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Predibase exits stealth with a low-code platform for building AI models

TechCrunch

Data science teams are stymied by disorganization at their companies, impacting efforts to deploy timely AI and analytics projects. based companies, 44% said that they’ve not hired enough, were too siloed off to be effective and haven’t been given clear roles. In a recent survey of “data executives” at U.S.-based

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NJ Transit creates ‘data engine’ to fuel transformation

CIO

In early 2020, the company’s infrastructure was an amalgam of “everything,” Fazal says, including mainframe, client/server, and SaaS systems, as well as 140 applications of all “flavors,” some customized, some off the shelf, some from big companies and some from small companies, he says. Data engine on wheels’.

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Automated Claims Processing: Using RPA and Machine Learning to Manage Insurance Claims

Altexsoft

And when it comes to decision-making, it’s often more nuanced than an off-the-shelf system can handle — it needs the understanding of the context of each particular case. But it does need more advanced approaches that mimic human perception and judgment like AI, Machine Learning, and ML-based Robotic Process Automation.

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Next Best Action Marketing: How to Implement Hyper-Personalization with Machine Learning

Altexsoft

They don’t notice or report online ads and posts, unsubscribe from newsletters, reject calls, and mute app notifications. In this article, we’ll discuss what the next best action strategy is and how businesses define the next best action using machine learning-based recommender systems. This changes the game for marketers.

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Intelligenza artificiale e gen AI: i quattro elementi per passare al “next level”

CIO

Infatti, secondo il “Report Imprese e Ict 2023” di Istat, la mancanza di competenze è il primo freno all’adozione delle tecnologie IA in Italia: il 55,1% delle imprese che hanno preso in considerazione il suo utilizzo senza poi adottarla ha rinunciato per carenza di skill e comprensione delle possibilità per il proprio business.

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

Altexsoft

As of today, different machine learning (and specifically deep learning) techniques capable of processing huge amounts of both historic and real-time data are used to forecast traffic flow, density, and speed. In 2021, NYC drivers lost an average of 102 hours in congestion – and before the pandemic that score was even worse.

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Supply Chain Analytics: Opportunities in Data Analysis and Business Intelligence

Altexsoft

These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development. Optimization opportunities offered by analytics. Analytics in planning and demand forecasting.