If you're planning to create a LibGuide that revolves around AI and its related technologies, here are resources that will help craft your AI LibGuide.
Below are AI Libguides that adjust to their universities.
University | URL |
---|---|
Rutgers University | Rutgers University's AI Guide |
University of South Florida | University of South Florida's AI Tools and Resources |
Thompson Rivers University | Thompson Rivers University's AI Guide for Students |
Colorado Community College System | Colorado Community College System's AI and ChatGPT Guide |
University of Texas Southwestern Medical Center | University of Texas Southwestern Medical Center's AI Chatbots Guide |
ECPI University | ECPI University's AI Chatbots Guide |
California State University, Long Beach | California State University, Long Beach's AI Technologies Guide |
University of Hawaii - West Oahu | University of Hawaii - West Oahu's AI Chatbots Guide |
Illinois Institute of Technology | Illinois Institute of Technology's AI Guide |
St. John Fisher University | St. John Fisher University's AI Tools and Resources Guide |
SUNY College of Environmental Science & Forestry | SUNY College of Environmental Science & Forestry's AI Guide |
AI News Sites for Librarians
Please find below a list of resources to help you stay updated on the latest advancements in the field of Artificial Intelligence. These resources cover a wide range of topics, including AI research, development, and trends.
ScienceDaily (www.sciencedaily.com): This website offers a broad range of articles on AI, including comparisons of different AI models and their applications in various fields.
Google AI Blog (ai.googleblog.com): This blog is an excellent resource for insights directly from Google's AI technology developers, covering Google Bard and other Google AI projects.
Stability AI Blog (https://stability.ai/news): This website provides information on Stability AI's developments, such as DeepFloyd IF and other text-to-image models.
OpenAI Blog (openai.com/blog): As the developers of ChatGPT and DALL·E, OpenAI's blog is a primary source for the latest updates and advancements related to their products.
MarkTechPost (www.marktechpost.com): This website provides detailed insights into the latest developments in AI technology, including multimodal AI systems like ChatGPT, Google Bard, and more. They offer comprehensive articles on various AI tools and their applications.
In addition, the following resources reflect ongoing trends and debates in the AI field:
MIT Technology Review (www.technologyreview.com): This site offers in-depth analysis and reports on emerging technology, including AI, and often covers the societal and ethical implications of AI advancements.
Wired (https://www.wired.com/tag/artificial-intelligence/): Wired provides articles and news on the latest trends in technology, including AI, and often discusses the impact of AI on society and the latest developments in the field.
Towards Data Science (towardsdatascience.com): This Medium publication provides personal insights and experiences from data scientists and AI practitioners, covering various aspects of AI and machine learning.
The Verge (www.theverge.com/ai): This website covers a wide range of technology news, including AI. They often discuss the impact of AI on society and the latest developments in the field.
AI Magazine (aimagazine.com): This magazine offers insights, analyses, and trends in AI, with content ranging from technical advancements to societal impacts.
Nature – AI Section (https://www.nature.com/news): For a more scientific and research-oriented perspective, Nature's AI section offers articles and studies about the latest advancements and challenges in AI.
VentureBeat (venturebeat.com/category/ai): VentureBeat frequently covers AI topics, with a focus on business, AI startups, and the impact of AI on various industries.
Harvard Business Review – AI Section (https://hbr.org/topic/subject/ai-and-machine-learning): HBR provides a more business-oriented perspective on AI, including its implications for management, strategy, and ethics.
AI Trends (www.aitrends.com): This website is focused solely on AI and covers the latest trends, research, and debates in the field. It's a great resource for keeping up with the evolving landscape of AI.
Please find below a list of resources that offer comprehensive coverage of AI subjects and are specifically focused on AI. These resources include books, journals, and multimedia:
Books
https://bookauthority.org/books/new-artificial-intelligence-books
Podcasts
The TWIML AI Podcast with Sam Charrington (https://twimlai.com/podcast/twimlai/): This podcast brings in a wide array of guests from the AI industry, including researchers, data scientists, engineers, business and IT leaders who have a strong understanding of technology. Host Sam Charrington is highly knowledgeable about AI concepts and has a talent for featuring both established and lesser-known experts in the field.The AI Breakdown (https://www.youtube.com/@theaibreakdown): This is a specialized daily news show analyzing AI advancements for industry professionals.
Machine Learning with Jay Shah (https://www.youtube.com/c/JayShahml/featured): Computer scientist and Ph.D. student Jay Shah hosts this podcast, exploring various applications of machine learning across industry and academia. With Shah's ability to make guests feel comfortable, the podcast leads to insightful discussions.
Machine Learning Street Talk (https://www.youtube.com/channel/UCMLtBahI5DMrt0NPvDSoIRQ): This podcast features technical discussions with knowledgeable guests in the machine learning industry. Hosted by Dr. Tim Scarfe, Dr. Yannic Kilcher, and Dr. Keith Duggar, it is known for its comprehensive research and unfiltered conversations.
Journals
Journal of Machine Learning Research (https://jmlr.org/): This is a platform for publishing machine learning research globally.
Cognitive Psychology (https://www.sciencedirect.com/journal/cognitive-psychology): This journal focuses on extensive articles in cognitive theory, covering research areas such as artificial intelligence, linguistics, developmental psychology, social psychology, and neurophysiology.
IEEE Transactions on Pattern Analysis and Machine Intelligence (https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=34): This journal focuses on traditional computer vision, image understanding, and pattern analysis. It also covers machine learning for pattern analysis.
IEEE Transactions on Neural Networks and Learning Systems (https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5962385): This journal focuses on the theory, design, and applications of neural networks and related learning systems.
Journal of Memory and Language (https://www.sciencedirect.com/journal/journal-of-memory-and-language): This journal contributes to the formulation of scientific issues and theories in the areas of language comprehension and production, memory, and cognitive processes.
Journal of the ACM (https://dl.acm.org/journal/jacm): It covers a broad range of topics in computer science, including artificial intelligence, computational biology, machine learning, and information theory.
AI Technology Spectrum
Here's a summary table that outlines various Artificial Intelligence (AI) technologies, their current state of development, possible applications, and potential implications. It can be a useful reference for understanding the landscape of AI and its impact on various industries and sectors.
AI Technology | Development | Applications | Implications |
---|---|---|---|
Machine Learning (ML) | Evolved from pattern recognition and computational learning theory. Uses statistical techniques to enable computers to improve at tasks with experience. | Widely used in data analytics, financial forecasting, recommendation systems, and more. | Raises concerns about privacy, job displacement, and decision-making biases. |
Deep Learning | A type of machine learning that uses artificial neural networks and representation learning, inspired by the brain's structure and function. | Key in image and speech recognition, natural language processing, and autonomous vehicles. | This task demands significant amounts of data and computing resources. However, it also carries the risk of misinterpretation and abusive use in surveillance. |
Natural Language Processing (NLP) | Combines computational linguistics with ML to enable understanding and manipulation of human language. | Used in chatbots, translation services, sentiment analysis, and content creation. | There are two major challenges when it comes to language: understanding context and grasping subtleties. Additionally, there are ethical concerns in generating content. |
Computer Vision | This refers to techniques used to obtain, analyze, and interpret visual data in order to generate either numerical or symbolic data. | Facial recognition, medical imaging, surveillance, and autonomous vehicles are some of the applications that rely on advanced technology. | There are concerns about privacy, potential biases in facial recognition, and ethical use of surveillance. |
Reinforcement Learning | The process of decision-making involves performing actions and receiving feedback on those actions, which helps to learn and improve decision-making abilities. | Applied in robotics, gaming, navigation systems, and real-time decision-making systems. | There are concerns revolving around the unpredictability of behaviors in complex environments, as well as ethical considerations in decision-making processes. |
Robotic Process Automation (RPA) | Software technology that enables the building, deployment, and management of software robots that mimic human actions while interacting with digital systems. | Used in automating routine tasks in business processes, customer service, and data entry. | Impacts on labor markets, job displacement, and reliance on automation for critical processes. |
Predictive Analytics | Uses statistical algorithms and machine learning techniques to predict future outcomes based on historical data. | It is widely utilized in various fields such as risk management, marketing, operations, and healthcare. | Concerns about data privacy, accuracy of predictions, and reliance on historical data may perpetuate biases. |
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