Tag: Peter Novig

Generative AI : A visually striking graphic that is split into two halves. On one side, depict a traditional library or database to symbolize Large Language Models

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Gary Smith
Date
January 6, 2025

Categorized
Artificial Intelligence, Large Language Models (LLMs)

Tagged
Bill Gates on ChatGPT, Blaise Agüera y Arcas, Chatbots playing Connections, Connections (New York Times word puzzle), Ethan Mollick on ChatGPT, Geoffrey Hinton on ChatGPT, LLMs playing Connections, Marc Andreessen on ChatGPT, OpenAI o1 on NYT word game Connections, Peter Novig, Sam Altman on AGI, Sam Altman on AI superintelligence, Sundar Pichai on ChatGPT}

Large Language Models (LLMs) Flunk Word Game Connections

_{Despite hype, ChatGPT and its competitors, in all their iterations, are still just text-generators based on statistical patterns in the text databases they train on} _{Gary Smith
January 6, 2025

6

Artificial Intelligence, Large Language Models (LLMs)}

Identification of statistical patterns in text that Large Language Models (LLMs) do not understand is not going to give us AGI, let alone superintelligence. Read More ›

LLM, AI Large Language Model concept. Businessman use tablet and laptop with LLM icons. A language model distinguished by its general-purpose language generation capability. Chat AI.

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Jeffrey Funk and Gary Smith
Date
December 5, 2024

Categorized
Large Language Models (LLMs)

Tagged
3.5 Opus (LLM), Andreessen Horowitz, Ben Horowitz, Blaise Agüera y Arcas, Elon Musk and AGI, Featured, Gemini (LLM), Large language models and AGI, Large language models and common sense, Large language modes (becoming less reliable), Marc Andreessen, Orion (LLM), Peter Novig, Preview-01 (LLM), Sam Altman and AGI}

The Promise of Artificial General Intelligence is Evaporating

_{Revenue from corporate adoption of AI continues to disappoint and, so far, pales in comparison to the revenue that sustained the dot-com bubble — until it didn’t} _{Jeffrey Funk and Gary Smith
December 5, 2024

7

Large Language Models (LLMs)}

Recognition is growing that fundamental challenges make LLMs unreliable. Increasingly expensive scaling will likely hasten the popping of the AI bubble. Read More ›