The Dawn of the AI Era: Expectations vs Reality
In the final quarter of 2022, the digital world was taken by storm with the advent of Open-Ai’s Chat-GPT, a generative AI tool that promised to revolutionise our work processes. Chat-GPT, amassed a staggering 100 million users within 2 months its launch, riding high on the wave of anticipation and excitement. The hype continued through Q2 of 2023 with the unveiling of GPT-4, an upgrade to GPT 3.5, a large language model that was expected to automate our mundane tasks and make life easier. But as is often the case the reality has so far fallen short of the hype.
Generative AIs, despite their impressive capabilities and potential, have not yet become an integral part of our personal and business lives. The reason? They lack the accessibility and practical applications needed for everyday use, especially for non-programmers or those not well-versed in IT. However, the landscape is changing rapidly, thanks to the open-source community and their relentless efforts to make these tools more user-friendly and versatile.
Promising AI Open-Source Projects
Two of the most promising developments in this direction are LangChain and Auto-GPT. LangChain is a software development framework that simplifies the creation of applications using large language models (LLMs). It allows LLMs to interact with their environment, enhancing their use cases by connecting to the internet, accessing company-specific documentation, and enabling read/write operations via APIs. Auto-GPT, on the other hand, is an application that uses OpenAI’s chatbots (GPT-4 and GPT-3.5) autonomously. Users can input a persona for the AI and set up to five goals, which the AI then works towards achieving through actions like web searches, file writing, and more.
Despite their promise, these applications remain niche and require a high level of technical proficiency to operate. Additionally, business IT policies often restrict the installation and use of new applications without permission, further hindering the adoption of these emerging technologies.
Summing Up
In conclusion, while the hype around AI in the past six months led many to believe we’d be living in a world of automation by now, the reality is that we’re still not in the AI era. The ‘future is near, but not yet’. While we await the next big breakthrough, it’s crucial for business leaders to start thinking about potential automation areas and the workflow of these tasks. This will position business to rapidly adopt AI software when accessible products come to mass market.
