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TDWI Upside - Where Data Means Business

Building an AI Strategy with Caroline Carruthers

Before jumping into AI, it’s important to have a strategy. You need to know what problem you are trying to solve, where you are now, and where you want to go. The CEO of global data consultancy Carruthers and Jackson explains what’s involved in building this strategy and where AI -- not just generative AI -- is headed.

Q&A: Can Neuro-Symbolic AI Solve AI’s Weaknesses?

Neuro-symbolic AI integrates several technologies to let enterprises efficiently solve complex problems and queries demanding reasoning skills despite having limited data. Dr. Jans Aasman, CEO of Franz, Inc., explains the benefits, downsides, and use cases of neuro-symbolic AI as well as how to know it’s time to consider the technology for your enterprise.

The Next Thing to Look For in AI Vendors: Interoperation

AI vendors that interoperate and partner well should significantly outperform their competitors.

How RAG Will Usher In the Next Generation of LLMs and Generative AI

Retrieval-augmented generation may provide a big step forward in addressing many of the issues that keep enterprises from adopting AI.

Data Stories: Functions and Risks of Generative AI

How large language models work, fake AI charts, and bias in the model.

Data Digest: Mitigating AI Risks

New EU regulations for AI, tactics for addressing biased AI, and the need for better data quality for AI systems.

Can Synthetic Data Jumpstart Your Strategic Projects?

Don’t let sparse data derail your analytics projects. Synthetic data can fill the gaps, but choosing the right generation method is key. Explore rule-based, statistical, and GAN approaches -- with their benefits and trade-offs.

Data Digest: Industries Applying AI Today

AI and generative AI applications in the legal, healthcare, and automotive industries.

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