Artificial Inteligence Engineering Software Engineering 
The IIL Blog
OCTOBER 24, 2023
By Eugene Bounds and Steve Ackert Recently, the buzzword artificial intelligence (AI) has been on everyone’s minds, not just in the tech world but across many industries, including project management. Euguene earned an M.S. degree in Information Systems from the University of Southern California and a B.B.A. He is a retired U.S.
Teamweek
JULY 12, 2024
TL;DR — Key Takeaways Artificial intelligence engineers may specialize in different areas of AI. Examples include NLP, machine learning, Deep Learning, Data Science, Image processing, and Continuous Learning. Different AI engineering jobs require different skills.
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Wrike
SEPTEMBER 26, 2023
Enter the Site Reliability Engineer (SRE), the unsung hero of the digital age. This comprehensive article will delve into the world of SREs, exploring their role, responsibilities, importance in business operations, the intersection of software engineering and systems administration, and the future trends shaping this crucial field.
MPUG
FEBRUARY 19, 2024
We built and deployed a system using large language models (LLMs) to do the work with accurac y that far exceeded the OEM’s expectations. By now, most people with even a passing interest in technology have experimented with large language models (LLMs) like Anthropic’s Claude, Open AI’s ChatGPT, or Google’s Gemini.
Proofhub
MARCH 24, 2023
For example, a software engineer may be passionate about artificial intelligence and machine learning. As their manager, you could allow them to take relevant courses to improve their skills. You could also assign them to a project that utilizes these skills.
Teamweek
AUGUST 1, 2023
Some of the most important data analyst skills include data analysis, statistical programming languages, data management, data visualization, good communication skills, machine learning and even Excel skills. It’s also a fav for analysts as it’s an easily readable and understandable language.
Leading Agile
JUNE 18, 2018
Cloud, fog, and mist computing combined with the Internet of Things (IoT) and artificial intelligence (AI) add up to even more very small services interacting with one another dynamically in ways their developers cannot predict. This may be a consequence of rushing the work. There’s a desire for rapid delivery.
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