Lifeboat Foundation

What deep learning algorithms can tell us about the visual narratives of the world’s news imagery, from depictions of violence to the importance of people to visual context – a look inside what we see about the world around us.

Imagine this car requiring no wheels as it hovers across the roads/ streets and no more flat tires.

A regime of cramming and testing is crushing young people’s instinct to learn and destroying their future.

Wall Street is a Darwinian battle for the almighty dollar. But Richard Craib thinks his AI-powered hedge fund will soar if everyone can just get along.

While many worry about artificial intelligence, Samsung believes it could be an important part of the future. Or at least that is what the latest rumors suggest.

From digital currency to machine learning, the financial industry is being rocked by exponential technologies. Blockchain, artificial intelligence, big data, robotics, quantum computing, crowdfunding, and computing systems are allowing startups to solve consumer needs in new ways.

The downfall of the world’s largest institutions may not be imminent, but these new technologies are breaking up the previously rock solid foundation of finance, and allowing the fintech world to spring through the cracks. What’s happening now will rewrite the future of finance for years to come. By recognizing this reality and planning for it now, financial professionals can learn to thrive in an increasingly uncertain global economy.

Continue reading “Financial Leaders: Make Your Mark on the Future at Exponential Finance” »

Recently, I saw an article making big deal that a robot can now write. Ok, it only took us 253 years to enhance it a little. Meet the Automaton from Sweden that could write and was designed to look like a young boy. Made in 1774 and still writes today.

We had Automaton that did this since 1774. 1st one was from Sweden and made in 1775.

Continue reading “‘The Writer’ Automaton” »

Wonder what Google thinks about this version of a robot playing Chess from 1769. The point is, we really have struggled in AI particularly robotics for over 250 years.

As you can hear I’m not a native speaker. Please execuse grammatical and pronunciation mistakes.

Continue reading “The Chess Turk explained” »

The human brain is nature’s most powerful processor, so it’s not surprising that developing computers that mimic it has been a long-term goal. Neural networks, the artificial intelligence systems that learn in a very human-like way, are the closest models we have, and now Stanford scientists have developed an organic artificial synapse, inching us closer to making computers more efficient learners.

In an organic brain, neuronal cells send electrical signals to each other to process and store information. Neurons are separated by small gaps called synapses, which allow the cells to pass the signals to each other, and every time that crossing is made, that connection gets stronger, requiring less energy each time after. That strengthening of a connection is how the brain learns, and the fact that processing the information also stores it is what makes the brain such a lean, mean, learning machine.

Neural networks model this on a software level. These AI systems are great for handling huge amounts of data, and like the human brain that inspired them, the more information they’re fed, the better they become at their job. Recognizing and sorting images and sounds are their main area of expertise at the moment, and these systems are driving autonomous cars, beating humanity’s best Go players, creating trippy works of art and even teaching each other. The problem is, these intelligent software systems are still running on traditional computer hardware, meaning they aren’t as energy efficient as they could be.

Continue reading “Artificial synapse bridges the gap to brainier computers” »