Stanford's Alpaca language model, trained through self-instruction and open source models, has the potential to revolutionize AI technology with its low cost and high accuracy in generating language models like GPT-3, but also raises concerns about the ease of creating cheap models by bad actors.

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  00:00

  Stanford's Alpaca language model, which behaves similarly to OpenAI's GPT-3 but is smaller and cheaper to reproduce, could revolutionize AI technology with its unexpectedly low cost.
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  01:42

  Stanford used self-instruct to train their meta model, which allowed their 600 model to compete with GPT 3.5.
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  02:53

  The breakthrough of self-instructing models led to the development of GPT 3.5, which can imitate and learn from other models without the need for human labeling and ranking.
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  03:48

  Stanford researchers have developed a new AI model called Alpaca that can create language models similar to GPT-3 by using a self-instruct process and open source models, which could potentially enable more people, including bad actors, to create new cheap models.
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  05:10

  Alpaca gets the question right about 80% of the time, while chatty BT and GPT4 often get it wrong.
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  05:59

  The AI model struggles with certain questions but excels in basic addition and subtraction, generating literary analogies, and solving Common Sense problems.
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  06:50

  The language model used in the experiment was not the strongest and could have been improved, but the results were achieved at a low cost and raise questions about the impact of larger models from companies like Apple.
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  08:09

  Amazon's chatbot technology, including Alexa TM and Ernie, outperforms GPT-3 and GPT-4, but without a paper release, their capabilities cannot be verified.

  • Amazon has been developing chatbot technology for a while, with a model called Alexa TM outperforming GPT-3 and their Ernie bot being better in Chinese language than even GPT-4, but without a paper release, it cannot be verified.
  • The rapid and cheap development of large language models may upend the economics of producing cutting-edge models, leading to questions about the incentive for companies and governments to invest in them and the potential for an arms race with outsiders trying to imitate them.