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Aug. 13, 2025, 9:32 a.m.
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| Cristianini N. Machina Sapiens..Intelligent Machines Passed the Turing Test 2026.pdf | 2.0 MB |
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SOURCE: Cristianini N. Machina Sapiens..Intelligent Machines Passed the Turing Test 2026
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MEDIAINFO
Textbook in PDF format Can machines think? This troubling question, posed by Alan Turing in 1950, has perhaps been answered: today we can converse with a computer without being able to distinguish it from a person. Machines can pass university exams and program other computers. ChatGPT, Bard, and other 'language models' have proved proficient at performing tasks far beyond their creators’ initial expectations, and we still do not know why. Trained simply to predict missing words in a text, such models have gained an understanding of the world and language that makes them capable of reasoning, planning, solving problems, as well as conversing almost flawlessly. Is this the secret of knowledge, and is it now in the hands of our creations? Perhaps we are no longer alone. And as we try to figure out how to share these powers with the 'aliens' who now work at our side, we can wonder what else they may learn tomorrow. Are we approaching a critical threshold beyond which machines will attain superhuman performance? Every intelligent agent needs a model of its environment, implicit or explicit, in order to be able to choose its actions appropriately. At its core, we can think of this model as an internal, simplified simulation of the environment's behaviour. When talking about Artificial Intelligence, we must always distinguish the agent (which we will sometimes also call bot, or intelligent machine) from the model of the world that animates it and from the algorithm that produces this model from experience. Machine learning algorithms aim to produce models of the world by observing it. Make a note of this; we will need it in the rest of the book. There are three levels: the agent we encounter in the world (e.g. ChatGPT), the internal model it uses to make decisions (e.g. GPT-3), and the algorithm that creates that model from the data (e.g. the Transformer). Since this Language Model was created by pre-training a Transformer generatively, they called it Generative Pretrained Transformer or GPT for its friends. Following on from The Shortcut, Nello Cristianini has authored another brilliant book – written like a gripping thriller – explaining the ideas behind a technology destined to change the world. If our worst terror has always stemmed from fear of the unknown, the cure, since time immemorial, is knowledge
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