Discover how companies are responsibly integrating AI in production. This invite-only event in SF will explore the intersection of technology and business. Find out how you can attend here.
During testing, a recently released large language model (LLM) appeared to recognize that it was being evaluated and commented on the relevance of the information it was processing. This led to speculation that this response could be an example of metacognition, an understanding of one’s own thought processes. While this recent LLM sparked conversation about AI’s potential for self-awareness, the true story lies in the model’s sheer power, providing an example of new capabilities that occur as LLMs become larger.
As they do, so do the emergent abilities and the costs, which are now reaching astronomical figures. Just as the semiconductor industry has consolidated around a handful of companies able to afford the latest multi-billion-dollar chip fabrication plants, the AI field may soon be dominated by only the largest tech giants — and their partners — able to foot the bill for developing the latest foundation LLM models like GPT-4 and Claude 3.
The cost to train these latest models, which have capabilities that have matched and, in some cases, surpassed human-level performance, is skyrocketing. In fact, training costs associated with the most recent models approach $200 million, threatening to transform the industry landscape.
Source: https://ourworldindata.org/grapher/test-scores-ai-capabilities-relative-human-performance
If this exponential performance growth continues, not only will AI capabilities advance rapidly, but so will the exponential costs. Anthropic is among the leaders in building language models and chatbots. At least insofar as benchmark test results show, their flagship Claude 3 is arguably the current leader in performance. Like GPT-4, it is considered a foundation model that is pre-trained on a diverse and extensive range of data to develop a broad understanding o …
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Discover how companies are responsibly integrating AI in production. This invite-only event in SF will explore the intersection of technology and business. Find out how you can attend here.
During testing, a recently released large language model (LLM) appeared to recognize that it was being evaluated and commented on the relevance of the information it was processing. This led to speculation that this response could be an example of metacognition, an understanding of one’s own thought processes. While this recent LLM sparked conversation about AI’s potential for self-awareness, the true story lies in the model’s sheer power, providing an example of new capabilities that occur as LLMs become larger.
As they do, so do the emergent abilities and the costs, which are now reaching astronomical figures. Just as the semiconductor industry has consolidated around a handful of companies able to afford the latest multi-billion-dollar chip fabrication plants, the AI field may soon be dominated by only the largest tech giants — and their partners — able to foot the bill for developing the latest foundation LLM models like GPT-4 and Claude 3.
The cost to train these latest models, which have capabilities that have matched and, in some cases, surpassed human-level performance, is skyrocketing. In fact, training costs associated with the most recent models approach $200 million, threatening to transform the industry landscape.
Source: https://ourworldindata.org/grapher/test-scores-ai-capabilities-relative-human-performance
If this exponential performance growth continues, not only will AI capabilities advance rapidly, but so will the exponential costs. Anthropic is among the leaders in building language models and chatbots. At least insofar as benchmark test results show, their flagship Claude 3 is arguably the current leader in performance. Like GPT-4, it is considered a foundation model that is pre-trained on a diverse and extensive range of data to develop a broad understanding o …nnDiscussion:nn” ai_name=”RocketNews AI: ” start_sentence=”Can I tell you more about this article?” text_input_placeholder=”Type ‘Yes'”]