As we close out 2024, we're pleased to share that our predictions from last December proved remarkably prescient in capturing the key developments that shaped the AI landscape this year.

The emergence of powerful multimodal foundation models became a defining trend, with major platforms integrating sophisticated vision and speech capabilities. We also correctly anticipated the rise of smaller, more efficient models as organizations sought to balance capability with computational constraints amid ongoing GPU shortages.

Our forecast about AI agents proved particularly accurate – we've seen an explosion of AI copilots and intelligent assistants across applications and browsers, fundamentally changing how users interact with technology. The push toward enhanced reasoning capabilities in large language models has also materialized, with several breakthrough developments in complex problem-solving and logical analysis.

The AI hardware landscape evolved exactly as predicted, with intensified competition among traditional chip manufacturers and innovative newcomers. Meanwhile, our projection about sovereign and industry-specific clouds gained momentum as organizations prioritized data governance and regulatory compliance.

Here is again a list of our 2024 predictions:

1. All large foundation models will become multi-modal, incorporating vision and speech capabilities.

2. Smaller language models optimized for efficiency will gain adoption, especially as GPU shortage persists.

3. AI agents like chatbots and digital assistants will disrupt more use cases - from copilots in applications to intelligent browser companions.

4. Reasoning capabilities will be the next frontier as large models move to deeper understanding required for complex reasoning.

5. As models grow in size, so too will their context windows.

6. Competition will intensify around AI chips among giants like NVIDIA, AMD, and Intel, alongside innovative startups introducing new specialized hardware.

7. With growing data regulation, we’ll see increased sovereign clouds and industry clouds tailored for AI verticalized workloads.

8. The hype around emerging areas like general AI will give way to more measured, use-case-driven development aligned with business needs.

9. As enterprise AI projects progress from POC to production, machine learning operations (MLOps) will gain momentum to scale AI in business.

10 . Societal considerations around AI ethics, governance, and safety will remain top discussion items next year.

We're particularly satisfied with our prediction about the shift from general AI hype to practical, business-focused applications. The growing emphasis on MLOps has indeed become crucial as enterprises move from experimentation to production deployment.

Looking back, these predictions reflected our deep understanding of the AI ecosystem's trajectory. As we venture into 2025, we remain committed to sharing insights that help organizations navigate the exciting future of AI technology.

Stay tuned for our 2025 predictions!