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Government & Public Sector

Accelerate civil services and relieve civil servants from monotonous tasks

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With Machine Learning, civil service operations can be optimized by:

automating simple, repetitive civil services completely
helping citizens to find and request the required service, e.g. by Chatbots or Question Answering
automating and updating sovereign duties and information services based on satellite imagery

Projects in Government & Public Sector

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Legal Review of Rental Contracts

Different methods from the field of NLP helped us to create a software that spots errors in legal contracts

Automatic Checking of Service Charge Statements

Semantic Search for Public Administration

dida developed an AI based algorithm to extract relevant information from authority documents

Crop Type Classification

Predict crop types from satellite data to support modern agriculture

Monitoring Urban Growth and Change

An image segmentation algorithm that supports sustainable city planning

Smart Access Control with Facial Recognition

We developed a multi-level security system with facial recognition for automatic access control.

Blog Posts in Government & Public Sector

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Computer Vision

The best (Python) tools for remote sensing

By Emilius Richter August 2nd, 2022

I present the best (Python) tools for remote sensing and processing of satellite data, based on our practical experience with them at dida. For some I provide application examples including code.

Introductions

Project proposals - the first step to a successful ML project

By Emilius Richter July 18th, 2022

For a software provider, the project proposal is the first step toward meeting the needs of the customer. In this article, I will describe the most important modules in machine learning project proposals.

Introductions

Ethics in Natural Language Processing

By Marty Oelschläger (PhD) December 20th, 2021

I explain why language models tend to reproduce stereotypes and prejudices with potentially harmful consequences - and how to use them with care.

Natural Language Processing

GPT-3 and beyond - Part 2: Shortcomings and remedies

By Fabian Gringel October 24th, 2021

Here I explain in which situations GPT-3 fails and why it is far from having proper natural language understanding, which approaches can help to mitigate these issues and might lead to the next breakthrough and what alternatives to GPT-3 there are already.

Natural Language Processing

GPT-3 and beyond - Part 1: The basic recipe

By Fabian Gringel September 27th, 2021

In this blog article I will explain how GPT-3 works, why some people think it’s dangerous, and how you can try out a GPT-3-like model yourself for free.

Computer Vision

CLIP: Mining the treasure trove of unlabeled image data

By Fabian Gringel June 21st, 2021

Contrastive Language-Image Pretraining (short: CLIP) makes use of image captions to train a zero-shot image classifier. In this blog article I will give a rough non-technical outline of how CLIP works, and I will also show how you can try CLIP out yourself!

Computer Vision

Migrating labels from Planet Scope to Sentinel-2

By Moritz Besser June 4th, 2021

In this blog article, I want to briefly describe the process of migrating labels from Planet Scope to Sentinel-2 images.

Projects

21 questions we ask our clients: Starting a successful ML project

By Emilius Richter May 21st, 2021

We discuss what questions should be considered and answered up front to launch a successful machine learning software project.

Use Cases in Government & Public Sector

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