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The Future of Large Language Models: Introducing OpenAI's "o1" Series 🚀
As a tech enthusiast, I'm excited to share with you the latest development in the world of Large Language Models (LLMs). Yesterday, OpenAI, the company behind
ChatGPT, released a new series of "Thinking" models called "o1". In this article, we'll delve into what these models can do and why they're a game-changer for
the future of LLMs.
The Limitations of Traditional LLMs 🤔
Traditional LLMs work by generating the most probable next token based on the input. This straightforward principle allows them to provide decent results, but
it's not without its limitations. For instance, when faced with complex questions or tasks, these models often struggle to provide accurate answers.
One classic example is the question "How many R letters in the word 'strawberry'?" 🤔 Traditional LLMs would typically answer 2, which is incorrect. To solve
this type of question, more advanced techniques such as a "Chain of Thoughts" are required.
Introducing OpenAI's "o1" Series 🔥
The "o1" series models address these limitations by introducing "reasoning" tokens that are truncated from the output. This allows them to iterate over the
answer multiple times until they provide a well-thought-out response. The result is more accurate and contextually relevant answers.
Two distinct models are available: o1-preview and o1-mini. If you're using the API, these models can be accessed as part of your workflow.
Pricing 💸
While the "o1" series is a significant upgrade over traditional LLMs, it comes at a price. The cost for using these models is higher than their predecessors:
- $15.00 per 1 million input tokens and $60.00 per 1 million output tokens for
o1-preview - $3.00 and $12.00 for
o1-minimodel
However, OpenAI plans to release the "o1" series for free ChatGPT users in the near future.
What's Next? 🔮
The "o1" series is not a replacement for traditional LLMs but rather an addition that solves more complex tasks. In the world of Wiregate, we firmly believe that
such models will eventually replace all other simple models.
What are your thoughts on the future of Large Language Models? Share your opinions in the comments below! 💬
Want to learn more about this topic? 🔍
- Check out our blog for more tech-related news and articles (https://blog.wiregate.io)
- Visit OpenAI's website for more information on the "o1" series:
Stay tuned for more updates on this topic! 🚀
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