The past few years have shown an immense growth in the adoption of AI applications. What was once seen as experimental, is now a crucial part of day to day businesses.
Companies across all industries have started applying best of breed AI to automate processes, derive insights and make better decisions.
New AI platforms are not anymore useful to the select few versed in the subject, but are now being accessible to less trained users broadly. Low-code/No-code platforms give AI functionality at the hands of anyone, and open source projects lowers the bar of building new cutting edge technologies. As an example, the open source project GPT-3, and its variant DALL-E, which generates images from text descriptions, have shown how the most advanced technologies can become mainstream.
Simultaneously, a new supporting technological ecosystem is being created.
The development of AI hardware enables the continuous improvement and sustainability of performance over complex AI models and big data. MLOps practices allow reliable and efficient deployment of machine learning models in production. AI Governance and Security tools ensure responsible and secure use of AI. Many more technologies will emerge in order to supplement what is already a massively growing industry.