosophy of artificial intelligence, which can be explained as: a science developing technology to mimic humans to respond in a circumstance. In simple words AI involves machines that behave and think like humans i.e Algorithmic Thinking in general. Computers start simulating the brain’s sensation, action, interaction, perception and cognition abilities.
Small companies will be empowered by AI and large enterprises will become more responsive to their customers. Artificial intelligence is the only technology which is going directly from disappointment to deadly with being beneficial in between. Lemmatization of artificial intelligence has many names i.e. narrow, strong/general or super also its subsets i.e machine learning, machine intelligence, machine consciousness, deep learning etc. Can we really stop this storm of artificial intelligence answer is definitely no as innovations has no stop button.
Can we regulate it; answer is yes for sure it can be regulated. Regulation can define boundaries and limits the usage level of AI in each domain of todays work. Additionally, there are related fields of Artificial Intelligence that study intelligent methods that also learn from data and their environment. Examples include Computational Intelligence and Mateheuristics.
The artificial intelligence has potential, capabilities and limits are for real and machine learning tools, techniques and technologies can be assessed for real in lieu of merely or primarily relying upon wishful thinking which can be dangerous. AI is the fantasy which has morphed into a positive reality, and AI is now a business game-changer. So as a business its impossible to stay away from this.
Any such decision can make business a historical even written in a books (I dont want to name but we all know few handset manufactures who were leaders and now a historical case studies) dangerous. The benefits of AI-powered business conversations are impossible to ignore, and if you are not ramping up new use cases then should be preparing for becoming a chapter in best selling history books.
AI will continue to effectively serve existing markets and business and at same time always eye on for new, and speed its overall pace of innovation & disruption. Its very interesting to see how fast this pace is evolving in 2009 trending companies were those who said “There’s an app for that/this”. In 2016 same companies said “There’s a bot for that”. The list of companies benefiting from AI and industries is growing by the day in addition to the various applications of machine learning.
The most striking AI solutions to FinTech, banks, insurance companies (now called InsureTech) and any other financial services company will probably be those that have the robust & smart financial systems with data security, machine learning (machine conciseness is very far for now) and strong analytics features in place. On usage and acceptance part of AI i.e. AI for intelligence or AI for automation we will probably see both types of services getting emphasis heavily by Fintechs to gain a competitive lead.
Eventually, AI will free up humans for higher-value tasks and drive employment. At the end a powerful position will be created by AI for companies who believe and trust in it. A great value and product propositions will be created to add value for its customers, end users and investors simultaneously. How to use AI is entirely upto us. When artificial intelligence was just science fiction, nobody thought it would become a real force in the business world. Even more growth by adding new subsets in its core i.e. data science, operations, customer success and sales.
Modern mobile payment infrastructure availability – Africa has payment instruments such as mobile wallets for merchant payments, bill payments, prepaid airtime top-up etc. Smart machines producing smart payments with inbuilt payment intelligence. High-powered algorithms are not a new phenomenon in finance though, and for this industry, the name of the game is efficiency and precision which suites more for FinTech due to their fast adopting nature and risk appetite.
Artificial intelligence is a broad and active area of research, but it’s no longer the sole province of academics; increasingly, companies are incorporating AI into their products. For now AI is controlled by humans and I wish in long term it should remain the same i.e. should never starts or think to control us or should not turns out uncontrollable. Baidu’s speech-to-text services are outperforming humans in similar tasks. Amazon is also applying deep learning for best-in-class product recommendations.
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.
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. 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.
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