1954
An IBM computer successfully translated over 60 sentences from Russian to English using a rule-based and logic-driven approach to execute specific natural language processing tasks.
‘70s
there was a surge in interest and research in AI, leading to the development of more advanced algorithms, such as the backpropagation algorithm. This breakthrough enabled neural networks to “learn” and improve their performance over time.
‘80s
Generative Adversarial Networks (GANs) were introduced, allowing two neural networks to “train each other” until the generator network could successfully deceive the discriminator network. This process enhances the quality of generated data and improves the ability to distinguish real data from synthetic ones.
At the same time, Deep Learning technology became more widespread, enabling advancements in text generation, speech synthesis, and music creation.
‘90s
The first GPT model, in its modern form, was developed, demonstrating exceptional abilities in text and image generation.
Today
GPT models have been enhanced over time. Today, they are larger, more intelligent, trained on better data, and designed to be safer.
The interaction between humans and computers involves various tasks to perform actions such as:
Language detection
Breaking down the sentence into single parts
Semantic analysis
Tone of voice analysis
Let’s take a look at the NLP tasks:
Neurally S.r.l.
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