MIT Technology Review’s Post

#PRWR7550 we discussed problematizing definitions and use cases last evening in class: how do we scale definitions and applications for everyday life use cases? I'm thinking about memoirs, recipes, personal letters, etc. Laura Fortenberry Jin Jo

An interesting summary about AI. If you’re confused about ‘what is AI’ or why AI arouse so many discussions, this article will clarify many doubts. “Artificial intelligence is the hottest technology of our time. But what is it? It sounds like a stupid question, but it’s one that’s never been more urgent. Here’s the short answer: AI is a catchall term for a set of technologies that make computers do things that are thought to require intelligence when done by people. Think of recognizing faces, understanding speech, driving cars, writing sentences, answering questions, creating pictures. But even that definition contains multitudes.” #MITTechnologyReview #AI #whatisAI #technology #artificialintelligence

One of the very best written, in depth, articles I’ve seen on an important paradox of our time: everybody talks about AI, but there’s no actual consensus on what it means… for the same reason, we dedicate an entire day to “what” AI is on my course on “AI in organizations” at IT-Universitetet i København

While AI does hold promise in changing healthcare, it’s critical to approach its implementation thoughtfully and strategically. By combining the efficiency of AI with human oversight, businesses can realize the full potential of AI in improving healthcare outcomes and promoting health equity. Thanks to Pharmaceutical Executive and CQ fluency's Dan Milczarski for this insightful piece to spark meaningful conversation on AI in healthcare.

As #AImodels and technology continue to develop, new exploits and risks may emerge. Many evaluation methods, such as code reviews, may not adequately address the nuances of #foundationmodels and #generativeAI in isolation. That’s where #RedTeaming comes in. Download our practical handbook to learn more. Coran D. , Sam Tyner-Monroe, Ph.D., Christopher Cullen Bennett B. Borden

WE EXPLAIN HOW TO BETTER EVALUATE ACCURACY AND TECHNICAL ROBUSTNESS OF AN AI MODEL, THROUGH RED TEAMING: AI models are rapidly advancing, offering ever greater complexities and capabilities across a spectrum of applications, from natural language to computer vision. And in their wake comes an international regulatory push to ensure AI functions in a transparent, accurate way, bringing with it the increasing need for robust evaluation methods to accurately assess AI models’ performance. Many evaluation methods, such as code reviews, may not adequately address the nuances of foundation models and generative AI in isolation. Effective and comprehensive evaluations, such as those developing under the proposed EU AI Act, therefore may require additional measures to be taken in order to meet the expectations of regulators and industry best practices. One alternative (or complimentary) way to evaluate the accuracy and technical robustness of an AI model is red teaming. This method involves deliberately probing an AI model to test the limits of its capabilities. This may be done manually, by teams of individuals (similar to video game testing in which bug searches are carried out) or by pitting AI models against each other. In our concise handbook, we explore red teaming – what it is, what its goals are, and how your company may make best use of it and become red team ready. #ai #redteaming #aimodels

🔬🆚🤖 Get ready for an intellectual showdown as we unravel the intriguing dynamics between Science and Artificial Intelligence (AI)! In this thought-provoking video, we dive deep into the realms of discovery, innovation, and the evolving landscape where scientific principles intersect with the power of AI. Whether you're a science aficionado or an AI enthusiast, this exploration is bound to spark curiosity and challenge perceptions. 🌐 Key Points Covered: The Foundations: Uncover the parallels and distinctions between the scientific method and the algorithms driving AI. How do empirical observations compare to machine learning data? Innovation Intersection: Explore how AI is transforming the scientific landscape, accelerating research, and opening new avenues for discovery in fields like medicine, physics, and environmental science. Limitless Potentials: Delve into the potentials and limitations of both science and AI. Where do their strengths align, and where do they diverge? Ethical Considerations: Navigate the ethical terrain as we discuss responsible AI practices and the moral compass that guides scientific endeavors. The Human Element: Reflect on the roles of human intuition, creativity, and critical thinking in both scientific exploration and AI development. 🤔 Why It Matters: As we navigate the ever-evolving landscape of knowledge and technology, understanding the interplay between science and AI is crucial. Join us on this journey of discovery, where we bridge the gap between empirical inquiry and artificial intelligence, unlocking a future where both can thrive in harmony. 👩💻 Subscribe, Like, Share: Don't miss out on this enlightening exploration! Hit the subscribe button, give us a thumbs up, and share your thoughts in the comments. Let's build a community of curious minds! 🌟 #ScienceVsAI #TechDebate #AIInnovation #ScientificDiscovery #FutureTech #EthicalAI

🌐 Exciting News! 🚀 Thrilled to announce the launch of Odia-t5-base, a powerhouse in the realm of Natural Language Processing! 🌟 This versatile text-to-text model is finely tuned to excel in a myriad of NLP tasks in the Odia language. Key Features: 1️⃣ Translate English to Odia 🌐🔄 2️⃣ Translate Hindi to Odia 🇮🇳🔄 3️⃣ Odia Sentence Summarization 📝🔍 4️⃣ Question Answering in Odia ❓🗣 5️⃣ Context-Based Question Answering in Odia 🧠🤔 Harness the power of Odia-t5-base for seamless and accurate language processing in various applications. Whether it's breaking language barriers through translation or distilling complex information into concise summaries, this model is designed to elevate your NLP experience in the Odia language. Thanks to, Odia Generative AI, for creating various datasets in the Odia language. It's been incredibly helpful during the training of this model! Join us in unlocking a new era of linguistic possibilities with Odia-t5-base! 🚀💬 #NLP #OdiaLanguage #Innovation #TechBreakthrough #LanguageProcessing #languageai #odia #huggingface #mt5 #genai https://lnkd.in/gqCArafD

Hey everyone, I am excited to share my latest project on GitHub: Fine-tuning LLaMA-3B with Unsloth AI: It's been a 1+ week since the release of LLaMA-3B, a massive language model from Meta, that boasts incredible capabilities. In this project, I explore the potential of fine-tuning this model for specific tasks using Shekswess/medical_llama3_instruct_dataset. This repository delves into the process of: ➡️ Understanding LLaMA-3B architecture and functionalities. ➡️ Preparing and fine-tuning the model for a chosen task (open for exploration!). ➡️ Evaluating the fine-tuned model's performance. Whether you're a seasoned NLP enthusiast or just curious about LLaMA-3B, this project offers valuable insights and a starting point for further exploration. Feel free to: Check out the code on GitHub (https://lnkd.in/dVJ8N_VD). OR Check out my fine-tuned llama3 model on hugging face: https://lnkd.in/dZraeVdr. Share your experiences with fine-tuning large language models! Let me know if you have any questions. #AI #linkedin #llm #llama3 #Genai

Integration and Consilience In the book I cover the issue of people skills and thinking in the emerging era of cybernetics and AI. The relationships between people and technology is changing rapidly yet, ironically, almost imperceptibly. My approach to research, curating and compiling is based on a strong multi, inter and cross-disciplinary theme with an integrationist, consilient focus.