The ethics of artificial intelligence

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If someone makes a decision you don't like you can complain to the manager. Computer programs are making more and more decisions. How can we design ethical artificial intelligence?


Adafruit Holiday Gift Guide: Machine Learning : Shopping Guides : Adafruit Industries, Unique & fun DIY electronics and kits

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Machine learning has come to the'edge', but you don't need super complex hardware to start developing your own TensorFlow models! We've curated a shopping guide to dip your toes into machine learning waters. We've got a range of Machine Learning boards. From the advanced Coral Dev Board single-board computer that's ideal when you need to perform fast machine learning (ML) inferencing in a small form factor, to small microcontrollers like the EdgeBadge that can run a very miniature version of TensorFlow Lite to do ML computations.


Artificial Intelligence and Cybersecurity

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Currently, AI is expensive and difficult to implement fully into businesses, and, at this time, AI is not ready to fully meet the demands of cybersecurity. The science fiction style concept of AI, the ability for a machine to mimic intelligent human behavior, does not exist at this time. However, machine learning can still be leveraged to support cybersecurity initiatives. The technology stack using machine learning is growing. Large tech companies rely on machine intelligence and have products that depend upon AI or machine learning.


Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks

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The electrocardiogram (ECG) plays an imperative role in the medical field, as it records heart signal over time and is used to discover numerous cardiovascular diseases. If a documented ECG signal has a certain irregularity in its predefined features, this is called arrhythmia, the types of which include tachycardia, bradycardia, supraventricular arrhythmias, and ventricular, etc. This has encouraged us to do research that consists of distinguishing between several arrhythmias by using deep neural network algorithms such as multi-layer perceptron (MLP) and convolution neural network (CNN). The TensorFlow library that was established by Google for deep learning and machine learning is used in python to acquire the algorithms proposed here. The proposed algorithm consists of four hidden layers with weights, biases in MLP, and four-layer convolution neural networks which map ECG samples to the different classes of arrhythmia.


trekhleb/nano-neuron

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NanoNeuron is over-simplified version of a Neuron concept from the Neural Networks. NanoNeuron is trained to convert a temperature values from Celsius to Fahrenheit. NanoNeuron.js code example contains 7 simple JavaScript functions (model prediction, cost calculation, forward and backwards propagation, training) that will give you a feeling of how machines can actually "learn". These functions by any means are NOT a complete guide to machine learning. A lot of machine learning concepts are skipped and over-simplified there!


Quantum Machine Learning: Future of AI

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What comes to mind when you hear the words Artificial Intelligence (AI)? Not too long ago, this phrase was reserved for talking about an imagined distant future where humans had robot servants and self-driving cars. This is the world we live in today. We have personal assistants like Siri to answer any of our questions, Tesla's that can get us from point A to B while we sleep, and endless filters on Snapchat that can transform our appearance instantly. The age of AI is here.


Intel may buy another AI chip developer, Habana Labs

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Intel is in advanced talks to buy AI chip developer Habana Labs for as much as $2 billion, according to an unnamed source that spoke to Calcalist. Habana Labs is based in Israel. Intel bought Mobileye, a company focused on autonomous driving also based in Israel, in 2017 for $15 billion. Intel wouldn't comment on the possible transaction, and Habana Labs did not respond to a request to comment. The company was founded in 2016 to develop processor platforms for training deep neural networks and inference deployment.


Artificial Friend or Virtual Foe - KDnuggets

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Researchers, entrepreneurs, and policy-makers are increasingly using AI to tackle development challenges. In other words, using AI for a greater good is a real thing. However, it is becoming clear that AI poses as many threats as benefits, although the former ones are usually neglected. I do not want to get into trust, accountability, or safety issues in this short piece (if you want, here there is more), but avoiding the negative effects of AI is why incorporating a set of ethical principles into our technology development process is so paramount. Ethics plays a key role by ensuring that regulations of AI harness its potential while mitigating its risks (Taddeo and Floridi, 2018) and it would help us understand how to use responsibly the power coming from this technology.


Leiden team wins challenge for faster MRI scan through artificial intelligence

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Researchers from Leiden, in cooperation with Philips, have won a challenge in which international research groups dedicate themselves to accelerating MRI scans with the help of artificial intelligence (AI). They developed an algorithm with which it is possible to use eight times less data than normal and still reconstruct an MRI image of a knee that is almost as good as one using the usual amount of data. In the fastMRI challenge, organised by the Facebook AI research lab and New York University, artificial intelligence specialists were challenged to apply their knowledge to making MRI scans faster and more efficient. The 34 teams taking part were supplied with a raw data set of a few hundred MRI scans of knees. They also received a number of incomplete data sets.


Alumna uses artificial intelligence to make talk therapy accessible, affordable Gies College of Business

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Making mental healthcare easily accessible to anyone is what led Rima Seiilova-Olson (MSTM '10) to become co-founder of Kintsugi Mindful Wellness, talk therapy software that combines machine learning and voice journaling to tackle stress, anxiety, depression and loss. "There's a big opportunity right now to use artificial intelligence for good. AI is not'summoning the demon' like Elon Musk says. When you're suffering, you need affordable access to help right away," said Seiilova-Olson, who met Kintsugi cofounder Grace Chang at an OpenAI hackathon in San Francisco. They quickly discovered they shared a passion for exploring how technology can help people address their mental health needs.