Google's TensorFlow framework sits at the heart of modern deep learning. Practical features make TensorFlow the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train complex models for vision, language, and more. TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. In this practical tutorial, you'll build reusable skills hands-on as you create production-ready applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers.

You can make money by selling AI-generated images, but don't think it's easy money. Some people will become extremely successful AI artists, others will create content that isn't very good, and some will give up. The best solution is to try new ways which are not obvious but are profitable.

AI and Business Decision In the past, executives relied on inconsistent and incomplete data before the revival of AI and its commercial application. With AI, we now have the option to look up to data-driven models and simulations. A modern AI system feeds on big data business diets instead of starting from scratch. Augmented intelligence is put to work in businesses. It eventually offers executive decision-makers revolutionary models to use as a basis for making decisions.

New York-based insurance provider Travelers, with 30,000 employees and 2021 revenues of about $35 billion, is in the business of risk. Managing all of its facets, of course, requires many different approaches and tools to achieve beneficial outcomes, and Mano Mannoochahr, the company†s SVP and chief data & analytics officer, has a crow†s nest perspective of immediate and long-term tasks to equally strengthen the company culture and customer needs. We needed to think about those disciplines together and make progress to maximize the benefit to our customers and our business overall.†Another focus is on finding and nurturing talent. It†s a pressing issue not unique to Travelers, but Mannoochahr sees that in order to deliver on those disciplines advancing analytics to foster a healthier business, he and his team recognize the need to cast a wider net. This is kind of a team sport for us, so it†s not just data scientists but software engineers, data engineers, and even behavioral scientists to understand how we empathize and best leverage the experience that our frontline employees have, as well as position these capabilities in the best way so we can gain their trust and they can start to trust the data and the tool to make informed decisions.

Content provided by IBM and TNW. Today's AI systems are quickly evolving to become humans' new best friend. We now have AIs that can concoct award-winning whiskey, write poetry, and help doctors perform extremely precise surgical operations. But one thing they can't do -- which is, on the surface, far simpler than all those other things -- is use common sense. Common sense is different from intelligence in that it is usually something innate and natural to humans that helps them navigate daily life, and cannot really be taught.

Tesla's second AI Day is fast approaching, and with it a flurry of speculations as to what will be discussed at the event -- a phenomenon that we at TechCrunch are certainly not above. AI Day is the luxury electric vehicle maker's annual event to hype up its artificial intelligence capabilities across different business segments, with the ultimate goal of recruiting the brightest minds and engineers. Even without Tesla's star head of AI Andrej Karpathy, who left the company in July, expect this event to be full of technical jargon and big promises from Tesla's executives, including the big dog himself, CEO Elon Musk. We'll talk about what we're expecting to hear about based on recent news, as well as last year's AI day event. But first, how to watch.

Let a million monkeys clack on a million typewriters for a million years and, the adage goes, they'll reproduce the works of Shakespeare. Give infinite monkeys infinite time, and they still will not appreciate the bard's poetic turn-of-phrase, even if they can type out the words. The same holds true for artificial intelligence (AI), according to Michael Woolridge, professor of computer science at the University of Oxford. The issue, he said, is not the processing power, but rather a lack of experience. His perspective was published on July 25 in Intelligent Computing, a Science Partner Journal.

Dover, DE, Sept. 21, 2022 (GLOBE NEWSWIRE) -- Metatron Inc. (OTC Pink: MRNJ), a mobile and web technology pioneer having developed over 2,000 apps on iTunes and Google Play, is pleased to announce that the Company has signed final agreement paperwork with Geek Labs Limited to complete Metatron's first acquisition of artificial intelligence technology. The acquisition was successfully negotiated by the two parties over the course of this past week. The acquisition will be a non-dilutive cash purchase and comes with immediate revenue-generating potential for Metatron. Furthermore, this technology acquisition is a wholly owned asset within the quickly growing $450 billion AI industry and can immediately be added to Metatron's corporate bottom line. CEO Joe Riehl commented: "One week ago we formally announced the formation of Metatron's Artificial Intelligence Division. Today we are announcing that we've inked a deal to complete our first AI tech acquisition. I want to send a crystal-clear message to our valued stakeholders that Metatron is entering a new chapter and taking fast steps to add impressive value for our investors. We already have our eye on a second acquisition and talks with the seller are at the midway point. Furthermore, our new AI division has begun planning projects with talented developers operating within the AI sector to build proprietary Metatron AI technology for use in specialty applications. Our new AI division also has begun performing due diligence on strategic AI patents that our team believes could be used in developing new technology and/or holding big tech companies accountable as more and more AI applications come into use."

Some people are worrying if AI is making things like the thesis. The fact is that AI can make things that seem very academic and qualified. But the text itself has no sense. If we want to make an AI that can find information from the Internet we must select some method that this system uses for selecting the texts that it connects to the document. Using linear programming methodology is almost impossible to create text that is suitable for anything.

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