Finding the true potential of algorithms

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Each semester, Associate Professor Virginia Vassilevska Williams tries to impart one fundamental lesson to her computer-science undergraduates: Math is the foundation of everything. Often, students come into Williams' class, 6.006 (Introduction to Algorithms), wanting to dive into advanced programming that power the latest, greatest computing techniques. Her lessons instead focus on how algorithms are designed around core mathematical models and concepts. "When taking an algorithms class, many students expect to program a lot and perhaps use deep learning, but it's very mathematical and has very little programming," says Williams, the Steven G. (1968) and Renee Finn Career Development Professor who recently earned tenure in the Department of Electrical Engineering and Computer Science. "We don't have much time together in class (only two hours a week), but I hope in that time they get to see a little of the beauty of math -- because math allows you to see how and why everything works together. It really is a beautiful thing."


Digit Recognition: A Beginner's Guide to Keras

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Over the last decade, the use of artificial neural networks (ANNs) has increased considerably. People have used ANNs in medical diagnoses, to predict Bitcoin prices, and to create fake Obama videos! With all the buzz about deep learning and artificial neural networks, haven't you always wanted to create one for yourself? In this tutorial, we'll create a model to recognize handwritten digits We use the keras library for training the model in this tutorial. Keras is a high-level library in Python that is a wrapper over TensorFlow, CNTK and Theano.


Where is machine learning going in 2020?

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If popular media is to be believed, Artificial Intelligence (AI) is everywhere and it's either going to solve all our problems or robots are going to take over the world and we're going to lose our jobs. AI is the new oil, or the new electricity. In the enterprise market, I'd like to think we are slightly more used to navigating the sweeping predictions and assumptions that come with emerging technology hype. At the beginning of 2019, there was a lot of chatter about enterprises finally being ready to make the move to deliver on the promise of machine learning (ML). However, what we actually saw, again, was enterprises struggling to get into production with ML and other types of AI.


#WorkTrends: Ageism and Its Impact on the Modern Worker - TalentCulture

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As an HR tech analyst, author and brand strategist, Meghan is sought after for her ideas about the future of work, is a regularly featured speaker at global business conferences, and serves on boards for leading HR and technology brands.


Predictive CPU isolation of containers at Netflix

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We've all had noisy neighbors at one point in our life. Whether it's at a cafe or through a wall of an apartment, it is always disruptive. The need for good manners in shared spaces turns out to be important not just for people, but for your Docker containers too. When you're running in the cloud your containers are in a shared space; in particular they share the CPU's memory hierarchy of the host instance. Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains.


Reality Engines offers a deep learning tour de force to challenge Amazon et al in Enterprise AI

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Bindu Reddy, co-founder and chief executive of startup Reality Engines, unveiled a slew of enterprise apps based on cutting-edge deep learning techniques. "Our moat comes both from constantly innovating and in getting more and more practice on key enterprise use-cases," said Reddy, who was formerly head of "AI verticals" at Amazon's AWS cloud service. Barely a year old, Reality Engines of San Francisco emerged from stealth mode on Tuesday, announcing a slew of artificial intelligence offerings to perform corporate tasks such as budgeting for cloud services or monitoring corporate networks for break-ins. Most exciting of all is that the tiny 18-person team has some very novel takes on deep learning forms of AI, the product of seasoned vets in machine learning technology and products. This is no me-too chatbot service, it would appear.


RecordPoint Records365 Demo Webinar - North America RecordPoint

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This event is running from 27 September 2018 until 30 January 2020. Records365 is a records management SaaS for organizations that need to meet industry or governmental regulations in one or more content sources such as Office 365, SharePoint, box, exchange online, physical records, file shares and more. Attend this webinar, hosted by Paul Kelly, RecordPoint's Technical Sales & Delivery Manager, for a quick and interactive overview of how Record365 delivers easy, modern, and trusted records management and compliance, including: – Platform agnostic records management compliant with local and global standards – In-place records management across a range of electronic and physical content sources – Rules-based classification to automate your records life-cycle – Leveraging the power of Artificial Intelligence to maximize your total compliance efforts – Simple event-based retention – Zero impact to end users


Reality Engines offers a deep learning tour de force to challenge Amazon et al in Enterprise AI ZDNet

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Bindu Reddy, co-founder and chief executive of startup Reality Engines, unveiled a slew of enterprise apps based on cutting-edge deep learning techniques. "Our moat comes both from constantly innovating and in getting more and more practice on key enterprise use-cases," said Reddy, who was formerly head of "AI verticals" at Amazon's AWS cloud service. Barely a year old, Reality Engines of San Francisco emerged from stealth mode on Tuesday, announcing a slew of artificial intelligence offerings to perform corporate tasks such as budgeting for cloud services or monitoring corporate networks for break-ins. Most exciting of all is that the tiny 18-person team has some very novel takes on deep learning forms of AI, the product of seasoned vets in machine learning technology and products. This is no me-too chatbot service, it would appear.


UPS will now use dynamic routing to get parcels to you on time

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UPS is bringing dynamic routing to its on-road integrated optimization and navigation (ORION) platform, as the package delivery and logistics giant looks to reduce the number of miles traveled, fuel consumed, and CO2 emitted. For context, UPS delivers some 21 million packages globally each day, with many UPS drivers making well over 100 stops per shift. Figuring out the optimum route that each driver should travel to expedite deliveries (and reduce costs) is a challenge given the sheer number of combinations available. It's generally accepted that avoiding left-turns is a good thing due to the idling involved, which means that maximizing the number of right turns is desirable -- but computing all the possible permutations for this across 100 delivery destinations is a task of herculean proportions. And that is what ORION is essentially about.


What Politicians Don't Understand About The AI Debate

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The U.S. economy continues to expand, with reports from the Bureau of Labor Statistics indicating there are more job openings in the U.S. than people to fill them. Despite this data, working Americans are very concerned about job loss due to AI and automation, especially as politicians fan the flames of fear to gain advantage as the election race heats up. Democratic primary candidate and tech entrepreneur Andrew Yang has proposed the Freedom Dividend, a form of universal basic income (UBI) to supplement income lost by automation. Senator Elizabeth Warren is instead focusing on policy reform, training her sights on the multinational corporations moving their factories overseas. Former Vice President Joe Biden has proposed 14 years of public education in an effort to prepare workers for a future where technology reigns.