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| bet | 10/13 | | Sana | 16.05.2024 | | Hajmi | 468,13 Kb. | | #237740 |
Bog'liq horijiy tilTheory of mind - In the examples we have seen so far, we have identified machines that are intelligent to a certain degree, but cannot really derive much from their defined set of values or libraries. Theory of mind AIs are different in the sense that they will be able to socialize and understand human emotions. In
other words, they will be able to better understand human behavior and interact with us just like any other human and not as a tradition learning machine. Theory of mind AI computers are currently in development by various companies around the world and as of yet to be built. The main contention for these type of AIs is that in order for them to be truly self-aware, they must understand emotions and be able to change as well as adapt to human behavior and interactions
Self-aware AI - Self aware AI machines are what most people imagine when thinking about artificial intelligence as seen in the movies. Machines built on a self-aware principle will be super intelligent, sentient and have a certain level of consciousness. The self-aware AI concept represents the holy grail of artificial intelligence, and we have yet to reach the level of technology needed to make machines truly self-aware.
Additionally, self-aware AIs also present moral and philosophical challenges as we continue to debate about what makes human/machine interactions truly reciprocal in action or influence.
When we talk about various types and forms of artificial intelligence, an average user might ask where should I begin?
Luckily, there are tools specifically developed and designed for the purpose of teaching your AI. The most popular frameworks being used today are Tenso Flow and Theano. Both of these learning platforms are open-source and have their specific advantages and disadvantages depending on need. TensorFlow is more user-friendly and is currently used more often. Theano has recently lost some of its popularity but still retains a strong online community. Theano leads in usability and speed, but TensorFlow is better suited for deployment and therefore is used more often by researchers and data scientists. There are other frameworks that you can use depending on your need so its best to research all the available options and then select the one suited for your specific needs.
While these frameworks have their own respective libraries for deep learning, a popular way of improving them is to use Keras. Keras is a high-level neural network API written in Python and capable of running on top of both TensorFlow, Theano or CNTK. For more information about what Keras is and how to install it, you can review our Knowledgebase article on Keras.
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