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Narrowing the confidence gap for wider AI adoption

AI News

Avi Perez, CTO of Pyramid Analytics, explained that his business intelligence software’s AI infrastructure was deliberately built to keep data away from the LLM , sharing only metadata that describes the problem and interfacing with the LLM as the best way for locally-hosted engines to run analysis.”There’s

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Achieve your AI goals with an open data lakehouse approach

IBM Journey to AI blog

Also, a lakehouse can introduce definitional metadata to ensure clarity and consistency, which enables more trustworthy, governed data. All of this supports the use of AI. And AI, both supervised and unsupervised machine learning, is often the best or sometimes only way to unlock these new big data insights at scale.

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Introducing watsonx: The future of AI for business

IBM Journey to AI blog

1] Users can access data through a single point of entry, with a shared metadata layer across clouds and on-premises environments. It empowers businesses to automate and consolidate multiple tools, applications and platforms while documenting the origin of datasets, models, associated metadata and pipelines.

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Build agentic systems with CrewAI and Amazon Bedrock

Flipboard

With deep expertise in generative AI and enterprise solutions, Joo partners with global leaders like AWS, NVIDIA, IBM, and Meta AI to drive innovative AI strategies. Joo (Joe) Moura is the Founder and CEO of CrewAI, the leading agent orchestration platform powering multi-agent automations at scale.

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Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access. Later this year, it will leverage watsonx.ai foundation models to help users discover, augment, and enrich data with natural language.

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3 key reasons why your organization needs Responsible AI

IBM Journey to AI blog

The True Cost of Noncompliance Responsible AI requires governance Despite good intentions and evolving technologies, achieving responsible AI can be challenging. AI requires AI governance , not after the fact but baked into AI strategy of your organization. So what is AI governance?

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Ugur Tigli, Chief Technical Officer at MinIO – Interview Series

Unite.AI

It really starts with understanding what you need – don’t go out and buy expensive GPUs just because you’re afraid you’ll miss out on the AI boat. I strongly believe that enterprise AI strategies will fail in 2024 if organizations focus only on the models themselves and not on data.