GPUs are famously expensive – high end Nvidia Teslas can be priced well above $10,000. Now a New York startup, Paperspace, has announced a free cloud GPU service for machine/deep learning development on the company's cloud computing and deep learning platform. Designed for students and professional learning how to build, train and deploy machine learning models, the service can be thought of as an ML/DL starter kit that helps developers expand their skills and try out new ideas without financial risk. Utilizing Nvidia Quadro M4000 and P5000 GPU's and called "Gradient Community Notebooks," the service is based on Jupyter notebooks and enables developers working with widely used deep learning frameworks, such as PyTorch, TensorFlow, Keras and OpenCV, to launch and collaborate on their ML projects. Similar to GitHub, Gradient Community Notebooks can be shared and "forked" into a user's own account while providing pre-loaded templates with various libraries, dependencies and drivers, the company said.
Facebook Inc. today updated its popular artificial intelligence software framework PyTorch with support for new features that enable a more seamless AI model deployment to mobile devices. PyTorch is used by developers to research and build AI models for software applications, and then move those apps straight to production thanks to its integration with leading public cloud platforms. PyTorch was first built by Facebook's AI research group as a machine learning library of functions for the programming language Python. It's primarily designed for use with deep learning, which is a branch of machine learning that attempts to emulate the way the human brain functions. It has led to major breakthroughs in areas such as language translation and image and voice recognition.
David Ferrucci led the team that built Watson, the IBM question-answering system that beat the top humans in the world at the game of Jeopardy. He is also the Founder, CEO, and Chief Scientist of Elemental Cognition, a company working engineer AI systems that understand the world the way people do. This conversation is part of the Artificial Intelligence podcast.
It's quite a direct statement to make, but at the end of the day, that's what it really comes down to. If your site content or service isn't catering to exactly what your audience is looking for, then they will leave within a few seconds and likely never come back. Unfortunately, this is something that happens millions of times per day across millions of sites on the internet. Too much emphasis is being placed on creating content and not enough on personalizing content. With user engagement, interests and browsing habits being collected and tracked more than ever before… websites and blogs of all sizes should be using this data to improve user experience through site content, navigation, calls-to-action, and user intent.
It is a truism that artificial intelligence (AI) is set to change the world in unimaginable ways. The giants of the tech industry have realised it and are investing heavily in it, as can be seen, for instance, from Microsoft's $1 billion investment in OpenAI, which in turn was founded by Tesla's Elon Musk, and seeks to use AI to benefit all of mankind. Again, Twitter has acquired four AI companies - the biggest of them being Magic Pony for $150 million in 2016 - in its bid to improve its system of recommending specific tweets in users' timelines. Even traditional businesses are using AI to improve their services, such as UK-based grocer Nisa Retail employing Amazon Web Services to meet its business challenges. India too has plunged headlong into AI and machine learning (ML) with numerous start-ups offering AI solutions in areas such as banking, logistics and transportation.
The graph represents a network of 4,041 Twitter users whose tweets in the requested range contained "futureofwork ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 14 October 2019 at 01:34 UTC. The requested start date was Monday, 14 October 2019 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 5,000. The tweets in the network were tweeted over the 3-day, 8-hour, 54-minute period from Thursday, 10 October 2019 at 15:06 UTC to Monday, 14 October 2019 at 00:00 UTC.
Facebook's head of artificial intelligence, Yann LeCun, seems to fit that profile to a T. "I work mostly by intuition," he writes in When the Machine Learns, a new book that is part biography, part science lecture, part AI history, published Wednesday in French as Quand la machine apprend. "I project in my head the borderline cases, that which Einstein called the'thought experiments'," writes LeCun. LeCun is animated on stage, clearly energized by trying to convey things at the edges of AI that have come from his thought experiments. That ability to imagine something that doesn't exist, perhaps at the limit of what's generally thought feasible, is the mark of engineers and innovators. LeCun is something of a rarity among the AI crowd, a scientist who is at home in algorithm design but also has one foot firmly in computer engineering.
In widening its punishment of China in the ongoing US-China trade war, the US has extended its blacklist to directly handicap its biggest competition in a much higher stakes race, for world domination in AI. Recently, almost ten more AI companies – including providers of video surveillance, facial and speech recognition and data recovery; were added to US trade black list. The reasons cited were related to the violation of human rights by the supposed usage of AI technology in China's repression the Muslim ethnic minority groups of the Uygur region. Here is an interesting digression; that one of the most notable Chinese AI companies in this most recent US blacklist is SenseTime Group (known for its facial recognition AI tech), whose founder Tang Xiao'ou was appointed as the foreign national to Malaysia's sovereign wealth fund, Khazanah Nasional. SenseTime is the top AI'unicorns' startup from China with a valuation of over USD7 billion.
Snapchat is rolling out Dynamic Ads – new ad unit designed specifically for Ecommerce advertisers. "Over the years, Snap has invested heavily in solutions for performance marketers to drive their business, and this new addition will only increase the depth of our offering." What Dynamic Ads offer that Snapchat's other advertising options do not is automated personalization, which offers new ways to scale and drive performance. Snapchat is selling the ad unit as a simple way to create mobile ads at scale while maintaining brand identity through mobile-first templates. Syncing a product catalog allows Snapchat to be continually updated about changes to products.
In this SAS How To Tutorial, Ari Zitin explores several examples of Python integration with SAS. There are many SAS Viya Cloud Analytic Services (CAS) that can be submitted from Python. In this Python integration demo, Ari focuses on predictive modeling. He shows how to connect to CAS, access in-memory data, bring data locally to use Pandas, and prepare data for predictive modeling. Ari then steps through how to build, score and assess a Decision Tree model.