Artificial Intelligence: Difference between revisions

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See [[wp:Artificial intelligence]] on Wikipedia

<s>[https://chatgpt.com/ ChatGPT], [https://claude.ai Claude],</s> [https://www.deepseek.com/ DeepSeek] is all the rage; stock market valuations of major companies like [https://www.marketwatch.com/investing/stock/goog Alphabet] (Google) or [https://www.marketwatch.com/investing/stock/nvda NVidia] fluctuate billions of dollars overnight due to perceived strength or weakness in the new technological arms race.

<s>Open AI's [https://chatgpt.com/ ChatGPT], Anthropic's [https://claude.ai Claude], Meta's LLaMA</s> China's [https://www.deepseek.com/ DeepSeek] is all the rage<ref>ed. note: I crossed out the prior models to illustrate the litany of new models that are hyped in rapid succession. Of course ChatGPT and OpenAI are still relevant - and release updates to their prior technology in the never-ending 'arms race' of AI.</ref>; stock market valuations of major companies like [https://www.marketwatch.com/investing/stock/goog Alphabet] (Google) or [https://www.marketwatch.com/investing/stock/nvda NVidia] fluctuate billions of dollars overnight due to perceived strength or weakness in the new technological arms race. Companies like [[wp:Mistral_AI|Mistral AI]], founded only in 2023, are worth billions of dollars.

This page will capture some of the interesting points about AI and its use or relevance in Knowledge Management, [[MediaWiki]], and probably some other tangents like deep fakes or politics.

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One interesting essay I read was "''[https://adam.harvey.studio/creative-commons Creative Commons and the Face Recognition Problem]''" by Adam Harvey. He describes how 100 million images from Flickr were used to train facial recognition systems using peoples wedding and vacation photos.

== Understanding AI ==

An excellent introduction to Artificial Intelligence and Large Language Models (LLMs) is an article [https://www.understandingai.org/p/large-language-models-explained-with Large language models, explained with a minimum of math and jargon] by Timothy Lee and Sean Trott - July 27, 2023<~~blockquote~~>''Tim Lee is a journalist with a master’s degree in computer science. The article is the result of two months of in-depth research. Co-author Sean Trott is a cognitive scientist at the University of California, San Diego.''</~~blockquote~~>

An excellent introduction to Artificial Intelligence and Large Language Models (LLMs) is an article [https://www.understandingai.org/p/large-language-models-explained-with Large language models, explained with a minimum of math and jargon] by Timothy Lee and Sean Trott - July 27, 2023<ref>''Tim Lee is a journalist with a master’s degree in computer science. The article is the result of two months of in-depth research. Co-author Sean Trott is a cognitive scientist at the University of California, San Diego.''</ref>

[[wp:Graphics_processing_unit|GPU]]<nowiki/>s - specialized electronic circuits initially developed for computer graphics - are an important aspect of AI (and other forms of computing such as neural networks, cryptocurrency).

==Llama confusion==

[[File:18-08-25-Åland RRK6596a.jpg|thumb|right|llama from disc golf island]]

[[wp:llama.cpp|llama.cpp]], is a library written in C++ that performs inference on various LLMs (including [[wp:Llama_(language_model)|Llama]]) by implementing tensor algebra so systems without GPUs can do "AI". [[Ollama]] is a LLM you can run on your own hardware, off-net.

== Vectors are not just for graphics ==

[[Svg|SVG]] is cool for graphics. But [[vectors]] aren't just for graphics.

The [https://vectors.nlpl.eu/ Nordic Language Processing Laboratory], [https://www.mn.uio.no/ifi/english/research/groups/ltg/ Language Technology Group] at the University of Oslo, Norway publishes their research tools which help visualize how word vectors work in LLMs For instance, here's the [https://vectors.nlpl.eu/explore/embeddings/en/MOD_enwiki_upos_skipgram_300_2_2021/cat_NOUN/ vector for cat] showing word relationships using '''English Wikipedia''' as the training corpus. (Click the link that says "Show the raw vector" to see the full numerical word vector).

== Biases in the Hive Mind ==

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 See [[wp:Artificial intelligence]] on Wikipedia
-<s>[https://chatgpt.com/ ChatGPT], [https://claude.ai Claude],</s> [https://www.deepseek.com/ DeepSeek] is all the rage; stock market valuations of major companies like [https://www.marketwatch.com/investing/stock/goog Alphabet] (Google) or [https://www.marketwatch.com/investing/stock/nvda NVidia] fluctuate billions of dollars overnight due to perceived strength or weakness in the new technological arms race.
+<s>Open AI's [https://chatgpt.com/ ChatGPT], Anthropic's [https://claude.ai Claude], Meta's LLaMA</s> China's [https://www.deepseek.com/ DeepSeek] is all the rage<ref>ed. note: I crossed out the prior models to illustrate the litany of new models that are hyped in rapid succession. Of course ChatGPT and OpenAI are still relevant - and release updates to their prior technology in the never-ending 'arms race' of AI.</ref>; stock market valuations of major companies like [https://www.marketwatch.com/investing/stock/goog Alphabet] (Google) or [https://www.marketwatch.com/investing/stock/nvda NVidia] fluctuate billions of dollars overnight due to perceived strength or weakness in the new technological arms race. Companies like [[wp:Mistral_AI|Mistral AI]], founded only in 2023, are worth billions of dollars.
 This page will capture some of the interesting points about AI and its use or relevance in Knowledge Management, [[MediaWiki]], and probably some other tangents like deep fakes or politics.
@@ Line 7: / Line 7: @@
 One interesting essay I read was "''[https://adam.harvey.studio/creative-commons Creative Commons and the Face Recognition Problem]''" by Adam Harvey. He describes how 100 million images from Flickr were used to train facial recognition systems using peoples wedding and vacation photos.
 == Understanding AI ==
-An excellent introduction to Artificial Intelligence and Large Language Models (LLMs) is  an article [https://www.understandingai.org/p/large-language-models-explained-with Large language models, explained with a minimum of math and jargon]  by Timothy Lee and Sean Trott - July 27, 2023<blockquote>''Tim Lee is a journalist with a master’s degree in computer science. The article is the result of two months of in-depth research. Co-author Sean Trott is a cognitive scientist at the University of California, San Diego.''</blockquote>
+An excellent introduction to Artificial Intelligence and Large Language Models (LLMs) is  an article [https://www.understandingai.org/p/large-language-models-explained-with Large language models, explained with a minimum of math and jargon]  by Timothy Lee and Sean Trott - July 27, 2023<ref>''Tim Lee is a journalist with a master’s degree in computer science. The article is the result of two months of in-depth research. Co-author Sean Trott is a cognitive scientist at the University of California, San Diego.''</ref>
+[[wp:Graphics_processing_unit|GPU]]<nowiki/>s - specialized electronic circuits initially developed for computer graphics - are an important aspect of AI (and other forms of computing such as neural networks, cryptocurrency).
+==Llama confusion==
+[[File:18-08-25-Åland RRK6596a.jpg|thumb|right|llama from disc golf island]]
+[[wp:llama.cpp|llama.cpp]], is a library written in C++ that performs inference on various LLMs (including [[wp:Llama_(language_model)|Llama]]) by implementing tensor algebra so systems without GPUs can do "AI". [[Ollama]] is a LLM you can run on your own hardware, off-net.
 == Vectors are not just for graphics ==
 [[Svg|SVG]] is cool for graphics. But [[vectors]] aren't just for graphics.
-The [https://vectors.nlpl.eu/ Nordic Language Processing Laboratory], [https://www.mn.uio.no/ifi/english/research/groups/ltg/ Language Technology Group] at the University of Oslo, Norway publishes their research tools which help visualize how word vectors work in LLMs For instance, here's the [https://vectors.nlpl.eu/explore/embeddings/en/MOD_enwiki_upos_skipgram_300_2_2021/cat_NOUN/ vector for cat] showing word relationships using '''English Wikipedia''' as the training corpus. (Click the link that says "Show the raw vector" to see the full numerical word vector).
 == Biases in the Hive Mind ==