How to architect a scalable data pipeline for HealthTech applications
HealthTech runs on data. From patient vitals and lab results to insurance claims and wearable device streams, there’s a constant firehose of information flowing in. And...
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Ethics-driven model auditing and bias mitigation
Introduction Artificial intelligence (AI) and machine learning (ML) systems are becoming increasingly integral to decision-making processes across various industries, inc...
How agentic AI reshapes your development
Artificial Intelligence has moved past its earlier, more passive role of assisting with data processing and predictions. Today, it’s entering a more autonomous, goa...
Utilize machine learning to improve employee retention rates
Employee turnover is one of the most pressing challenges modern businesses face. It drains resources, lowers morale and slows team momentum. Traditional HR tools like sur...
Closing the AI skills gap
Interview w/ Mike Spaeth, VP of United States AI Institute The phrase “AI skills gap” gets thrown around so often that it risks becoming background noise. O...
The hidden cost of over-instrumentation: Why more tracking can hurt product teams
Stop tracking everything: Rethink your data strategy If you’ve ever opened a product analytics dashboard and scrolled past dozens of unlabeled metrics, charts with no v...
How to Build and Optimize High-Performance Deep Neural Networks from Scratch
With explainable AI, intuitive parameters easy to fine-tune, versatile, robust, fast to train, without any library other than Numpy. In short, you have full control over ...
Unlocking the value of AI with DevOps accelerated MLOps
Since the early 2000s, the advent of digital transformation has compelled businesses across industries to reimagine their business processes, customer interactions, produ...
Revamping enterprise content management with language models
The relatively recent capacity for front-end users to interface with backend systems, documents, and other content via natural language prompts is producing several notab...
Decentralized ML: Developing federated AI without a central cloud
Introduction – Breaking the cloud barrier Cloud computing has been the dominant paradigm of machine learning for years. Massive data charts are uploaded on a centra...