Fermilab’s Post

#Topics Deep Learning Supercharges Galactic Calculations [ad_1] University of Tokyo researchers have applied deep learning to supernova simulations, significantly improving accuracy and efficiency, with potential applications in astrophysics and beyond, including climate and earthquake modeling. Credit: SciTechDaily.com A novel method of simulating supernovae could shed light on our cosmic origins. Supernovae, which are exploding stars, play a pivotal role in galaxy formation and evolution. However, simulating these phenomena accurately and efficiently has been a significant challenge. For the first time, a team including researchers from the University of Tokyo has utilized deep learning to enhance supernova simulations. This advancement accelerates simulations, crucial for understanding galaxy formation and evolution, as well as the evolution of chemistry that led to life. When you hear about deep learning, you might think of the latest app that sprung up this week to do something clever with images or generate humanlike text. Deep learning might be responsible for some behind-the-scenes aspects of such things, but it’s also used extensively in different fields of research. Recently, a team at a tech event called a hackathon applied deep learning to weather forecastin...

#Topics Deep Learning Supercharges Galactic Calculations [ad_1] University of Tokyo researchers have applied deep learning to supernova simulations, significantly improving accuracy and efficiency, with potential applications in astrophysics and beyond, including climate and earthquake modeling. Credit: SciTechDaily.com A novel method of simulating supernovae could shed light on our cosmic origins. Supernovae, which are exploding stars, play a pivotal role in galaxy formation and evolution. However, simulating these phenomena accurately and efficiently has been a significant challenge. For the first time, a team including researchers from the University of Tokyo has utilized deep learning to enhance supernova simulations. This advancement accelerates simulations, crucial for understanding galaxy formation and evolution, as well as the evolution of chemistry that led to life. When you hear about deep learning, you might think of the latest app that sprung up this week to do something clever with images or generate humanlike text. Deep learning might be responsible for some behind-the-scenes aspects of such things, but it’s also used extensively in different fields of research. Recently, a team at a tech event called a hackathon applied deep learning to weather forecastin...

Over the past decade, machine learning has totally transformed how we do research. These algorithms are game-changers for analyzing data, making predictions and uncovering insights in fields ranging from biology to astronomy. taxodiary.com/?p=53102 #ExplainableAI

My latest paper on the Galactic Center, utilizing Machine Learning, Deep Learning, and Bayesian Statistics, has been officially published. Check it out here: [Link to the paper](https://lnkd.in/eQBVytFc) #MachineLearning #DeepLearning

🚀 Exploring the Stars with Physics-Informed Neural Networks (PINNs) 🌌 Ever wondered how we can unravel the mysteries of compact stars like neutron stars and white dwarfs? Traditional methods rely on complex equations that are often tough to solve. But what if we could combine the power of physics with cutting-edge machine learning? Enter Physics-Informed Neural Networks (PINNs)! 🤖✨ PINNs are a game-changer in astrophysics. They allow us to embed the laws of physics directly into neural networks, helping us solve equations that describe the structure and behavior of these dense, enigmatic stars. Instead of just crunching numbers, PINNs understand the physical rules of the universe, making them more accurate and efficient than traditional methods. Why does this matter? Well, with PINNs, we're not just limited to textbook solutions. We can explore new scenarios, simulate extreme conditions, and gain insights that were previously out of reach. This opens up a whole new frontier in our understanding of the cosmos! 🌠 Whether you're into AI, astrophysics, or just love the idea of blending science and technology, PINNs are definitely something to watch. They're helping us push the boundaries of what we know about the universe—one equation at a time. #Astrophysics #MachineLearning #AI #PhysicsInformedNeuralNetworks #SpaceExploration #ScienceInnovation

In an era when the creation of artificial intelligence (AI) images is at the fingertips of the masses, the ability to detect fake pictures—particularly deepfakes of people—is becoming increasingly important.

I completed a Small Project where I built a RAG App that takes context of Stephen Hawking's "A Brief History of Time" to answer questions about astronomy and astrophysics. You can find the Jupyter Notebook at: https://lnkd.in/d8JF97ai General Flow for the RAG Chatbot: 🔵 Reading Dataset, Data Cleaning, Dividing in Chunks 🔵 Encoding Each Source of Data, and Store it as a Dataframe, to prevent recomputation 🔵 Create an instance of Llama3. Take User prompt a input 🔵 Fetch K-Nearest-Neighbours for text matching with the prompt. Reframe the prompt accordingly 🔵 Encode the prompt and pass it to the model I took the extracted content, chunked it into pages, retrieved the best n examples via KNN, and fed that to Llama3 along with the prompt. I am hoping to explore re-ranker based RAGs next. #tech #ai #promptengineering #chatgpt #meta

In an era when the creation of artificial intelligence (AI) images is at the fingertips of the masses, the ability to detect fake pictures—particularly deepfakes of people—is becoming increasingly important.