Unity-ML Agents: The Mayan Adventure

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In the last two articles, you learned to use ML-Agents and trained two agents. The first was able to jump over walls, and the second learned to destroy a pyramid to get the golden brick. It's time to do something harder. When I was thinking about creating a custom environment, I remembered the famous scene in Indiana Jones, where Indy needs to get the golden statue and avoid a lot of traps to survive. I was thinking: could my agent could be as good as him?


Industrial Machine Vision Solutions from Intel

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Machine vision is the ability for machines to see their environment and make decisions based on visual input, such as image data or video data in an industrial setting. It's carried out through a combination of specialized hardware and software that provide image-based sensing and processing in industrial settings. It can also be used to maintain a safe and secure industrial environment. Machine vision has been one of the key drivers of industrial automation in recent years. It helps automate factory and plant processes by collecting and intelligently responding to patterns in visual data.


DeepMind's Agent57 beats humans at 57 classic Atari games

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In a preprint paper published this week by DeepMind, Google parent company Alphabet's U.K.-based research division, a team of scientists describe Agent57, which they say is the first system that outperforms humans on all 57 Atari games in the Arcade Learning Environment data set. Assuming the claim holds water, Agent57 could lay the groundwork for more capable AI decision-making models than have been previously released. This could be a boon for enterprises looking to boost productivity through workplace automation; imagine AI that automatically completes not only mundane, repetitive tasks like data entry, but which reasons about its environment. "With Agent57, we have succeeded in building a more generally intelligent agent that has above-human performance on all tasks in the Atari57 benchmark," wrote the study's coauthors. "Agent57 was able to scale with increasing amounts of computation: the longer it trained, the higher its score got."


Regulation: For AML, fintech is both problem and answer

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One subject never fails to light up the eyes of senior bankers and regulators when they're questioned about their efforts to end the money laundering-related scandals that have spread across northern Europe over the last two years: technology. There can be no more damning indictment of the integrity of a bank, or its host nation, than the public revelation that a licensed institution is being used as a laundromat for ill-gotten gains. And what is more enlivening for money-laundering supervisors and bank-compliance officers than showing your firm and country is at the forefront of a technology that could make these troubles disappear? Some of the biggest actors in Europe's financial sector are converts. The UK's Financial Conduct Authority is particularly enthusiastic about using technology to fight money laundering.


Making Industrial Robots Collaborative

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With its FreeMove system in use in the aerospace, automotive, appliance, and construction equipment manufacturing industries, Veo Robotics is proving that high-speed, heavy-payload robots can be cobots too. Robotic arm market to grow to US$14.78bn by 2026 Can AI Detect Your Emotion Just By How You Walk?


Google and the Oxford Internet Institute explain artificial intelligence basics with the 'A-Z of AI'

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Artificial intelligence (AI) is informing just about every facet of society, from detecting fraud and surveillance to helping countries battle the current COVID-19 pandemic. But AI is a thorny subject, fraught with complex terminology, contradictory information, and general confusion about what it is at its most fundamental level. This is why the Oxford Internet Institute (OII), the University of Oxford's research and teaching department specializing in the social science of the internet, has partnered with Google to launch a portal with a series of explainers outlining what AI actually is -- including the fundamentals, ethics, its impact on society, and how it's created. The Oxford Internet Institute is a multidisciplinary research and teaching department of the University of Oxford, dedicated to the social science of the Internet. At launch, the "A-Z of AI" covers 26 topics, including bias and how AI is used in climate science, ethics, machine learning, human-in-the-loop, and Generative adversarial networks (GANs).


IT expert roundtable: Driving sales efficiency with Dynamics 365 and Microsoft AI

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Dynamics 365 for Sales and Microsoft AI are used to present the highest-priority sales leads to sellers. With this new solution, sellers can quickly act on the leads most likely to become customers. The solution creates a simple, intelligent system for discovering and contacting the best lead and makes our sellers more efficient and effective. During this webinar experts from Core Services Engineering Organization (CSEO) answered questions on how to use Microsoft AI with Dynamics 365 for Sales.


The Man who forever changed Artificial Intelligence

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Sign in to report inappropriate content. History of Artificial Intelligence: The success of Neural Networks has sparked the AI revolution in the last 10 years. From Atari Games to Go, to Dota and to Starcraft. What many people don't know - the basic idea of Neural Networks has been around since the late 1950s. My name is Sebastian Schuchmann and I hope you enjoy watching!


Interview: How artificial intelligence will change medicine

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Question: You lead the "Scientific Data Management" research group at TIB – Leibniz Information Centre for Science and Technology. You focus your research on how big data technologies can be used in the health sector to improve health care. What exactly are you researching? The amount of available big data has grown drastically in the last decade, and it is expected a faster growth rate in the coming years. Specifically, in the biomedical domain, there are a wide variety of methods, e.g.


Azure/ai-toolkit-iot-edge

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The integration of Azure Machine Learning and Azure IoT Edge enables organizations and developers to apply AI and ML to data that can't make it to the cloud due to data sovereignty, privacy, and/or bandwidth issues. All models created using Azure Machine Learning can now be deployed to IoT gateways and devices with the Azure IoT Edge runtime. Models are operationalized as containers and can run on many types of hardware, from very small devices all the way to powerful servers. We're releasing this toolkit to help get you started with AI and Azure IoT Edge. The toolkit will show you how to package deep learning models in Azure IoT Edge-compatible Docker containers and expose those models as REST APIs.