IT thoughts

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It isn't a secret I always loved the technology and solutions NVIDIA provides. Professionally my first encounter was with some Quadro cards and Citrix HDX 3D Pro. The ability to deliver a virtual desktop without poor graphics or finally being able to deliver powerful virtual desktops for GPU demanding applications was amazing. The technology opened up new opportunities. All of a sudden engineers, architects and designers scattered around the world where able to collaborate with their massive assemblies without the need to wait on file synchronization processes.


The Planning Machine

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In June, 1972, Ángel Parra, Chile's leading folksinger, wrote a song titled "Litany for a Computer and a Baby About to Be Born." Computers are like children, he sang, and Chilean bureaucrats must not abandon them. The song was prompted by a visit to Santiago from a British consultant who, with his ample beard and burly physique, reminded Parra of Santa Claus--a Santa bearing a "hidden gift, cybernetics." The consultant, Stafford Beer, had been brought in by Chile's top planners to help guide the country down what Salvador Allende, its democratically elected Marxist leader, was calling "the Chilean road to socialism." Beer was a leading theorist of cybernetics--a discipline born of midcentury efforts to understand the role of communication in controlling social, biological, and technical systems.


Humble Data Science & Machine Learning Bundle

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Here at Humble Bundle, you choose the price and increase your contribution to upgrade your bundle! This bundle has a minimum $1 purchase. All of the content in this bundle is available on most internet browsers. Choose where the money goes - between the publisher and WIRES, RSPCA Australia, and a charity of your choice via the PayPal Giving Fund. If you like what we do, you can leave us a Humble Tip too!


Reinforcement Learning 101

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Reinforcement Learning(RL) is one of the hottest research topics in the field of modern Artificial Intelligence and its popularity is only growing. Let's look at 5 useful things one needs to know to get started with RL. Reinforcement Learning(RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences. Though both supervised and reinforcement learning use mapping between input and output, unlike supervised learning where the feedback provided to the agent is correct set of actions for performing a task, reinforcement learning uses rewards and punishments as signals for positive and negative behavior. As compared to unsupervised learning, reinforcement learning is different in terms of goals.


Receiver Operating Characteristic Curves Demystified (in Python)

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In Data Science, evaluating model performance is very important and the most commonly used performance metric is the classification score. However, when dealing with fraud datasets with heavy class imbalance, a classification score does not make much sense. Instead, Receiver Operating Characteristic or ROC curves offer a better alternative. ROC is a plot of signal (True Positive Rate) against noise (False Positive Rate). The model performance is determined by looking at the area under the ROC curve (or AUC).


Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications

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The problem of finding the sparsest vector (direction) in a low dimensional subspace can be considered as a homogeneous variant of the sparse recovery problem, which finds applications in robust subspace recovery, dictionary learning, sparse blind deconvolution, and many other problems in signal processing and machine learning. However, in contrast to the classical sparse recovery problem, the most natural formulation for finding the sparsest vector in a subspace is usually nonconvex. In this paper, we overview recent advances on global nonconvex optimization theory for solving this problem, ranging from geometric analysis of its optimization landscapes, to efficient optimization algorithms for solving the associated nonconvex optimization problem, to applications in machine intelligence, representation learning, and imaging sciences. Finally, we conclude this review by pointing out several interesting open problems for future research.


AI computational power leaves Moore's Law in the dust Newsflash

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Moore's Law has held up pretty well over the past few decades. The observational'law' was based on the rate at which the number of microcomponents in a microchip or integrated circuit increased. Essentially, this predicted that available computational power or processing speeds would double every 18 months. The rate held more or less steady from 1975 until 2012, but now the advent of artificial intelligence (AI) has seen an increasingly rapid acceleration in processing power. According to Stanford University's 2019 AI Index, the speed at which computational power is doubling has increased massively.


The future is now when it comes to embracing chatbots & AI.

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The future is now when it comes to embracing AI (artificial intelligence). These futuristic ideas are no longer a glimmer in our eyes. We are now fully integrating chatbots and AI in conjunction with Customer Care. It's time to stop talking about the idea of AI and start embracing that they are where Customer Service is NOW. Chances are, you have incorporated AI in your personal life in the form of Alexa, Siri, and Google assistant.


Google favors temporary facial recognition ban as Microsoft pushes back

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The regulation of facial recognition is emerging as a key disagreement among the world's biggest tech companies, with Alphabet and Google CEO Sundar Pichai suggesting a temporary ban, as recently suggested by the EU, might be welcome, while Microsoft's chief legal officer Brad Smith cautions against such intervention. "I think it is important that governments and regulations tackle it sooner rather than later and give a framework for it," Pichai said at a conference in Brussels on Monday, reports Reuters. "It can be immediate but maybe there's a waiting period before we really think about how it's being used ... It's up to governments to chart the course." But in an interview published last week, Smith, who also serves as Microsoft's chief legal officer, was dismissive of the idea of a moratorium. "Look, you can try to solve a problem with a meat cleaver or a scalpel," Smith told NPR when questioned about a potential ban.