Healthy eating isn't about perfection. It's about making nutritious choices more often. Choosing more vegetables, fruits, whole grains, proteins, dairy, and healthy fats while limiting added sugars, highly processed foods, and foods high in saturated fats and sodium can help lower your risk for chronic diseases, including type 2 diabetes and heart disease. No need to swim against the current—small changes add up. This #SharkWeek#, start with one healthy choice at a time. 🌊 Start with your next meal: Fill much of your plate with fruits and vegetables and prioritize fiber-rich whole grains. #SharkWeek# #ChronicDisease# #Nutrition# #CDCHealth# #EatRealFood#

Wildfire season is here. Do you know what to do if smoke reaches your area? Wildfire smoke can reach far away from where fires burn, and it can make anyone sick. Those with asthma, COPD, heart disease, diabetes, chronic kidney disease, or who are pregnant are at especially high risk. If smoke reaches your area, here's what you can do to protect yourself and your family. #CDCHealthySummer# #WildfireSafety# #AirQuality# #WildfireSmoke#

What if you could build an epidemic outbreak prediction model in minutes rather than weeks? Title: Planetary prediction engine: Automating global models via Earth AI URL: Google's Planetary Prediction Engine (PPE) automatically builds geospatial prediction models from natural language queries. For problems like public health, food security, and infectious disease outbreaks, it compresses weeks of manual data curation and feature engineering into minutes — no specialized engineering team required. Key Points 🌍 A three-stage automated pipeline — from query to model Stage 1 translates natural language into geographic constraints and retrieves covariates from Data Commons and Google Earth Engine. Stage 2 fuses structured covariates with embeddings from Population Dynamics Foundation Models and AlphaEarth. Stage 3 searches across regularized linear models, gradient-boosted trees, and MLPs. Each stage embeds a "Feature Gate" (leakage prevention) and an "Overfitting Guard Protocol" (self-correcting risk assessment). 🔬 Multimodal fusion outperforms either modality alone — across every experiment Combining structured statistical covariates with latent foundation model embeddings captures information neither source provides individually. This synergy was confirmed across all experiments, establishing a new architectural pattern for geospatial prediction. 📊 Validated across three high-stakes domains ・US CDC health indicators (21 types): R² 76.8% vs 60.0% baseline ・Nigeria food security downscaling: R² 66.1% vs 31.5% baseline (2× improvement) ・DRC Ebola outbreak prediction: Recall@10 83.3% (+10.3 percentage points vs Bayesian baseline) The real impact is democratization: humanitarian organizations and researchers without dedicated engineering teams can now get evidence-based predictions within minutes when it matters most. #EarthAI# #PublicHealth#

Welcome to Agentic Enterprise City! 🌉 Step inside, explore the future of AI, and enter for a chance to win a $1,000 gift card. To enter the Agentic Enterprise City Sweepstakes, leave a reply on this reel that: 1. Tags your favorite participating Agentic Enterprise City customer (options below) 2. Briefly describes their agentic solution (either in-person at @Dreamforce or at 3. Tags @Salesforce 4. Includes #DF26# and #SFsweepstakes# Dare to double your chances? Leave a second reply tagging 3 friends Choose your customer: @ASU @ATT @CanadaGoose @Crocs @CVSHealth @F1 @LiveNation @LorealGroupe @MarriottBonvoy @SouthwestAir The Prize: One winner from this reel will score a $1,000 gift card from a participating AEC customer of their choice (subject to country availability) We're also running this on the @Salesforce Instagram—you can enter both, but limit one prize per person Note: Salesforce employees are excluded from winning. Read the official rules at