Continuous Learning Data Integration Generative AI 
JANUARY 28, 2025
Plot your path At their core, AI agents are generative AI language models wrapped around existing corporate functions, services, and databases, enabling natural language interaction with these components. The enterprises existing data, processes, and talent can serve as the foundation for AI agent implementation.
AWS Machine Learning Blog
OCTOBER 2, 2024
Large enterprises are building strategies to harness the power of generative AI across their organizations. Managing bias, intellectual property, prompt safety, and data integrity are critical considerations when deploying generative AI solutions at scale.
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AWS Machine Learning Blog
MARCH 18, 2025
Extraction of relevant data points for electronic health records (EHRs) and clinical trial databases. Data integration and reporting The extracted insights and recommendations are integrated into the relevant clinical trial management systems, EHRs, and reporting mechanisms.
AWS Machine Learning Blog
SEPTEMBER 28, 2023
In either case, as knowledge management becomes more complex, generative AI presents a game-changing opportunity for enterprises to connect people to the information they need to perform and innovate. To help tackle this challenge, Accenture collaborated with AWS to build an innovative generative AI solution called Knowledge Assist.
Unite.AI
JULY 15, 2024
One of the key advantages of decentralized AI in cybersecurity is tamper-proof data integrity. Blockchain technology ensures that once data is recorded on the ledger, it cannot be altered or deleted without the consensus of the network.
AWS Machine Learning Blog
MARCH 17, 2025
Healthcare agents can integrate LLM models and call external functions or APIs through a series of steps: natural language input processing , self-correction, chain of thought, function or API calling through an integration layer, data integration and processing, and persona adoption.
Unite.AI
JUNE 13, 2024
What inspired data.world to develop the AI Context Engine, and what specific challenges does it address for businesses? From the beginning, we knew a Knowledge Graph (KG) would be critical for advancing AI capabilities. A significant challenge in AI applications today is explainability.
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