AI Development ML Engineer Software Development 
Towards AI
FEBRUARY 15, 2024
Author(s): Jennifer Wales Originally published on Towards AI. AI Engineers: Your Definitive Career Roadmap Become a professional certified AI engineer by enrolling in the best AI ML Engineer certifications that help you earn skills to get the highest-paying job.
Chatbots Life
MAY 16, 2023
Master of Code proposes to create a Proof of Concept (POC) within 2 weeks after the request to explore the advantages of using a Generative AI chatbot in your company. 10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland.
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Snorkel AI
MAY 4, 2023
Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.
Snorkel AI
MAY 4, 2023
Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.
AWS Machine Learning Blog
NOVEMBER 16, 2023
Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.
AWS Machine Learning Blog
APRIL 29, 2024
Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. How Metaflow integrates with Trainium From a Metaflow developer perspective, using Trainium is similar to other accelerators.
AWS Machine Learning Blog
JANUARY 26, 2024
Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. Lastly, we connect these together with an example LLM workload to describe an approach towards architecting with defense-in-depth security across trust boundaries.
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