As the cybersecurity industry continues to push artificial intelligence (AI), practitioners race to keep up with businesses’ explosive adoption rates. Security is seeking to maintain the delicate balance between being a business enabler, implementing sound governance, and empowering businesses to make risk-informed decisions around technology use and integration.
Luckily, several resources are coming from industry leaders such as the Cloud Security Alliance (CSA), Open Web Application Security Project (OWASP), and now Databricks regarding AI security. In this analysis, I will take a high-level look at Databricks’ recently released whitepaper, the Databricks AI Security Framework (DASF), and explain its key takeaways for cybersecurity professionals.
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Model Types
The paper opens by defining the three broad types of models used in AI: predictive machine learning (ML) models, state-of-the-art open models, and external models. Predictive models include PyTorch and HuggingFace and state-of-the-art open models include Llama-2-70b-chat. State-of-the-art open models are foundational to large language models (LLMs) and used for…
