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) …
Satellites could help locate stranded whales more efficiently and in real-time. Scientists have begun harnessing the power of the technology's high-resolution imagery to detect and monitor whales stranded on the shore from space. The team noted that the use of satellites will help find stranded whales in remote locations, as well as spot potentially deteriorating ocean conditions. Satellites could help locate stranded whales more efficiently and in real-time. Scientists have begun harnessing the power of the technology's high-resolution imagery to detect and monitor whales stranded on the shore from space Chile witnessed one of the largest mass mortality of baleen whales in 2015 on the remote beaches of Patagonia – at least 343 died.
Google said its fix for a controversial face recognition feature that allows the Pixel 4 to be unlocked while users' eyes are closed will arrive'in the coming months.' The company says the feature will address a problem first highlighted by the BBC that allows the phone to be unlocked using facial recognition while someone is sleeping via simply adding an option that requires ones eyes to be open. 'We've been working on an option for users to require their eyes to be open to unlock the phone, which will be delivered in a software update in the coming months,' the company wrote in a statement. Conversely, Apple's iPhone requires users' eyes to be open before it unlocks and defers to a passcode if it's unable to read one's face. Google's Pixel 4 (pictured above) was unveiled in an event in New York City this month but has already run into trouble as skeptical users express concern over its facial recognition software The Verge reports that an earlier versions of Google's newest flagship mobile device may have contained an option to require one's eyes to be open before unlocking it with a faceprint, though that option was never included in the final product.
An AI that can spot a brain haemorrhage on an X-ray scan could help diagnose strokes, head injuries and ruptured blood vessels. The software was able to identify signs of bleeding in the head with similar accuracy to radiologists. While computers won't be replacing doctors any time soon, one area where they are making progress is in identifying signs of disease from images. Software can recognise moles that are likely to be cancerous from photographs, as well as eye damage caused by diabetes from pictures of the back of the eye, with near-human levels of ability. Now Esther Yuh at the University of California, San Francisco, and her colleagues have developed a program that can interpret CT scans of heads.
Google has never widely been considered the top banana when it comes to smartphones, a designation bestowed instead on Samsung or Apple, depending on whether your loyalties lie with Android or iOS. But the last couple of years, Google's Pixels have presented an awfully strong case: solid Android phones with superb cameras that you can usually get for less than you pay for a top Galaxy or iPhone. So it goes with the Pixel 4 I've been using over the several days. It has a 5.7-inch display and starts at $799 (or $899 for its larger 6.3-inch sibling, the Pixel 4 XL) and for the first time is being embraced by all the U.S. wireless carriers out of the gate; in the past years, Verizon had the exclusive. As with other Pixels, the obedient Google Assistant is readily at hand, summoned through a familiar "Hey, Google" or "OK, Google" command, tapping an icon, and now even by squeezing the sides of the phone.
"Bias in AI" refers to situations where machine learning-based data analytics systems discriminate against particular groups of people. This discrimination usually follows our own societal biases regarding race, gender, biological sex, nationality, or age (more on this later). Just this past week, for example, researchers showed that Google's AI-based hate speech detector is biased against black people. In this article, I'll explain two types of bias in artificial intelligence and machine learning: algorithmic/data bias and societal bias. I'll explain how they occur, highlight some examples of AI bias in the news, and show how you can fight back by becoming more aware.
The Outlook Calendar Scheduling team is currently looking for a highly motivated data scientist who can help build scalable prediction, machine learning, and AI to change the way people use calendar to organize their life. If you are passionate about designing and building the next generation time management intelligence and scheduling solution used by hundreds of millions of users every day then this is the job for you.
We explored metabolic pathways related to early-stage BCa (Galactose metabolism and Starch and sucrose metabolism) and to late-stage BCa (Glycine, serine, and threonine metabolism, Arginine and proline metabolism, Glycerophospholipid metabolism, and Galactose metabolism) as well as those common to both stages pathways. The central metabolite impacting the most cancerogenic genes (AKT, EGFR, MAPK3) in early stage is d-glucose, while late-stage BCa is characterized by significant fold changes in several metabolites: glycerol, choline, 13(S)-hydroxyoctadecadienoic acid, 2′-fucosyllactose. Insulin was also seen to play an important role in late stages of BCa. The best performing model was able to predict metabolite class with an accuracy of 82.54% and the area under precision-recall curve (PRC) of 0.84 on the training set. The same model was applied to three separate sets of metabolites obtained from public sources, one set of the late-stage metabolites and two sets of the early-stage metabolites.
In the modern-day, the impact that technology has on business operations is undeniable – no matter what industry the organisation is in. Allowing employees to be more productive and deliver a more personalised product to consumers, it's not something that should be ignored. Over the last few years, the global insurance industry has started to advance by utilising the benefits that come with updating their technology. Noticing the importance of customer expectations, many businesses are stepping away from the traditional processes in favour of the contemporary. However, not all insurance companies are keeping up with the advancement – which has led to them collaborating with long-established insurtech organisations or an insurtech startup.
In the past few years there has been a large increase in tools trying to solve the challenge of bringing machine learning models to production. One thing that these tools seem to have in common is the incorporation of notebooks into production pipelines. This article aims to explain why this drive towards the use of notebooks in production is an anti pattern, giving some suggestions along the way. Let's start by defining what these are, for those readers who haven't been exposed to notebooks, or call them by a different name. Notebooks are web interfaces that allow a user to create documents containing code, visualisations and text.