software


Explainable AI: Why visualizing neural networks is important

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Last week, researchers from OpenAI and Google introduced Activation Atlases, a tool that helps make sense of the inner workings of neural networks by visualizing how they see and classify different objects. At first glance, Activation Atlases is an amusing tool helps you see the world through the eyes of AI models. But it also one of the many important efforts that are helping explain decisions made by neural networks, one of the greatest challenges of the AI industry and an important hurdle in trusting AI in critical tasks. Artificial intelligence, or namely its popular subset deep learning, is far from the only kind of software we're using. We've been using software in different fields for decades.


Robots As A Service: A Technology Trend Every Business Must Consider

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From all indicators, robots as a service (RaaS) is growing rapidly. ABI Research predicts there will be 1.3 million installations of RaaS by 2026 generating $34 billion in revenue. Let's look at what robots as a service entails, the reasons for its growth and some companies that offer RaaS solutions and the tasks it can support. Many are now familiar with the concept of software as a service (SaaS) or big data as a service (BDaaS), the pay-as-you-go or subscription-based service model. In a similar set-up, those who sign up for robots as a service get the benefits of robotic process automation by leasing robotic devices and accessing a cloud-based subscription service rather than purchasing the equipment outright.


Inside the Mind and Methodology of a Data Scientist - Birst

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When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. And it doesn't help reduce the confusion when every tech vendor rebrands their products as AI. So, what do these terms really mean? What are overlaps and differences? And most importantly, what can this do for your business?


De-mystifying AI and its potential for further application in a B2B context

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AI, or Artificial Intelligence, is often demonised and portrayed as some cyborg entity just about ready to take our jobs and eventually kill us all, but more and more businesses, martech and adtech providers are using different AI subsystems each day to advance their services. The term AI is contentiously used to describe a broad spectrum of systems and software's, the controversy arises from where we can begin to describe a machine as being'intelligent' opposed to simply following complex but nonetheless human-reliant algorithms. Regardless of strict definition, there are helpful systems within the subsets of AI which already exist that B2B marketers need to utilise. Machine learning is a subset of AI that can help marketers to improve productivity by taking over mundane tasks, particularly work involving dissecting datasets (like our Argus platform for example). If you're not already using some forms of machine learning, it might be helpful to understand why some sytstems have been reported to increase the productivity of business by 40% (Source: Accenture) and how you can effectively incorporate machine learning into your marketing strategy.


Quickly learn a new language with AI-powered Lingvist ZDNet

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Census data that shows that 231 million Americans speak only English at home and do not know another language well enough to communicate in it. But how can you learn a new language without going back to school? Machine learning could be a solution to this problem, by cutting down on the 200 hours it takes to learn a language using traditional methods. Language company Lingvist intends to decrease this time by using machine learning software to adapt to your learning style. The algorithm certainly seems to work well -- and the way certain words are reinforced makes sure that they stick in your mind.


Why Tech Firm Scale AI Is the Next $1 Billion Unicorn Star

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Scale AI Inc., a three-year-old startup run by a 22-year-old, is teaching machines how to see. For that, it just joined Silicon Valley's list of unicorns with a fresh $100 million investment that puts its valuation above the coveted $1 billion mark, and its artificial intelligence (AI) technology has already attracted big-name customers in the field for autonomous vehicles, according to Bloomberg. Alphabet Inc.'s (GOOGL) Waymo, General Motor Co.'s (GM) Cruise, and Uber Technologies Inc. (UBER) are all buying what Scale has to offer, because well, self-driving cars are machines that need to be able to see. Scale stands out because it has built a set of software tools that are significantly reducing the time it takes to train a machine how to process and interpret visual imagery. And less time means lower costs.


Facial recognition is now rampant. The implications for our freedom are chilling Stephanie Hare

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Last week, all of us who live in the UK, and all who visit us, discovered that our faces were being scanned secretly by private companies and have been for some time. We don't know what these companies are doing with our faces or how long they've been doing it because they refused to share this with the Financial Times, which reported on Monday that facial recognition technology is being used in King's Cross and may be deployed in Canary Wharf, two areas that cover more than 160 acres of London. We are just as ignorant about what has been happening to our faces when they're scanned by the property developers, shopping centres, museums, conference centres and casinos that have also been secretly using facial recognition technology on us, according to the civil liberties group Big Brother Watch. But we can take a good guess. They may be matching us against police watchlists, maintaining their own watchlists or sharing their watchlists with the police, other companies and other governments.


Jensen Huang interview: Why AI is the single most powerful force of our time

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Nvidia CEO Jensen Huang proudly proclaimed on an analyst earnings call this week that artificial intelligence is the "single most powerful force of our time." Nvidia reported Q2 earnings and revenues that beat analysts' expectations as demand for graphics and artificial intelligence chips picked up. After the earnings call, I interviewed Huang about the company's progress. During the analyst call, he said there are more than 4,000 AI startups working with the company -- as compared to 2,000 AI startups in April 2017. In our interview, Huang said the actual number of AI startups Nvidia is tracking is closer to 4,500.


Global Big Data Conference

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I become addicted to learning a new language with the Lingvist language software within a day of using it. Census data that shows that 231 million Americans speak only English at home and do not know another language well enough to communicate in it. But how can you learn a new language without going back to school? Machine learning could be a solution to this problem, by cutting down on the 200 hours it takes to learn a language using traditional methods. Language company Lingvist intends to decrease this time by using machine learning software to adapt to your learning style.


AI applications, not definitions: demystifying the current landscape - Grit Daily

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AI isn't science fiction or a future technology we're waiting to adopt. It is, right now, affecting every aspect of our daily lives, and that includes how we develop applications, products, and services. Every few years, there's a new buzzword technology that drives mass hype as it promises to disrupt the status quo: software, mobile, IoT, 3D printing, virtual reality, blockchain. In 2016, every company desperately wanted to latch on to artificial intelligence (AI). So while the earliest innovators (think Alan Turing) were studying how computers could mimic humans in the 1950s, we just recently witnessed a hype cycle triggered by the potential for AI to cause the next generational shift in computing.