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Tomorrow's Intelligent Malware Will Attack When It Sees Your Face

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You may think today's malware is bad, but artificial intelligence may soon make malicious software nearly impossible to detect as it waits for just the right person to sit in front of the computer. That's according to work by a group of researchers with IBM, which they revealed at the BlackHat cybersecurity conference last week. Here's how the new smart spyware works and why it's such a large potential threat. Traditional virus-catching software finds malicious code on your computer by matching it to a stored library of malware. More sophisticated anti-virus tools can deduce that unknown code is malware because it targets sensitive data.


Developing bionics: How IBM is adapting mind-control for accessibility

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What if there was a way to give everyone suffering from conditions like paralysis or Locked-in syndrome the means to operate prosthetic devices and tech gadgets using mind-control? Well, there is – or at least, there will be. IBM Research recently developed an end-to-end proof-of-concept for a method of controlling an off-the-shelf robotic arm with a brain-computer interface built using a take-home EEG monitor. To accomplish this, the researchers developed AI to interpret the data from the EEG monitor as commands for the robotic arm. That may not sound like something that will change everything overnight – and IBM isn't the only or first company to dabble in brain-computer interfaces.


IBM responds to recent Watson media coverage

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Back in 2011, IBM's new Watson technology was the focus of a lot of excited expectation about what its artificial intelligence platform – having famously bested human opponents on Jeopardy! Seven years later, some media reports are wondering whether Watson's potential was over-promised. Recent stories, in Stat News, the Wall Street Journal and elsewhere have taken aim at the AI technology's diagnostic track record, drawn attention to potential patient safety risks, and questioned whether the billions of dollars Big Blue has spent building and training the platform have worth it. The Stat News story reported on internal IBM documents that showed "multiple examples of unsafe and incorrect treatment recommendations" from the Watson for Oncology system. The Wall Street Journal pointed out that "more than a dozen IBM partners and clients have halted or shrunk Watson's oncology-related projects."


What Went Wrong With IBM's Watson

Slate

What if artificial intelligence can't cure cancer after all? That's the message of a big Wall Street Journal post-mortem on Watson, the IBM project that was supposed to turn IBM's computing prowess into a scalable program that could deliver state-of-the-art personalized cancer treatment protocols to millions of patients around the world. Watson in general, and its oncology application in particular, has been receiving a lot of skeptical coverage of late; STAT published a major investigation last year, reporting that Watson was nowhere near being able to live up to IBM's promises. After that article came out, the IBM hype machine started toning things down a bit. But while a lot of the problems with Watson are medical or technical, they're deeply financial, too.


IBM finds a way to watermark AI's to protect them from theft and sabotage – Fanatical Futurist by International Keynote Speaker Matthew Griffin

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What if machine learning models, much like photographs, movies, music, and manuscripts, could be watermarked nearly imperceptibly to denote ownership, stop intellectual property thieves in their tracks, and prevent attackers from compromising their integrity? Thanks to IBM's new patent-pending process, they now can be. In a phone conversation with analysts this week Marc Stoecklin, IBM's manager of Cognitive Cybersecurity Intelligence, detailed the work of several IBM researchers who've been busy trying to find new ways to embed unique identifiers, or watermarks to you and I, into neural networks. Their concept was recently presented at the ACM Asia Conference on Computer and Communications Security (ASIACCS) 2018 in Korea, and might be deployed within IBM or make its way into a client-facing product in the very near future. "For the first time, we have a [robust] way to prove that someone has stolen an [AI] model," Stoecklin said.


The Two Sides of the Artificial Intelligence Coin

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The growth of artificial intelligence in recent years has been astounding -- yet AI is still in the very early stages of growth. Where are we today with this new technology, and where are we heading? Which companies are struggling, and why? AI for years has been a staple of science fiction -- from the starship Enterprise's talking computer in Star Trek in the 1960s, to the bionic Steve Austin in The Six Million Dollar Man in the 1970s, to Arnold Schwarzenegger's time-traveling killer robot in the Terminator movies of the 1980s, to give just a few examples. Now AI has moved beyond sci-fi and become real, with all sorts of technologies.


The Two Sides of the Artificial Intelligence Coin

#artificialintelligence

The growth of artificial intelligence in recent years has been astounding -- yet AI is still in the very early stages of growth. Where are we today with this new technology, and where are we heading? Which companies are struggling, and why? AI for years has been a staple of science fiction -- from the starship Enterprise's talking computer in Star Trek in the 1960s, to the bionic Steve Austin in The Six Million Dollar Man in the 1970s, to Arnold Schwarzenegger's time-traveling killer robot in the Terminator movies of the 1980s, to give just a few examples. Now AI has moved beyond sci-fi and become real, with all sorts of technologies.


AI for code encourages collaborative, open scientific discovery

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We have seen significant recent progress in pattern analysis and machine intelligence applied to images, audio and video signals, and natural language text, but not as much applied to another artifact produced by people: computer program source code. In a paper to be presented at the FEED Workshop at KDD 2018, we showcase a system that makes progress towards the semantic analysis of code. By doing so, we provide the foundation for machines to truly reason about program code and learn from it. The work, also recently demonstrated at IJCAI 2018, is conceived and led by IBM Science for Social Good fellow Evan Patterson and focuses specifically on data science software. Data science programs are a special kind of computer code, often fairly short, but full of semantically rich content that specifies a sequence of data transformation, analysis, modeling, and interpretation operations.


Use Cases and Trends in Artificial Intelligence for Financial Services - Lend Academy

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Artificial intelligence (AI) is everywhere these days as more companies look to automate repetitive tasks to save money and reallocate staff to more meaningful work. We wanted to explore some of the current use cases for AI based technologies in financial services and where the industry is heading in the coming years. Cut through the hype and you will find financial firms have started to implement AI in a few different areas. Back office operations and data management has been the biggest beneficiary as companies can run algorithms across full data sets and cut out repetitive tasks. A new report by Capgemini states that the financial services industry can add more than $500bn in revenue by implementing automation.