Top 7 TED Talks about Machine Learning

As we’ve already discussed in the previous articles, Machine Learning is getting more and more traction, visibility, and importance throughout the whole IT industry, and outside of it. Today, we can build our own Machine Learning models and algorithms at home. This means that technology overall is crossing the chasm, and is becoming widely accepted. It is no longer technology for research, but for developing real-world solutions.

For building these models, we can use a variety of technologies, such as: Tensorflow and Python, .NET and JavaScript. We’ve already written about some ideas how can you use Machine Learning in SLA forecasting, and implementation (Using Machine Learning in Service Level Agreements and Data and SLA Forecasting – Implementation and Usage articles).

If you’re just getting into the Machine Learning waters, and want to learn more of it, we’ve added here some of the YouTube links to TED talks about Machine Learning, Deep Learning and AI, to get you going. ☺

TED Talks

Sundar Pichai – How ML and DL improved technologies

Here Sundar (CEO of Google) talks about the progress, and improvements in Machine Learning across the period of time, so that we can get a better understanding of the progress of the Machine Learning. Also, his input and knowledge as a CEO of one of the worlds largest technological companies may shine additional light, especially if you’re just starting your interest in this. Watch the full talk here.

Blaise Aguera y Arcas – How computers are learning to be creative

Another interesting talk from one of the Google engineers which brings us closer to ‘creativity’ of the computers, and the Machine Learning itself. Also here we see an interesting demonstration on how Neural Networks can be trained to run ‘in reverse’ – at least for image generation, rather than recognition. Watch the full talk here.

Fei Fei Li – How we teach computers to understand pictures

Closer overview, and better understanding of how do computers ‘see’, learn, and understand pictures. We are provided here to the insight, of one of the industry’s expertes to how they have built a database of 15 million pictures, and how they have ‘teach’ a computer to recognize them. Watch the full talk here.

Zeynep Tufekci – Machine intelligence makes human morals more important

Very interesting spin on learning, and ‘intelligence’ of the computer, alongside with the progress of it, and some moral and ethical dilemmas that way. Also, here we see, and hear, a good comparison between the AI, its intelligence and ethics. Watch the full talk here.

Dr. Dennis Ong – IoT and Machine Learning – Changing the future

Good talk on implementation, utilization of IoT and Machine LearningL to solve some of the most challenging problems in the cities and municipalities. From his vast experience in Verizon, Nokia, Lucent and AT&T, Dr. Ong provides some suggestions on how to approach, and bridge IoT and Machine Learning to help out in solving of the modern city problems. Watch the full talk here.

Joseph Redmon – How computers learn to recognize objects instantly

Talk that provides a better understanding on how image classification, and recognition work. Also, Joseph demonstrates the ‘YOLO’ (You Only Look Once) system, that can identify objects from images and videos, with extreme speed. Watch the full talk here.

Gary Kasparov – Don’t fear intelligent machines. Work with them.

In this talk, one of the greatest (if not THE greatest) chess master, who had, and lost, memorable match with IBM’s ‘Deep Blue’ computer talks about his overview. He also shares his vision, and prediction, on where the machines can take us in the future, and how they can help us. Watch the full talk here.

Conclusion

Based off of what we wrote about so far, these talks provide further insight, and importance, of the Machine Learning, and its progress. As you can see, people from very different areas do understand it, and utilize it actively (or are planning to). Hopefully, if you’ve just heard of Machine Learning, or are interested to dive into it, this talk will help you a bit more.