Securing_Generative_AI_in_the_Enteprise.pdf

Google Categorizes 6 Real-World AI Attacks to Prepare for Now

Researchers Give Birth to the First GenAI Worm

Valoir Study of AI and Ux

Retail Roadblock: Lack of Data Strategy Stands in the Way of Generative AI Progress

kl3m.ai - the cleanest LLM in the world

Non-profit Fairly Trained certifies an AI large language model as free of copyright infringement, in a blow to a key claim of AI firms

WIPO - getting-the-innovation-ecosystem-ready-for-ai.pdf

WIPO - generative-ai-navigating-intellectual-property.pdf

Mayo Clinic’s Healthy Model for AI Success

Many Americans think generative AI programs should credit the sources they rely on

Accenture - Human By Design

Andreessen Horowitz - 16 Changes to the Way Enterprises Are Building and Buying Generative AI

AI Risk Management Framework | NIST

NTT Data, IFTF

<aside> 💡 “Ask AI To Write” Prompt: ’boiling it all down, what are the key starting point recommendations to begin the readying the enterprise for genAI?’

1. Establish a dedicated team to understand and implement Generative AI technologies.
2. Regularly update and educate all stakeholders about the potential and risks of Generative AI.
3. Invest in the necessary infrastructure and tools that can support Generative AI.
4. Identify and understand the legal and ethical considerations related to Generative AI.
5. Partner with AI firms or consultancies to gain expertise and insights into Generative AI.
6. Implement a robust data strategy to support the functioning of Generative AI.
7. Prioritize security measures and develop a plan to prevent potential Generative AI attacks.
8. Integrate Generative AI into the existing innovation ecosystem of the enterprise.
9. Develop a risk management framework to deal with possible issues related to Generative AI.
10. Ensure the AI models used are free of copyright infringement.

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<aside> 💡 “Ask AI To Write” Prompt: ’what are the top 5 risks?’

1. Data Privacy and Security: "Generative AI models have the potential to compromise data security, and this risk is a major concern for enterprises." - NIST
2. Ethical and Legal Considerations: "The use of AI comes with various ethical and legal considerations that enterprises must understand and navigate." - Andreessen Horowitz
3. Lack of Expertise: "Implementing AI technologies requires a certain level of expertise that many enterprises may lack." - Google
4. Infrastructure and Tools: "Investing in the necessary infrastructure and tools to support Generative AI is a challenge for many enterprises." - Mayo Clinic
5. Risk Management: "Enterprises need to develop a robust risk management framework to deal with potential issues related to Generative AI." - Accenture </aside>