It’s the buzz everywhere — from classrooms to boardrooms. Generative artificial intelligence, originally a concept only found in the pages of speculative fiction, now plays a pivotal role in our digital lives. But what is it and how does it work? 🤔 Dive into our latest blog to find out: https://mcafee.ly/3xNQF8z
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Generative AI is the specific type of artificial intelligence that powers many of the AI tools available today in the pockets of the public. The “G” in ChatGPT stands for generative. Today’s Gen AI’s evolved from the use of chatbots in the 1960s. Now, as AI and related technologies like deep learning and machine learning have evolved, generative AI can answer prompts and create text, art, videos, and even simulate convincing human voices.
It’s the buzz everywhere — from classrooms to boardrooms. Generative artificial intelligence, originally a concept only found in the pages of speculative fiction, now plays a pivotal role in our digital lives. But what is it and how does it work? 🤔 Dive into our latest blog to find out: https://mcafee.ly/3xNQF8z
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VoiceCraft - A new zero-shot speech editing and text-to-speech model. Just tried it out. Really amazing speed at inference. You can also do voice cloning and it only needs like 3 seconds of reference. At the moment, it only supports English though. Models are on Huggingface 🤗 Really cool to see how TTS research has progressed. Wasn't like that when we started it at Axel Springer. 🎙️ Demo: https://lnkd.in/gbxqmz_d 📝 Paper: https://lnkd.in/gbTNnF_Z
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"Slamming people with advertisements, newsletter popups, busy sidebars, and AI features that no one needs is profoundly inaccessible. Processing information costs energy, it tires us out, and the modern web is an absolute dystopia of sensory bombardment." For the latest Pixel Pioneers speaker spotlight, I talked to Scott Riley about the second edition of his book, Mindful Design, what we will be able to take away from his talk, and the application of cognitive psychology – good and bad – to digital product design: https://lnkd.in/ehS_-8gp
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Not just in RL, but in any optimization, doing single-objective optimization almost always leads to unwanted side effects. The paper mentions : "MORL methods could model the reputational harm as an additional objective to be minimised. But this may be very difficult to define quantitatively. " This goes for any optimization whether it is: 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 - Create a recommendation system that both increases revenue, customer satisfaction with reduced risk of unfairness. - Find ML models that solve the problem best, while using as little computation as required. 𝒄𝒉𝒂𝒏𝒈𝒆𝒔 𝒊𝒏 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝒑𝒓𝒐𝒄𝒆𝒔𝒔 - Change your pricing strategy to minimize churn, maximize revenue and conversion. 𝑲𝑷𝑰'𝒔 𝒕𝒐 𝒋𝒖𝒅𝒈𝒆 𝒑𝒆𝒓𝒇𝒐𝒓𝒎𝒂𝒏𝒄𝒆 - Make best strategic decisions that both maximize growth, while minimizing employee turnover and without reducing the quality. For that reason I am working on a framework that unifies any optimization problem under the same multi-objective definition.
A new pre-print, where we argue that everyone is doing RL wrong 🙂, and advocate adopting the multi-policy utility-based paradigm from multi-objective RL even for single-objective problems. https://lnkd.in/gxeQ8cwS
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American philosopher Jerry Fodor’s highly influential text, The Modularity of the Mind, introduced then-fresh ideas about the architectural systems underlying perception and language in the 1980s. His thinking was highly influential for early computation thinkers and the first #conversationalAI systems. We're reading the 10 most influential books on computation and cognition. Next we read Noam Chomsky's Syntactic Structures 🔍 Follow along and please chime in if you're interested 📚
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Dear Network, I am back and of course with pockets full. I'm thrilled to share that our journey through the Image Processing Fundamentals series has arrived to its end, culminating in the last chapter on "Image Classification." In this last, I introduced a range of classifiers used in image processing, covering various types, both classical and modern. For those who missed any part of the series, you can find all the lectures, including the latest chapter, right here. Feel free to explore the rich content and gain insights into the fascinating world of image processing. Stay tuned for what's coming next ^^ #ImageProcessing #ComputerVision #LearningJourney #LinkedInLearning #ImageClassification #TechEducation
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Linear Time O(N) novel solution to N-Queen Problem👑. Excited to share our latest research paper on a groundbreaking heuristic-based linear time O(N) solution to the N-Queen problem! 🎉 Special thanks to my mentors, Dr. Vikrant Sharma and Dr. Satvik Vats, for their invaluable guidance throughout this journey. Grateful for their expertise, encouragement, and unwavering support, which played a pivotal role in bringing this innovative solution to fruition. This paper represents a significant leap in addressing the N-Queen problem efficiently, and I'm thrilled to contribute to the field of algorithmic optimization. 🚀 #Research #Algorithm #Innovation #NQueenProblem #Gratitude
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Data Scientist | AI Enthusiast | Machine Learning & Deep Learning Specialist | AI Researcher | Passionate About Medical Imaging Research
Image Processing Notes
Dear Network, I am back and of course with pockets full. I'm thrilled to share that our journey through the Image Processing Fundamentals series has arrived to its end, culminating in the last chapter on "Image Classification." In this last, I introduced a range of classifiers used in image processing, covering various types, both classical and modern. For those who missed any part of the series, you can find all the lectures, including the latest chapter, right here. Feel free to explore the rich content and gain insights into the fascinating world of image processing. Stay tuned for what's coming next ^^ #ImageProcessing #ComputerVision #LearningJourney #LinkedInLearning #ImageClassification #TechEducation
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Impact Entrepreneur in Arts and STEAM education | New Media Artist and XR Experience Designer | Speaker on Culture Tech | Artistic Director of Never Gallery Ready | Head of Arts & Culture at Creative Commons Canada
Have you ever wished to be in conversation with a great mind from another era? Or perhaps imagined what that dialogue would look and feel like, what insights it might bring, how it might expand your understanding of their thinking? Raising Mcluhan is a project exploring the ways in which AI/LLMs can make that dream a reality, with Marshall McLuhan, Canadian media theorist and philosopher. Join me, Andrew McLuhan , Sandro Pasquali and Freyja van den Boom this Saturday at Gray Area ‘s Grand Theatre in San Francisco , 5-7pm to learn more about the 15 year undertaking we’re designing to be a living archive, time machine and context engine. And so very much more. The Raising McLuhan project, a media tech labour of love designed by media makers, archivists, technologists and philosophers with the aim to ‘raise’ Marshall McLuhan (as from the dead, from a child, from obscurity) and parent (rather than train) an AI model on McLuhan’s «body» of work and the legacy his archives hold. Come hear from the project team about their visions and entry points for this planned multi-year project. It begins in 2024 and 1964 when Understanding Media: The Extensions of Man was first published. The project will intimately grow to include many multimedia experiences that will deepen our understandings of how the medium is the message—then, now, and tomorrow. #raisingmcluhan #artificalintellegence #llms #newmedia #oldmedia #mixedreality #interdisciplinary #archives #techerhics #marshallmcluhan
Raising McLuhan - Talk and Presentation with Andrew McLuhan
https://grayarea.org
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I was recently asked. How do you remember so many things? A simple hack I use is repetition. Repetition can help with information retention especially when you go back to the content over and over again. In so doing, you not only retain what you’ve learned, but also, give time for your brain to absorb it. In memory research, this is known as the “spacing effect”. To read more, check out this article: https://lnkd.in/gx5fuEpN
The Best Strategy for Learning May Depend on What You’re Trying to Remember
scientificamerican.com
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