As the great language models took the domain of artificial intelligence by storm, all the sci-fi movies grew up watching an entire generation, people speculated about an era ruled by robots, all the heated debates over the perspective of ethics. . All these points become more true as the ability of ChatGPT and now GPT4 amazed the whole world.
While users were still playing with chatGPT3, exploring the tip of the iceberg, OpenAI revealed GPT4 LLM, which can not only “read” the texts you input, but can also “see” and “understand” the images you feed it. Better trained, better powered in terms of data, and far better in terms of processing input data in one fell swoop, this marked the beginning of the race to build more AI-powered tools that can make a dent in the computing universe we know. . of as such
One such tool is Pico’s MetaGPT. This powerful no-code solution for building apps exceeds all expectations.
In a nutshell, this web service allows you to build other web applications without prerequisites of any coding language or indeed without any technical expertise.
Anything you can imagine, you can build. It simply asks you what you want to build, then asks for the prompts you want from the user, and then based on the prompt, what you want to do with it and what actions you want to perform. Once fed with this information, you can generate a web application for it. Pico claims that it can understand all of the world’s major languages, so language locality as a barrier to interaction with the app is gone forever. It generates the app they host for and a shareable URL to allow others to test what it’s built. We tested it here, and it seems pretty spot on.
MetaGPT is highly customizable, allowing you to iterate on any changes you want to incorporate. These iterations can be anything from a design change to a bug fix.
Users love this solution so far. The project is not only fascinating, but Pico’s MetaGPT is also solving a crucial problem: driving usage and research driven by the notion of proof of concept with the interaction of these LLMs, as the world knows the GPT plugin market of OpenAI as an attempt to build an extension marketplace powered by GPT engines, a business model quite similar to the Play Store or Apple Store we all use regularly. While this seems like a pretty lucrative solution, currently due to the hype of these models there is a long waiting list and very limited access for any general user which is kind of a setback for ML tech enthusiasts. /AI who want to investigate. the model to better understand its operation.
Developer community driven projects that took advantage of the slack of OpenAI to learn the implementation of GPT powered APIs in a better way have created some amazing projects like AutoGPT, which have accelerated the craze and diverted attention away from GPT LLM to projects that incorporate these LLMs in a better and more useful way.
The delay in the release of OpenAI’s GPT4 multimodal feature is creating an increasing space in this domain, adding to the research and development of such projects, improving applications based on current capabilities and broadening the horizon to introduce new use cases.
With GPT engines in play, communities engaged in rapid development, and a desire to be better, to “understand” and interpret a “use case” more efficiently, the line between artificial reality and real reality is blurring. reducing exponentially. Widespread knowledge of such technologies, and the buzz it creates, raises some concrete concerns about using such advanced models, but at the same time it instills an age-old human nature: curiosity. Curiosity to know how much further we can go and how much more we can achieve.
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Anant is a Computer Science Engineer currently working as a Data Scientist with a background in Finance and AI-as-a-Service products. He is interested in creating AI-powered solutions that create better data points and solve everyday problems in powerful and efficient ways.
