ChatGPT 與WolframAlpha整合運用(GPT-3.5 and Wolfram|Alpha via LangChain by James Weaver)

[MorrisWah]

最近，Google Brain 團隊討論了大腦被表示為一種演算法的概念。問題是我們是否會看到一個單一的黑盒子，從視覺到語言再到機器人都能做到，還是會有獨立的模型用於不同的提示或問題。不同的實驗室目前正在探索不同的方法來解決這個問題。

在人工智能領域中有一位顯著的玩家是斯蒂芬·沃爾夫拉姆博士(Dr. Stephen Wolfram)，他已經在這個領域工作了43年。他的引擎 Wolfram Alpha 是一個計算引擎，擅長用簡單的語言提供數學結果。它已經被實現在多個操作系統和應用程序中。

最近，沃爾夫拉姆博士寫了一篇博客，問了一個問題，那就是如果將計算知識庫 Wolfram Alpha 和聊天 GPT 相結合，會是什麼樣子。這個想法是，通過將ChatGPT連接到 Wolfram Alpha，它就能夠以更像人類的方式給出更精確的答案。

ChatGPT + WolframAlpha (GPT-3.5 and Wolfram|Alpha via LangChain by James Weaver)

Recently, the team at Google Brain discussed the concept of the brain represented as an algorithm. The question was whether we would see a monolithic black box that does everything from vision to language to robotics, or if we would have discrete pieces with different models for different prompts or questions. The different labs are currently exploring different ways of approaching this concept.

One notable player in the field of artificial intelligence is Dr. Stephen Wolfram, who has been working in the field for 43 years. His engine, Wolfram Alpha, is a computational engine that is good at providing math results in plain language. It has been implemented across multiple operating systems and applications.

Recently, Dr. Wolfram wrote a blog post asking the question of what it would look like if Wolfram Alpha, a computational knowledge base, was combined with ChatGPT, a large language model. The idea is that by connecting ChatGPT to Wolfram Alpha, it would be able to add the formality and precision when answering questions in a more human-like manner.

ChatGPT has made billions or trillions of connections between words, but it doesn't keep any of the original data and can't go back to look up a Wikipedia article. It works with natural language and is able to translate and answer questions based on what it has seen. On the other hand, Wolfram Alpha takes a question or computation, brings it into a linguistic understanding, and gives a symbolic representation before pulling out the structured data and computing an answer.

In summary, the combination of Wolfram Alpha and chat GPT has great practical potential as it combines the computational knowledge and precision of Wolfram Alpha with the natural language understanding and human-like responses of chat GPT. This would create a powerful tool that can provide precise and accurate answers to a wide range of questions.