As big linguistic models have taken over the field of artificial intelligence, all the sci-fi movies of an entire generation that grew up watching them, people speculating about an era ruled by robots, all the heated debates about the perspective of morality. All of these points have been pushed into greater reality by the ability of ChatGPT and now GPT4 has surprised the entire world.
While users were still playing around with chatGPT3, exploring the tip of the iceberg, OpenAI unveiled a GPT4 LLM, which can not only “read” the text you enter, but also “see” and “understand” the images you give it. Better trained, better fed in terms of data, better ramified in terms of batch processing of input data, this marks the beginning of the race to build more AI-powered tools that can make a dent in the world of computation we perceive as such.
This tool is Pico’s MetaGPT. This powerful, no-code solution for building apps knocks all expectations out of the park.
Simply put, this web service allows you to create other web applications without any prerequisites for any coding language or, in fact, any technical expertise.
Whatever you imagine, you can build. It simply asks you what you want to develop, then it asks you what prompts you want to get from the user, and then depending on the router, what you want to do with it, and what actions you want to take. Once fed this information, it can produce a web application for itself. Pico claims it can understand all major languages in the world, so local language as a barrier to interacting with the app is gone forever. It generates the app they’re hosting for and a shareable URL to let others try out what you’ve built. We’ve tried it here, and it seems to be on point.
MetaGPT is highly customizable, allowing you to replicate any changes you wish to include. These iterations can be anything from a design change to a bug fix.
Users love this solution so far. Not only is the project cool, but Pico’s MetaGPT also solves a critical problem: fueling use and research driven by proof-of-concept with LLMs interacting as the world perceives OpenAI’s GPT plug-in market as an attempt to build a plugin market powered by GPT engines, a business model quite similar to a store Games or Apple Store which we all use regularly. While this seems like a fairly win-win solution, at the moment, given the hype of these models, there is a long waiting list and very limited access for any general user, which is a bit of a setback for ML/AI enthusiasts who want to poke. model to better understand its performance.
Developer-led projects that have taken up the slack in OpenAI to learn to deploy GPT-enabled APIs in a better way have led to the creation of some amazing projects like AutoGPT, which have accelerated the craze and shifted attention from GPT LLMs to such projects that integrate these MAS in a better and useful way .
The delay in launching OpenAI’s multimedia GPT4 feature is creating an increasingly large space in this area, adding to the R&D for such projects, enhancing applications built on existing capabilities and broadening the horizon by offering new use cases.
With GPT engines running, communities engaged in rapid development, and the desire to be better, to “understand” and to interpret the “use case” more efficiently, the line between artificial reality and actual reality is blurring dramatically. The widespread awareness of such technologies, and the hype they create, raises some tangible concerns about the use of such advanced models, but at the same time it instills an ancient human nature, which is curiosity. Curiosity to see how far we can go and how much we can achieve.
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Data Scientist currently working for S&P Global Market Intelligence. He has worked as a data scientist for emerging AI product companies. Reader and learner at heart.
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