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SKP's Java/Java EE Gotchas: Clash of the Titans, C++ vs. Java!

DZone

As a Software Engineer, the mind is trained to seek optimizations in every aspect of development and ooze out every bit of available CPU Resource to deliver a performing application. Considering all aspects and needs of current enterprise development, it is C++ and Java which outscore the other in terms of speed. Ahem, Slow!

Java 207
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RSA guide 2024: AI and security are top concerns for organizations in every industry

Dynatrace

As organizations train generative AI systems with critical data, they must be aware of the security and compliance risks. Whether multicloud or hybrid , public or private, cloud-native architecture offers flexibility and agility to help organizations deliver software faster. Check out the resources below for more information.

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The top eight DevSecOps trends in 2022

Dynatrace

As businesses take steps to innovate faster, software development quality—and application security—have moved front and center. According to GitLab’s 2021 Global DevSecOps Survey , 36% of respondents develop software using DevSecOps, compared with only 27% in 2020. It does so by creating repeatable, automated software-driven processes.

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Black Hat 2023: Pairing causal AI and generative AI for cybersecurity threats

Dynatrace

They can also use generative AI for cybersecurity, write prototype code, and implement complex software systems. Because generative AI is probabilistic in nature, its value depends on the quality of data that trains its algorithms and prompts. Developers use generative AI to find errors in code and automatically document their code.

DevOps 194
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Quality Sense Podcast: Alan Richardson — On Test Automation

DZone

With more than 25 years of experience in testing and development, he offers consultancy and training in agile testing and test automation. Alan is the author of different books including “Java For Testers” and “Dear Evil Tester.” He shares a plethora of content on his Youtube channel , podcast and blog. What’s the Interview About?

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

These include ETL pipelines, ML model training workflows, batch jobs, etc. Similarly, ML model training workflows usually consist of tens of thousands of training jobs within a single workflow. Users can write the code in Java syntax as the parameter definition. Here is an example workflow defined by different DSLs.

Java 202
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2021 Data/AI Salary Survey

O'Reilly

Most respondents participated in training of some form. Learning new skills and improving old ones were the most common reasons for training, though hireability and job security were also factors. Company-provided training opportunities were most strongly associated with pay increases. Demographics.

Azure 145