Efficient Computing for Deep Learning, Robotics, and AI (Vivienne Sze) MIT Deep Learning Series

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OUTLINE: 0:00 - Introduction 0:43 - Talk overview 1:18 - Compute for deep learning 5:48 - Power consumption for deep learning, robotics, and AI 9:23 - Deep learning in the context of resource use 12:29 - Deep learning basics 20:28 - Hardware acceleration for deep learning 57:54 - Looking beyond the DNN accelerator for acceleration 1:03:45 - Beyond deep neural networks CONNECT: - If you enjoyed this video, please subscribe to this channel.


PyTorch 1.4 adds experimental Java bindings and more

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PyTorch 1.4 has been released, and the PyTorch domain libraries have been updated along with it. The popular open source machine learning framework has some experimental features on board, so let's take a closer look. PyTorch Mobile was first introduced in PyTorch 1.3 as an experimental release. It should provide an "end-to-end workflow from Python to deployment on iOS and Android," as the website states. In the latest release, PyTorch Mobile is still experimental but has received additional features.


North P&I Club introduces Concirrus as new digital partner

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North P&I Club has announced that it has chosen Concirrus as a digital partner. Concirrus's digital platform, Quest Marine P&I, will contribute to North's loss-prevention and risk-assessment capabilities, the company said. "The activities of the club's loss-prevention department contribute significantly to the understanding of our members' operations, and these will be augmented by leveraging the latest machine-learning techniques and behaviour-based data analytics, which we can access through Quest Marine P&I," said Colin Gillespie, director of loss prevention at North P&I Club. "This in turn has the potential to bring longer-term benefits to underwriting and risk selection, and we believe that the platform will become an important part of our loss-prevention tool kit." The Quest Marine P&I platform brings together billions of rows of dynamic marine and customer data into a single, customisable web application.


AI Isn’t a Solution to All Our Problems

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From the esoteric worlds of predictive health care and cybersecurity to Google's e-mail completion and translation apps, the impacts of AI are increasingly being felt in our everyday lived experience. The way it has crepted into our lives in such diverse ways and its proficiency in low-level knowledge shows that AI is here to stay. But like any helpful new tool, there are notable flaws and consequences to blindly adapting it. AI is a tool--not a cure-all to modern problems. AI tools aim to increase efficiency and effectiveness for organizations that implement them.


How Machine Learning Is Changing The Face Of Financial Services Information Security Buzz

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Few industries have as much historical and structured data than the financial services industry, making it the perfect playing field for machine learning technologies. Investment banks were pioneers of AI technologies, using machine learning since as early as the 1980s. Nowadays, traders and fund managers rely on AI-driven market analysis to make investment decisions that are paving the way for fintech companies to develop new digital solutions for financial trading. AI-driven solutions such as stock-ranking based on pattern matching and deep learning for formulating investment strategies are just some of the innovations available on the market today.


How Machine Learning Is Changing The Face Of Financial Services Information Security Buzz

#artificialintelligence

Few industries have as much historical and structured data than the financial services industry, making it the perfect playing field for machine learning technologies. Investment banks were pioneers of AI technologies, using machine learning since as early as the 1980s. Nowadays, traders and fund managers rely on AI-driven market analysis to make investment decisions that are paving the way for fintech companies to develop new digital solutions for financial trading. AI-driven solutions such as stock-ranking based on pattern matching and deep learning for formulating investment strategies are just some of the innovations available on the market today.


Operationalizing AI

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When AI practitioners talk about taking their machine learning models and deploying them into real-world environments, they don't call it deployment. Instead the term that's used is "operationalizing". This might be confusing for traditional IT operations managers and applications developers. Why don't we deploy or put into production AI models? What does AI operationalization mean and how is it different from the typical application development and IT systems deployment?


Operationalizing AI

#artificialintelligence

When AI practitioners talk about taking their machine learning models and deploying them into real-world environments, they don't call it deployment. Instead the term that's used is "operationalizing". This might be confusing for traditional IT operations managers and applications developers. Why don't we deploy or put into production AI models? What does AI operationalization mean and how is it different from the typical application development and IT systems deployment?


Iran is still willing to negotiate with U.S., foreign minister says

The Japan Times

DUBAI, UNITED ARAB EMIRATES – Iran is not ruling out negotiations with the United States even after an American drone strike that killed a top Iranian general, the country's foreign minister said in an interview released Saturday. Mohammed Javad Zarif told Germany's Der Spiegel magazine that he would "never rule out the possibility that people will change their approach and recognize the realities," in an interview conducted Friday in Tehran. There has been growing tension between Washington and Tehran since in 2018, when President Donald Trump pulled the United States out of the nuclear deal with Iran. The U.S. has since reimposed tough sanctions that have crippled Iran's economy. But Zarif suggested Iran was still willing to talk, though reiterated his country's previous demand that first the U.S. would have to lift sanctions.


AI helping Japan railway companies to combat problems with snow

The Japan Times

Japanese railway companies are turning to artificial intelligence to help tackle potential problems for their shinkansen bullet trains caused by accumulations of snow. West Japan Railway Co. is developing an AI system to gauge the amount of snow attached to Hokuriku Shinkansen trains that cut through Niigata, Toyama and Ishikawa prefectures adjacent to the Sea of Japan. The railway operator currently decides how many personnel to deploy for snow clearance a day beforehand, based on information from meteorological data providers and past experience, but it is often not very accurate. AI will gather data from images of trains that have accumulated snow while traveling, study weather conditions and predict the number of personnel necessary for clearance work. Test operations have proved positive so far and the system is set for full introduction next winter.