A guide for companies and administrations to better assess and plan AI projects. In several AI seminars, some questions from AI enthusiasts have emerged as particularly relevant. This article names questions from practice and answers them practically.
Introduction
Someone who wants to solve a problem with AI often doesn't know if it's possible or how much effort it will take. The following practical collection of answers to questions about AI solutions shows what is possible.
The questions come from a recently held webinar, but also from other contacts with customers and interested parties. The answers are based on experiences from projects in which customer wishes were implemented.
Many business applications can be solved excellently and economically with proprietary AI.
The projects all included a relevant share of AI programming. Open-source AI models were always used, and occasionally interfaces to ChatGPT, Claude 3, Command R+ or other commercial language models were also employed.
The answers to the questions raised are intended to provide guidance on how to better identify, assess, plan, and execute AI projects.
Questions from practice about AI and answers
In bold is the question stated. Below it, in normal text flow, is the answer.
Which application case is particularly well-suited for entry into AI?
Due to the very good results and the low hardware requirements, the following use cases are very suitable for getting started with AI solutions – without having to use ChatGPT!
- Knowledge Search: Search through own documents or tickets in the ticket system.
- Search Function Website: Intelligent search function for texts and PDFs on your own website.
- Complaint Management: Based on previous cases give a recommendation to the employee as to how a current complaint should be best handled.
- Damage Regulation: Analogous to Complaint Management.
- Intelligent Internet Search: Retrieve search results from a search engine (via interface/API) and intelligently sift through them. Irrelevant hits are filtered out of 1000 matches.
- FAQ Response System: Either question-answer pairs or documents containing answers are required (questions that the documents answer can be synthetically generated).
- Classification of documents, texts, headings, images, signals: Assign each document to one of several predefined categories. Automated learning of the correct categories. High hit rate possible.
These applications can run on your company's or organization's own hardware without having to send data to third parties.
Which application cases are still suitable for a solution with AI?
In particular, it should be mentioned:
- Chatbot / Knowledge Assistant: Conversation with memory, answer in own words, use of internet knowledge for finding answers…
- Content Generation: Generating high-quality creative content, such as blog posts; Summarizing document contents
- Object Recognition: Recognize object classes (Person, House, …) on images and videos, intelligent motion detection.
- Image Generation: Generate images based on given text, generate images similar to input image. Automated copyright checking is possible.
- Translation of Language and Text: Transcription, speech output, translation from one language into any of 100 other languages.
The effort required for this is often low. Only the hardware requirements are higher than for the application cases mentioned in the previous section.
What is Offline-AI?
Offline-AI is an optimized AI that can function without an internet connection but can communicate with the outside world when needed.
Advantages:
- Full data control
- Often better results than ChatGPT, Gemini, etc
- Often cheaper
What are the realistic time resources for an AI project?
For a prototype and a feasibility study, the effort is often very low. When it comes to processing your data, this data (as always) needs to be read in. This is a conventional task. .
Time works for you: Start your AI project, and you can be sure that technological progress in the AI field will benefit you in a few months.
How easily can a language model be swapped with another AI one?
In short: Most of the time this is child's play possible. Many language models follow the same system architecture. They can be replaced by changing fewer lines of code. New, better language models can therefore be used as a Drop-In Replacement, to use a technical term.
What are the licensing costs for AI programs and AI language models?
The open-source market offers an extremely high quality and up-to-dateness in the AI field that cannot be compared to any other open-source market.
This applies to both AI frameworks and AI language models (and other AI models).
The licensing costs are therefore, in short, zero.
It looks different when using the API of ChatGPT or similar services. Costs apply, which depend on the intensity of use.
Can AI be run on its own hardware?
Yes. A plastic example from practice: This text was written on a laptop that runs KI language models with 30 billion parameters (30B models). What is possible on a laptop works all the better on a KI server.
For AI server: Either rent (from German or purely European providers) or buy. The main costs when buying result from the costs of the graphics card(s).
For many use cases, such as knowledge search or generating recommendations for damage reports or customer complaints, a minimal hardware is sufficient.
What is the care effort for a AI application?
The care required is rather lower than with other IT systems, often even zero. If new knowledge documents are available, these can be automatically read in and processed. The effort naturally arises when new knowledge is gathered to further improve the quality of the system or add new knowledge. Without adding new knowledge, the effort is rather close to zero.
My name is Klaus Meffert. I have a doctorate in computer science and have been working professionally and practically with information technology for over 30 years. I also work as an expert in IT & data protection. I achieve my results by looking at technology and law. This seems absolutely essential to me when it comes to digital data protection. My company, IT Logic GmbH, also offers consulting and development of optimized and secure AI solutions.
