Digital Revolution – “Thinking” like a human: How o3 and o3 Mini are changing the AI ​​world

How does 'thinking' work in more powerful AI models like o3 and o3 Mini?

The “thinking” in advanced AI models like OpenAI's o3 and o3 Mini is based on the ability to process information in a contextualized and dynamic manner. These models use advanced neural networks and massive amounts of data to recognize complex patterns, understand relationships, and draw informed conclusions. Compared to previous models, o3 and o3 Mini can not only analyze data, but also develop creative solutions and adapt to unexpected scenarios.

Advantages:

1. Flexibility: The models can handle different tasks, from word processing to problem solving to prediction.
2. Speed: Complex calculation tasks are solved in fractions of a second, saving time in research and industry.
3. Precision: The accuracy of analyzing data, text and programs has improved significantly.

Through these capabilities, o3 and o3 Mini provide a foundation for innovation in areas such as medicine, engineering and the creative industries.

Prof. Dr. Anabel Ternès is an entrepreneur, futurologist, author, radio and TV presenter. She is known for her work in digital transformation, innovation and leadership. Ternès is also President of the Club of Budapest Germany, board member of the Friends of Social Business and a member of the Club of Rome.

What does the term 'General Artificial Intelligence' (AGI) mean and how does it differ from other forms of artificial intelligence?

The term General Artificial Intelligence (AGI) describes a form of AI that has human-like cognitive abilities. Unlike specialized AI systems that are limited to specific tasks (for example, image recognition or language translation), AGI is designed to handle a variety of tasks, learn, and adapt to new challenges. AGI can think and make decisions across contexts, similar to a human.

Key differences:

1. Ability to generalize: AGI can transfer knowledge from one area to others, while specialized AI systems are only effective in their specific area.
2. Autonomy: AGI systems can independently develop new solutions and continuously improve.
3. Objective: AGI can track and plan for long-term goals rather than being limited to immediate tasks.

AGI is the next milestone in AI research and has the potential to fundamentally change all areas of life.

How can researchers apply for early access to these new AI models and what are the benefits of this access?

Researchers can apply for early access to models like o3 through platforms like OpenAI or partner companies like AWS. The process typically includes:

1. Submitting an application: Researchers must describe their planned projects and explain how the AI ​​will be used.
2. Evaluation: Applications are reviewed by experts with a focus on ethical use and innovative areas of application.
3. Authorization and access: If the application is successful, researchers will receive access to the models and technical support.

Advantages of early access:

1. Research advantage: Researchers can test the latest technologies and use them for innovative projects.
2. Partnership opportunities: Access to experts and networks from OpenAI or AWS.
3. Scalability: Use of powerful cloud services to process large amounts of data.

What complicated computing and programming tasks can be solved by these new AI models?

The new AI models like o3 are able to handle extremely complex tasks. This includes:

Biomedicine: Analysis of genomes, discovery of new drugs and modeling of protein structures.

Engineering: Optimization of production processes, simulation of materials and support in design processes.

Finance: Predicting market trends, risk analysis and fraud detection.

Creative industries: Generation of high quality texts, music and visual content.

Impact on industries:

1. Healthcare: More efficient diagnoses and personalized therapies improve patient care.
2. Research: Accelerating scientific breakthroughs through faster data understanding.
3. Company: Reduce costs and increase productivity through automation and optimization.
4. Education: Develop personalized learning systems tailored to the needs of individual students.

The introduction of such AI models could trigger a comprehensive transformation by speeding up processes, reducing costs and driving innovation. However, it also brings with it challenges, such as ethical issues and dealing with potential job losses.