Will the confluence of IoT and AI redefine the world?

[ CrossPost from Authros Post ]

When I finished my studies in Physics I had doubts about how I should guide my professional career. Two areas interested me about the rest: Telecommunications and Artificial Intelligence (). I chose the first for purely monetary short-term reasons. But I never leaved the second, and finally now, more than 20 years later I have the opportunity of work with the two thanks to the Internet of Things 4.0.

As I already reflected in my previous article “From the IoT Evolution to the Revolution of the Cognitive Age”, the Internet of Things is changing the face of society and the industry in a profound manner, but with the introduction of AI, consumers, enterprises and governments will be able to embark on projects never thought possible before.

For many years we will find a mix of unconnected machines, connected machines and AI enabled machines. Our challenge is to make them all collaborate under ethical principles avoiding using AI for creating psychopath and sociopath machines.

Let´s start connecting every machine

Every machine that can be connected, will be connected. Machine-to-machine communication (M2M) has been building a promising basis for innovative and disruptive models that will open up new opportunities. Take a look at “How Do Machines Talk To Each Other?  for a simple explanation about connected machines.

According with some estimations, 8.4 billion objects had been connected at the end of 2017, a 30% increase with respect to 2016. Experts from Cisco expect 50 billion devices to be interlinked via the by 2020. The potential number of networkable objects has been estimated at 1.5 trillion. This includes computers, tablets and smartphones but also wearables, entertainment electronics, domestic appliances, vehicles and industrial machinery. It is evident that connected machines bring an immediate benefit to the owner. Connected machines provide the agility needed to make smarter decisions and open up new business opportunities.

The goal of IoT: Connect every machine to everyone, everything, everywhere... in real time

Next Step, get value from data collected from Machines

But connecting machines itself is only an intermediate stage. The continual flow of information that connected machines make available permits management of the machine’s entire life cycle, from the installation stage to that of maintenance and up to replacement.

For machines owners, this translates to guaranteed system operation, with a development in the business model for the machines, which moves on from the purchase of a physical item to the purchase of the expected benefit. The provision of a suitable machines, its appropriate installation and its corresponding maintenance are entirely the responsibility of the supplier.

A key aspect in achieving this goal is data processing: the volumes gathered are such that the provision of valuable services is impossible without adequate information management.

Data processing involves an approach with several stages:

1.      Descriptive analytics

2.      Predictive analytics

3.      Prescriptive analytics

4.      Automated analytics

As IoT devices are generating a large amount of data and we want to do the analysis of the data, we need machine learning to find out the insight of the data or analyze the data.

New expertise and new tools are therefore needed to finalise the information processing procedure: new data analyst figures and SW tools to implement the machine learning process enter the process decisively to create valuable services based on the data gathered. So much innovation must in any case be combined with solid applicative expertise and specific technical expertise in the machines analysed. Only synergy between these figures will permit the creation of valuable new services.

For machine manufacturers, to capture and process machine data in real time will allow them to more freely and manage their machine's health remotely for better after-sales service. Their customers will also enjoy a better user experience, and be able to easily monitor and control of their information in real time from anywhere.

Connected machines talking to each other and with humans will dramatically change the way how we will live and work.

The time of machines with Artificial Intelligence is arriving

Artificial intelligence and the Internet of Things become even more powerful together. AI and IoT are symbiotic, AI makes the machine learn from its experiences and manage with new data. I am not exaggerating when I say that AI is the best friend of the IoT.

As IoT scales to millions and millions of increasingly intelligent and interactive devices all around us collecting, distributing, and processing data in a in a combination of fog and cloud computing, many observers believe that AI offers the best chance of quickly and accurately making sense of all that data and putting it to work solving real-world problems. Data life cycles, flow, data classifications, reporting, and countless aspects of IoT will be dictated by the intelligence of AI.

A study reported in Science magazine shows that “self-taught AI is better than doctors at predicting heart attacks” because of the complexity of risk factors involved.

Both AI and IoT are still in the early stages of their development cycles, saddled with immature , limited tooling, and still-emerging use cases often struggling to demonstrate enough real business value to justify their investments and live up to their advance billing.

In the short term, AI can help design more efficient IoT networks, ensuring there’s enough capacity without overbuilding and enhancing .

There are many decisions made by AI engines that need to be fed back quickly and accurately to the IoT devices. The potential advantages and benefits of IoT and AI are unlimited.

The confluence of Internet of Things and Artificial Intelligence is set to redefine the world.

A with many types of Machines

An intelligence quotient (IQ) is a total score derived from several standardized testsdesigned to assess human intelligence. In humans, scores from intelligence tests are estimates of intelligence. IQ essentially reflects how well we did on a specific test as compared to other people of our age group. While IQ can be a predictor of things such as academic success, you know that it is not necessarily a guarantee of life success.

If we translate this concept to the Machines world, we must think that not all machines will have the same Machine intelligence quotient (MIQ). In this article dated 2002, the authors analysed those engineering systems or products that were said to be intelligent and extracted four common constructs, each of which consists of several variables. Based on them, they suggested two typical models, which are represented as entities in three-dimensional construct space. In order to find a number, called machine intelligence quotient (MIQ), they adopted two fuzzy integrals, Sugeno fuzzy integral and Choquet fuzzy integral.

An update and consensus about MIQ is necessary. At the end of the day we all will want to compare the intelligence of our machines with the machines our competitors, family and friends.

In the article “Understanding the four types of AI, from reactive robots to self-aware beings” the author suggest that “We need to do more than teach machines to learn. We need to overcome the boundaries that define the four different types of artificial intelligence, the barriers that separate machines from us – and us from them”.

In spite we are probably far from creating machines that are self-aware, researchers will be able to design or evolve machines that are more than exceptional at classifying what they see in front of them.

Must we fear that in a not distant future, an AI system will be able to design other AI systems?

 We will walk with AI machines that have consciousness, AI machines that can form representations about themselves. We must avoid fearing walk with AI machines and for that all AI Systems must have consciousness. 

The challenge of living in a new brave world of AI machines and Enhanced humans

Humans are going to be artificially intelligent”. That's the prediction of Ray Kurzweil, director of engineering at Google. Kurzweil predicts that humans will become hybrids in the 2030s. That means our brains will be able to connect directly to the cloud, where there will be thousands of computers, and those computers will augment our existing intelligence. He said the brain will connect via nanobots -- tiny robots made from DNA strands.

A prediction that is line with my article “Bring Your Own Cyber Human (BYOCH) – Part 1: Augmented humans”.

As we humans had formed societies that allowed us to have social interactions, AI systems will form societies that allow them to have cyber-social interactions. 

If AI systems are indeed ever to walk among us, they’ll have to be able to understand that each of us has thoughts and feelings and expectations for how we’ll be treated. And they’ll have to adjust their behaviour accordingly.

We are in the dawn of a new cyber society. A society where organizations shall design plans to utilize the unique skillsets of both AI Systems and humans. A society where Humans and AI systems shall work and live together and without fear. A society where humans shall use newfound time and freedom to advance strategic skills and individual talents.


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