Nature and surroundings communicate with human beings in object language, then brain transforms it in human language for learning and understanding. To develop human learnography, it is important to transform object language into human language for knowledge transfer processing.
What are the roles of transformers in the development of artificial intelligence?
Transformers are a type of neural network architecture that have played a significant role in the development of artificial intelligence, particularly in the field of natural language processing (NLP). Here are some of the key roles that transformers have played in the development of artificial intelligence (AI).
1. Language modeling
Transformers have been used to build language models that can predict the likelihood of a word or phrase given the surrounding context. These language models have been used in a variety of natural language processing (NLP) tasks, such as text classification, sentiment analysis and machine translation.
2. Sequence-to-sequence learning
Transformers have been used to build sequence-to-sequence models, which are used in machine translation, text summarization and other applications. These models use an encoder-decoder architecture, with the encoder processing the input sequence and the decoder generating the output sequence.
3. Attention mechanisms of transformer
Transformers use a mechanism called self-attention to weight the importance of different parts of input sequence. This has proven to be a powerful way of capturing long-range dependencies in sequences, and has been used in a variety of other machine learning applications beyond natural language processing (NLP).
4. Transfer learning
Pre-trained transformer models such as BERT, GPT-2 and RoBERTa have achieved state-of-the-art performance on a wide range of natural language processing tasks. These models are trained on large amounts of text data and can be fine-tuned on smaller, task-specific datasets to achieve high performance with minimal training data.
In conclusion, transformers have been a key driver of progress in artificial intelligence, particularly in the field of natural language processing (NLP) . They have enabled a wide range of applications that were previously difficult or impossible. Transformers have also pushed the state-of-the-art in many areas of artificial intelligence (AI) research.
What are the key roles of brain transformers in the development of human intelligence?
It’s worth noting that while transformers in artificial neural networks are inspired by the learnography of human brain, there may be the possibility of similar analog of neuronal transformers in the brain. In fact, the brain does have a number of structures and processes that are thought to play important roles like knowledge transformer in the development of human intelligence. Here are some of the facts about the development of human intelligence (HI).
1. Neuronal plasticity
The brain’s ability to change and adapt in response to new experiences is thought to be a key factor in human intelligence. This is synaptic potential, and brain plasticity allows us to learn new skills and acquire knowledge throughout our lives.
2. Attention
Human brain has a complex system for allocating attention, which allows us to selectively focus on important information and filter out distractions. This is thought to be a critical component of cognitive control and goal-directed behavior in problem solving activities.
3. Working memory
Working memory is the system by which the brain temporarily holds and manipulates information for use in a task. Working memory also provides critical space for the processing of knowledge transfer. This is thought to be an important component of many aspects of intelligence, such as reasoning, problem-solving and decision-making.
4. Associative learning
The brain is capable of forming associations between space, objects, events and different stimuli. Associative learning transfer allows us to make predictions about the world and respond appropriately to new situations.
5. Social cognition
Human intelligence is also shaped by our ability to understand and interact with other people in the community. The brain has specialized regions and networks that are involved in social cognition, including the ability to infer others’ mental states and emotions.
In conclusion, the development of human intelligence is thought to depend on a complex interplay of genetic, environmental and cultural factors, as well as the brain’s own intrinsic mechanisms for learning, attention and memory. I will write more in the next blog about the roles of brain transformers in the development of human intelligence. It is remarkable that artificial intelligence develops from human learnography, but nothing has been done for the advancement of human intelligence in school system.
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