Lifeboat Foundation

Google’s Arts and Culture vertical has been known to release fun apps and tools to help people engage with art and history. In 2018, it launched a feature to let you find your fine art doppelganger by taking a selfie, and more recently it added ways for you to apply filters to your photos to take on the style of masters like Van Gogh or Da Vinci. Now, the company is launching a web-based AI tool to let users interact with ancient Egyptian hieroglyphs and also help researchers decode the symbols with machine learning. It’s called Fabricius, named after the “father of epigraphy, the study of ancient inscriptions,” according to Google, and will let you send roughly translated messages in hieroglyphs to your friends.

Fabricius has three sections: Learn, Play and Work. In the first part, you go through a quick six-stage course that introduces you to the history and study of hieroglyphs. There are activities here that include tracing and drawing a symbol, with machine learning analyzing your drawings to see how accurate you were. For example, my drawing of an Ankh symbol after having seen it for five seconds was determined to be 100 percent correct, while my attempt at a sceptre was deemed 98 percent accurate.

The high energy consumption of artificial neural networks’ learning activities is one of the biggest hurdles for the broad use of Artificial Intelligence (AI), especially in mobile applications. One approach to solving this problem can be gleaned from knowledge about the human brain.

Although it has the computing power of a supercomputer, it only needs 20 watts, which is only a millionth of the energy of a supercomputer.

One of the reasons for this is the efficient transfer of information between neurons in the brain. Neurons send short electrical impulses (spikes) to other neurons—but, to save energy, only as often as absolutely necessary.

New machine learning training approach could help under-resourced academic labs catch up with big tech.

Graphcore is offering a cheaper and more streamlined approach to AI tasks.

TOKYO (Reuters) — In August, a robot vaguely resembling a kangaroo will begin stacking sandwiches, drinks and ready meals on shelves at a Japanese convenience store in a test its maker, Telexistence, hopes will help trigger a wave of retail automation.

Following that trial, store operator FamilyMart says it plans to use robot workers at 20 stores around Tokyo by 2022. At first, people will operate them remotely — until the machines’ artificial intelligence (AI) can learn to mimic human movements. Rival convenience store chain Lawson is deploying its first robot in September, according to Telexistence.

“It advances the scope and scale of human existence,” the robot maker’s chief executive, Jin Tomioka, said as he explained how its technology lets people sense and experience places other than where they are.

White Castle is introducing a burger-grilling robot — and it might flip the entire restaurant industry.

Dr. Ben Goertzel CEO & Founder of the SingularityNET Foundation is particularly visible and vocal on his thoughts on Artificial Intelligence, AGI, and where research and industry are in regards to AGI. Speaking at the (Virtual) OpenCogCon event this week, Dr. Goertzel is one of the world’s foremost experts in Artificial General Intelligence. He has decades of expertise applying AI to practical problems in areas ranging from natural language processing and data mining to robotics, video gaming, national security, and bioinformatics.

Are we at a turning point in AGI?

Dr. Goertzel believes that we are now at a turning point in the history of AI. Over the next few years he believes the balance of activity in the AI research area is about to shift from highly specialized narrow AIs toward AGIs. Deep neural nets have achieved amazing things but that paradigm is going to run out of steam fairly soon, and rather than this causing another “AI winter” or a shift in focus to some other kind of narrow AI, he thinks it’s going to trigger the AGI revolution.

The science of using AI to detect and predict emotions is shaky but the U.S. military and a handful of well-funded startups are hoping to prove the doubters wrong, whatever the risks.

Can artificial intelligence enhance human surgeons with AI superpowers to reduce medical errors?