Aufstieg autonomer AI-Agenten (DE long version)

AI-Agenten markieren eine neue Stufe in der Anwendung von künstlicher Intelligenz. Sie gehen weit über die reaktiven Fähigkeiten bisheriger AI-Assistenten wie Siri, Alexa oder Google Assistant hinaus und bieten proaktive, selbstständige Erledigung von digitalen Aufgaben einschließlich der Programmierung. Wenn man es etwas weiter fasst und Roboter einschließt, bezieht es sich sogar nicht nur auf die digitale Welt. Das ist allerdings ein Thema für sich, was in einem gesonderten Artikel beleuchtet wird. 

Mehr Infos zur praktischen Anwendung von AI-Agenten, die eigenständig Zielvorgaben umsetzen. 

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Rise of autonomous AI Agents (EN short version)

AI agents mark a new stage in the application of artificial intelligence. They go far beyond the reactive capabilities of previous AI assistants like Siri, Alexa, or Google Assistant, offering proactive, autonomous completion of digital tasks. 

Read more about the capabilities in following article (click on more) or in the long version with a brief comparison of ecosystems by downloading the full article (pdf): Rise of AI Agents

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IoT platforms for smart devices

The IoT platform market has developed rapidly in recent years.

Numerous niche providers have given way, while a few powerful platforms have established themselves, capable of meeting the demands of the future. These platforms enable device manufacturers to efficiently process data streams, utilize open APIs for developing and deploying applications, and ideally also support payment processing for microservices – a crucial factor given the growing importance of monetizing IoT services.

This table and the additional information give an idea about an very important selecting process for the appropriate IoT platform for your specific requirements.

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Examples of Use Cases for AI + IoT (AIoT)

Some use cases for the combination of AI and IoT (AIoT), to optimize processes, reduce costs, increase safety, and improve quality of life.

Smart City:

  • Environmental monitoring: Sensors measure air quality, noise levels, and other environmental factors. AI analyzes these data to detect environmental pollution and develop measures to improve quality of life.
  • Intelligent traffic control and street lighting: AI analyzes traffic data from sensors and cameras to optimize traffic light timings in real time, reduce congestion, and improve traffic flow. Sensors detect brightness and movement. AI controls street lighting as needed and saves energy.
  • Parking management: Sensors record the occupancy of parking spaces. AI guides drivers to free parking spaces and optimizes parking space management.
  • Waste management: Sensors in waste containers report the fill level. AI optimizes the routes of waste collection vehicles and reduces unnecessary trips. 

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Links to news – see what happened after my projects

What is happened after my projects has been finished.

The following article [pdf] in a professional magazin gives an overview of logistic solutions with proALPHA (sorry, only in German): Artikel-im-Sonderheft_Logistik-Heute_02-2018_Seite 38-39 [GER]

Cognitive abilities in AI, such as learning, reasoning, problem-solving, and perception, are crucial for driving technological advancement and fostering a deeper understanding of AI. Here’s why: AI can be a sparring partner or personal assistant with deep understandig e.g. of excel or your specific software after learning procedures. This can lead to software improvements.

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Why is cognitive AI (Artificial Intelligenz) + IoT (Internet of Things) changing the world

On the following link are statements by global player in digitalization of production environments.

On the end of the article you will find my conclusion. Thanks for your feedback and comments …

https://www.produktion.de/trends-innovationen/id-4-gruende-warum-it-anbieter-die-produktion-perfektionieren-105.html

Cognitive AI refers to artificial intelligence systems that aim to simulate human thought processes. These systems are designed to understand, learn, and interact with the world in a way that resembles human cognition. Unlike traditional AI, which often relies on pre-programmed rules or statistical models, cognitive AI strives to develop its own understanding of the world through experience and learning.

Key characteristics of cognitive AI include:

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