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LLM Defense Strategies

Becoming Human

An ideal defense strategy should make the LLM safe against the unsafe inputs without making it over-defensive on the safe inputs. Figure 1: An ideal defense strategy (bottom) should make the LLM safe against the ‘unsafe prompts’ without making it over-defensive on the ‘safe prompts’. and 45.2%, respectively.

LLM 111
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Scale AI Launches Defense Solution to Take Critical Decisions in Minutes Instead of Weeks

Analytics Vidhya

The defense industry is no different, and making the right decisions quickly can often be a matter of life and death. Every second counts today, and making timely decisions is essential. This is where Scale AI comes in.

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Machine Learning: Adversarial Attacks and Defense

Analytics Vidhya

The post Machine Learning: Adversarial Attacks and Defense appeared first on Analytics Vidhya.

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Leveraging CISA Known Exploited Vulnerabilities: Why attack surface vulnerability validation is your strongest defense 

IBM Journey to AI blog

This allows teams to understand the real risk facing their organization while simultaneously assessing if the investments they have made in security defense solutions are worthwhile. The compensating controls they have put in place are effective at detecting and blocking breaches. The costs increased by 15% over the last three years to USD 4.45

Algorithm 191
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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Putting the right LLMOps process in place today will pay dividends tomorrow, enabling you to leverage the part of AI that constitutes your IP – your data – to build a defensible AI strategy for the future.

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Delivering security and scalability in today’s business landscape requires more than setting up a front line of defense

IBM Journey to AI blog

Learn more about IBM Hyper Protect Crypto Services The post Delivering security and scalability in today’s business landscape requires more than setting up a front line of defense appeared first on IBM Blog.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning Blog

Lastly, we connect these together with an example LLM workload to describe an approach towards architecting with defense-in-depth security across trust boundaries. Defense-in-depth security best practices mitigate many of the common risks that any workload faces, helping you and your teams accelerate your generative AI innovation.