IBM Watson steps into real-world cybersecurity

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Google, IBM look to mimic the human brain

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Several years ago, there were reports that an IBM artificial intelligence (AI) project had mimicked the brain of a cat. Being the smartass that I am, I responded on Twitter with, "You mean it spends 18 hours a day in sleep mode?" That report was later debunked, but the effort to simulate the brain continues, using new types of processors far faster and more brain-like than your standard x86 processor. IBM and the U.S. Air Force have announced one such project, while Google has its own. What Google is proposing is a template for how to create a single machine learning model that can address multiple tasks.


What's Next For Deep Learning?

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Reinforcement learning algorithms that can reliably learn how to control robots, etc. Better generative models. Algorithms that can reliably learn how to generate images, speech and text that humans can't tell apart from the real thing. Learning to learn and ubiquitous deep learning. Right now it still takes a human expert to run the learning-to-learn algorithm, but in the future it will be easier to deploy, and all kinds of businesses that don't specialize in AI will be able to leverage deep learning. More cyberattacks will leverage machine learning to make more autonomous malware, more efficient fuzzing for vulnerabilities, etc.


Global Bigdata Conference

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Reinforcement learning algorithms that can reliably learn how to control robots, etc. Better generative models. Algorithms that can reliably learn how to generate images, speech and text that humans can't tell apart from the real thing. Learning to learn and ubiquitous deep learning. Right now it still takes a human expert to run the learning-to-learn algorithm, but in the future it will be easier to deploy, and all kinds of businesses that don't specialize in AI will be able to leverage deep learning. More cyberattacks will leverage machine learning to make more autonomous malware, more efficient fuzzing for vulnerabilities, etc.


Google's AI Fight Club Will Train Systems to Defend Against Future Cyberattacks

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When artificial intelligence (AI) is discussed today, most people are referring to machine learning algorithms or deep learning systems. While AI has advanced significantly over the years, the principle behind these technologies remains the same. Someone trains a system to receive certain data and asks it to produce a specified outcome -- it's up to the machine to develop its own algorithm to reach this outcome. Alas, while we've been able to create some very smart systems, they are not foolproof. Data science competition platform Kaggle wants to prepare AI systems for super-smart cyberattacks, and they're doing so by pitting AI against AI in a contest dubbed the Competition on Adversarial Attacks and Defenses.