With Wolfram Alpha ChatGPT plugins are reaching another level. Imagine a platform that can respond in a manner similar to a human, like ChatGPT, but also has access to Wolfram Alpha’s “computational superpower,” which enables you to make accurate calculations that are beyond the scope of human capacity.
Due of ChatGPT’s capacity to produce responses that appear to be accurate for various contexts—including essays, mock interviews for jobs, blog posts, etc.—it has been the talk of the town for a time. But, when we employ it more, we become aware of its limitations. In this situation, Wolfram Alpha is useful.
Not every “useful” work is truly “human-like,” as Wolfram Alpha’s founder and CEO Stephen Wolfram argues. Actually, performing computations that are beyond the capabilities of humans was the main reason why computers were created in the first place. And Alpha excels in that area.
The ways in which with Wolfram Alpha ChatGPT plugins reach another level
In case you didn’t know, neither AI model is flawless. Although ChatGPT may be able to mislead some grandmothers into thinking it is a real person, it frequently fails when it comes to calculations. Also, it makes a lot of “guesses,” which makes it inappropriate for rigorous investigation.
It won’t be able to answer questions about recent events (because there is no Internet connection), hard facts, or even simple math problems.
Because of this, you can’t rely on ChatGPT for accurate responses.
In contrast to ChatGPT, Wolfram Alpha may have trouble grasping the subtleties of a user’s query and the motivation behind it, despite its superior computational powers. Let’s investigate what makes them unique.
AI systems can be created using either a statistical or symbolic method.
When it is trained on a big corpus of text and learns the correlations and patterns between words and phrases, ChatGPT employs a statistical approach to produce responses that resemble those of a human.
On the other hand, Wolfram Alpha takes a symbolic approach. It is a knowledge-based system that does calculations and provides answers to queries by using a set of rules, logic, and knowledge representations.
In contrast to ChatGPT, Wolfram has its own calculation language that can formalize symbolic representations of as many real-world variables as feasible. You can ask it to answer any fact-based inquiry, including ones involving mathematic calculations, data analysis, and the provision of factual data on the climate, geography, and economy.
This advantage, however, extends beyond people as Alpha has the potential to significantly improve other AI models.
The two models can complement one another and work better as a system if we combine Wolfram Alpha ChatGPT plugin. Wolfram Alpha can leverage its knowledge to provide exact, symbolic computational language, whereas ChatGPT can produce writing that resembles what a human would write. As a result, the user can ask inquiries in everyday language and receive precise responses based on actual data.
The results produced by Wolfram Alpha can also be explained in natural language using ChatGPT.
Wolfram stirs up interest
Recently, Wolfram Alpha and ChatGPT were proposed to be combined by Stephen Wolfram, sparking curiosity. Although he withheld any specifics, his blog post made us ponder whether the Wolfram Research team is covertly developing something ground-breaking. Additionally, he aggressively encourages programmers to come up with their own suggestions for fusing the two language paradigms.
James Weaver, IBM’s advocate for quantum computing, meanwhile, took matters into his own hands and assembled a group of programmers to construct his own rendition of this merger. Although it’s not exactly what Stephen had in mind, he names it ChatGPT-LangChain and it closely resembles what Stephen had in mind.
LangChain develops a solution that combines both Alpha and GPT 3.5 rather than teaching ChatGPT to function with Alpha (the technology that ChatGPT is built on). Depending on the user’s query, the system makes an API call to either Alpha or GPT 3.5.
It will make an API call to Alpha if the query is one that is better suited for a computational model (needs precise data or calculations). However, if the query calls for more creativity and less precision, GPT 3.5 will be called via an API.
Consider it as giving distinct brain regions the freedom to carry out specially designed jobs. While Weaver’s concept is straightforward and useful, a more polished version is probably going to be made available in the coming months as more people realize the benefits of a more comprehensive AI chatbot.
There are other plugins than the Wolfram Alpha ChatGPT plugin that can serve you for different purposes while enabling ChatGPT to receive data from the internet and present factual, up-to-date data. We explained the new plugins in another article if you want to check out: OpenAI ChatGPT plugins connect the chatbot to the internet
