Scientists trained an AI through the eyes of a baby in an effort to teach the tech how humanity develops - amid fears it could destroy us. Researchers at New York University strapped a headcam recorder to Sam when he was just six months old through his second birthday. The footage of 250,000 words and corresponding images was fed to an AI model, which learned how to recognize different objects similar to how Sam did. The AI developed its knowledge in the same way the child did - by observing the environment, listening to nearby people and connecting dots between what was seen and heard. The experiment also determined the connection between visual and linguistic representation in the development of a child.

As we rely more on natural language processing to help us navigate our world, it's more important than ever that these artificial intelligence models -- used increasingly in applications such as caption generation for the visually impaired -- remain true to reality. "The issue is that deep learning-based neural language generation models have no guarantees in generating factually correct sentences that are faithful to the input data," said UC Santa Barbara computer scientist William Wang. Over the many iterations it takes for a language generation model to learn how to describe or predict what a scene depicts, elements can creep in, causing phenomena such as errors in data-to-text translations or object hallucinations, in which the caption contains an object or an action that doesn't exist in the image. As a result, unless you have a way of reining in these errors (or you're surrealist painter René Magritte) these mismatches could spell the end of the usefulness of the language generation model being used. "This is a huge problem," said Wang. "Imagine you are using a news summarization system to read earnings reports -- the loss of faithfulness can give you wrong numbers, wrong facts and misinformation. Similarly, if a visually impaired person relies on an image captioning system to see the environment, wrong generation could create serious consequences."

"The issue is that deep learning-based neural language generation models … "The current research in machine learning and AI primarily focus on …

A recent article in Nature highlights a discovery that pushes the boundaries of our imaginations and challenges some of the very attributes that make us human. The piece details how artificial intelligence is creating speech by interpreting brain signals (and even offers an audio recording for a chance to hear it for yourself). It's a key advancement for people who can't speak because it provides a direct technologically-enabled path from thought to speech. The implications of this discovery go beyond the recreation of speech: A.I. was used to decode brain waves and then reassemble neural impulses. While the focus of this study was on the mechanistic components of speech, such as direct muscle movement, it still acquired information from the early stages of thought development to construct words that were identifiable about 70% of the time.

If popular culture is an accurate gauge of what's on the public's mind, it seems everyone has suddenly awakened to the threat of smart machines. Several recent films have featured robots with scary abilities to outthink and manipulate humans. In the economics literature, too, there has been a surge of concern about the potential for soaring unemployment as software becomes increasingly capable of decision making. Yet managers we talk to don't expect to see machines displacing knowledge workers anytime soon -- they expect computing technology to augment rather than replace the work of humans. In the face of a sprawling and fast-evolving set of opportunities, their challenge is figuring out what forms the augmentation should take.

Every student who has panicked while reading the same page of a textbook over and over again may suspect this. But stress cramming for an exam does not work, because the facts are likely to be lost from your memory. Instead it is best to learn through practice tests to protect your brain from the effects of stress, with a study showing that we remember more this way. Every student who has panicked while reading the same page of a textbook over and over again may suspect this. Some 120 students were asked to learn a set of 30 words and 30 images. Each item was displayed for a few seconds on a computer screen.

The number of sophisticated cognitive technologies that might be capable of cutting into the need for human labor is expanding rapidly. But linking these offerings to an organization's business needs requires a deep understanding of their capabilities. If popular culture is an accurate gauge of what's on the public's mind, it seems everyone has suddenly awakened to the threat of smart machines. Several recent films have featured robots with scary abilities to outthink and manipulate humans. In the economics literature, too, there has been a surge of concern about the potential for soaring unemployment as software becomes increasingly capable of decision making. Yet managers we talk to don't expect to see machines displacing knowledge workers anytime soon -- they expect computing technology to augment rather than replace the work of humans.

The number of sophisticated cognitive technologies that might be capable of cutting into the need for human labor is expanding rapidly. But linking these offerings to an organization's business needs requires a deep understanding of their capabilities. If popular culture is an accurate gauge of what's on the public's mind, it seems everyone has suddenly awakened to the threat of smart machines. Several recent films have featured robots with scary abilities to outthink and manipulate humans. In the economics literature, too, there has been a surge of concern about the potential for soaring unemployment as software becomes increasingly capable of decision making. Yet managers we talk to don't expect to see machines displacing knowledge workers anytime soon -- they expect computing technology to augment rather than replace the work of humans.

The number of sophisticated cognitive technologies that might be capable of cutting into the need for human labor is expanding rapidly. But linking these offerings to an organization's business needs requires a deep understanding of their capabilities. If popular culture is an accurate gauge of what's on the public's mind, it seems everyone has suddenly awakened to the threat of smart machines. Several recent films have featured robots with scary abilities to outthink and manipulate humans. In the economics literature, too, there has been a surge of concern about the potential for soaring unemployment as software becomes increasingly capable of decision making. Yet managers we talk to don't expect to see machines displacing knowledge workers anytime soon -- they expect computing technology to augment rather than replace the work of humans.