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title: Best AI Security posts of 2024 | daily.dev
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# Best of AI Security — 2024

1. 1  
[](/posts/building-a-generative-ai-platform-ntdnnn6zj "Building A Generative AI Platform")  
Article  
![Avatar of huyenchip](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/ebf9e4841738434f9029c81815ce7b0c)Chip Huyen · 2y  
Building A Generative AI Platform  
The post details the construction of a generative AI platform, highlighting the common components such as context enhancement, guardrails, model routers, gateways, and caching techniques. It explores the complexities of context construction through retrieval-augmented generation (RAG) and the necessity of guardrails for input and output protection. The article also discusses the importance of adding routers and gateways for handling multiple models, optimizing for cost and latency, and ensuring security. Observability and orchestration principles for managing extensive AI application flows are also covered.  
129  
3
2. 2  
[](/posts/top-16-security-llm-tools-and-why-we-need-them-sgxh9difx "Top 16 Security LLM tools and why we need them")  
Article  
![Avatar of community](https://media.daily.dev/image/upload/t_logo,f_auto/v1655817725/logos/community)Community Picks · 2y  
Top 16 Security LLM tools and why we need them  
Explore the risks of using LLM models and discover top security tools for LLM applications. Acumen AI offers comprehensive security solutions for LLMs.  
26
3. 3  
[](/posts/why-llm-watermarking-will-never-work-lgcfajjhs "Why LLM watermarking will never work")  
Article  
![Avatar of medium_js](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/medium)Medium · 2y  
Why LLM watermarking will never work  
The post argues that watermarking, or the process of embedding detectable patterns in AI-generated text, is ineffective in distinguishing between AI-generated and human-generated content. It discusses three critical conditions that render watermarking ineffective: the existence of capable LLMs that don't implement watermarking, the allowance of user control over token selection, and the availability of open-source models. The author questions the true goals behind watermarking and suggests that focusing on detecting harmful content directly would be more effective in reducing AI-generated harms.  
16  
1

[See all AI Security archives](/tags/ai-security/best-of)

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