Europe


AI video screening still a long way off, says Facebook executive

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Facebook Inc.'s chief artificial intelligence scientist said the company is years away from being able to use software to automatically screen live video for extreme violence. Yann LeCun's comments follow the March livestream of the Christchurch mosque shootings in New Zealand. 'This problem is very far from being solved,' LeCun said Friday during a talk at Facebook's AI Research Lab in Paris. Facebook was criticised for allowing the Christchurch attacker to broadcast the shootings live without adequate oversight that could have resulted in quicker take-downs of the video. It also struggled to prevent other users from re-posting the attacker's footage.


Estonia to Empower AI-Based Judge in Small Claims Court - 150sec

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In recent years, the technology field has been abuzz with the advent of ever-improving AI-based technology. Whilst much of that tech is in its formative stages, there are real tangible signs of its application emerging. In Estonia, it seems that the technology is destined to be used in what traditionally would be the least innovative of areas – the country's courts system.


Microsoft invests in seven AI projects to help people with disabilities

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Over the next year, the recipients will work on things like a nerve-sensing wearable wristband. Another project seeks to develop a wearable cap that reads a person's EEG data and communicates it to the cloud to provide seizure warnings and alerts. Other tools will rely on speech recognition, AI-powered chatbots and apps for people with vision impairment. This year's grantees include the University of California, Berkeley; Massachusetts Eye and Ear, a teaching hospital of Harvard Medical School; Voiceitt in Israel; Birmingham City University in the United Kingdom; University of Sydney in Australia; Pison Technology of Boston; and Our Ability, of Glenmont, New York. "What stands out the most about this round of grantees is how so many of them are taking standard AI capabilities, like a chatbot or data collection, and truly revolutionizing the value of technology," Microsoft's Senior Accessibility Architect Mary Bellard said in a blog post.


Artificial intelligence improves power transmission

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To integrate volatile renewable sources into the energy supply, capacities of the power grid have to be increased. The need for new lines can be reduced by better utilization of existing lines as a function of weather conditions. To this end, researchers of Karlsruhe Institute of Technology (KIT) work on self-learning sensor networks to model the cooling effect of weather based on real data. In favorable conditions, the line's power transmission can be enhanced in this way. To transport power from producers to consumers, to prevent temporary shutdown of plants that generate power from regenerative sources, in particular at high wind intensities, and to ensure high supply security in general, considerable extension of the existing grid infrastructure is required.


Ocado and DeepMind bosses among experts appointed to new government council to improve UK's artificial intelligence sector

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Ocado and Google DeepMind executives are among a cohort of experts that have been called to advise the Government on how to boost the use of artificial intelligence in Britain. Paul Clarke, chief technology officer of the e-commerce company, and DeepMind co-founder Mustafa Suleyman will join the new lineup of the Government's AI council, an advisory group set up as part of a push to boost investment in the technology. Mastercard vice chairman Ann Cairns, Amazon machine learning director Neil Lawrence and Microsoft research lab director Chris Bishop are also among those who gained seats on the new council. The executives are expected to promote the use of AI by businesses in the UK and advise the Government about future public investments in the industry. The Government already set aside £3m for AI projects aimed at boosting productivity in financial and legal services last year as part of this effort.


r/MachineLearning - [D] AutoML/Neural Architecture Search has a giant CO2 footprint

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Energy does mean a thing. You are never creating energy, you are only transforming it. Meaning you are still taking energy from somewhere. Having enough energy for everyone to light their house is actually a rising problem since with less atom energy it gets harder to manage and distribute. While it gets hard to distribute that energy we are wasting tons of energy on ML.



The ethics of AI: is artificial intelligence any good? Granta Innovation

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Our first article (What is AI?) highlighted that Artificial intelligence already has a huge impact on our lives. People are concerned about AI replacing jobs or being misused, with good reason. So here we take a broad look at the ethics of AI. AI is software: it's no more intrinsically good or bad than a database or website. Because AI has great power, the way we apply it is critically important.


Robot race: These three countries are winning

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The three countries are leading an artificial intelligence (AI) revolution, Malcolm Frank, head of strategy at leading outsourcing firm Cognizant, told CNNMoney in an interview. Frank is the co-author of a recent book entitled "What to Do When Machines Do Everything," on the impact artificial intelligence will have on the global economy in the coming years. "I think it's three horses in the race, and that's probably the wrong metaphor because they are all going to win," he said. "They are just going to win differently." While AI is progressing quickly elsewhere too, Frank said the other development hotspots are mainly city hubs such as London and Stockholm, or far smaller economies such as Estonia.


Kicking neural network design automation into high gear

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A new area in artificial intelligence involves using algorithms to automatically design machine-learning systems known as neural networks, which are more accurate and efficient than those developed by human engineers. But this so-called neural architecture search (NAS) technique is computationally expensive. A state-of-the-art NAS algorithm recently developed by Google to run on a squad of graphical processing units (GPUs) took 48,000 GPU hours to produce a single convolutional neural network, which is used for image classification and detection tasks. Google has the wherewithal to run hundreds of GPUs and other specialized hardware in parallel, but that's out of reach for many others. In a paper being presented at the International Conference on Learning Representations in May, MIT researchers describe an NAS algorithm that can directly learn specialized convolutional neural networks (CNNs) for target hardware platforms -- when run on a massive image dataset -- in only 200 GPU hours, which could enable far broader use of these types of algorithms.