A look ahead at the fast-paced evolution of technology, regulation and business A look ahead at the fast-paced evolution of technology, regulation and business Moments like this don’t come around often. The coming years will see outsized investment Figure 1: Each layer of the generative AI tech stack will rapidly evolve in generative AI, LLMs and foundation models. What’s unique about this evolution is that the technology, regulation, and business adoption Applications: Generative AI and LLMs will be increasingly are all accelerating exponentially at the same accessible to users in the cloud via APIs and by being embedded time. In previous innovation curves, the directly into other applications. Companies will consume them technology typically outpaced both adoption as they are or will customize and fine-tune them with proprietary and regulation. data. The technology stack Fine-tuning: The importance of model fine-tuning will create demand for a multidisciplinary set of skills spanning software The complex technology underpinning engineering, psychology, linguistics, art history, literature and generative AI is expected to evolve rapidly library science. at each layer. This has broad business Foundation models: The market will rapidly mature and diversify implications. Consider that the amount of as more pre-trained models emerge. New model designs will compute needed to train the largest AI models offer more choices for balancing size, transparency, versatility and has grown exponentially – now doubling performance. between every 3.4 to 10 months, according to 8 Data: Improving the maturity of the enterprise data lifecycle various reports. Cost and carbon emissions are therefore central considerations in will become a prerequisite for success – requiring mastery of adopting energy-intensive generative AI. new data, new data types and immense volumes. Generative AI features within modern data platforms will emerge, enhancing adoption at scale. Infrastructure: Cloud infrastructure will be essential for deploying generative AI while managing costs and carbon emissions. Data centers will need retrofitting. New chipset architectures, hardware innovations, and efficient algorithms will also play a critical role. A new era of generative AI for everyone | 9