Google just released the AlphaEarth Foundations with 64 dimensions... of satellite embeddings at 10-m resolution at the global scale! It is very interesting! Check it out Blog post: Dataset: Paper: #AI #geospatial #remotesensing #geoaishow more

🚀 The #GeoAI Python package now supports feature segmentation... from high-resolution satellite and aerial imagery using text prompts, such as trees, buildings, etc. It efficiently processes large datasets with automatic tiling and can save results as a single image. Stay tuned for more features coming soon! 📓 Access the notebook: 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearningshow more

Frontier research just crossed a new threshold. Mind Lab... is now public. And it begins with trillion-scale RL trained at only 10% of the usual compute.show more

Google just took a big step towards building ChatGPT... for Earth. AlphaEarth Foundations does something clever -- instead of drowning in petabytes of Earth observation data, it creates compact summaries of every 10x10m square on Earth by fusing optical, radar, LiDAR, and climate data. The kicker is it can see through clouds in Ecuador and reveal hidden agricultural patterns in Canada. MapBiomas and Global Ecosystems Atlas already using it for conservation work.show more

Because two is better than one. New episode of... #TheBooth just dropped, check it out at the linkshow more

Google just wired DeepMind and Earth Engine directly into... the biggest geospatial dataset on the planet. For two decades, millions of people used Google Earth to scale the Himalayas or zoom in on their childhood neighbourhoods. In 2026, Google is basically trying to shift the entire platform toward professional execution. They turned a massive digital twin of the world into an agentic AI engine for global infrastructure. The technical foundation is (obviously) all about data. Google integrated 20-metre and 40-metre elevation contours globally. Engineers and urban planners now have instant access to the exact topographic context required for site planning anywhere on Earth. The data catalogue updates continuously to maintain the freshest imagery possible. Collaboration used to kill geospatial projects. Teams would lose momentum through stale materials or bad handoffs. Google fixed this by building frictionless data import systems. You can now drop KML, KMZ, and GeoJSON files directly onto the global map. Entire departments can align on a single source of truth, moving from a raw question to a definitive answer instantly. The biggest upgrade is the introduction of agentic geospatial intelligence. Users can open 'Ask Google Earth' and search massive satellite and Street View databases using natural language. You type a command, and the AI handles the manual data wrangling. It identifies new site locations and analyses infrastructure before you even open a spreadsheet.show more

Before Kubernetes, engineers could get paged to manually scale... infra at any time, even Christmas. In 2014 Google open sourced K8s, which now power a huge percent of the world's cloud infra. I wrote a blog about it, with fully interactive visualizations.show more

You can now ask Google Gemini: "Is this video... made with AI?" 🔍 Upload the file and it will check for the SynthID watermark to help verify if it was created or edited by Google tools. Find out more →show more

Today's real world asset tokenization market is just the... start. Industry experts predict it will equal - and could even surpass - the scale of the entire crypto market in five years. At Plume, we're building the onchain global economy for RWAfi to make it happen.show more

I've tried the new Google Omni, which is their... new AI video model. It actually generates the videos very fast, and it's pretty decent at making gender swap/tf videos (here is one I made). I'm still trying to figure out how to make actual body swap videos with it too 🤔show more

YouTube is a massive asset for $GOOGL in the... AI economy. It sits at the intersection of search, education, entertainment & commerce so Google can bake AI into the ecosystem with no behavior change. YouTube is Google’s compounding advantage.show more

We’re not just training models anymore. We’re deploying intelligence... at scale. On the latest episode of Advanced Insights, AMD CTO MarkPapermaster sits down with Oracle's Chris Gandolfo to talk AI, infrastructure, and what it really takes to train and deploy LLMs at scale.show more

A brand new trend of microdramas is upon us.... Today 2 PM, at the AI Impact Summit, Kuku TV steps into the spotlight with India's First AI generated microdramas, setting the tone for a new era of tech enabled storytelling from India. This is the AI usage I like. Check it out.show more

Is it me or they just landed at the... beginning of the runway? With jal_kanashow more

One last read before the break (and we promise... it’s worth it!) 📚 From time-saving AI strategies to free Google Certified Educator exams, our final newsletter of 2025 is packed with updates to get you ready for the new year. Check it out!show more

NVIDIA just released a very impressive text-to-video paper. Video... Latent Diffusion Models (Video LDMs) use a diffusion model in a compressed latent space to generate high-resolution videos. Here's a brief overview of how it works: 1. Pre-train image LDM on a dataset of images. 2. Turn the image LDM into a Video LDM by adding temporal layers to model video frames. 3. Fine-tune the Video LDM on encoded video sequences to create a video generator. 4. Temporally align diffusion model upsamplers to generate high-resolution videos. 5. Validate Video LDM on real driving videos of 512x1024 resolution, achieving state-of-the-art performance. 6. Apply the approach in creative content creation with text-to-video modeling. Paper: Project:show more

My new video piece, SUICIDE III, will premiere at... the #DEFCON31 AI Village this week - here's a sneak peek. Come check it out and say hi to me at the Creative Misuse of AI Systems talk :]show more

Ever wish you could focus on just the interesting... parts of your 2D plots? Caleb Thomas, a talented member of the MATLAB user community, has made it possible with his open-source Zoomed Axes contribution. Check it out 👉show more

Today we’re releasing SAIR, the Structurally Augmented IC50 Repository.... SAIR is the Largest Open-Sourced Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📰Read the Press Release: 📥Learn More and Download the Dataset at #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQshow more

Google released Gemma 3 270M, a new model for... hyper-efficient local AI! We'll fine-tune this model and make it very smart at playing chess and predict the next move. Tech stack: - Unsloth AI for efficient fine-tuning. - Hugging Face transformers to run it locally. Let's go! 🚀show more