technology
database, distributed system, AI, quantum computing
-
FLOAT32, FLOAT16, AND BFLOAT16: PRECISION’S ROLE IN DEEP LEARNING
(continued from previous section) 🟧 Impact on Deep Learning Processes The choice of floating-point format significantly affects various aspects of deep learning, including training speed, memory usage, and computational accuracy. Let’s explore these impacts in detail. Training Speed The precision format directly influences the speed of neural network training: Many deep learning frameworks now support Continue reading
-
Float32, Float16, and BFloat16: Precision’s Role in Deep Learning
Introduction: The Importance of Numerical Precision In the world of deep learning, the way numbers are represented can have a significant impact on model performance, training speed, and hardware requirements. At the heart of this lies floating-point arithmetic, a method computers use to handle real numbers with finite precision. Three floating-point formats have become particularly Continue reading
-
gRPC | Quantum Leaps in Secure Microservice Communication
✱ All the quantum terms are used as methaphor, not actual quantum communication will actually use any of these protocols. however, quantum computing is another subject to tell later In the vast multiverse of distributed systems, where microservices dance like subatomic particles, a powerful force emerges to bring order to the chaos: gRPC. Much like Continue reading
Think like a butterfly 