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TIAA modernizes the customer journey with AI

CIO

Sastry Durvasula, chief information and client services officer at TIAA, says the multilayered platform’s extensive use of machine learning as part of its customer service line partnership with Google AI makes JSOC a formidable tool for financial and retirement planning and guiding customers through complex financial journeys.

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Hugging Face collaborates with Microsoft for new AI-powered Azure service

TechCrunch

Fresh off a $100 million funding round , Hugging Face, which provides hosted AI services and a community-driven portal for AI tools and data sets, today announced a new product in collaboration with Microsoft. ” “The mission of Hugging Face is to democratize good machine learning,” Delangue said in a press release.

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Propensity Model: How to Predict Customer Behavior Using Machine Learning

Altexsoft

It’s a common practice for companies and their marketing teams to try guessing how likely certain groups of customers are going to act under certain circumstances. To help companies unlock the full potential of personalized marketing, propensity models should use the power of machine learning technologies.

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Traffic Prediction: How Machine Learning Helps Forecast Congestions and Plan Optimal Routes

Altexsoft

Traffic prediction is mainly important for two groups of organizations (we’re not talking about folks planning a weekend getaway, you know). Traffic prediction is mainly important for two groups of organizations (we’re not talking about folks planning a weekend getaway, you know). National/local authorities. street lights).

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Should you build or buy generative AI?

CIO

In the shaper model, you’re leveraging existing foundational models, off the shelf, but retraining them with your own data.” Whether it’s text, images, video or, more likely, a combination of multiple models and services, taking advantage of generative AI is a ‘when, not if’ question for organizations.

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Interpreting predictive models with Skater: Unboxing model opacity

O'Reilly Media - Data

Over the years, machine learning (ML) has come a long way, from its existence as experimental research in a purely academic setting to wide industry adoption as a means for automating solutions to real-world problems. There is also a trade off in balancing a model’s interpretability and its performance.

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Revolutionizing Business Operations with Future-Fit Software

Tandem

With the ever-expanding set of emerging technologies — big data, machine learning (ML), artificial intelligence (AI), next-gen user experiences (UI/UX), edge computing, the Internet-of-things (IoT), microservices, and Web3 — there is a huge surface area to address. Swift reconfiguration necessitates a shift in mindset and culture.

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