How AI complicates enterprise risk management

Man standing in the city

Despite the gains artificial intelligence has already brought to the enterprise, there is still much hand-wringing over its potential for unintended consequences. While the headlines tend to focus on AI running amok and destroying all mankind, the practical reality is that current generations of AI are more likely to wreak havoc on business processes — and profits — if not managed properly. But how can you control something that, by its nature, is supposed to act autonomously? And by doing so, won’t the enterprise be hampering the very thing that makes AI such a valuable asset in the workplace?

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Fiddler AI gets $32M in series B funding to grow its Modeling Performance Management Platform


Since 2018, Fiddler AI has been working to make AI easier to use for enterprises by making the mysteries under the hood more approachable and simpler to understand by users. And now, armed with $32 million in new Series B funding from investors led by Insight Partners, Fiddler AI is looking to expand and build out its machine learning model performance management platform to bring its services to a broader group of customers.

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This nifty online guide compares AI/ ML tools and platforms

End-to-end ML platforms

This Week in Machine Learning, an organization dedicated to demystifying AI/ML operations for everyone, recently filled a need in the market by launching a ‘Solutions Guide’ to open source and enterprise AI tools and platforms. TWIML’s Solutions Guide consists of several infographics and a litany of research and information meant to make the search for just the right ML solution easy.

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Unlock the full potential of Anti-Money Laundering (AML) analysts with Artificial Intelligence (AI).

Child in chalk drawn space helmet

In their day-to-day risk assessment operations, Anti-Money Laundering (AML) analysts spend much of their time dedicated to routine and repetitive tasks. According to a study published by the research firm “Celent” (Source: Ray, Arin. 2018. The Dawn of a New Era in AML Technology), banks report that between 60 and 80% of analysts’ time is spent on low level data management.

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ModelOps: The key to managing AI Models at scale

AI Change

AI is being used by enterprises to solve major business problems, yet still struggle with effectively deploying and maintaining those algorithms in what is often called the “last mile” of the AI journey. ModelOps, which operationalizes AI models, has been gaining traction to effectively automate the rollout and maintenance of AI, carrying it across the finish line and ensuring that it continues to improve and increase in value.

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IBM closes acquisition of Turbonomic to deliver comprehensive AIOps capabilities for Hybrid Cloud


IBM announced the closing of its acquisition of Turbonomic, Inc., an Application Resource Management (ARM) and Network Performance Management (NPM) software provider based in Boston, MA.

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A brief into to NLP in the Media & Communication Industry

Natural Language Processing (NLP) possesses a massive influence on the media and communication industry. The ability to track people’s choice, filter irrelevant information, speed, and accuracy makes this technology standing apart in the industry. In this write-up, we will understand the role of NLP in the media industry, its impact, and how it will help to clear out the issues which are hampering the overall growth.

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