Data Mapping Using Machine Learning - KDnuggets

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From small to large businesses, just about every company is fighting for a chance to get their audience's attention. Regular marketing campaigns performed 20 years ago just don't cut it anymore. To get ahead of the curve and beat out your competitors, you often have to market directly to the source, especially if you cater to the millennial generation. Collecting data is one way many businesses learn how to target their audience. To market directly to your potential buyer, you need to know what they're interested in, what they need, where they are and where they're most likely to respond to your advertisements.


wei-tim/YOWO

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Code will be uploaded soon! YOWO is a single-stage framework, the input is a clip consisting of several successive frames in a video, while the output predicts bounding box positions as well as corresponding class labels in current frame. Afterwards, with specific strategy, these detections can be linked together to generate Action Tubes in the whole video. Since we do not separate human detection and action classification procedures, the whole network can be optimized by a joint loss in an end-to-end framework. We have carried out a series of comparative evaluations on two challenging representative datasets UCF101-24 and J-HMDB-21.


White-Collar Workers May Be Most Impacted By AI, Says Brookings Report

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As far as the ongoing debate over who is going to be most impacted by the AI trend -- blue-collar or white-collar workers -- the answer, as it turns out, is white collar, says new research from the Brookings Institution. "Better-paid, white-collar or office occupations may be most exposed to AI," Brookings said in summarizing the major findings of a report set to be published today (Nov.


Sony Launches AI Unit to Revolutionise the Way We Cook Talk IoT

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Japanese electronics giant Sony today announced the establishment of Sony AI to "unleash human imagination and creativity with AI. This new organization, with offices globally in Japan, Europe, and the United States, will advance fundamental research and development of AI (artificial intelligence). Sony AI will drive the research and development of AI in both physical and virtual space through multiple world-class flagship projects as well as other explorative research projects, including AI ethics. Initially, Sony AI will launch three flagship projects in the areas of gaming, imaging & sensing, and gastronomy. But the Japanese electronics giant wants to play a bigger role in the food industry. "AI and robotics will not replace chefs.


Nexus FrontierTech closes $3.8m seed funding - UKTN (UK Tech News)

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London-based Nexus FrontierTech, an AI solutions firm specialising in modernising data-intensive processes within the regulatory and compliance realm, has announced that it has closed a $3.8 million seed round to propel its R&D and global expansion. Founded in 2015, Nexus builds configurable, scalable solutions to help businesses streamline operations and tackle the issues of inefficiency and data waste. The company also has a proprietary AI automation platform that enterprises can use to shorten the implementation cycle of production-level AI models from months to within hours. The funding round was led by a family office based in Geneva, Switzerland, followed by a number of private investors, which include Nick Fry, former CEO of Mercedes AMG Petronas F1, Jennifer Lewis, former Managing Director of GIC, Singapore Sovereign Wealth Fund, and Tom Yoritaka, former Managing Director of Cisco Global Ventures. A number of these investors are also on the firm's Advisory Board and heavily involved in the company's expansion and growth strategies.


Artificial Intelligence Delivers at a Global Scale - Seed World

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Artificial Intelligence (AI) is the science of training machines to perform human tasks. The term was invented in the 1950s when scientists began exploring how computers could solve problems on their own. We take for granted how our brains effortlessly calculate the world around us, every second of every day. AI is the concept that a computer can do the same. While AI is the broad science of immolating human learning, machine intelligence (MI) is a specific subset of AI that trains the machine how to learn from data.


ScaleMatrix and Nvidia Launch 'Deploy Anywhere' DGX HPC and AI in a Controlled Enclosure

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HPC and AI in a phone booth: ScaleMatrix and Nvidia announced today at the SC19 conference in Denver a joint offering that puts up to 13 petaflops of Nvidia DGX-1 compute power in an air conditioned, water-cooled ScaleMatrix Dynamic Density Control (DDC) "clean room" cabinet. Built for modular deployments and designed for high-demand AI workloads, ScaleMatrix said its ruggedized cabinet can be erected "anywhere power and a roof exist," and it includes biometric security and fire suppression. At the high end of the product line is a composable SKU comprised of the Nvidia DGX-1 system, a single rack running at 42kW, containing 13 DGX-1 units and delivering 13 Pflops of throughput. Other configurations come with a DGX POD deployment, four DGX-2s, run at 43kW and deliver 8 Pflops of compute, the companies said. The units will be sold with storage and networking following DGX POD reference architecture designs, such as NetApp's ONTAP AI solution.


Asia Times Why China will win the race for AI Opinion

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The role of the development of artificial intelligence in geopolitics usually means competition between the United States and China. While reports are inconclusive about which country will ultimately win (if this is the right term), there is a glaring shortcoming in the United States that China will largely avoid. In 2017 China accounted for 48% of global AI venture capital while the US only accounted for 38%. But only two years later the trend reversed, possibly because of headwinds from the trade war. Neither is it talent acquisition and a brain drain.


Artificial Intelligence Could Improve Health Care for All -- Unless it Doesn't

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You could be forgiven for thinking that AI will soon replace human physicians based on headlines such as "The AI Doctor Will See You Now," "Your Future Doctor May Not Be Human," and "This AI Just Beat Human Doctors on a Clinical Exam." But experts say the reality is more of a collaboration than an ousting: Patients could soon find their lives partly in the hands of AI services working alongside human clinicians. There is no shortage of optimism about AI in the medical community. But many also caution the hype surrounding AI has yet to be realized in real clinical settings. There are also different visions for how AI services could make the biggest impact.


CloudFactory raises $65 million to prep and process data sets

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AI and machine learning algorithms require data. But the bulk of that data is of no use if it isn't first labeled by human annotators. This predicament has given rise to a cottage industry of startups, including Scale AI, which recently raised $100 million for its extensive suite of data labeling services. That's not to mention Mighty AI, Hive, Appen, and Alegion, which together occupy a data annotation tools segment that's anticipated to be worth $1.6 billion by 2025. CloudFactory is yet another vying for attention.