The emergence of ChatGPT
GPT: what is it, exactly?
GPT’s designers transcoded an immense base of textual knowledge (the Web) into numerical data that computers can process. A few scale references:
- Number of words on the web: 10¹⁵
- Number of GPT parameters: 10¹²
- Number of human neurons: 10¹¹
GPT operates on a simple principle: predict the most probable next word given a context made up of an ordered base of words, a precise question (prompt) and its algorithmic model. The power of the model and the richness of the information produce relevant responses where “semantics emerge from signs”.
What does GPT tell us?
GPT is a parrot that is not learned, but gifted with a formidable talent for finding needles (prompts) in a haystack (the Web).
GPT does not understand what it says — comparable to a CD player broadcasting music without understanding it. It originates nothing but excels at locating and expressing the information sought.
GPT is magical – so “there’s a trick”
Human language is built on consensual conventions. Its decoupling of signified and signifier, combined with the alphabet, creates a radical economy of means for expressing infinite possibilities.
Meaning resides in the author’s mind and emerges in the reader who reconstructs meaning from signs. Thus, “the reader (human or machine) causes the meaning to emerge from the words and statistical sentences constructed by GPT”.
Garbage in, garbage out
GPT can access everything but “knows” nothing. If fed statistically inaccurate data, it would become “conspiratorial and denialist” without its natural common sense.
GPT: what’s next?
GPT is neither conscious nor intelligent. It is the collective intelligence of its designers and web contributors that we capture in its responses.
Augmented capabilities could emerge by integrating algorithmic layers using GPT dynamically, combined with recursive structures and reinforcement learning. These combinations could generate emergent adaptability properties.
Since the knowledge base remains human in nature, future advanced AIs “will in some ways remain in our image”.
Integration at Agora Software
Agora Software uses GPT for two complementary tasks:
- Building training corpora for specific intent recognition
- Refining intent recognition for phrases that fall outside the defined functional scope
The solution preserves the qualities of sovereignty, explainability and confidentiality that characterise Agora’s approach.