Monthly Archives: February 2020

Dr. Luis Perez-Breva

Luis Perez-Breva is a Massachusetts Institute of Technology (MIT) professor and the faculty director of innovation teams at the MIT School or Engineering. He is also an entrepreneur and part of The Martin Trust Center for MIT Entrepreneurship. Luis works to see how we can use technology to make our lives better and also on how we can work to get new technology out into the world. On an episode of the AI Today podcast, Professor Perez-Breva managed to get us to think deeply into our understanding of both artificial intelligence and machine learning.

Are we too focused on data?

Anyone who has been following artificial intelligence and machine learning knows the vital centrality of data. Without data, we cant train machine learning models. And without machine learning models, we dont have a way for systems to learn from experience. Surely, data needs to be the center of our attention to make AI systems a reality.

However, Dr. Perez-Breva thinks that we are overly focusing on data and perhaps that extensive focus is causing goals for machine learning and AI to go astray. According to Luis, so much focus is put into obtaining data that we judge how good a machine learning system is by how much data was collected, how large the neural network is, and how much training data was used. When you collect a lot of data you are using that data to build systems that are primarily driven by statistics. Luis says that we latch onto statistics when we feed AI so much data, and that we ascribe to systems intelligence, when in reality, all we have done is created large probabilistic systems that by virtue of large data sets exhibit things we ascribe to intelligence. He says that when our systems arent learning as we want, the primary gut reaction is to give these AI system more data so that we dont have to think as much about the hard parts of generalization and intelligence.

Many would argue that there are some areas where you do need data to help teach AI. Computers are better able to learn image recognition and similar tasks by having more data. The more data, the better the networks, and the more accurate the results. On the podcast, Luis asked whether deep learning is great enough that this works or if we have a big enough data set that image recognition now works. Basically: is it the algorithm or just the sheer quantity of data that is making this work?

Rather, what Luis argues is that if we can find a better way to structure the system as a whole, then the AI system should be able to reason through problems, even with very limited data. Luis compares using machine learning in every application to the retail world. He talks about how physical stores are seeing the success of online stores and trying to copy on that success. One of the ways they are doing this is by using apps to help customers navigate stores. Luis mentioned that he visited a Target where he had to use his phone to navigate the store which was harder than being able to look at signs. Having a human to ask questions and talk to is both faster and also part of the traditional experience of being in a brick and mortar retail location. Luis says he would much rather have a human to interact with at one of these locations than a computer.

Is the problem deep learning?

He compares this to machine learning by saying that machine learning has a very narrow application. If you try to apply machine learning to every aspect of AI then you will end up with issues similar to the ones he experienced at the Target. Basically, looking at neural networks as a hammer and every AI problem as a nail. No one technology or solution works for every application. Perhaps deep learning only works because of vast quantities of data? Maybe theres another algorithm that can generalize better, apply knowledge learned in one domain to another better, and use smaller amounts of data to get much better quality insights.

People have tried recently to automate many of the jobs that people do. Throughout history, Luis says that technology has killed businesses when it tries to replace humans. Technology and businesses are successful when they expand on what humans can do. Attempting to replace humans is a difficult task and one that is going to lead companies down the road to failure. As humans, he points out, we crave human interaction. Even in the age where people are constantly on their technology people desire human interaction greatly.

Luis also makes a point that many people mistakenly confuse automation and AI. Automation is using a computer to carry out specific tasks, and it is not the creation of intelligence. This is something that many are mentioning on several occasions. Indeed, its the fear of automation and the fictional superintelligence that has many people worried about AI. Dr. Perez-Breva makes the point that many ascribe human characteristics to machines. But this should not be the case with AI systems.

Rather, he sees AI systems more akin to a new species with a different mode of intelligence than humans. His opinion is that researchers are very far from creating an AI that is similar to what you will find in books and movies. He blames movies for giving people the impression of robots (AI) killing people and being dangerous technologies. While there are good robots in movies, there are a few of them and they get pushed to the side by bad robots. He points out that we need to move away from this pushing images of bad robots. Our focus needs to be on how artificial intelligence can help humans grow. It would be beneficial if the movie-making industry could help with this. As such, AI should be thought of as a new intelligent species were trying to create, not something that is meant to replace us.

A positive AI future

Despite negative images and talk, Luis is sure that artificial intelligence is here to stay, at least for a while. So many companies have made large investments into AI that it would be difficult for them to just stop using them or to stop the development.

As a final question in the interview, Luis was asked where he sees the industry of artificial intelligence going. Prefacing his answer with the fact that based on the earlier discussion people are investing in machine learning and not true artificial intelligence, Luis said that he is happy in the investment that businesses are making in what they call AI. He believes that these investments will help the development of this technology to stay around for many years.

Once we can stop comparing humans to artificial intelligence, Luis believes that we will see great advancements in what AI can do. He believes that AI has the power to work alongside humans to unlock knowledge and tasks that we werent previously able to do. The point when this happens, he believes, is not that far away. We are getting closer to it every day.

Many of Luiss ideas are contrary to popular beliefs by many people who are interested in the world of artificial intelligence. At the same time, the ideas that he shares are presented in a very logical manner and are very thought-provoking. Time will tell if these ideas are in fact correct.

Go here to see the original:

This AI Researcher Thinks We Have It All Wrong - Forbes

By Shakiel Mahjouri.15 hours ago

Melissa McCarthy has made a career out of being herself and she advises others to do the same.

McCarthy, 49, covers this weeks issue ofPeople. The Life of the Party actress celebrates her own unique qualities and discusses life with her daughters.

RELATED: Melissa McCarthy Plays Epic Prank On Unsuspecting Employees

How boring would it be if we were all the same? Were drawn to each other because of all our weird, unexplainable character quirks, the Little Big Shots host says. Life is short. Just be yourself!

McCarthy shares two daughters Vivian, 12, and Georgette, 10 with husband Ben Falcone. A big part of the actresss parenting has been to foster self-confidence.

My oldest has a really good head on her shoulders, but kids that age are always thinking, Does someone think I look silly? I tell them its all silly and were all idiots! she says. The second you embrace that and have realfriends, you realize thats the fun part.

RELATED: Melissa McCarthy Feels A Little Bit Sorry For Trolls

Who is the dumbest and the goofiest? McCarthy asks. Those are the friends youll have all your life.

McCarthy next stars in her husbands films Superintelligence opposite James Corden, and Thunder Force with Octavia Spencer.

Link:

Melissa McCarthy Shares Advice With People: Life Is Short, Just Be Yourself - ETCanada.com

Driven by technology, the world is evolving at a rapid rate, with an increase in accessibility to all. Technology has become the fabric of our new reality, and the Australian mining industry is no different.

In Australia, businesses are accelerating the adoption of machines, robotics and artificial intelligence (Al), with 80 per cent of companies reporting AI is starting to make a presence in some form. Weve already seen great strides in mining, with autonomous transport in the form of trucks and trains, as well as self-healing equipment in plants and mining sites which proactively interact and work with technicians.

According to research by the World Economic Forum, 54 per cent of employees will need to be upskilled or reskilled by 2022, and by 2025, machines will be performing more than half of the work tasks, compared with the 29 per cent they do today.

AI gives humans superpowers in the form of amplification, interaction and embodiment. The way work is performed, where it takes place, who is responsible for tasks and how we reward employees is being reimagined.

By 2022, 58 per cent of tasks will be performed by humans and 42 per cent by machines and algorithms. Its predicted by 2021 there will be 7.5 billion active bots working in tandem with humans.

However, it is no longer a matter of Human vs Machines but rather Human + Machines.

Industries have successfully used technology and automation to improve efficiencies for decades. Thats nothing new. But the emergence of human and machine collaboration is.

Humachines (not to be mistaken with cyborgs), is a form of superintelligence which combines the smarts of big data and machine learning with a humans analytical, creative and intuitive mindset. Already, 49 per cent of business leaders believe its going to be the answer to achieving their strategic objectives and push the boundaries of how we work.

In fact, its expected AI enabled human and machine interfaces will replace one third of applications by 2024. Additionally, 49 per cent of business leaders believe the Human + Machine collaboration is important to achieve their strategic priorities. With humachine intelligence set to grow within the next five years, the Western Australian resources and mining industry has much to gain. At a time when the industry is going through unprecedented change, the opportunity to make a positive impact on climate sustainability, safety and the elimination of waste through the collaboration between human and machine is immense. Experts in human and technology collaboration, Accenture, calls this Triple Zero. This includes:

So, what does the future roadmap look like for the human workforce?

Its about redefining roles, exploring new business models and adapting to a more digitally savvy and fluid workforce, where we harness the power of machines to amplify human capabilities on the mine site. Machines are not just technology driven tools anymore, they are the next generation of employees.

Accenture Australia & New Zealand Natural Resources Lead Ann Burns said this wasnt a man versus machine scenario, its about how the two could co-exist and accelerate productivity in tandem.

Business leaders who look to understand and embrace the power of human and machine will find innovation will be rapid, and it will present new opportunities to make things better, easier, faster, smarter, safer and more sustainable.

For the mining industry, it will enable companies to tap into machine and human collaboration as the reality to their future success, unlocking new growth for WA and Australia.

Accentures Perth innovation hub works with global companies from all the resources and energy sectors to drive transformation and real innovation for them to grow at pace and scale. Visit the Perth Innovation Hub website to find out more.

Original post:

Hu+Machine: collaboration key to success for Australian mining - The West Australian