If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The NHS is having to'pick up the pieces' of growing use of cheap genetic tests, doctors warned last night. Popular DNA tests such as those made by '23andMe' - which are widely available in pharmacists and online - can easily be misinterpreted, experts said. A panel of experts from Southampton University, Exeter University and Southampton Hospital said'direct-to-consumer' genetic tests are unreliable and leave people confused and uncertain. Writing in the British Medical Journal, they said genetic information is complex and even if people are shown to be at risk they need carefully walking through the results by a doctor – not left to panic at home. The writers, who include Professor Anneke Lucassen, president of the British Society for Genetic Medicine, said these tests should'absolutely not be used to inform health decisions without further scrutiny'.
An Astronomer has released our best and sharpest look to date at Comet Borisov, the second ever-known interstellar object to visit our solar system, using NASA's Hubble Space Telescope to capture the new image. The comet was travelling at around 110,000 miles per hour when University of California Los Angeles astronomer David Jewitt studied it on October 12, 2019, when it was 260 million miles away. The comet -- which is named after the Crimean astronomer who discovered it -- will pass within around 177,000 miles (285,000 kilometres) of the Earth in early December this year. It is trailing behind it a 100,000 mile-long tail of dust, which is released as the comet melts in the Sun's glare. After this, it will head back out towards interstellar space, passing Jupiter around the middle of 2020.
You'll know that Autonauts has taken over your thinking when you first reach for a real pen and paper while playing. For the many genres this intriguing game capably spans, interacting with it is really about keeping up with a spiralling to-do list. And at some point that list will exceed the capacity of your brain and spill over on to the closest paper to hand. To lose yourself to Autonauts is to find notes like "reprogram plank-sorting robots!" scrawled on the backs of envelopes scattered around your computer. Autonauts is a game about colonising new worlds; landing alone on an unspoiled planet, your task is to build a thriving civilisation.
StradVision has raised $16.6M in total. We talked with Junhwan Kim, its CEO. How would you describe StradVision in a single tweet? StradVision is a pioneer in deep learning-based vision processing technology, providing the software that will allow Advanced Driver-Assistance Aystems (ADAS) in autonomous vehicles to reach the next level of safety, and usher in the era of the fully autonomous vehicle. How did it all start and why?
Academic machine learning involves almost exclusively offline evaluation of machine learning models. In the real world this is, somewhat surprisingly, often only good enough for a rough cut that eliminates the real dogs. For production work, online evaluation is often the only option to determine which of several final-round candidates might be chosen for further use. As Einstein is rumored to have said, theory and practice are the same, in theory. So it is with models.
Natural language processing (NLP) is a branch of artificial intelligence. It helps computers understand, interpret and manipulate human text language. Today there are an enormous amount of emails, social media text, video stream, customer reviews, customer support requests, etc. All of these textual data become the perfect place to apply NLP. We need NLP tools and techniques to process, analyze, and understand unstructured "big data" in order to release the power in analytics.
For many organizations, automating hundreds or thousands of manual tasks has become a competitive necessity. However the same attributes that make automation so effective also open up organizations to new risks. The reason: Because AI enables a company to remotely manage machines and make them interact with other machines, bad actors could take control of the technology and wreak havoc. Consider the common threats to a computer network: malignant software such as viruses and phishing emails for tricking people into revealing valuable information. If a worker clicks on a malware link and damages his computer on the network, the virus can spread to others.
The rise of artificial intelligence has brought with it a strange paradox: Although AI itself is grounded in data and logic, business users can be tempted to throw rationality out the window when dealing with AI models. After all, AI algorithms have been imbued with nearly magical properties, capable of telling a business how to identify risky customers, predict customer behavior, structure the perfect incentive program to reduce customer churn, and just generally provide elegant, unbiased answers to a business's most vexing questions. If only we could put our trust in what we wish were pure, scientifically derived AI models. Alas, it is more complicated than that. In this article, I will describe two of the major pitfalls associated with artificial intelligence models, discuss why it can be so difficult to avoid these pitfalls, and offer some ideas on how to move past them to make AI more useful and profitable.