deep learning


New Research Highlights the Long Road Still Ahead for AI - DZone AI

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The media has been awash with breathless prose about the capabilities of artificial intelligence in recent years. One would be forgiven for thinking that machines are practically at human levels of cognition already, or at least will be very soon. A recent study from UCLA highlights just how far there still is to go. The study illustrated a number of quite significant limitations that the researchers believe we have to understand and improve upon before we let ourselves get carried away. The researchers ran a number of experiments to test the progress made with machine vision.


Most Popular Open Source Projects in Python Programming

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Machine learning and software development make up a large part of all the open-sources projects created with the help of Python. In recent years, these projects caused the creation of many working places for programmers interested in open-source development. Naming the most popular such open-source projects written in Python, it is necessary to mention TensorFlow, Keras, Scikit-learn, Flask, Django, Tornado, Pandas, Kivy, Matplotlib, and the Requests. TensorFlow is an open source software library for machine learning of a wide range of tasks. The library is developed by Google to meet its needs in systems that can build and train neural networks to detect and decrypt images and correlations, similar to the teachings and understandings applied by people.


SK Telecom and Deutsche Telekom to collaborate on blockchain ID

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SK Telecom and Deutsche Telekom will collaborate to create a new blockchain ID that will borderless, they said. SK Telecom and Deutsche Telekom will collaborate to create a blockchain ID with the aim to ease authentication processes, the companies have announced. The South Korean telco will sign an memorandum of understanding to that effect with its German counterpart's research arm, T-Labs, at the upcoming Mobile World Congress (MWC). The two will use blockchain technology to create a mobile digital ID that can be used for authentication, entry control, transactions, and contracts. The ultimately aim will be to make a "borderless" ID, much like a passport, that can used across different countries.


Image Classification

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Recent advances in deep learning made tasks such as Image and speech recognition possible. Most people talk about these days whilst discussing machine learning / deep learning is Tensorflow and Neural Networks. Deep Learning is nothing but a subset of Machine Learning Algorithms which is specifically good at recognizing patterns but typically requires a large number of data. This post describes a Keras based Convolution Neural Net for image classification from scratch. There are several scripts which use pre-trained models available for image classification such as Google's Inception model.


Artificial Intelligence: The Next 24 Months TechNative

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Recent developments are poised to move AI to center stage, leading to revolutions across businesses around the globe. However, challenges remain, and an uncertain future makes it difficult to predict exactly where and how AI will be most effective. Protiviti and ESI ThoughtLab recently conducted a survey of 300 senior executives across the globe to uncover just how AI is being implemented and what to expect in the coming years. According to the survey, just 16 percent of businesses report gaining significant value from AI. Over the next two years, however, this number is expected to more than triple, potentially leading to a majority of businesses relying on AI.


How companies use collaborative filtering to learn exactly what you want

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How do companies like Amazon and Netflix know precisely what you want? Whether it's that new set of speakers that you've been eyeballing, or the next Black Mirror episode -- their use of predictive algorithms has made the job of selling you stuff ridiculously efficient. But as much as we'd all like a juicy conspiracy theory, no, they don't employ psychics. They use something far more magical -- mathematics. Today, we'll look at an approach called collaborative filtering.


Facebook's Yann LeCunn reflects on the enduring appeal of convolutions

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Thirty years ago, Yann LeCun pioneered the use of a particular form of machine learning, called the convolutional neural network, or CNN, while at the University of Toronto. That approach, moving a filter over a set of pixels to detect patterns in images, showed promise in cracking problems such as getting the computer to recognize hand-written digits with minimal human guidance. Years later, LeCun, then at NYU, launched a "conspiracy," as he has termed it, to bring machine learning back into the limelight after a long winter for the discipline. The key was LeCun's CNN, which had continued to develop in sophistication to the point where it could produce results in computer vision that stunned the field. The new breakthroughs with CNNs, along with innovations by peers such as Yoshua Bengio, of Montreal's MILA group for machine learning, and Geoffrey Hinton of Google Brain, succeeded in creating a new springtime for AI research, in the form of deep learning.


Deep Learning Market 2019 Analysis and Precise Outlook- Amazon Web Services (AWS), Google, IBM, Intel, Micron Technology, Microsoft – Marketbizmail - Enterprise & Hybrid Cloud Services

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The report presents an in-depth assessment of the Deep Learning including enabling technologies, key trends, market drivers, challenges, standardization, regulatory landscape, deployment models, operator case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents forecasts for Deep Learning investments from 2019 till 2025. The global Deep Learning market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of 31.2% during 2019-2025. The report presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market. For comprehensive understanding of market dynamics, the global Deep Learning Market is analysed across key geographies namely: United States, China, Europe, Japan, South-east Asia, India and others.


Deep Learning Used To Create Fake Airbnb Listings

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Taking a vacation can sometimes be extremely stressful – finding the right, affordable plane tickets, packing up, getting past the airport security hassles, and most importantly, finding a place to stay. In order to escape from the mind-boggling prices and taxes, we are introduced to a website, Airbnb, which lists apartments around the world for rent. Now, a new website which uses deep learning, suggests fake Airbnb listings which might look convincing enough for people to believe they are real. How can we trust an Airbnb host and their listing? There are a plethora of photos, a detailed description and many reviews previous guests have left which ensure the apartment is the way it was described.


Most popular programming language frameworks and tools for machine learning

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If you're wondering which of the growing suite of programming language libraries and tools are a good choice for implementing machine-learning models then help is at hand. More than 1,300 people mainly working in the tech, finance and healthcare revealed which machine-learning technologies they use at their firms, in a new O'Reilly survey. The list is a mix of software frameworks and libraries for data science favorite Python, big data platforms, and cloud-based services that handle each stage of the machine-learning pipeline. Most firms are still at the evaluation stage when it comes to using machine learning, or AI as the report refers to it, and the most common tools being implemented were those for'model visualization' and'automated model search and hyperparameter tuning'. Unsurprisingly, the most common form of ML being used was supervised learning, where a machine-learning model is trained using large amounts of labelled data.