Lifeboat Foundation

You don’t have to be a gambler to appreciate the complexities of the card game Texas Hold ‘Em. It involves a strategy that needs to evolve based on the players around the table, it takes a certain amount of intuition, and it doesn’t require the player to win every hand. Just a few days ago, an artificial intelligence (AI) algorithm named Libratus beat four professional poker players at a no-limit Texas Hold ‘Em tournament played out over 20 days.

If you have even the slightest understanding of how to write code, you would realize that it is impossible to actually code a software program to do that with such “imperfect information”. The AI algorithm did exceptionally well and was utilizing strategies that humans had never used before. Professional poker players are in no danger of losing their jobs, but the incredible capabilities of what AI is mastering these days should make everyone wonder just how safe their jobs actually are.

Let’s take the $3 billion medical imaging market. It’s no secret that AI is now performing certain medical imaging tasks better than human doctors. Pundits say “well, people will always trust a human doctor over an AI” and the answer we’d have to that is “not if the AI is going to give a more accurate answer “. It’s only a matter of time before every X-ray machine is connected to the cloud and one human doctor per hospital puts his hand on your shoulder when he reads you the output from the AI algorithm. Kind of like this:

Continue reading “9 Artificial Intelligence Startups in Medical Imaging” »

If we ever want future robots to do our bidding, they’ll have to understand the world around them in a complete way—if a robot hears a barking noise, what’s making it? What does a dog look like, and what do dogs need?

AI research has typically treated the ability to recognize images, identify noises, and understand text as three different problems, and built algorithms suited to each individual task. Imagine if you could only use one sense at a time, and couldn’t match anything you heard to anything you saw. That’s AI today, and part of the reason why we’re so far from creating an algorithm that can learn like a human. But two new papers from MIT and Google explain first steps for making AI see, hear, and read in a holistic way—an approach that could upend how we teach our machines about the world.

“It doesn’t matter if you see a car or hear an engine, you instantly recognize the same concept. The information in our brain is aligned naturally,” says Yusuf Aytar, a post-doctoral AI research at MIT who co-authored the paper.

Continue reading “MIT and Google researchers have made AI that can link sound, sight, and text to understand the world” »

Google’s “MultiModal” can manage eight tasks at once.

Geoffrey Hinton, a scientist at the heart of artificial intelligence’s recent breakthroughs, has helped make Toronto a leading research location.

Kentucky-based software company Advanced Solutions has developed what it calls the world’s first 3D human tissue printer that operates on a six axis robot.

Called the BioAssemblyBot, the machine is the second generation of 3D printers focused on producing biomedical materials intended to revolutionizing healthcare.

The goal is to 3D print human organs, Advanced Solutions president and CEO Michael Golway told CNBC on Friday.

Continue reading “This robot is learning how to print a human organ” »

“The future of gamification is nearly here with virtual and augmented reality features and the addition of artificial intelligence. These elements can personalize the experience and continually increase the challenge involved to keep the audience hooked. “ https://www.forbes.com/sites/theyec/2017/06/22/how-to-add-ga…8cd53b5b3b

My mission statement is to push the boundries of the new tech tools that we are being given in the UX/ UI and prototyping design fields. This week I have been experimenting with Augemented and Virtual Reality. During the Summer Solstice I visited the Crystal Palace Dinosaurs and tested out a few augemented reality offerings using augmented reality dinosaurs to complement the existing dinosaur scenery and built the following website to include my examples and also to showcase A-Frame and Sketchfab which will be producing VR within websites which will be used for e-commerce and online shopping soon.

https://bcgallie.wixsite.com/jurassicpalace

This autonomous car is a hospital on wheels.

Ride sharing and self-driving vehicles will redefine our relationship with cars. Auto makers and startups are already gearing up for the change.

Deep learning has transformed the field of artificial intelligence, but the limitations of conventional computer hardware are already hindering progress. Researchers at MIT think their new “nanophotonic” processor could be the answer by carrying out deep learning at the speed of light.

In the 1980s, scientists and engineers hailed optical computing as the next great revolution in information technology, but it turned out that bulky components like fiber optic cables and lenses didn’t make for particularly robust or compact computers.

In particular, they found it extremely challenging to make scalable optical logic gates, and therefore impractical to make general optical computers, according to MIT physics post-doc Yichen Shen. One thing light is good at, though, is multiplying matrices—arrays of numbers arranged in columns and rows. You can actually mathematically explain the way a lens acts on a beam of light in terms of matrix multiplications.

Continue reading “Deep Learning at the Speed of Light on Nanophotonic Chips” »