Alaa Moussawi, chief data scientist at New York City Council, emphasizes the importance of organizations developing their own generative AI systems using open-source tools like DeepSeek and Llama. Speaking at the Leap 2025 tech event in Saudi Arabia, he highlighted the minimal costs associated with testing and deploying AI technologies. Moussawi shared insights from the council's first AI project in 2018, aimed at enhancing the legislative process through evidence-driven methods.
The council's initial AI application, a duplicate checker for legislation, was designed to streamline the legislative process by ensuring originality in proposed laws. Moussawi advocates for organizations to engage with generative AI, stressing that the underlying algorithms are not secretive and can be efficiently utilized with open-source models. He encourages others to experiment with local implementations of these technologies to improve their operations.
• NYC Council promotes DIY AI using open-source tools for legislative efficiency.
• Generative AI can be developed with minimal costs and resources.
Generative AI refers to systems that can create content or data based on input, enhancing productivity.
RAG combines retrieval of relevant documents with generative models to improve output accuracy and reduce errors.
Vector embedding is a technique that represents words as numerical vectors in high-dimensional space, facilitating similarity checks.
The council utilizes AI to enhance legislative processes and ensure originality in proposed laws.
DeepSeek is an open-source tool recommended for building generative AI applications in various organizations.
Llama is another open-source model that organizations can use to develop their own AI solutions.
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