Best-selling author Walter Isaacson has been working with NotebookLM to analyze Marie Curie's journals for research on his next book.
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Doctoral Researcher. Cost-efficient DL/ML/AI. Software Developer with 20+ of years experience. ex-Unity, ex-Nokia.
The first scientific paper where I’m the corresponding author has been published: https://lnkd.in/dDWPRq24. Thanks for the work and support by the co-authors! Reading and summarizing all these papers from others builds a solid foundation for the experimental part of my research.
Systematic Literature Review on Cost-Efficient Deep Learning
ieeexplore.ieee.org
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Whether you are an MS scholar, a PhD scholar, or a consultant working on research proposals, research theses/dissertations, business plans, or any project write-up, this video will be a valuable resource for you in every aspect. https://lnkd.in/dduznpG4
MS / PhD Research Proposal: AI Based Tips & Guidelines (Part 3: Jenni.ai) Urdu/Hindi
https://www.youtube.com/
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How do you increase the impact of a #paper when publishing? Researchers from the NCCR Digital Fabrication and the ETH Zurich Competence Center for Materials and Processes (MaP) explored this question in the "Scientific Writing and Publishing with Impact" #workshop. The course discussed how to write a “good” paper and provided an overview of the #publishing process. It also addressed writing in the times of generative #AI and offered strategies for promoting #science on #SocialMedia. Participants learned about #OpenAccess publishing, planning their writing, and getting started effectively. Additionally, the course helped researchers choose the right journal and understand #bibliometrics. Thanks to the ETH Library, which organised the course, and to Caroline Welte, Réka Mihálka, Vinzenz Greiner, Marius Stricker, Christine Bärtsch and Mahmoud Hemila for your input.
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What If We Trained Our Kids the Way We Train AI Models? Artificial Intelligence Learning In the world of artificial intelligence (AI), the learning process begins with data collection. AI models require a vast amount of data to learn from, and the quality of this data significantly impacts the model's performance. Once the data is collected, it undergoes preprocessing, which involves cleaning and organizing the data to make it suitable for training. The next step is feature extraction, where AI models identify and focus on the most important aspects of the data. The AI model then enters the training phase, where it makes predictions based on the data and adjusts its algorithms based on the accuracy of these predictions. Finally, the AI model is tested on new data to see how well it can apply what it's learned. This entire process, from data collection to testing, is carefully designed to enable the AI model to understand and make sense of the world. Children's Learning Process Similarly, children's learning process can be seen as parallel to the way AI models learn. Children learn from the 'data' of their life experiences. Every interaction, every story read, every game played contributes to their understanding of the world. This learning process is often guided by adults who provide context, simplify complex ideas, and encourage children to ask questions, much like the preprocessing stage in AI. Children are also taught to focus on the essentials or 'features' from the information they encounter, such as identifying the moral of a story or the critical steps in a math problem. The practice and correction phase in children's learning is akin to the training phase in AI, where children try new things, make mistakes, receive feedback, and adjust their approach. Finally, just like AI models, children apply their learning in new contexts - they use their skills to solve real-world problems, apply reading skills to new books, and use social skills in different settings. Please read the following article in Science.com https://lnkd.in/d6GwDenZ #ArtificialIntelligence #ChildDevelopment #Education #MachineLearning #Parenting #LearningToLearn #FutureOfEducation #AIinEducation #EdTech #21stCenturySkills
Science | AAAS
science.org
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Good morning LinkedIN community! I am not a robot.... yet, lol. This is a fitting day for me to re-launch my professional life. Leap year and a giant leap into AI research as a non-technical collaborator. #ai, #airesearch My current goals are to develop a skill set and network for AI collaboration. I'm both interested in the practical applications of AI, and the deeper issues it provokes in us. Here is list of fires I'm poking at. 1. AI and the global scholarly system (PR journal articles), a self-organizing yet well-defined universe with it's own citation matrix. Following up on my MA thesis here. Hint: Citations Are All We Need. If you know why I said that, you'd likely get my idea and want to steal it lol. I need Google Scholar humans to look at this. https://lnkd.in/gvQZGdYK #googlescholar 2. I want to take another crack at housing policy with a book on transforming the homelessness crisis, dignity for all. The process of book development collaboration will be the basis for training AI to guide-map 'complex and multifaceted problems', so that these words are no excuse for getting it all wrong! #homelessness #housingcrisis #aiknowledge 3. Writing and research at Goditsme.org . Here we are going in the opposite direction toward the micro and inner dimensions of consciousness, sentience, self-awareness and animation, as well as communication translation beyond the human. Animal, vegetable, mineral - we humans still have a zillion questions for you. What?! Sorry, say that again. Amazing!! #consciousness, #philosophyofmind, #panpsychic Plus you'll want to talk to my avatar lol. Or maybe not, lol. We shall see. It's a cutting edge adventure. 4. Transparent direct coffee trading and roasting ecommerce platform for independent coffee businesses, farmers and roasters. This is a business I've been asked to look at that should empower all of these relationships. I like coffee. Seems that others like it too. So that should work out great :) #coffee
Article 50 million: an estimate of the number of scholarly articles in existence
onlinelibrary.wiley.com
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I have peer-reviewed many manuscripts and still do. Here, authors are using Gen AI to write an introduction for their paper, which is not how it should be done! But what about the manuscript reviewer and editor? This raises questions not only about the authors' approach but also about the role of manuscript reviewers and editors in maintaining the integrity and quality of scientific publications... #publication #generativeai #science
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Branding and marketing Manager| Accessibility, Web 3.0 & WCAG| Growth marketing- CX| Design Thinking | MBA International Marketing
As the 8:13 am train rhythmically transports me to work, I'm immersed in my weekly research routine. A Monday train ride is a hangover between academia and work. In a world where time is of the essence, digital sources have become my trusted companions. Don't get me wrong, I adore libraries, but in this fast-paced era, we need technology that matches our pace. Litmaps – the game-changer in my academic arsenal. As I navigate through a sea of papers, this tool structures my research, keeping me on the sane side of scholarly pursuits. It generates a seed map from your source topic, streamlining papers that are of similar citations. This post is more like a glimpse into my Monday journal, not an advertisement. It's about sharing an #AI tool I've discovered. If you're knee-deep in academic papers, what tools are you using and how are you coping? Image source: litmaps.com #AcademicResearch #LitmapsMagic #ResearchTools
Literature Map Software for Lit Reviews & Research | Litmaps
litmaps.com
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5 free generative AI tools to Boost your research efficiency! 1. ChatPDF: https://www.chatpdf.com/ 。Feature: Speeds up paper reading! 。Summary: Upload the paper and get quick answers through Q&A with the AI agent. This tool is particularly useful if you have an assignment that involves reading a paper and answering questions. 2. Unriddle: https://www.unriddle.ai/ 。Feature: Speeds up paper reading! 。Summary: The AI agent can answer key questions in your literature using a Q&A and can highlight the original text. 3. Perplexity: https://www.perplexity.ai/ 。Feature: Speeds up paper searching! 。Summary: Ask questions, and the AI agent will answer your question and cite the relevant article. It is an efficient tool for obtaining quick insights. 4. Elicit: https://elicit.com/ 。Feature: Speeds up paper searching and reading! 。Summary: Ask questions, and the AI agent will recommend the most relevant literature to you and provide a summary. This tool is very useful when you are crafting the introduction to your paper. 5. Connected Papers: https://lnkd.in/gUFgz_JR 。Feature: Visualize the relationship between articles! 。Summary: Use graphs to visually understand the relationship between documents and accelerate your journey to becoming a domain expert. This is the coolest website I’ve seen for finding relevant research. Note: Exercise caution when using these tools, as the answers may not always be correct or accurate. #AItools #connectedpapers #chatpdf #unriddle #perplexity #elicit
Connected Papers | Find and explore academic papers
connectedpapers.com
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I recently discovered Connected Papers, a visual AI resource for conducting literature searches! This tool is easy to use and helps you quickly identify similar papers with just one "seed paper". Check it out and see how it can revolutionize your literature searches. What’s more, it’s free!. #AI #literaturereview #ConnectedPapers
Connected Papers | Find and explore academic papers
connectedpapers.com
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