In 2022, we experienced a great leap forward in AI technology with Generative AI.
Products like ChatGPT and GitHub Copilot (AI code generator), as well as the underlying foundation models that power such systems (Stable Diffusion, DALL·E 2, GPT-3, to name a few), are taking technology into realms once thought to be reserved for humans. With generative AI computers can now arguably exhibit a form of creativity. We believe the best is still to come, and in 2023 we will see a new wave of applications using Generative AI rapidly emerge. Already analysts are predicting that the industry will balloon to become a $110 billion industry by 2030.
Notable Efficiencies Observed:
1. Cost Efficiencies: Just as the internet brought marginal cost of distribution down to zero, Generative Pre-Trained Transformer (GPT) Models have brought the cost of content creation down to zero.
Previously machine learning algorithms used in mainstream products were mostly called “discriminative”, meaning they could discriminate between various types of data. In these cases, new data isn’t being created – the outputs from the AI are strictly limited by the training and input data. The profound state change with generative AI is that these models can create data and content in the form of coherent and novel outputs.
2. Productivity Efficiencies: Until now, software couldn’t solve the zero to one problem because it worked FOR us. Generative Tech will work WITH us from the beginning of any project. – James Currier, Nfx (venture capital firm)
Much like the platform shifts and step-changes in productivity that occurred with personal computing, mobile and the cloud, we are transitioning into the “Age of Augmentation”, bringing forth a whole new world of automation possibilities across every sector and industry, where humans are assisted by machines in almost every task.
In the coming decade, we expect software to collaborate with us. It will be the new normal.
One of the most profound augmentations is the ability to write code. Importantly, the power of these capabilities is now accessible to all, including developers who lack specialized machine learning skills and, in some cases people with no technical background through the advent of low code/no code tooling. Leveraging these foundation models can also reduce the time for developing new AI applications to a level not previously seen. The CEO of Replit, a collaborative tool and AI code generator for software development and emerging unicorn, offers a glimpse into a potential future state enabled by these advancements.
With the orders of magnitude efficiencies that can be unlocked – Defined is focused on companies that embrace these changes as they will be best positioned to succeed.
In Part 2 to follow next week, we’ll explore how AI is being leveraged to build the next-generation of software applications.