Our CTO's 2024 predictions: Three big things for gen AI

Each new year brings with it opportunities for reflection and change. With the huge shift gen AI has brought to the enterprise, global culture, and the wider world, now is a great moment to consider what it will take to make the most of AI in your organization.

Fortunately, we have one of the most sage technology leaders in Will Grannis , Google Cloud’s CTO, here to share his predictions for what it takes to make the most of gen AI this year, and how to do it it safely, securely, sustainably, and creatively.

For organizations everywhere, the AI excitement of 2023 is quickly giving way to something more interesting and useful: AI-enabled business results that matter. The reasons include recent advances in AI capabilities across the computing stack that allow organizations in any industry, geography, or phase of growth to access potential normally reserved for the few. With a lot of people working with these new capabilities, expect a lot of innovation and results.

Families of models like Google's Gemini are the strongest expressions yet of generative AI's initial breakthrough, enabling people and devices to interact in natural human language. Computers guided by human prompting synthesize unimaginable amounts of data to digest information, make predictions, assist with tasks, or create novel content, from text-to-images to new computer code. Gemini takes things further than ever as the world’s first native multimodal model.

Before, you needed separate models to make sense of text, audio, code, images, mathematics, or video. Gemini can handle all of these all at once, much like the way humans simultaneously read, speak, and observe the world around them as they collaborate.

After the "wow" moments in 2023, many enterprises face the question, "What does it mean for our business, and what does it cost?" As Google Cloud’s chief technology officer , my work puts me in a fortunate position to understand where the technology is going (the convergence of AI assistants, platforms, and infrastructure), and how some of the world's preeminent organizations are already leveraging it. Broadly, I see three key pillars that will impact how companies understand, deploy and use gen AI in 2024: economics and energy, ubiquity and access, and trust and security.

Economics and energy

The viability of gen AI in an enterprise often centers on key costs, in both financial and increasingly in environmental terms. Disciplined execution satisfies both the financial life of the business and the growing importance of adhering to regulation and corporate citizenship.

Gen AI uses immense computation, with cost and social challenges around energy use. Customers will require knowledge of how energy is managed for data centers and the flexibility to optimize production using the cleanest possible regions and zones. It will likely affect the practice of writing software and may employ carbon budgeting as part of the developer practice. Our customers want us to continue our significant sustainability efforts , and it’s a safe bet that sustainable gen AI will rise in demand and importance in 2024.

The large language models, or LLMs , that power gen AI require efficient training, fine tuning, inference, and life cycle management. Cost curves demand focused and principled execution, particularly as projects scale up. That's one reason why we've built an optimized AI infrastructure to power Vertex , our flagship AI platform.

Google incorporated AI into search in 2015 . Experiencing this AI scale-out challenge first-hand — and knowing that historically, 50% or more of software costs are maintenance, including refinement — made efficiency an early priority for us. So we developed Tensor Processing Units (TPUs), which are specialized chips that handle AI workloads, including gen AI, at a sharply lower cost and better energy use . Being great stewards of scarce customer investment dollars and a finite global energy supply are non-negotiable priorities for all modern organizations.

Ubiquity and access

For many, the first experience with gen AI will be in products like a tool for transforming old databases into new and more powerful products, an assistant to help manage your working life, or a bot offering high-quality answers to medical questions. These all rest on a new computing paradigm that uses more data, from more sources, in more flexible ways. The information in hospital billing, for example, might be aggregated to spot national health trends or repurposed to track how long it takes to deliver services in different locations, spotting nursing shortages.

Continue reading on Transform with Google Cloud to find out more about the second and third pillars of gen AI success.