In the rapidly evolving landscape of artificial intelligence, the year 2024 is poised to witness significant advancements in the realm of Generative AI.
Building upon the foundation laid in 2022 by groundbreaking models like DALL-E 2, GPT-3, and Stable Diffusion, Gen AI is set to become a transformative force, catalyzing breakthroughs in established AI approaches and unleashing a wave of innovation.
Here are some of the major areas where Gen AI will make a splash in the realm of Data & Analytics this coming year:
One of the key areas where Gen AI will shine in 2024 is in the generation of high-quality, labeled training data. This addresses a long-standing bottleneck for supervised learning algorithms that hunger for vast amounts of labeled datasets. Gen AI's ability to synthesize diverse content, including images, text, video, and audio, offers a solution to this problem. By providing abundantly available synthesized data, Gen AI enables traditional computer vision, natural language processing (NLP), and speech recognition models to rapidly enhance their accuracy. Furthermore, the integration of data augmentation techniques via generative adversarial networks (GANs) will significantly boost the performance of legacy AI models.
Download the Full Trends Report
In 2024, Gen AI is poised to have a major impact on predictive analytics. As generative models like GPT become more advanced, they will be able to synthesize large amounts of realistic data that can be used to train predictive models, thus improving accuracy. Generative AI will also enable more automated feature engineering, allowing predictive models to take into account more variables that are synthesized by the generative models. This will not only empower businesses to make data-driven decisions with a higher degree of confidence, but also positively impact cost savings, efficiency, and competitive advantage at an organizational level.
In 2024, we can expect to see the emergence of powerful hybrid AI solutions that combine the capabilities of generative models like GPT-3 with traditional machine learning (ML) algorithms such as logistic regression and support vector machines (SVMs). These hybrid models will leverage Gen AI's representations as trainable feature extractors, resulting in enhanced performance and flexibility. These capabilities will prove invaluable in various industries, where AI and expert systems play a critical role.
Real Use Case
SDG is actively working with both Snowflake and Dataiku to help our clients leverage hybrid AI solutions. One particularly noteworthy case is our work with a large, global pharmaceutical company. SDG helped our client scale for hybrid AI by developing ready-to-use data science models that recommend the most relevant actions for the pharma organization’s sales and marketing teams based on sales and transactions patterns (learn more about this with our Next Best Action Solution Accelerator). We also leveraged Snowflake and Dataiku to develop large language model proof of concepts for data analyst productivity tools.
As we look ahead to 2024, it's clear that Generative AI is on the cusp of revolutionizing the world of Data & Analytics. Its ability to synthesize data, enhance data quality, and drive predictive analytics will empower organizations to harness the full potential of their data resources. However, with great power comes great responsibility, and it will be crucial for businesses to navigate the ethical and security challenges that accompany these advancements. In the coming years, the synergy between human intelligence and Generative AI will drive innovation, accelerate discoveries, and usher in a new era of data-driven excellence.
Download the Full Trends Report