Lifeboat Foundation

Learn how to incorporate AI into real world projects using the latest tools and applications, and how AI can to add value to your business.

It’s finally the last month of the year and you know what that means: the holiday flood known as Christmas. Celebrated by many, it’s a time of the year where presents are exchanged and songs are sung. Only, this year, one of those songs won’t be sung (let alone written) by a human being. Nope, this time an artificial intelligence is giving it a go!

In the spirit of Christmas, listen to the carolling tune of an artificial intelligence as it attempts to capture the very essence of what makes this holiday so beloved.

Deep learning has been making it possible for powerful machines to approximate and imitate abilities and techniques once thought to be uniquely human. Mathematicians have struggled to explain how they work so well and may now get some answers by looking outside mathematics and into the nature of the universe.

Microsoft said Thursday it was adopting a set of ethical principles for the use of its facial recognition technology, and urged the government to follow its lead with regulations barring unlawful discrimination and focusing on transparency.

In a blog post, Microsoft president Brad Smith pushed for the government, as well as tech companies, to regulate facial-recognition technology and ensure it “creates broad societal benefits while curbing the risk of abuse.”

“The facial recognition genie, so to speak, is just emerging from the bottle,” Smith said in the post. “Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues.”

Continue reading “Microsoft president calls for government regulation of facial-recognition technology to ‘ensure that the year 2024 doesn’t look like a page from the novel 1984’” »

This robotic strawberry harvester saves farmers hours of time and effort.

Over the past few years, classical convolutional neural networks (cCNNs) have led to remarkable advances in computer vision. Many of these algorithms can now categorize objects in good quality images with high accuracy.

However, in real-world applications, such as autonomous driving or robotics, imaging data rarely includes pictures taken under ideal lighting conditions. Often, the images that CNNs would need to process feature occluded objects, motion distortion, or low signal to noise ratios (SNRs), either as a result of poor image quality or low light levels.

Although cCNNs have also been successfully used to de-noise images and enhance their quality, these networks cannot combine information from multiple frames or video sequences and are hence easily outperformed by humans on low quality images. Till S. Hartmann, a neuroscience researcher at Harvard Medical School, has recently carried out a study that addresses these limitations, introducing a new CNN approach for analyzing noisy images.

Many years after, the young dreamer has surpassed his imagination. He is now a lead engineer on InSight — NASA’s spacecraft which recently landed on Mars. He is in charge of the mission’s robotic arm mechanism.

China has launched the first mission to land a robotic craft on the far side of the Moon, Chinese media say.

The Chang’e-4 mission will see a static lander and rover touch down in Von Kármán crater, located on the side of the Moon which never faces Earth.

The payload blasted off atop a Long March 3B rocket from Xichang Satellite Launch Center.

Artificial intelligence (AI), machine learning and deep learning have made huge strides in 2018. In this post we look at some of the key AI predictions for 2019, where is will be used, how it will make the biggest impact, as well as the key challenges we have to address.