Remove Data Engineering Remove Examples Remove Off-The-Shelf
article thumbnail

How AI orchestration has become more important than the models themselves

CIO

As many companies that have already adopted off-the-shelf GenAI models have found, getting these generic LLMs to work for highly specialized workflows requires a great deal of customization and integration of company-specific data. million on inference, grounding, and data integration for just proof-of-concept AI projects.

article thumbnail

When is data too clean to be useful for enterprise AI?

CIO

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Data 211
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Giving more tools to software engineers: the reorganization of the factory

Erik Bernhardsson

I had my first job as a software engineer in 1999, and in the last two decades I've seen software engineering changing in ways that have made us orders of magnitude more productive. These are just examples — I could go on all day. It's a popular attitude among developers to rant about our tools and how broken things are.

article thumbnail

Interpreting predictive models with Skater: Unboxing model opacity

O'Reilly Media - Data

Data Scientist Cathy O’Neil has recently written an entire book filled with examples of poor interpretability as a dire warning of the potential social carnage from misunderstood models—e.g., There is also a trade off in balancing a model’s interpretability and its performance.

article thumbnail

Generative AI is a make-or-break moment for CIOs

CIO

And, in fact, McKinsey research argues the future could indeed be dazzling, with gen AI improving productivity in customer support by up to 40%, in software engineering by 20% to 30%, and in marketing by 10%. It does not allow for integration of proprietary data and offers the fewest privacy and IP protections.

article thumbnail

7 data trends on our radar

O'Reilly Media - Ideas

Whether you’re a business leader or a practitioner, here are key data trends to watch and explore in the months ahead. Increasing focus on building data culture, organization, and training. The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated.

Trends 109
article thumbnail

Build your gen AI–based text-to-SQL application using RAG, powered by Amazon Bedrock (Claude 3 Sonnet and Amazon Titan for embedding)

AWS Machine Learning - AI

However, off-the-shelf LLMs cant be used without some modification. RAG is a framework for building generative AI applications that can make use of enterprise data sources and vector databases to overcome knowledge limitations. This can be overwhelming for nontechnical users who lack proficiency in SQL.