chillstar
Full Member
It takes all kinds to make a universe.
Posts: 156
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Post by chillstar on Jan 23, 2024 19:53:47 GMT
Meet Ameca. Who has taken the international AI culture by a storm.
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Post by HAL on Feb 9, 2024 16:33:20 GMT
Well, at least it appears to be honest.
Issac Asimov's worst nightmare.
I wonder if they purposely made it androgynous.
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chillstar
Full Member
It takes all kinds to make a universe.
Posts: 156
|
Post by chillstar on Feb 9, 2024 17:12:49 GMT
Yeah, that AI is breaking his three laws of robotics all right. Thart's enough to worry anyone.
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Post by HAL on Feb 10, 2024 23:51:48 GMT
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chillstar
Full Member
It takes all kinds to make a universe.
Posts: 156
|
Post by chillstar on Apr 18, 2024 1:56:14 GMT
Ameca can easily win The World's first AI beauty contest featuring computer generated women. Click [here] |
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chillstar
Full Member
It takes all kinds to make a universe.
Posts: 156
|
Post by chillstar on Apr 21, 2024 21:56:33 GMT
The National Robotarium has bought Ameca, often called “the world’s most advanced” humanoid robot. Read [here] |
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chillstar
Full Member
It takes all kinds to make a universe.
Posts: 156
|
Post by chillstar on Apr 21, 2024 22:02:49 GMT
What are AI's categories? One might ask.
Here are most:
1. Reactive machines: These are the simplest form of AI which can only react to the current situation based on the pre-programmed responses. It doesn't have the ability to learn from past experiences.
2. Limited memory: This category of AI comes with the ability to learn from past experiences and adjust their behavior accordingly. However, they have a limited memory.
3. Theory of mind: AI systems that can understand human emotions and thoughts. They have the ability to respond accordingly to their level of understanding.
4. Self-awareness: AI systems in this category have self-awareness and self-consciousness. They are able to understand their own emotions and behaviors, thus able to make decisions accordingly.
5. Natural language processing: This is an AI system that can understand human language and respond accordingly.
6. Computer vision: AI systems that can recognize images, videos, and other visual data and come up with the respective decisions.
7. Robotics: AI systems that can perform physical tasks and navigate through the environment.
8. Expert systems: These AI systems are designed specifically for solving complex problems in a particular domain.
9. Cognitive computing: AI systems that focus on the development of cognitive abilities in machines such as problem-solving, reasoning, and decision-making.
10. Machine learning: AI systems that have the ability to learn from data and improve performance over time.
11. Deep learning: A specific type of machine learning that involves highly complex neural networks that can learn from large amounts of data.
12. Neural networks: A type of AI that uses interconnected layers of nodes to simulate the human brain and recognize patterns from data.
13. Genetic algorithms: These use a trial-and-error approach to solving complex problems, relying on the concept of natural selection.
14. Fuzzy logic: This is an AI system that deals with uncertainty and imprecise information.
15. Swarm intelligence: AI systems that work together to solve problems, mimicking the behavior of social insects.
16. Intelligent agents: AI systems that can interact with the environment, make decisions, and act on behalf of the user.
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