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5 machine learning essentials nontechnical leaders need to understand

TechCrunch

We’re living in a phenomenal moment for machine learning (ML), what Sonali Sambhus , head of developer and ML platform at Square, describes as “the democratization of ML.” Consider upskilling your current team of software engineers into data/ML engineers or hire promising candidates and provide them with an ML education.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. The future will be characterized by more in-depth AI capabilities that are seamlessly woven into software products without being apparent to end users. An overview.

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Remember when developers reigned supreme? The market for software coding goes soft

CIO

It seems like only yesterday when software developers were on top of the world, and anyone with basic coding experience could get multiple job offers. In February, CEO Marc Benioff told CNBCs Squawk Box that 2025 will be the first year in the companys 25-year history that it will not add more software engineers.

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How AI can alleviate help desk workloads

CIO

As many as 56% of IT workers 1 say the help desk ticket volume is up, according to a recent survey by software vendor Ivanti. The reasons include more software deployments, network reliability problems, security incidents/outages, and a rise in remote working. These technologies handle ticket classification, improving accuracy.

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How AI and ML Can Accelerate and Optimize Software Development and Testing

Speaker: Eran Kinsbruner, Best-Selling Author, TechBeacon Top 30 Test Automation Leader & the Chief Evangelist and Senior Director at Perforce Software

While advancements in software development and testing have come a long way, there is still room for improvement. With new AI and ML algorithms spanning development, code reviews, unit testing, test authoring, and AIOps, teams can boost their productivity and deliver better software faster.

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9 IT skills where expertise pays the most

CIO

AI skills broadly include programming languages, database modeling, data analysis and visualization, machine learning (ML), statistics, natural language processing (NLP), generative AI, and AI ethics. The name stands for Bourne Again Shell and was originally released in 1989 as a free software alternative to the Bourne shell.

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Are you ready for MLOps? 🫵

Xebia

Both the tech and the skills are there: Machine Learning technology is by now easy to use and widely available. So then let me re-iterate: why, still, are teams having troubles launching Machine Learning models into production? No longer is Machine Learning development only about training a ML model.