AIaaS: Artificial Intelligence – Suddenly it’s everywhere. Are you AI ready if not then be ready to be read in history books. Different AI provider platforms offer a number of styles of machine learning and AI.
Artificial Intelligence & People
AIaaS are we not missing the fact that artificial intelligence is about the people, not the machines. Technology and non-technology companies are now investing and bringing out the real and materialistic values of Artificial Intelligence to the real world. It’s almost after a frustrating and hard work of the decade.
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, and not 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 need or wants can just plug and play this service to get benefits rather than leaving it just a few big hands.
Investment in artificial intelligence is growing fast. Tech giants of AIaaS service providers like Google, Microsoft, Apple and Baidu knew for their dominance in digital technologies globally are spending a couple of tens of billions united state dollars on AI with 90% of this spent on R&D and deployment, and 10% on AI acquisitions.
AI Development across the Globe
It takes money to make money and now a lot of that money is going into the development of artificial intelligence. Any intelligence level surpassing human intelligence is called the superintelligence level which is still 50 years plus ahead.
Machine learning, as enabling palpable technology, received the largest share of both internal and external investment. In Short, get AI ready or ready to be swapped by AI very soon. Before getting into deeper with this amazing term i.e. Artificial Intelligence lets glance through it from the helicopter view perspective.
Anything which needs information processing in the 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.
The animal picture is a dog or cat etc. AI doesn’t need to demystify anything more as its metaheuristic approach has almost overshadowed going to be legacy technologies and computational power of cognitive systems techniques.
Tiny Plastic/Metal Pieces with AI Power
We all are most likely living in the era of most expounding time where are so fortunate to see such a huge transformation of technology from large mainframes to PCs to cloud, from huge bulky big telephone handsets to tiny piece of plastic or metal in our pockets, started from few megabytes of memory to few petabytes also witnessing what is coming our way in years to come. Alan Turing, an early computer scientist who thrown very simple test known as “Turning Test” about artificial intelligence.
In Turning test he proposed a simple test to decide whether a computer had achieved true artificial intelligence only by giving the 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 – AIaaS
is huge and some time can also be very confusing and used interchangeably. We may not be able to define all of them here but let’s 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 chatbots may not come under AI, Data mining, Data Science, Big Data are few to name.
Artificial intelligence is everywhere in the media, its hype is not hidden. Recent comments from few billionaires about AI (some commented in favour 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.
AI still far from reality but not a myth anymore
Separating AI as a myth from reality can be tough at this time but in future, it will come handy and gets easy through the hype and hyperbole that surrounds artificial intelligence. It relates to job elimination perception, a 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.
Still, most of the people think Artificial intelligence is about robots only but the reality we all know is much different. Bots, Robots, AI subsets and Agents (Siri etc) are just getting smarter with this black box 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 for some time yes but 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 the hidden risk of blind trust in AI’s ‘black box’. AI as a Service has 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.
Financial Business innovation & AI
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 other billionaires) as most of the industries across can feel.
All can observe the 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 about equality of a palpable arithmetical kind is practically unattainable by governments, are not altogether to be put aside.
AI will help and do betterment for humanity. This kind of revolution tells us where we are heading. If you’re waiting for A.I, look around you-you will find some form of artificial intelligence at work almost everywhere/ Though its pinnacle will take around 50 or more years; machine consciousness is indomitable will happen sooner or later. PayPal is using deep learning as a best-in-class approach to block fraudulent payments and has cut its false-alarm rate in half.
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 and not compete with it.
Artificial Intelligence As A Transformative Technology
Please note: I am the big fan, follower and lover of everything about AI which can bring only the best things as just good enough. Accenture recently published research showing that AI has the potential to boost corporate profitability by an average of 38 per cent, and lead to an economic boost of $US14 trillion across 16 industries in 12 countries by 2035.
In the 1940s and 1950s, a number of researchers explored the connection between neurology, information technology theory, and cybernetics. In today’s time to set up as a hub for AI development or RnD is not a difficult task as long funding for research work is available at hand. 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.
AI at the core of the business of financial-services can give better use in customer-experience functions as such business can expand AI adoption swiftly in response to the economic 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’s degree program, I completely agreed that AI will always stay PhD program or just for researchers only. We all know that there is no definitive single future, but instead, there is an unlimited range of possible or probable futures. AI is coming up strongly via predictive analysis letting us equip for our future.
This is not to say however that human beings cannot expect 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 behaviour, verifiable history, our present conditions.
Impact of AI on confidentiality, integrity and availability
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. Lemmatisation 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 have no stop button?
Can we regulate it; the answer is yes for sure it can be regulated. Regulation can define boundaries and limits the usage level of AI in each domain of today’s 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 Metaheuristics.
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 the business a historical even written in a book (I don’t want to name but we all know few handsets manufacturers 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 they should be preparing for becoming a chapter in best-selling history books.
How to use AI is entirely up to 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.
Required Business Capabilities
AI will continue to effectively serve existing markets and business and at the same time always eye on for new, and speed its overall pace of innovation & disruption. It’s 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. In 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.
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. AI is controlled by humans and I wish in long-term it should stay the same. AI should never control us or should not turns out uncontrollably. Baidu’s speech-to-text services are outperforming humans in similar tasks. Amazon is also applying deep learning for best-in-class product recommendations.
Points to Note:
All credits if any remains on the original contributor only. AI is a bundled technology here which is powering every single business.
Books & Other Material Referred
- Open Internet & Live conferences feedback and interactions.
- AILabPage (group of self-taught engineers) members hands-on lab work.
Feedback & Further Question
Do you have any questions about Deep Learning or Machine Learning? Leave a comment or ask your question via email. Will try my best to answer it.
Conclusion – At end allow me to say AI is a friendly technology that is here. AI will get into our lives and businesses without fail and all future products. Artificial intelligence is the craze in silicon valley, but on Wall Street, well, there’s a lot of scepticism. Unfortunately, so far only intelligence got artificial but the risk remains for real and natural. Natural language generation can create, write and tell your business stories but still raise hands when risk overtakes.
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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Categories: Artificial Intelligence