In the realm of storage devices, Hard Disk Drives (HDDs) and Solid State Drives (SSDs) stand out as the two primary options available to consumers.
While multi-core processors marked a significant leap forward, the quest for even greater performance and efficiency led to the emergence of heterogeneous architectures.
CMOS 2.0 approach transcends traditional scaling methodologies, embracing novel concepts like heterogeneous integration and neuromorphic computing.
Chiplets, the building blocks of modern semiconductor architecture, are modular chips meticulously crafted to seamlessly integrate and form comprehensive system-on-chip (SoC) solutions.
In-memory computing revolutionizes traditional data processing methods by storing and processing data directly in the main memory (RAM) of a computer system, rather than relying on disk-based storage.
Samsung, a key player in memory technology, has unveiled projections indicating that DDR6 memory could achieve data rates of up to 12,800 MT/s, effectively doubling the maximum data rate of DDR5.
AI models often involve large-scale matrix operations, such as multiplying input data by weight matrices and adding biases. This process forms the basis of forward and backward propagation algorithms used in training neural networks.
Breaking into this field requires more than just technical know-how—it demands a strategic approach and a commitment to continuous learning.
Typically, less than 100 nanometers in diameter, this minuteness allows them to exploit unique quantum effects, enabling enhanced light matter interaction. An interaction highly useful in making Photonic Integrated Circuits.
In the ever-evolving landscape of artificial intelligence, the shift towards edge computing has become a defining trend, and at the forefront of this revolution stands NVIDIA Jetson.