The world of the most innovative technology is being struck by the GPT-3 outputs. The most surprising is the fact that the results are almost indistinguishable from the human work.
But what is GPT-3 and why is everyone talking about it?
Many would say it’s a dream come true for everyone who dislikes doing homework or lacks diligence – because GPT-3 would do the work instead of them.
Why can it perform all these tasks?
The distinctive trait of all neural networks is the fact that they are a black box, meaning it’s impossible to observe why it decides the way it decides.
But the source of its ‘superpower’ is described within the name itself.
The abbreviation GPT-3 stands for ‘Generative Pre-trained Transformer 3’.
The main purpose of inventing an artificial intelligence system like GPT-3 was to generate text in exchange for a prompt of any kind.
Thus you grant GPT-3 an idea which is then coherently developed in a way that prompt assigned it to. Most important is that the outcome is original. It’s far from being a collection of COPY&PASTEs from certain related texts. After some time GPT-3 spent learning, it gained sense of language and underlying linguistic rules.
Computer algorithms can build sentences in a meaningful way because they are properly pre-trained.
Its core is a network of algorithms, called neural networks.
This means that a certain process of computer data evaluation is repeated over and over again. The main purpose of repetition is to improve the final result automatically throughout. It resembles the learning process of the human brain.
That’s why it is also called machine learning.
The data processed is natural language. In fact, a neural network learns how we communicate via pre-training by examining an immense amount of texts.
For instance, GPT-3 has been pre-trained with 175 billion parameters, making it the most impeccable artificial writer that ever existed, and 500 billion words from online platforms, making it the most educated one.
‘Transformer’ denotes mostly the way of GPT-3’s information interpretation and further communication. After interpreting the input, GPT-3’s artificial intelligence system will generate differently relevant word orders, where only the most accurate one is communicated forwards.
To roughly outline, this is possible because of integrating principles of semantics and syntax; a linguistic science that deals with meaning of the words and how they are built into sentences.
This means that the pre-trained system knows how sentences are constructed and which words sequences make sense and are meaningful. Following this principle, the GPT-3 system transforms a prompt to the desired text.
What impact could those features have on the future of translation industry?
Read our blog post next week to discover more novelties and advantages GPT-3 could bring!
Frequently asked questions
GPT-3 is a language prediction model, created by OpenAI, a San Francisco-based artificial intelligence research laboratory.
The abbreviation GPT stands for ‘Generative Pre-trained Transformer’. And the 3 means that it’s the third-generation language prediction model in the GPT series.
If you’re updated with all the latest novelties of the technology industry, you must have heard of the wonders GPT-3 produced – it generates everything from prose, factual texts to computer code and even poetry.
The indistinctive trait of all neural networks is the fact that they are a black box, meaning it’s impossible to observe why it decides the way it decides.
But the source of its superpower is described within the name itself: Generated Pre-trained Transformer 3.
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