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Accelerating energy development in Utah! The UGS launched new interactive web apps that consolidate decades of carbon storage and geothermal data for researchers and industry professionals. Explore the data here–ow.ly/IFa350Z19c0 #utahgeology

For Windows Codex App users with FOMO on running Codex remotely with Codex iOS/Android app - just add these lines to your config.toml [features] section: remote_connections = true remote_control = true workspace_dependencies = false Ensure your mobile ChatGPT is updated and provisioned/connected to the OpenAI servers. Restart Codex app, go to Settings>Connections and refresh and it should work. New threads might not work but adding on to existing threads seem to work. @OpenAIDevs needs to start doing multi-platform releases like us PC Windows Developers - especially since they can just point Codex at the challenge.

Codex in the ChatGPT app let your agents work for you from anywhere

IMPORTANT ANNOUNCEMENT!!! Moving forward, all maintenance and outage notifications will be posted on our official outage status page. If you have questions or need assistance, feel free to give us a call at (801) 613-3880. Check your service status here: UTOPIA Fiber: status.utopiafiber.com Bountiful Fiber: status.mybountifulfiber.com

THE MATH YOU NEED TO START UNDERSTANDING LLMS THE FOUNDATION BEHIND MODERN AI MODELS Large Language Models (LLMs) are powered by mathematics. Behind every prediction, embedding, and generated response is a combination of linear algebra, probability, calculus, and optimization. You do not need a PhD in mathematics to start learning LLMs, but understanding the core concepts gives you a major advantage. LINEAR ALGEBRA — THE LANGUAGE OF LLMS → VECTORS Vectors represent words, tokens, and embeddings inside neural networks. → MATRICES Matrices store and transform large amounts of numerical data efficiently. → DOT PRODUCT Used to measure similarity between embeddings and power attention mechanisms. → MATRIX MULTIPLICATION Core operation behind neural network computations and transformer architectures. → EIGENVECTORS & DIMENSIONALITY Help models compress and organize information in high-dimensional spaces. PROBABILITY & STATISTICS — HOW MODELS PREDICT → PROBABILITY DISTRIBUTIONS LLMs predict the probability of the next token in a sequence. → CONDITIONAL PROBABILITY Used to estimate the likelihood of words based on previous context. → MEAN, VARIANCE & STANDARD DEVIATION Important for normalization and understanding data distributions. → BAYESIAN THINKING Helps explain uncertainty and prediction confidence in AI systems. → SOFTMAX FUNCTION Converts model outputs into probabilities for token prediction. CALCULUS — HOW MODELS LEARN → DERIVATIVES Measure how changes in parameters affect model outputs. → GRADIENTS Guide neural networks toward lower error during training. → CHAIN RULE Critical for backpropagation across deep neural networks. → OPTIMIZATION FUNCTIONS Used to minimize loss and improve prediction accuracy. OPTIMIZATION — TRAINING LARGE MODELS → GRADIENT DESCENT The foundation of neural network training. → LEARNING RATE Controls how fast or slow a model updates weights. → LOSS FUNCTIONS Measure how wrong the model’s predictions are. → REGULARIZATION Helps prevent overfitting and improves generalization. INFORMATION THEORY — UNDERSTANDING TOKENS → ENTROPY Measures uncertainty in predictions. → CROSS-ENTROPY LOSS Common loss function used in transformer-based models. → TOKENIZATION Breaks text into smaller units for model processing. THE MOST IMPORTANT CONCEPT FOR TRANSFORMERS → ATTENTION MECHANISM Allows models to focus on relevant words in a sequence. The attention mechanism heavily relies on matrix multiplication, vector similarity, and probability distributions. WHY THIS MATH MATTERS → Helps you understand how transformers actually work → Makes debugging and fine-tuning easier → Improves your understanding of embeddings and token prediction → Gives you a strong foundation for AI engineering and research BEST WAY TO LEARN THE MATH → Start with linear algebra basics → Learn probability before deep learning → Understand derivatives conceptually before advanced calculus → Practice with small neural network examples → Focus on intuition before equations TOOLS THAT MAKE LEARNING EASIER → NumPy for matrix operations → PyTorch for tensor computations → Jupyter Notebook for experiments → Visualization tools for gradients and embeddings FINAL THOUGHT You do not need to master every mathematical field before building with LLMs. Start with the fundamentals, connect the concepts to real AI systems, and learn progressively as you build projects. MASTER LLMS IN DEPTH Grab the complete LLMs Handbook here: codewithdhanian.gumroad.com/l/haeit

Plugins for Excel, PowerPoint, Word, … coming soon

Park City is gearing up to host @thesnowleague's Season Two, marking a new milestone for winter sports in Utah. Founded by @shaunwhite, this event brings top athletes for competitions, artists for concerts and more. With stunning Wasatch views and @PCski's top-tier facilities, it's a premier experience for all. 🔗 Learn more here: bit.ly/4ctR01u

Utah has been named the No. 1 state in the nation for economic outlook for the 19th consecutive year. Unlike rankings that look backward, this one measures the policies most likely to support opportunity in the years ahead. Utah has remained at the top since the index began. More here: alec.org/press-release/…

🔥 Claude Code : Project Structure 🔥 #claudecode #agentic

Ballots were mailed out today! Are you ready to vote on judges? Visit judges.utah.gov to review their performance evaluations.

Interested in becoming a volunteer courtroom observer? Contact us at judges.utah.gov

Why are judicial evaluations so positive this year? It's part of the process. This is one of our most frequently asked questions, comment if you have others!

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A $100,000 salary in January 2020 has the same buying power as $124,353 in April 2025, according to the U.S. Bureau of Labor Statistics. In other words, if you haven’t received a raise since 2020, higher inflation feels like losing $24,000 of your salary, per YF.

JUST IN: Brazil proposes national Bitcoin reserve with bill

President Trump is being called a conspiracy theorist after sharing a post on Truth Social claiming, “There is no Joe Biden—he was executed in 2020.” The post goes on to allege that what the public sees are not real people, but clones, body doubles, and robotic, soulless entities made to impersonate Biden.

Tulsi Gabbard just dropped a bombshell, claiming she has declassified documents revealing that former President Joe Biden put U.S. citizens on the terror watch list simply for speaking out against COVID-19 mandates. Among those allegedly targeted were parents who raised concerns about their kids being forced to get vaccinated. Even Americans who criticized Biden’s border policies, according to Gabbard, were quietly added to the list.

⚡️ JUST IN: Coinbase ($COIN) is set to join the S&P 500.