Analytics Architecture Machine Learning Scalability 
CIO
OCTOBER 13, 2023
In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).
Confluent
FEBRUARY 6, 2019
Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.
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CIO
AUGUST 8, 2023
By bringing compute power closer to the point of action, edge computing allows real-time data processing, analytics, and decision-making, thereby improving the well-being and efficiency of front-line workers. Traditional, centralized computing architectures cannot deliver the speed and reliability required for critical frontline tasks.
Netflix Tech
JANUARY 25, 2023
Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. All data should be also available for offline analytics in Hive/Iceberg. The most important of such a data pipeline is created by the Machine Learning team.
Altexsoft
JUNE 29, 2021
In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The role of a machine learning engineer in the data science team.
CIO
FEBRUARY 14, 2023
To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. AI continues to transform customer engagements and interactions with chatbots that use predictive analytics for real-time conversations.
AWS Machine Learning - AI
FEBRUARY 26, 2024
Our proposed architecture provides a scalable and customizable solution for online LLM monitoring, enabling teams to tailor your monitoring solution to your specific use cases and requirements. A modular architecture, where each module can intake model inference data and produce its own metrics, is necessary.
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