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Challenges & Opportunities: Small Language Models

Top challenges and insights from tech leaders developing small language models (SLMs).

Executive Summary

We surveyed 500+ tech leaders across industries about their language-based AI projects. Learn how organizations like yours are achieving precision, reducing costs, and overcoming common hurdles with tailored AI applications.

1

The State of AI Deployment

Learn how SLMs can be a cost-effective, scalable alternative to larger AI models, with practical advice for training, data preparation, and deploying them effectively.

2

Expert Insights from Tech Leaders

Understand how 500+ tech leaders across industries are approaching AI adoption and get benchmarks to evaluate your organization's progress.

3

Actionable Insights for AI Deployment

Learn how top tech leaders are tackling the key challenges of deploying AI, including cost optimization, fine-tuning models, and navigating budget constraints.

4

Takeaways and Conclusions

AI teams are prioritizing data quality, operational agility, resilient infrastructures, and compliance.

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Are SLMs Right for Your AI Use Case?

Read the report to learn more.

Are SLMs Right for Your AI Use Case?

Read the report to learn more.

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