Generative artificial intelligence exploded into the public consciousness in 2022, and in 2023 AI began to take root in the business world. Now is the pivotal year for the future of AI, as researchers and enterprises seek to establish how this evolutionary leap in technology can bring the most impact to businesses that make up our everyday lives.

Generative AI has already reached its “hobbyist” phase, with last year seeing an increasing number of foundation models with open licenses. Enhanced with fine-tuning techniques and datasets developed by the open-source community, many open models can now outperform all but the most powerful closed-source models on most benchmarks, despite far smaller parameter counts.

Although the ever-expanding capabilities of state-of-the-art models will garner the most media attention, the most impactful developments may be those focused on finding the right business use cases, the ability to customize based on real business needs and the right governance that make generative AI more trustworthy, sustainable and accessible, for enterprises and end users alike.

Here are some important AI game changers to look out for as we approach mid-2024.

First, small(er) language models advancements.

In domain-specific models – particularly large language models (LLMs) – we’ve likely reached the point of diminishing returns from larger parameter counts. Massive models jumpstarted this ongoing AI golden age, but they are not without their drawbacks. Only the very largest companies have the funds and server space to train and maintain energy-hungry models with hundreds of billions of parameters.

According to one estimate from the University of Washington in the United States, training a single GPT-3-sized model requires the yearly electricity consumption of over 1,000 households; a standard day of ChatGPT queries rivals the daily energy consumption of 33,000 US households. Smaller models, meanwhile, are far less resource-intensive.