2014 AI Development ML Engineer 
FEBRUARY 28, 2023
Downstream of the well-known data labeling problem exist additional data bottlenecks that will hinder the development of later-stage AI and its deployment to production environments. These problems are why, despite the early promise and floods of investment, technologies like self-driving cars have been just one year away since 2014.
Towards AI
AUGUST 25, 2023
Any competent software engineer can implement any algorithm. Even if you are an experienced AI/ML engineer, you should know the performance of simpler models on your dataset/problem. I also have a medium article on AI Learning Resources. References [1] Artificial Intelligence Engineering [2] J. 12, 2014. [3]
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AWS Machine Learning Blog
NOVEMBER 16, 2023
Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.
Chatbots Life
MAY 16, 2023
as a certified partner for delivering end-to-end Conversational AI professional services leveraging LivePerson’s Conversational Cloud. Services : Mobile app development, web development, blockchain technology implementation, 360′ design services, DevOps, OpenAI integrations, machine learning, and MLOps.
AWS Machine Learning Blog
JUNE 24, 2024
They were a true force multiplier for our AI development.” – Dr. Ketaki Shriram, Co-Founder and CTO of Krikey AI. Conclusion The time and cost savings, along with access to premium labeled data, highlights the immense value SageMaker Ground Truth offers startups working with generative AI.
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