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EFF: Stupid patents are dragging down AI and machine learning

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Each month, the patent lawyers at the Electronic Frontier Foundation shine a spotlight on one particular patent they believe is a drag on innovation. This month, they're looking at one of the fastest-growing sectors of technology: machine learning and artificial intelligence. EFF lawyer Daniel Nazer has picked out an artificial intelligence patent belonging to Hampton Creek, a San Francisco food-tech company that markets products under the brand name "just." Nazer acknowledges that Hampton Creek's patent isn't as bad as some of the other ones highlighted in the EFF Stupid Patent series, but it's worth pointing out because of the serious problems it could create for innovation in machine learning.


How AI is defining insurtech strategy

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AI – which Margaris prefers to call "the influence of machine learning or deep learning" – is starting to be felt across the insurtech, fintech and associated industries, he said. "AI, through machine learning and deep learning, will eventually become the entrepreneur of the future--and we humans need to compete against it." A company still needs to have a compelling business case that attracts clients, but AI, machine learning and deep learning for sure will be part of the equation to compete successfully in their space." Margaris has reiterated what has been the most important technology lesson learned over the past four decades, and continues to be the lesson going forward with each new technology wave.


Why artificial intelligence is different from previous technology waves

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I took my first "business machines" class in high school in 1991, attended my first computer science class in 1994 (learning Pascal), and moved to Silicon Valley in 1997 after Cisco converted my internship into a permanent position. The eight I'm covering in this article include desktop operating systems, web browsers, networking, social networks, mobile apps, Internet of Things, cloud computing, and artificial intelligence. In the social network space, development is completely centralized by the owners of the platforms (Twitter, Facebook, etc.) A technology with a low barrier to entry and decentralized platform development has the greatest potential for future impact.


AI: Move over FinTech - InsurTech is here and its got bots

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With insurance, you never get a reward, there's just a cost," says Filiippo Sanesi, head of research and partner management at Startupbootcamp InsurTech, an accelerator for insurance startups based in London. The billions of images around the world mean that not only is the value from performing this task with AI enormous, but it's also possible to train the AI because you've got these mountains of data," Tractable's co-founder and chief executive Alex Dalyac, tells Verdict. "We're not just distributing products; we're working towards building accurate, personalised insurance products around people's lives." "We're not just distributing products; we're working towards building accurate, personalised insurance products around people's lives," says Hugh.


Ayasdi Named to the 2017 AI 100 by CB Insights

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CB Insights revealed the AI 100 winners during The Innovation Summit in Santa Barbara, a gathering of top executives and investors to explore the industries of the future. The CB Insights research team selected the winners based on a combination of data submitted by the companies, responses to interview questions and the company's Mosaic Score. Mosaic is an algorithm built with funding from the National Science Foundation that gives predictive intelligence into the health of private companies. "At Ayasdi, we see clearly that intelligent applications enabled by AI and big data will be as transformative for knowledge-based processes as the industrial revolution was for mechanical processes," said Ayasdi CEO Gurjeet Singh. "Intelligent applications running on our platform are already becoming a fundamental part of our customer's operations with breakthrough results.


Beyond A.I. Forum

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Join Tandem National Security Innovations on Wednesday, Jan. 11th at the Booz Allen Hamilton Innovation Center in Washington DC for an evening devoted to understanding the impact of artificial intelligence and the future it holds for small businesses and startups. We have invited industry leaders and government officials specializing in artificial intelligence and robotics to discuss how A.I. could revolutionize manufacturing, medicine, transportation and a host of other industry sectors. Learn how to set yourself apart in this quickly advancing field. The government wants to invest in artificial intelligence and machine learning programs to modernize national security agencies. Learn about where they want to invest and the new contracting mechanisms agencies are using to recruit startups and small businesses.


How machine learning helps the United Nations monitor global events - TechRepublic

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The United Nations is a vast organization with a diverse set of technology needs. The organization is an umbrella under which numerous sub-organizations--UNHCR and UNICEF, for example--operate somewhat autonomously. The UN is charged with providing global humanitarian relief, resolving multinational disputes, and tracking global crime. The UN generates and tracks information on a global scale but has trouble managing large piles of data and is staffed with policy makers who are not inherently tech-savvy. To grapple with the challenge of big data--in support of the Sustainable Development Goals--the UN partnered with Deepsense.io,


Accenture Combines AI And IoT To Build Technology That Serves Humans

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Global technology major Accenture is looking to use the power of combination of the best technologies in the world to build solutions that are unique for their clients. "Accenture is like a glue organisation," says Marc Carrel-Billiard, global managing director -Technology R&D, Accenture. Accenture's technology R&D division is working towards combining different technologies wherein Artificial intelligence (AI) and Internet of Things (IoT) are at the core of it. Their engineers are combining AI with deep learning and machine learning to interpret the large amounts of data being generated from the 20 billion connected devices today. "So, if you combine all the data coming from the sensors with all the computing power, machine learning...we have the best of both worlds.


Overcoming Bias : This AI Boom Will Also Bust

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Imagine an innovation in pipes. If this innovation were general, something that made all kinds of pipes cheaper to build and maintain, the total benefits could be large, perhaps even comparable to the total amount we spend on pipes today. And if most of the value of pipe use were in many small uses, then that is where most of these economic gains would be found. In contrast, consider an innovation that only improved the very largest pipes. This innovation might, for example, cost a lot to use per meter of pipe, and so only make sense for the largest pipes.


What Is The Difference Between Artificial Intelligence And Machine Learning?

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Artificial Intelligence (AI) and Machine Learning (ML) are two very hot buzzwords right now, and often seem to be used interchangeably. They are not quite the same thing, but the perception that they are can sometimes lead to some confusion. So I thought it would be worth writing a piece to explain the difference. Both terms crop up very frequently when the topic is Big Data, analytics, and the broader waves of technological change which are sweeping through our world. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider "smart".