American Physical Society’s Post

Looking forward to this panel about AI and trust in science today (Tuesday) at 2pm!

Scientific discovery is the most important use of AI.

James Evans: Scientific Progress A conversation with Professor James Evans from the University of Chicago about scientific progress. #artificiality #ai #artificialintelligence #generativeai

𝐃𝐚𝐲3: 𝐓𝐡𝐞 𝐃𝐚𝐫𝐭𝐦𝐨𝐮𝐭𝐡 𝐂𝐨𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞: 𝐀 𝐌𝐢𝐥𝐞𝐬𝐭𝐨𝐧𝐞 𝐢𝐧 𝐀𝐈 𝐇𝐢𝐬𝐭𝐨𝐫𝐲 Explore the historic gathering that marked the birth of Artificial Intelligence as a field of study, setting the stage for decades of innovation and discovery! In the summer of 1956, a group of pioneering scientists and mathematicians convened at Dartmouth College for a historic event that would shape the future of Artificial Intelligence. The Dartmouth Conference, led by luminaries like John McCarthy and Marvin Minsky, marked the formal birth of AI as an interdisciplinary field of study. At Dartmouth, attendees discussed ambitious goals such as "making machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves." While the initial optimism surrounding AI led to inflated expectations, the conference laid the groundwork for decades of research and experimentation that would eventually yield significant breakthroughs. https://lnkd.in/gZTpAFV2 #AIHistory #ArtificialIntelligence #TechEvolution #AIOrigins #InnovationHistory #TechLegacy #AIInception #TechThrowback #HistoricalAI #AIJourney

Reflections on #AI in Scientific Discovery: Insights from Bonnie Kruft from Microsoft. Youtube is probably one of the best inventions if used rightly, you can learn so much for free. Here is another "gem" I came across last week. A talk by Bonnie Kruft from Microsoft discussing the integration of #AI in scientific discovery. Here are some key takeaways and my reflections on her talk. 🔍 **Challenges in Scientific Discovery** Bonnie pointed out that while large language models (LLMs) are great at understanding natural language, scientific discovery requires much more. The fields of physics, chemistry, and biology need precise calculations, experimentation, and often work with limited data—areas where LLMs currently struggle. **Four Main Challenges in Scientific Discovery**: 1. **Precise Numerical Computation**: Scientific tasks often involve complex calculations and simulations that LLMs aren’t designed to handle. 2. **Experimentation as the Arbiter of Truth**: In science, theories and discoveries must be validated through experiments, something LLMs can't directly participate in. 3. **Scarce and Expensive Data**: Scientific data is often hard to come by and expensive to generate, making it challenging to train AI models in this area. 4. **Importance of Prior Knowledge**: Science relies heavily on existing knowledge and mathematical models, which LLMs do not naturally possess. 🔬 **Using Differential Equations** Bonnie highlighted the importance of leveraging the known laws of physics, which are described by differential equations. These equations can help improve AI's capabilities in scientific research, even though they are computationally demanding. **Innovative Approaches**: - **Generating Synthetic Training Data**: By using differential equations to approximate solutions, researchers can create synthetic datasets to train AI models, making the process faster and more efficient. - **Incorporating Invariances and Equivariances**: Encoding the inherent properties and symmetries of physical systems into AI models can significantly enhance their ability to learn and reason. 🚀 **#AI in Materials Science and Drug Discovery** Bonnie shared some exciting examples of how AI is already making a difference in materials science and drug discovery. **Materials Science: Screening Lithium-Ion Battery Electrolytes**: - Bonnie's team, in collaboration with Microsoft's Azure Quantum team, developed AI systems to screen potential electrolyte materials for lithium-ion batteries. - This AI-powered screening process identified a promising sodium-based electrolyte, which was later validated through experiments and showcased at the World Economic Forum in Davos. It's not everything dues to LinkedIn character limitation, so better watch the whole video. https://lnkd.in/exx6EcTT

Episode #2 with the new format, discussing #ai in #higher #education with Dr. José Muñoz , let me know what you think.

🐱🐶 Excited to share that I've developed a Cat-Dog Classifier using fast.ai and deployed it on Hugging Face with Gradio! This project has been a fantastic opportunity to dive into machine learning and deploy a practical application. Check it out and see how well it can distinguish between our furry friends: Cat-Dog Classifier https://lnkd.in/gzUByqRG #MachineLearning #DeepLearning #FastAI #Gradio #HuggingFace #DataScience #AI #Project #CatDogClassifier

We are delighted to introduce the second part of a special issue in the #RoyalSocietyPublishing of Philosophical Transactions A: Physics-Informed #MachineLearning and its #StructuralIntegrity Applications, compiled and edited by Shun-Peng Zhu (#ESIA17–ISSI2023 Session Chair for Probabilistic Failure Assessment), Abílio M P De Jesus, Filippo Berto, John G Michopoulos, Francesco Iacoviello, and Qingyuan Wang. This theme issue explores the advances in physics-informed machine learning (#PIML) and its structural integrity applications through accurate failure mechanism modelling, combining either deterministic or probabilistic analyses by using Artificial intelligence (#AI) methods. Specifically, this collection discusses several critical issues related to learning from massive amounts of data, and highlights current research endeavours and the challenges to data science in structural integrity and safety, especially incorporating physics into machine learning models.   For more information about its content and how to access the issue, please visit: https://shorturl.at/foAGO

while it took 45 minutes to complete #LLM fine-tuning, the prep work on dataset took a entire day! more details comming here , #inspirellm is here to stay ! #genai #ai slow steps towards atleast general AI not #AGI https://lnkd.in/gaSjVifd

A Secret meeting with Socrates, Aristotle, Plato & Karl Marx 😁 It is being talked about why they wrote such big and complex theories and put the students studying in political science in danger. 😆 Made with Dall-e-3 Ai made by Me #aiartwork #aiart #ai #philosophy #philosophymemes #politicalscience #ahamedjunaeidtonmoy