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Laptop on table representing Quantization of Neural Network Model for AI Hardware
Technology

Quantization of Neural Network Model for AI Hardware

Background In recent years, deep learning-based Artificial Intelligence (AI) and Machine Learning (ML) models are moving from cloud to the edge devices for various factors such as bandwidth as in Figure-1. Power consumption, latency, hardware size are important aspects for inference at the edge. Moreover, The Models developed in the cloud[…]

Technology

Customizing a Propensity To Buy Model

Background This blog outlines the steps involved and things to care about for transfer learning a propensity model. Sales team members could be inundated with several prospects. The best use of their time is by lead scoring and focusing on the prospects that have best chance to close. A Propensity-To-Buy model helps[…]

data discipline in large organization
Technology

Data Discipline in large Organizations

Background Data is the new Oil. Companies should treasure data. The new class of powerful Machine Learning (ML) and Artificial Intelligence (AI) algorithms are data hungry and are as good as the data provided to them. Several useful (profitable) insights can be derived from data across the organization benefiting different[…]

Industrial IoT
Customer Success

Industrial IoT ML/AI models for TCO improvement

Highlights Industrial adoption of Internet of Things (IoT) and digitization has provided great visibility into the several processes in a Factory or a Manufacturing Unit. The Analytics on top of the monitored data helped managers and executives improve the productivity by manually monitoring each of the metrics. Large[…]

Compute-near-Storage-Cloud
Technology

Compute near Storage in Cloud for FPGA acceleration

Background This blog outlines the advantages of compute attached to storage and reference architecture to implement it in cloud with FPGAs. Almost all the deep learning algorithms are very memory intensive and it takes more energy (power) to get data into and out of the CPU/GPU than the compute itself. Optimal sche[…]

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