Artificial Intelligence (AI) seen by Sudha Jamthe and the BTS students

February 9, 2016
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Nine hours’ time between San Francisco and Barcelona was not an issue, when Sudha Jamthe, Ex-Mobile Business Leader of Ebay, IoT author and member of the Strategic Advisory Board of Barcelona Technology School (BTS), shared her thoughts with the BTS students in a Hangouts meeting about her last article in TechCrunch “Breaking the barrier of humans and machines”.

Sudha came up with the idea of artificial intelligence (AI) article, stating that this is an evergreen topic and when it comes to new technology related to it there will always be discussion. She explained that Alexa, an Amazon Echo device which basically can respond to almost every question you made “her”, caused her curiosity due the accuracy of some of “her” answers and led Sudha to learn Machine learning, on which Alexa is based. Or like Amy, an ai.com algorithm that has the capability to organize your daily schedule, participating actively in your day to day activities.

Sudha-J.-and-BTS-students-edit

Due this technology in constant evolution, she wrote the article trying to respond somehow what the devices can learn?

Machine learning
Nowadays, every big company, such as Google, Amazon, Facebook, etc. is learning “Machine learning”, but they’re applying it differently. The base is to understand the customer behavior and in this way explain the computers all possible conditions to act. An important artificial intelligence concept “Deep learning” states that computers can come up with their own “rules”, learning them from a set of algorithms, fed by a large supply of data, allowing “them” to make inferences about that data and to determine all kind of possible situations. This kind of information led machines to learn to make decisions at the most opportune moments.

In relation to this, we can see the close relationship between machine learning and Internet of Things (IoT). As the quick and constant expansion of devices connected to the IoT continues, the quantity of data being created by them will increase in an exponential level; in order to review and understand this data, the machine learning comes across to take advantage of the hidden insights it holds, to find patterns that can be learned from so better decisions can be made.

The collected data combined with AI, makes increasingly life easier with devices that think, before you do, in all possible conditions through data.

An example of this is Self Driving Car, with rules of what can or what cannot happen on the road. In the automotive industry, similar systems are being created, adapting situations to the driving context in which even the state of mind of the driver is taken into consideration to prevent accidents; the system would alert the next drivers to be cautious on an atypical behavior some other driver is having.

Facial recognition is one of the most used methods in the state of mind detection; in fact, more than a thousand millions of facial expressions are used to program algorithms capable to recognize and classify basic emotions, such as anger or joy, with an accuracy of up to 90%. Facial recognition method is also being experimented by some retail stores to customize the client experience, being possible to recognize a female from a male, age profile, etc.

These are just some examples of why learning “machine learning” is an exciting subject.

How is this applied in companies?
Companies are driven to what they think is good for the customer, in order to keep them satisfied and build a profitable relationship with them.
The normal process that companies use is based in the knowledge of the human talent of each key department. There is a team behind the release of every product, doing the process “manually” based in previous data and experiences, focused on obtaining “growth” for the business. But as Sudha states, some things could happen in the process, for example, maybe a feature that is good for America is not good for Europe or Asia and at that moment is when the process gets complex.

There is the failure possibility in every business process. In this way, Machine learning is a solution to avoid or minimize, at least, the risk for the company and optimize those processes.

Singularity
In a world where computers are taking more protagonism, it comes a common question related to the power that these machines are having on humans. One of the students came up with the example that maybe computers can turn into a kind of “big brother”, as they are having now so much information about our lives; this led us to think that we are being monitored somehow.
About this “fragile” barrier between humans and computers, we learnt from Sudha the Singularity concept, a hypothetical era where those boundaries of human and machine will blur, computers would become smarter than us and they will stop listening our commands.

Futurists such as Ray Kurzweil, author of The Singularity is Near, have predicted that in a “post-Singularity world”, humans would live in virtual reality, indistinguishable from normal reality. Kurzweil predicted that the Singularity will come to pass by 2045, a time when machine will be more powerful than the human brain; at that time, we would have expanded the intelligence over “human machine civilization”. If you want to listen to Kurzweil, explaining the Singularity theory, go to this link:

Even though fast growing advances in technology are making machines powerful, these still have to answer to humans, they remain being tools, smart tools. In Machine learning/deep learning concept, Sudha states that is an important human exercise to feed the data system of these machines, so logically there is nothing that can give consciousness to them yet. But according to her vision, that futuristic world where machines are in control is a non-scary and also cool world. She said we really are not afraid of computers, we are afraid of the persons who are behind them. If society become in anarchy where we do not care about humans anymore, and let things happen; then the problem would be with the social structure not with machines/robots.

Machine learning and education
A student question was related to how machine learning can help students nowadays and how this helps a social cause as education.

Sudha explained that Machine learning is a tool that can be adapted to any cause. In fact, her recommendation for the students is to start learning about the subject, because besides of helping them to improve their education and get jobs thanks to this knowledge, it is a tool that will allow them to create interesting ideas and take them to the next level.

As an example of innovation and creativity adapted to society, we have “Smart cities”, and Barcelona is, certainly, one of them. In fact, the city is generating an entrepreneurial and dynamic ecosystem in constant evolution.

Everyday new startups, acceleration programs, venture capital entities, coworking spaces, among others, choose Barcelona to develop its activity. This ecosystem is generating demand of new talent with digital knowledge and skills and due this, the Master in Digital Solutions Development of Barcelona Technology School, of which Sudha is active member, is a program with the objective to prepare talent ready to drive this digital transformation.

As Sudha stated, nowadays, there are a lot of efforts going on to improve education. The main objective is to make it feasible and accessible for everybody worldwide.

Impact of technology in Medicine:
During the conversation, another doubt of a futuristic world came up from another student: How it would be the impact of technology on medicine? Somehow machines would be able to learn more about us like a doctor?

Sudha explained us that Medicine is a complex matter when speaking about technology; in fact in her book Internet of things (IoT) Business Premier, she dedicates a complete chapter to the health care field. There is a tendency to see everything scary or exciting; there are futuristic ideas in which Doctors, nurses, etc. will be replaced by robots.

In a medical environment is normal, as human, to be scared or to speculate about certain conditions. At that moment, the human contact/relationship with another person is somehow essential, but nowadays artificial intelligence is having more protagonism in the medicine field.

In an article published on the Mobile Health Global web, titled “Will robots replace Doctors?”, Doctor Bertalan Meskó, medical futurist and author of The Guide to the Future of Medicine, indicates that with Artificial intelligence (AI) they could take better decisions, they could determine the best treatment after a diagnosis. Artificial Intelligence is making great progress, but still the role of a doctor is irreplaceable.
In fact, these machines, which are also called cognitive computers, have the advantage of allowing the doctor to focus all of his or her attention on the patient, instead of having to concentrate on finding information. Therefore, to combine human and artificial intelligence is key; Meskó defends the idea of “the best potential pair is a human with technology.”

Sudha’s gave us a clear example of this medical improvement, telling us about a pill, a small biodegradable sensor that gets the vital signs, communicating all the info to an app, a tool for Doctors to get better diagnosis. It’s true that there is a lack of information while going to have a checkup, we do not use to tell everything to the Doctor, but this small device avoids that error factor. This has been medically approved in the United States.

As you can see Sudha is passionate about technology, and everything is new in the subject catch her eye. She is especially passionate about Internet of Things (IoT); in fact her second book Internet of things Business Premier, in which she makes a deep analysis of how industries can use IoT for business, has been published this December.

Technology is, without a doubt, a topic extended to all stages nowadays. When speaking about the subject, there are so many things going on that it is almost impossible to find something not related to it. As Sudha told us, is up to each person how to apply technology today, to be active in this technological era and take those ideas we are passionate about, to the next level.

Sudha Jamthe
Sudha Jamthe is a globally recognized entrepreneurial mobile product leader, futurist and instructor at Stanford. She loves guiding the next wave of technology innovations to form entrepreneurial ecosystems and new business disruptions. Sudha is a champion for girls who code.
She has been a venture mentor at MIT and Director at Bay area, Facebook, Twitter, Pinterest and Google+ meetups. She also actively contributes to TechCrunch, Mashable, Gigaom and Venturebeat. She sits on the Advisory Board of Blockhain University and Barcelona Technology School.
She is the author of two IoT books: “IoT Disruptions” and “The Internet of Things Business Primer”.

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