• AIcodeX
  • Posts
  • AI forecast Future Drought

AI forecast Future Drought

PLUS: Bitcoin Miners Embrace AI

Author

AI codeX
April 22, 2024

Join Now  | Advertise

WELCOME, AI LOVERS 

In today’s AI Decode →

  • AI forecast Future Drought

  • Bitcoin Miners Embrace AI

  • BBC to invest £6m

MIT

Lincoln Laboratory researchers are using AI to get a better picture of the atmospheric layer closest to Earth's surface. Their techniques could improve weather and drought prediction. Decoding the Details

Decoding the Details :

  • The PBL is the lowest layer of the troposphere where the Earth's surface interacts with the atmosphere,

  • Researchers are using deep learning to create 3D-scanned profiles of the atmosphere, resolving the vertical structure more clearly, and improving the accuracy of temperature and humidity observations.

  • One key application is enhancing drought prediction by studying the humidity levels in the PBL, shows promise for more accurate drought forecasting.

Bitcoin miners upgrade power centers and get into AI to brace for slashed revenue post halving

 Decoding the Details :

  • The bitcoin halving took effect late on Friday, cutting the issuance of new bitcoin in half.

  • Bitcoin miners have spent years diversifying their business models and upgrading their facilitates to brace for the cut to revenues.

  • Some mining firms have diversified into supporting the underlying infrastructure necessary for artificial intelligence..

  1. The BBC is investing £6 million in AI to transform its educational platform BBC Bitesize making it more personalized and interactive for students from primary school onwards. aims to attract younger audiences.

 Decoding the Details :

  • The investment will turn BBC Bitesize from a digital textbook into a personalized learning platform that adapts to the user's needs, providing tailored testing, content suggestions, and identifying learning gaps.

  • The BBC is exploring AI-powered features like those used by language learning apps like Duolingo, offering follow-up content recommendations to deepen subject understanding.

  • with the goal of fostering a relationship with the next generation of license fee payers by providing a trusted and engaging educational resource.

 🧰 AI Tools

  • Open Agent Studio - A powerful no-code agent editor

  • DuckDuckGO AI Chat - Private AI chat, no AI training on your conversations

  • Healax - Mental health solution for students

  • Journey AI - Convert customer research into journey maps

  • Pietra Product Design Studio - Design a best-selling product using AI

  • SwitchLight - Switch lighting in photos within seconds

🧬New Research

PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generation
Creating realistic 3D object movements for new interactions is hard. Estimating objects' physical properties is difficult due to lack of data. PhysDreamer makes static 3D objects move realistically when interacted with, using knowledge from video generation models. Tested on elastic objects, judged realistic by users. Allows plausible object responses to interactions in virtual worlds.

TextSquare: Scaling up Text-Centric Visual Instruction Tuning

Text-centric visual question answering models improved using Square-10M dataset created from closed-source models. Model TextSquare surpassed open-source state-of-the-art on benchmarks, outperforming GPT4V and Gemini. VQA reasoning data provided contextual insights, improving accuracy and mitigating hallucinations. Scaling text-centric VQA datasets showed exponential increase in data volume directly proportional to model performance improvement, validating Square-10M's scale and quality.

 

OCONut: Crafting the Future of Segmentation Datasets with Exquisite Annotations in the Era of ✨Big Data✨

COCONut is proposed as new, large dataset with human-verified mask labels for 383K images. Uses innovative assisted-manual annotation pipeline leveraging neural networks to help human annotators. Solves issue of manually annotating millions of objects which would take years.

 

AutoCrawler: A Progressive Understanding Web Agent for Web Crawler Generation

Introduces crawler generation task for web information pages. Proposes AutoCrawler framework combining large language models with crawlers. AutoCrawler leverages HTML structure for progressive understanding, learns from errors, prunes HTML for better action generation. Allows crawlers to handle diverse, changing web environments more efficiently.

Customizing Text-to-Image Diffusion with Camera Viewpoint Control

Adobe brings camera viewpoint control to text-to-image models!.method requires a 360 degree multi-view dataset of around 50 images per object to work.