IBM Journey to AI blog

MAY 9, 2023

Indeed, the more AI is embedded into daily workflows, the more you need proactive governance to drive responsible, ethical decision-making across the business. Watsonx.governance can help build the necessary guardrails around AI tools and the uses of AI.

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NVIDIA

NOVEMBER 25, 2024

AI is changing industries and economies worldwide. Workforce development is central to ensuring the changes benefit all of us, as Louis Stewart, head of strategic initiatives for NVIDIA’s global developer ecosystem, explains in the latest AI Podcast. “AI AI is fueling a lot of change in all ecosystems right now,” Stewart said.

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Unite.AI

OCTOBER 25, 2024

With these capabilities, the DA platform ensures that organizations can achieve faster, more accurate decision-making and optimize strategies for improved business outcomes. Can you elaborate on how the Quote AI tool improves quoting processes for businesses? GDPR, CCPA) and industry regulations (e.g.,

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Unite.AI

JUNE 14, 2024

His work, most recently on the Scopus AI project at Elsevier, underscores his commitment to redefining the boundaries of how we engage with information and create a trusted relationship with users. How have your experiences at companies like Comcast, Elsevier, and Microsoft influenced your approach to integrating AI and search technologies?

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IBM Journey to AI blog

FEBRUARY 23, 2024

If a query surpasses the bot’s capabilities, these AI systems can route the issue to live agents who are better equipped to handle intricate, nuanced customer interactions. However, there are also potential challenges and limitations to consider: Data bias : AI models rely on data provided by humans, which can be biased in various ways.

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Unite.AI

JUNE 17, 2024

By cultivating these three competencies, individuals can navigate the AI era with confidence and create their own irreplaceable value proposition. How can organizations ensure that AI tools are augmenting rather than replacing human workers? Another critical factor is to involve employees in the AI implementation process.

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Kavita Ganesan

FEBRUARY 28, 2023

EXPLAINABILITY AI explainability is the ability for AI systems to provide reasoning as to why they arrived at a particular decision, prediction, or suggestion. For example, if an AI system predicts that a patient has a high risk of lung cancer, why did it arrive at that prediction ? The physician?

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Explainability AI AI AI Tools 52

O'Reilly Media

FEBRUARY 18, 2025

Its about asking the right questions to understand how well your AI is working and how to make it better. In the next chapter, well share a counterintuitive approach to AI strategy that can save you time and resources in the long run. This cheat sheet will show you how to avoid jargon and speak plainly about AI.

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AWS Machine Learning Blog

MAY 9, 2024

Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI. To provide ethical integrity , an AI/ML CoE helps integrate robust guidelines and safeguards across the AI/ML lifecycle in collaboration with stakeholders.

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AWS Machine Learning Blog

MARCH 28, 2024

It provides a modular and flexible framework for combining LLMs with other components, such as knowledge bases, retrieval systems, and other AI tools, to create powerful and customizable applications. LangChain is an open source Python library designed to build applications with LLMs.

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Topbots

FEBRUARY 4, 2025

Figure 3: Knowledge graphs explicitly encode relationships between entities, reducing the guesswork in your AI system Instead of relying purely on statistical correlations, an AI system enriched with knowledge graphs can: Validate predictions against domain-specific rules (e.g., Infer missing information (e.g.,

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Flipboard

DECEMBER 3, 2024

By integrating multiple data sources and explainable research results, including weather patterns and soil data, the agent delivers personalized and context-aware recommendations. Laksh Puri is a Generative AI Strategist at the AWS Generative AI Innovation Center, based in London.

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IBM Journey to AI blog

MAY 14, 2024

Review frameworks and assessment tools so you have a clear indication of any strengths and weaknesses that will impact your ability to implement AI tools and help with associated risks. This process can help you identify a problem or opportunity that an AI solution can address.

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