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

Yohan
45,065 次观看 • 4 个月前
Google Earth now lets you create AI images using... real-world locations. With the new Nano Banana AI feature, you can pick any place in Google Earth, click “Create Image,” and describe what you want to see. The AI can turn that location into a historical scene, a futuristic city or a fantasy world The feature uses Google Earth’s satellite and 3D map data as the base, so the AI-generated images are built from real locations.show more

Pirat_Nation 🔴
24,731 次观看 • 5 天前
Conducting road safety audits, scheduling maintenance, or planning logistics... routes used to require combing through imagery or, worse, driving miles of roads yourself. Not anymore. New AI-powered data layers in Google Earth are changing that. Pulling from billions of Google Street View images, these layers now spot infrastructure assets like stop signs, speed limit signs, and more to map infrastructure for you. By combining these assets into a single project and diving into Street View you can locate and validate assets on Google Earth in seconds. These layers are now available for Professional & Professional Advanced customers on web and Android, with coverage expanding over the coming weeks.show more

Google Earth
20,498 次观看 • 1 个月前
Create Stunning Time-Series Satellite Images in Seconds! The GEE... Data Catalogs Plugin v0.5 for QGIS is now available and it's a powerful upgrade. You can now create time-series satellite imagery with just a few clicks using a simple interface. The new version also supports direct downloads to your computer, making the workflow faster and more efficient. Key Features: - Access over 80 petabytes of satellite and geospatial datasets from Google Earth Engine - Generate animated time-series imagery effortlessly - Export results directly from QGIS to your local machine Useful Links: QGIS Plugin Page: GitHub Repository: Video Tutorial: #QGIS #geospatial #EarthEngine #Python #datascience #satelliteshow more

Qiusheng Wu
14,101 次观看 • 6 个月前
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

Bilawal Sidhu
165,867 次观看 • 1 年前
.Sentient has just integrated Messari 's data and research... into its AI-powered search platform, Sentient Chat. This partnership basically allows users to access Messari’s research directly through the Agent Hub in Sentient Chat where they can get instant answers and insights from Messari reports. The integration is done via Messari Copilot, which means users can now easily get to Messari’s crypto data without having to dig through extensive reports themselves. Messari's data and research now feeds into Sentient’s Agentic Perplexity, here users can access this in the Agent Hub for all their crypto related questions. Integrating Messari’s research now helps provide an open & community-driven platform for AI-powered search, ensuring that users have access to the best crypto data and insights in real time, while also expanding the functionality of Sentient’s Agent Hub, where users can find and use a growing library of AI agents for various tasks. Now I don't know about you but I know where I'll be getting my stats from moving forward.show more

Polygon Stats
32,701 次观看 • 1 年前
An interesting issue with Tesla Robotaxi where it took... us to a Starbucks, but the Google data had the incorrect location. At drop off we were 0.2 miles from the Starbucks, so we had a short walk. Is there a way the Tesla AI team could add functionality in the app so riders can update map info to correct errors or inaccuracies on the underlying map data and then this propagates to the fleet? Being able to do this with a pin drop on the map instead of having to use an address might make this very easy and user friendly! Or, as a bigger ask, would it be possible for the car to be able to use visual images on its own to look for a Starbucks sign and on the fly, get us closer and update the map data on its own?show more

Joe Tegtmeyer 🚀 🤠🛸😎
80,355 次观看 • 1 年前
You can now create AI images directly from Google... Slides. No need to spend hours searching for images for your presentations. And this feature is available for free. Here's how to activate it: 1. Go to labs .google .com 2. Scroll down to "Google Workspace". 3. Click on the "Learn more" button to access the waitlist. When it's activated, you'll see the button that appears in Google Slides as in the video. Click on it and enter your prompt: E.g.: "a cat in front of a raspberry pie". You can even choose different styles: photography, vector art, sketch, ... This will save a lot of time when creating slideshows! Don't hesitate to follow me to learn how to do more with AI.show more

Paul Couvert
318,240 次观看 • 2 年前
The companies racing Elon Musk to build AI are... paying him more than 2 billion dollars a month to do it. Anthropic pays SpaceX 1.25 billion dollars a month. Google pays 920 million. They are not buying rockets. They are renting compute, the scarce Nvidia chips that train frontier models, from a data center in Memphis called Colossus that Musk's rocket company now owns. SpaceX folded xAI into itself in February, and with it the 220,000 chips built to train Grok. Then it rented them to Grok's rivals. Anthropic took the entire first building. Google leased 110,000 more. The contracts signed so far run past 80 billion dollars. SpaceX is no longer a rocket company that dabbles in AI. It is one of the largest AI compute landlords on Earth, and its biggest tenants are the rivals it is trying to beat. Musk is not choosing between building AI on the ground and building it in space. He is using one to fund the other. The 80 billion in ground contracts is the cash engine. Starmind, the million-satellite constellation built to leave the ground behind, is what the cash builds. So the rivals are financing his exit from the planet. Every dollar Anthropic and Google pay for compute in Memphis helps fund the orbital network designed to strand them on the surface. They are paying the toll on the road they are trying to win, and the toll is building Musk a road no one else can reach. The piece works out who is really renting from whom.show more

Shanaka Anslem Perera ⚡
97,858 次观看 • 1 个月前
Set the Grok widget on your Android for instant... access to a real AI assistant By default, nearly all Android devices come with the Google Search widget But it’s 2025 - more than 90% of the time, you just need direct answers and an assistant that remembers your past conversations Google Search is basically irrelevant for those cases How to upgrade your home screen to Grok: ➝ Long-press the Google Search widget → tap “Remove” ➝ Long-press the home screen → Widgets → Find “Grok” → Drag to home Grok is fast, powerful, and always ready — a true AI assistant for your daily needsshow more

X Freeze
20,887 次观看 • 8 个月前
Okay, this is seriously cool. A team from Google... DeepMind, including DeepMind Cofounder Shane Legg, published a paper "From AGI to ASI". In the paper, they include instructions for an AI agent to read along with you. You can open the paper in Codex's in-app browser and have GPT-5.5 read it with you and explain all the concepts. This is the future. AI agents will be part of the target audience, and help us to understand anything we want.show more

Dan McAteer
53,480 次观看 • 1 个月前
Are you an Insurance Advisor/Mutual Fund Distributor or advise... clients on financial products? To make life easier for financial advisors, we have now integrated the ProtectMeWell API into a Google Sheet This means that you can work on a Google Sheet and generate reports (👇) like these for your prospective customers in real-time. 🚀Would you want to be an early adopter of "ProtectMeWell on Google Sheets"? Here is the deal 1⃣ I am seeking the help of 20 passionate advisors for closed user group testing. On a first come, first serve basis. DM me, if you are interested 2⃣ I will extend access to the Google Sheets for two weeks for ₹999. 100% refundable when you provide me with at least 5 actionable areas of improvement from a usability perspective of Google Sheets. 3⃣ When it is launched for the wider audience (late August 2023) you get to use it for free until 31 March 2024 (subject to 10,000 API calls) PS: To clarify, it is not the testing exercise of API (or algorithm), which is robust and has been used by over 100K people. The focus is on the usability of Google Sheets so that a wider audience finds it easy to navigate Sounds interesting? DM me Please amplify for good karma 🙏show more

Sumit Ramani
42,240 次观看 • 3 年前
Terrain impacts nearly every project. Luckily, Google Earth’s measure... tool just got a major upgrade. Introducing elevation profiles. Simply draw a line, as you always have, to instantly generate a detailed and interactive elevation profile in the inspector panel. Whether you are tackling complex route and transportation planning, conducting viewshed analysis, or mapping out logistics for heavy machinery, you can now instantly contextualize terrain dips and peaks directly on the map.show more

Google Earth
29,468 次观看 • 3 个月前
1/ Gemini 2.5 is here, and it’s our most... intelligent AI model ever. Our first 2.5 model, Gemini 2.5 Pro Experimental is a state-of-the-art thinking model, leading in a wide range of benchmarks – with impressive improvements in enhanced reasoning and coding and now #1 on Arena by a significant margin. With a model this intelligent, we wanted to get it to people as quickly as possible. Find it on Google AI Studio and in the Google Gemini for Gemini Advanced users now – and in Vertex in the coming weeks. This is the start of a new era of thinking models – and we can’t wait to see where things go from here.show more

Sundar Pichai
864,455 次观看 • 1 年前
Building RAG is easy. Parsing real, unstructured data is... the hard part. Most tools fail when documents get complicated. RAGFlow by InfiniFlow makes the entire process visual and flawless 🔥 It is an (open-source!) engine built specifically to find the exact needle in a data haystack, even across literally unlimited tokens. The platform comes packed with: → "Quality in, quality out" parsing for highly complex formats → Multiple recall paired with fused re-ranking → A built-in Python and JavaScript code executor for agents → An orchestrable ingestion pipeline Here's why it stands out: 1️⃣ Structural Understanding Instead of just scraping text, it handles tables across pages, scanned copies, slides, and Excel sheets natively using deep document understanding. 2️⃣ Grounded Citations Every answer is verifiable. The UI highlights the exact chunks used, allowing you to trace any response directly back to the source material. 3️⃣ Enterprise Synchronization Keep your context constantly updated with native data sync from Google Drive, Notion, Discord, and Confluence. Stop letting bad document parsing ruin your RAG systems. Best part? It's 100% Free and open-source. Link to the repo in 🧵↓show more

Charly Wargnier
19,220 次观看 • 4 个月前
Today we’re introducing Google AI Threat Defense - a... comprehensive AI-powered cybersecurity solution designed to help continuously monitor for and stop AI-powered threats before they can impact your business. Here’s how it works: 1. AI Threat Defense uses our cybersecurity platform Wiz to scan and prioritize what applications and systems have the highest security risk. 2. Gemini and other frontier AI models can then autonomously perform continual deep scanning of your applications - starting with those at the highest risk - to identify security vulnerabilities. 3. The capabilities of CodeMender - a new software repair agent - are then used to verify and accelerate the patching of vulnerabilities. 4. And our Wiz autonomous agents continuously test your systems to find unknown vulnerabilities before adversaries do so that you can remediate them before you are attacked. While other model providers focus on using AI to find and flag vulnerabilities, Google AI Threat Defense actively prioritizes your most critical real-world risks and accelerates their remediation using a variety of models since no single model finds a superset of the vulnerabilities found by all other models.show more

Thomas Kurian
197,641 次观看 • 2 个月前
A Letter to Our Community: The Road Ahead for... Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷show more

Axis Robotics
27,858 次观看 • 7 个月前
Hedera Joins Google And IBM To Build Legal Layer... For AI Agents Hedera (Hedera) hedera-hashgraph:native has joined as a founding member of the Legal Context Protocol, a new open standard giving AI agent transactions a legal framework, per CoinTelegraph. The protocol is backed by the American Arbitration Association and firms including Google, IBM, Circle and Cardano. It aims to make legal terms, consent and dispute resolution verifiable when AI agents transact on behalf of humans. Hedera co-founder Mance Harmon said there needs to be "a clear answer to what happens if something goes wrong." Gartner projects the agentic payment economy will hit $15 trillion in spending by 2028.show more

BSCN
40,610 次观看 • 1 个月前
OpenAI's Deep Research is getting a run for its... money. Deep Lake was just released, and it's a different take on an AI system that can do deep research on your own data. You can use Deep Lake to build AI search with reasoning on your private and public data. (Look at the attached videos to get an idea of how it works.) If you want to research proprietary and sensitive data, Deep Research won't help you because it's limited to public data. Deep Lake, however, will allow you to use your private data. On top of that, Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) You can even use mixed-data queries! Deep Lake can search your data from S3, Dropbox, and GCP. It learns from your queries over time, making the results as relevant to your work as possible!show more

Santiago
171,340 次观看 • 1 年前