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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO

From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. Data architecture coherence. more machine learning use casesacross the company.

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Snorkel AI scores $35M Series B to automate data labeling in machine learning

TechCrunch

One of the more tedious aspects of machine learning is providing a set of labels to teach the machine learning model what it needs to know. It also announced a new tool called Application Studio that provides a way to build common machine learning applications using templates and predefined components.

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Explosion snags $6M on $120M valuation to expand machine learning platform

TechCrunch

Explosion , a company that has combined an open source machine learning library with a set of commercial developer tools, announced a $6 million Series A today on a $120 million valuation. The round was led by SignalFire, and the company reported that today’s investment represents 5% of its value.

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Hungry for resources, AI redefines the data center calculus

CIO

The AI revolution is driving demand for massive computing power and creating a data center shortage, with data center operators planning to build more facilities. But it’s time for data centers and other organizations with large compute needs to consider hardware replacement as another option, some experts say.

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The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Download the report to find out: How enterprises in various industries are using MLOps capabilities.

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Traceable AI nabs $60M to secure app APIs using machine learning

TechCrunch

But because they can provide access to sensitive functions and data, APIs are an increasingly common target for malicious hackers. “However, sophisticated API-directed cyberthreats and vulnerabilities to sensitive data have also rapidly increased. Businesses need machine learning here.

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AI’s data tsunami: Why your data stewardship needs an overhaul

CIO

This isn’t science fiction – it’s the reality for organizations that are unprepared for AI’s data tsunami. As someone who’s navigated the turbulent data and analytics seas for more than 25 years, I can tell you that we’re at a critical juncture. And it’s transforming how we operate our businesses, recruit our teams, and manage data.

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How to Choose an AI Vendor

You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. This report explores why it is so challenging to choose an AI vendor and what you should consider as you seek a partner in AI.

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Data Science Fails: Building AI You Can Trust

The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. The new DataRobot whitepaper, Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully.