WendyLang: Bridging the Gap Between Natural Language Understanding and System Interaction
The emergence of sophisticated language models like GPT-4, an AI developed by OpenAI, represents a paradigm shift in user interface technology comparable to the advent of graphical user interfaces and mouse input systems. This next wave of technology — natural language understanding and reasoning — is creating a more fluid and intuitive link between humans and digital systems. However, like any revolutionary technology, there are a few hurdles that we need to overcome.
The Imperfect Link
The primary challenge is that although language models excel in understanding and generating human-like text, they are not yet proficient in directly communicating with software systems. While recent advancements in technology have enabled some degree of interaction via plugins, there are still significant limitations.
For instance, we can mention projects like AutoGPT and LangChain that use language models to logically solve problems step-by-step, parsing output to guide subsequent actions. While innovative, these projects often suffer from high latency due to the need to generate plans from scratch for each interaction. This latency can be disruptive and frustrating in everyday situations where quick, repetitive actions are required.
A Potential Solution: WendyLang
So, how do we address this issue? The answer might lie in a concept called WendyLang. The idea is to create an intermediate pseudo-language that is used to translate requests into actions, serving as a bridge between the language model and the digital system.
WendyLang’s pseudo-code syntax is designed to be safe, excluding risky commands and ensuring all variables are kept separate from the code. This not only prevents potential security risks but also makes WendyLang highly compatible with language models like GPT-4, which have been trained extensively on coding examples.
Moreover, WendyLang scripts are designed to be human-readable and reusable, meaning that successful parts of a script can be used as subparts for larger scripts. This encourages script optimization and efficiency and makes it easy for users to edit or write their scripts.
Enhancing Efficiency
To minimize latency and conserve resources, WendyLang is designed to remember successful scripts and use them as a routine the next time a similar request is made. Additionally, WendyLang can utilize idle times to “dream” — a process during which it attempts to optimize and organize memorized scripts for more efficient execution. It can also update routines if APIs or methods are changed.
In essence, WendyLang serves as a bridge, enabling language models like GPT-4 to interact directly with digital systems. This not only improves the efficiency of these systems but also greatly enhances their usability, leading to more intuitive and fluid human-computer interaction.
This ongoing evolution in natural language understanding and reasoning promises to transform the way we interact with digital systems, making them more accessible, intuitive, and efficient. As we continue to refine and improve upon these technologies, the once-imperfect link between humans and digital systems will become more seamless and integrated.
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WendyLang: Bridging the Gap Between Natural Language Understanding and System Interaction was originally published in Artificial Intelligence in Plain English on Medium, where people are continuing the conversation by highlighting and responding to this story.
https://ai.plainenglish.io/wendylang-bridging-the-gap-between-natural-language-understanding-and-system-interaction-f6985cd2b1a8?source=rss—-78d064101951—4
By: Sami Kalliokoski
Title: WendyLang: Bridging the Gap Between Natural Language Understanding and System Interaction
Sourced From: ai.plainenglish.io/wendylang-bridging-the-gap-between-natural-language-understanding-and-system-interaction-f6985cd2b1a8?source=rss—-78d064101951—4
Published Date: Fri, 16 Jun 2023 01:05:15 GMT
