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Why you should care about debugging machine learning models

O'Reilly Media - Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. This article is meant to be a short, relatively technical primer on what model debugging is, what you should know about it, and the basics of how to debug models in practice. What is model debugging?

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Leveraging AMPs for machine learning

CIO

The problem is that it’s not always clear how to strike a balance between speed and caution when it comes to adopting cutting-edge AI. Data scientists and AI engineers have so many variables to consider across the machine learning (ML) lifecycle to prevent models from degrading over time.

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OctoML raises $28M Series B for its machine learning acceleration platform

TechCrunch

OctoML , a Seattle-based startup that offers a machine learning acceleration platform build on top of the open-source Apache TVM compiler framework project , today announced that it has raised a $28 million Series B funding round led by Addition. We look forward to supporting the company’s continued growth.”

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5 dead-end IT skills — and how to avoid becoming obsolete

CIO

Here leaders offer insights on careers that need to adapt to survive and offer tips on how to move forward. With AI or machine learning playing larger and larger roles in cybersecurity, manual threat detection is no longer a viable option due to the volume of data,” he says. Vincalek agrees manual detection is on the wane.

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INE Security Alert: Using AI-Driven Cybersecurity Training to Counter Emerging Threats

CIO

As Artificial Intelligence (AI)-powered cyber threats surge, INE Security , a global leader in cybersecurity training and certification, is launching a new initiative to help organizations rethink cybersecurity training and workforce development.

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Efficiently train models with large sequence lengths using Amazon SageMaker model parallel

AWS Machine Learning - AI

Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters and larger input sequence length. This approach reduces memory pressure and enables efficient training of large models.

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How to know a business process is ripe for agentic AI

CIO

Then it is best to build an AI agent that can be cross-trained for this cross-functional expertise and knowledge, Iragavarapu says. We are fast tracking those use cases where we can go beyond traditional machine learning to acting autonomously to complete tasks and make decisions.

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