March 2025
Intermediate to advanced
282 pages
9h 5m
French
Content preview from Ingénierie prompte pour LLMs
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Chapitre 11. Regarder vers l'avenir
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L'histoire de l'humanité n'a de sens que sur une échelle logarithmique. Il a fallu aux humains d'innombrables éons pour comprendre l'agriculture, des millénaires au-delà pour inventer l'écriture, des siècles de plus pour inventer la machine à vapeur, et des décennies de plus pour inventer l'automobile, l'ordinateur et le smartphone. Quelques années plus tard, vers 2012, le Deep Learning est apparu sur le devant de la scène.
Le GPT-2 d'OpenAI a été annoncé en 2019, puis le ChatGPT a été annoncé en 2022. Cela a déclenché une explosion du développement autour des LLMs. De nombreuses entreprises se sont lancées dans la course - Anthropic, Google, Microsoft, Meta, xAI, NVIDIA, Mistral et bien d'autres encore - toutes construisant de nouveaux LLMs qui ont dépassé les précédents en termes de capacité, d'aptitude et de vitesse. En l'espace de quelques mois, les LLMs se sont transformés en moteurs de complétion de documents, en moteurs de chat et en agents capables d'interagir avec le monde extérieur.
Attachez vos ceintures, lecteurs. Si tu penses que le rythme du changement est rapide aujourd'hui, alors attends, il ne fera que s'accélérer. (Peut-être que ce Ray Kurzweil avait vu juste !) Dans ce dernier chapitre, nous allons nous pencher sur certains des développements qui se profilent à l'horizon et sur la façon ...
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