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Gen AI without the risks

CIO Business Intelligence

Developing and deploying successful AI can be an expensive process with a high risk of failure. Six tips for deploying Gen AI with less risk and cost-effectively The ability to retrain generative AI for specific tasks is key to making it practical for business applications. The possibilities are endless, but so are the pitfalls.

Risk 128
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How to Manage Risk with Modern Data Architectures

Cloudera

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

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Digital Risk is Primary Focus for Corporate Boards in 2020 & Beyond

John Wheeler

Digital risk continues to grow in importance for corporate boards as they recognize the critical nature of digital business transformation today. Not only that, but 49% of directors cite the need to reduce legal, compliance and reputation risk related to digital investments. However, digital risk is different.

Risk 117
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What is GRC? The rising importance of governance, risk, and compliance

CIO Business Intelligence

The need to manage risk, adhere to regulations, and establish processes to govern those tasks has been part of running an organization as long as there have been businesses to run. Stanley also notes that “technology advances, like AI, IoT and cloud computing, have also introduced compliance challenges and new cybersecurity threats.”

Risk 103
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Why Secure Your IoT Data With a Zero-Trust Strategy?

CDW Research Hub

In fact, many organizations have begun adopting zero-trust IoT security strategies to protect their IoT data from potential breaches. By some estimates, as many as 300 billion connected devices will be integrated into IoT platforms and IoT applications within the next 10 years. Why is zero trust necessary for IoT?

IoT 52
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Architectural Patterns for real-time analytics using Amazon Kinesis Data Streams, Part 2: AI Applications

AWS Big Data

Now get ready as we embark on the second part of this series, where we focus on the AI applications with Kinesis Data Streams in three scenarios: real-time generative business intelligence (BI), real-time recommendation systems, and Internet of Things (IoT) data streaming and inferencing. The event tracker performs two primary functions.

IoT 93
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Accelerating Industry 4.0 at warp speed: The role of GenAI at the factory edge

CIO Business Intelligence

While warp speed is a fictional concept, it’s an apt way to describe what generative AI (GenAI) and large language models (LLMs) are doing to exponentially accelerate Industry 4.0. Manufacturers have been using gateways to work around these legacy silos with IoT platforms to collect and consolidate all operational data.