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Risk Management for AI Chatbots

O'Reilly on Data

Doing so means giving the general public a freeform text box for interacting with your AI model. Welcome to your company’s new AI risk management nightmare. ” ) With a chatbot, the web form passes an end-user’s freeform text input—a “prompt,” or a request to act—to a generative AI model.

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Why you should care about debugging machine learning models

O'Reilly on Data

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

CIOs feeling the pressure will likely seek more pragmatic AI applications, platform simplifications, and risk management practices that have short-term benefits while becoming force multipliers to longer-term financial returns. CIOs should consider placing these five AI bets in 2025.

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5 top business use cases for AI agents

CIO Business Intelligence

Meanwhile, in December, OpenAIs new O3 model, an agentic model not yet available to the public, scored 72% on the same test. Were developing our own AI models customized to improve code understanding on rare platforms, he adds. That adds up to millions of documents a month that need to be processed.

Software 143
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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Note that the emphasis of SR 11-7 is on risk management.). Image by Ben Lorica.

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New framework aims to keep AI safe in US critical infrastructure

CIO Business Intelligence

Industry asked for intervention Naveen Chhabra, principal analyst with Forrester, said, “while average enterprises may not directly benefit from it, this is going to be an important framework for those that are investing in AI models.” Hopefully, we will see this framework continue to evolve.”

Risk 119
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The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 210