Artificial Intelligence: Regulation is hardly possible (Proof: concrete examples)

Powerful systems have a good and bad side, just like current AI systems do. Regulation of AI is often discussed, but I think it's no longer possible. The progress of artificial intelligence can't be stopped anymore. Concrete examples from my local AI system show this. By the way, "local" also means controllable data protection.

Introduction

No hype anymore, but a revolution. That's AI from now on. And that is probably the greatest technological upheaval in human history. Whoever thinks this is exaggerated probably knows too little about the current possibilities offered by KI algorithms.

In any case, numerous representatives from politics, economy, science as well as society have recognized that the possibilities of AI also bring a danger with them. This danger shall be dampened down, which is referred to as regulation.

Regulations can be enforced by governments, regulatory bodies or self-regulatory organizations. They may apply to various areas such as financial markets, environmental protection, healthcare, consumer protection or labor law. Regulations are intended to help prevent abuse, fraud, monopolies and other unwanted practices in order to ensure a fair and functioning system for all parties involved.

Definition of the term Regulation according to my requested AI.

In essence, I understand regulation as a legal framework, that is, binding provisions armed with sanctions.

In what follows, I explain why I consider regulation as no longer possible in order to freeze or even reduce current capabilities of artificial intelligence. Also, slowing down its growth would be difficult and not very useful.

Regulation of AI is no longer possible

Let's start with something positive. The abilities of today's AI algorithms, models and software packages are breathtaking. That is also said that it goes both about mathematical model as well as about software, datasets, fully trained neural networks and available computing infrastructures. That was not like this until recently. How often have I already heard, even from computer scientists: That existed already. Not true.

Here are a few applications that can be done with little effort and run locally on your own computer without having to give your data to Microsoft, Google, OpenAI or Amazon:

• Knowledge Assistants: Wouldn't you like to get information from your Intranet through a question-and-answer dialogue, just once? No annoying searching through directories, no unsatisfying search mask with few relevant keywords. Or how about a code search in your repository, using a natural language query command?
• Summary of texts: You can find some real examples in posts on Dr. GDPR.
• Keyword Extraction: I've also implemented this myself, as a local system. Both helpful for quick text comprehension as well as possibly for search engine optimization (as long as it's not yet based on semantic search algorithms)
• Identify answered questions: What questions does this post answer? And what is the answer in one sentence? You can find real examples in this blog.
• Translations in other languages: DEEPL does a great job. But maybe you want something of your own, cheaper or simply more flexible instead of a Black Box? Or they would like to provide their own API.
• Speech Processing: Transcription, Time Index Recognition, Translation, Speaker Recognition, Music Noise Filtering… Text after language and language after text, then translated into ten languages. How would that be? Already done and impressive results achieved.
• Video Generation: For example, generating an animated, quite realistic person that moves her lips in sync with a given text while speaking it.
• Generating Images from Texts: You're familiar with it from DALL-E or Midjourney. How about a system of your own? Keywords: Data Protection, Own Images, Higher Flexibility, Code Ownership
• Generating Text from Images: Image component recognition. What can be seen on the following image?

Input image (original image):

The AI has the task of recognizing and describing image components.

Here is the result:

The objects in the image were numerous recognized, namely: Person (2x), Wall, Curtain, Table, Bottle (multiple times), Paper, Bowl. A variant of the algorithm even recognizes the wine glass, which is cut off at the front. Another variant also recognizes the podium as such.

• Image+Audio for Video: Creating 3D objects (in video form) from 2D objects (images), combined with animation and synchronization. Here's a real example:

Input image (original image):

Textinput (partially generated by AI): Input-text (German) –> Output/Input-text (English) –> Output/Input-Audio (can be any language, I've just for fun generated an audio file from a text using an AI):

Computer-generated result