Does anyone really need a £340 electric toothbrush when one costing £6 will do the same job?

Daily Mail - Science & tech

Artificial intelligence that can predict your every move, high-tech sensors, flashing coloured lights and an in-built charger. No, this isn't the latest sports car dreamed up by Silicon Valley wizards. It's the latest all-singing, all-dancing electric toothbrush – the Oral-B Genius X – which uses the same technology as that behind driverless vehicles and robots that diagnose diseases. The gadget can give users a new insight into their brushing habits, even down to the pressure applied on each tooth, makers claim. Oh, and it costs an eye-watering £340.


Why Britain's most eminent scientist is convinced cyborgs will rule the planet within 80 years

Daily Mail - Science & tech

It is 8.30am and Britain's most eminent scientist is taking a windswept stroll through Dorset's rolling hills. It seems hard to believe that James Lovelock – sprightly despite a walking stick and bristling with a fierce, bright-eyed intelligence – will turn 100 this week. But the man known for proposing one of the most visionary scientific theories of the last century starts the day just as he always does, with a brisk walk from his coastguard's cottage by the shores of Chesil Beach with his beloved wife, Sandy. That Lovelock is conscious of his own mortality is to be expected. But that he is also musing on the future of the Earth he will never live to see – one which involves cyborgs, no less – is, perhaps, rather more surprising.


Toyota fetches new way to use AI, self-drive tech in Tokyo Games

The Japan Times

Miniature remote controlled cars have proved to be a crowd pleaser at track and field throwing events, but for the Tokyo 2020 Olympics, Toyota Motor Corp. is upping the game with a hi-tech way to fetch javelins and hammers: pint-sized, self-driving AI robot cars. The automaker Monday unveiled a prototype of its next-generation field support robot, a miniature shuttle bus-shaped contraption based on its "e-Palette" ride-sharing vehicle under development, to be used at the Tokyo Games. The vehicle, roughly the size of a toddler's ride-on toy car, can travel at a maximum speed of 20 kilometers per hour and sports three cameras and one lidar sensor which enable it to "see" its surroundings. Draped around the top of its body is a band of LED lights that illuminate when the vehicle uses artificial intelligence to follow event officials toward the equipment hurled by athletes onto the pitch during shot put, discus throw, hammer throw and javelin events. After the equipment, which can weigh as much as eight kilograms for hammers, is loaded into the vehicle by the official, a press of a button located toward its front sends the car zipping back to athletes for later use.


Kitchen disruption on the horizon as tech firms add AI, big data to food production

The Japan Times

WASHINGTON - Looking for that perfect recipe, or a new flavor combination that delights the senses? Increasingly, players in the food industry are embracing artificial intelligence to better understand the dynamics of flavor, aroma and other factors that go into making a food product a success. Earlier this year, IBM became a surprise entrant to the food sector, announcing a partnership with seasonings maker McCormick to "explore flavor territories more quickly and efficiently using AI to learn and predict new flavor combinations" by utilizing data collected from millions of data points. The partnership highlights how technology is being used to disrupt the food industry by helping develop new products and respond to consumer preferences and offer improved nutrition and flavor. "More and more, food companies are embracing digitization and becoming data-driven," said Bernard Lahousse, co-founder of Foodpairing, a startup with offices in Belgium and New York that develops digital food "maps" and algorithms to recommend food and drink combinations.


It's a facial-recognition bonanza: Oakland bans it, activists track it, and pics taken from dating-site OkCupid feed it

#artificialintelligence

We'll be talking about everyone's favorite topic at the moment: facial recognition. First San Francisco, Somerville ... now Oakland: California's Oakland has become the third US city to ban its local government using facial recognition technology, after its council passed an ordinance this week. Council member Rebecca Kaplan submitted the ordinance for city officials to consider earlier this year in June. The document describes the shortcomings of the technology and why it should be banned. "The City of Oakland should reject the use of this flawed technology on the following basis: 1) systems rely on biased datasets with high levels of inaccuracy; 2) a lack of standards around the use and sharing of this technology; 3) the invasive nature of the technology; 4) and the potential abuses of data by our government that could lead to persecution of minority groups," according to the ordinance.


Top Machine Learning Algorithms – Data Scientist Basic Tool Kit Vinod Sharma's Blog

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Machine Learning Algorithms – DataScientist may be the sexiest job of today but the understanding, implementation, applied ML experience is missing. Having the top algorithms on your fingertips in real business is missing big time. The real job for any data scientist is the ability to clarify, demonstrate, extract real values out of data and reap rewards. "Machine Learning" as a basic skill sounds like teleportation tool to many businesses especially for the companies which are actually data factories i.e social media platforms. Describing and picturising the top few machine learning algorithms is the main idea of this post.


OPINION: How to prepare students for the rise of artificial intelligence in the workforce The Chronicle Herald

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The future impacts of artificial intelligence (AI) on society and the labour force have been studied and reported extensively. In a recent book, AI Superpowers, Kai-Fu Lee, former president of Google China, wrote that 40 to 50 per cent of current jobs will be technically and economically viable with AI and automation over the next 15 years. Artificial intelligence refers to computer systems that collect, interpret and learn from external data to achieve specific goals and tasks. Unlike natural intelligence displayed by humans and animals, it is an artificial form of intelligence demonstrated by machines. This has raised questions about the ethics of AI decision-making and impacts of AI in the workplace.


Machine Learning Jump-start Series (MLJS)

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NTU Library is pleased to present a series of ten workshops on Machine Learning. The objective of this series is to equip NTU staff, students and alumni, with the basic expertise to apply different machine learning concepts and techniques to a wide range of applications using Microsoft Azure Machine Learning Service. Each workshop presents a unique set of content relating to different machine learning concepts and techniques. Each is designed to stand on its own. For example, there is no requirement to attend MLJS03 before attending MLJS04.


How to Develop a Word-Level Neural Language Model and Use it to Generate Text

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A language model can predict the probability of the next word in the sequence, based on the words already observed in the sequence. Neural network models are a preferred method for developing statistical language models because they can use a distributed representation where different words with similar meanings have similar representation and because they can use a large context of recently observed words when making predictions. In this tutorial, you will discover how to develop a statistical language model using deep learning in Python. How to Develop a Word-Level Neural Language Model and Use it to Generate Text Photo by Carlo Raso, some rights reserved. The Republic is the classical Greek philosopher Plato's most famous work. It is structured as a dialog (e.g. The entire text is available for free in the public domain. It is available on the Project Gutenberg website in a number of formats.


Recognizing Human features using Deep Networks by Akshay Bahadur at #ODSC_India

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This demo would be regarding some of the work that I have already done since starting my journey in Machine Learning. So, there are a lot of MOOCs out there for ML and data science but the most important thing is to apply the concepts learned during the course to solve simple real-world use cases. One of the projects that I did included building state of the art Facial recognition system [VIDEO]. So for that, I referred to several research papers and the foundation was given to me in one of the courses itself, however, it took a lot of effort to connect the dots and that's the fun part. In another project, I made an Emoji Classifier for humans [VIDEO] based on your hand gestures.