Goto

Collaborating Authors

How deep is the brain?

#artificialintelligence

Recent AI advances in speech recognition, game-playing, image understanding, and language translation have all been based on a simple concept: multiply some numbers together, set some of them to zero, and then repeat. Since "multiplying and zeroing" doesn't inspire investors to start throwing money at you, these models are instead presented under the much loftier banner of "deep neural networks." Ever since the first versions of these networks were invented by Frank Rosenblatt in 1957, there has been controversy over how "neural" these models are. The New York Times proclaimed these first programs (which could accomplish tasks as astounding as distinguishing shapes on the left side versus shapes on the right side of a paper) to be "the first device to think as the human brain." Deep neural networks remained mostly a fringe idea for decades, since they typically didn't perform very well, due (in retrospect) to the limited computational power and small dataset sizes of the era.


What Is Machine Learning - A Complete Beginner's Guide In 2017

#artificialintelligence

Today things are a little different – thanks to the rollout of the internet, the proliferation of mobile, data-gathering phones and other devices and the adoption of online, connected technology in industry, we literally have more data than we know how to deal with. No human brain can hope to process even a fraction of the digital information it has available. The idea that it can, is one half of what is driving the world-changing breakthroughs we are seeing today. The other half is the "brain" of machine learning. Because as well as simply ingesting data, a machine has to process it in order to learn.


The world's first demonstration of spintronics-based artificial intelligence

#artificialintelligence

Researchers at Tohoku University have, for the first time, successfully demonstrated the basic operation of spintronics-based artificial intelligence. Artificial intelligence, which emulates the information processing function of the brain that can quickly execute complex and complicated tasks such as image recognition and weather prediction, has attracted growing attention and has already been partly put to practical use. The currently-used artificial intelligence works on the conventional framework of semiconductor-based integrated circuit technology. However, this lacks the compactness and low-power feature of the human brain. To overcome this challenge, the implementation of a single solid-state device that plays the role of a synapse is highly promising.


The world's first demonstration of spintronics-based artificial intelligence

#artificialintelligence

IMAGE: Figure 1 shows three kinds of patterns, "I ", "C ", and "T ", expressed in 3x3 blocks used for the associative memory operation experiment. Researchers at Tohoku University have, for the first time, successfully demonstrated the basic operation of spintronics-based artificial intelligence. Artificial intelligence, which emulates the information processing function of the brain that can quickly execute complex and complicated tasks such as image recognition and weather prediction, has attracted growing attention and has already been partly put to practical use. The currently-used artificial intelligence works on the conventional framework of semiconductor-based integrated circuit technology. However, this lacks the compactness and low-power feature of the human brain.


Training AI to Be Curious

#artificialintelligence

"Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition." We often use human consciousness as the ultimate benchmark for artificial exploration. The human brain is ridiculously intricate. While weighing only three pounds, it contains about 100 billion neurons and 100 trillion connections between those.