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Reading list

What is Deep Learning? DL vs ML vs AI Why Deep Learning is So Popular?
Applications of Deep Learning Multi Layer Perceptron Visualizing the Neural Network Understanding Decision Boundary Forward and Backward Propagation Intuition
Applications of Deep Learning Multi Layer Perceptron Visualizing the Neural Network Understanding Decision Boundary Forward and Backward Propagation Intuition
Gradient Descent Algorithm Variants of Gradient Descent Algorithm
Introduction to Loss Function Binary and Categorical Cross Entropy
Why Do We Need Activation Functions? Linear Activation Function Sigmoid and Tanh Function Softmax How to Select Right Activation Function?
Perceptron Weights in Perceptron Introduction to Artificial Neural Network
Understanding Forward Propagation Mathematically Understand Backward Propagation Mathematically Implementing Neural Networks in Python
Problems with Gradient Descent Gradient Descent with Momentum Adagrad and Adadelta
Introduction to Learning Rate Schedulers
Overview of Deep Learning Frameworks Implementing Neural Networks using Keras Functional API in Keras Implementing Neural Networks using Keras Hyperparameter Tuning of MLP in Keras
Understanding Early stopping Understanding Dropout Vanishing and Exploding Gradients Weights Initialization Techniques Implementing Weight Initializing Techniques Batch Normalization Image Augmentation Techniques Image Generator and Fit Generator Model Checkpointing Implementing Model Checkpointing Dealing with Class Imbalance Ensemble Deep Learning
Introduction to GPU and TPU TensorRT
Introduction to Unsupervised Learning How to Solve Unsupervised Learning Problems? Introduction to Autoencoders Implementing Autoencoders
A Beginners Guide to Codeless Deep Learning
TensorFlow Serving Build Deep Learning Models for Android
Introduction to PyTorch and Tensors Mathematical and Matrix Operations in PyTorch Important PyTorch Modules Implement CNN in PyTorch Transfer Learning in PyTorch Working with Text Data in PyTorch Building a RNN model in PyTorch Autoencoders in PyTorch

Samsung Unveils Fastest-Ever DRAM Chip for AI Applications

K.C. Sabreena Basheer
K.C. Sabreena Basheer Last Updated : 22 Apr, 2024
2 min read

Samsung Electronics has introduced a revolutionary LPDDR5X DRAM chip, heralding a new era in artificial intelligence (AI) applications. This chip boasts unparalleled speed, capacity, and power efficiency, setting a new standard for on-device AI processing. Let’s find out more about this latest innovation from Samsung.

Also Read: Meta Unveils Its Best AI Chip Yet

Samsung Unveils Fastest-Ever DRAM Chip for AI Applications

Technological Breakthrough

Samsung has unveiled the industry’s fastest LPDDR5X DRAM chip, achieving an impressive data transfer speed of up to 10.7 gigabits-per-second (Gbps). Leveraging cutting-edge 12 nanometer (nm)-class process technology, Samsung has engineered this chip to be the smallest among existing LPDDR variants, reinforcing its position as a leader in low-power DRAM technology.

Also Read: AMD Introduces Ryzen Pro 8000 and 8040 Series CPUs for Business Computing

Optimized for On-Device AI

With the rise of on-device AI applications, there is a growing demand for low-power, high-performance memory solutions. Samsung’s LPDDR5X chip addresses this need by delivering more than a 25% improvement in performance and over 30% increase in capacity compared to its predecessors. This makes it the ideal choice for a wide range of devices, including smartphones, laptops, servers, and automobiles, where on-device AI processing is paramount.

Enhanced Power Efficiency

Samsung’s LPDDR5X chip incorporates advanced power-saving technologies to maximize energy efficiency. By implementing optimized power variation and expanded low-power mode intervals, this chip achieves a remarkable 25% increase in power efficiency over previous generations. As a result, mobile devices equipped with this chip can offer extended battery life, while servers can minimize energy consumption, leading to lower total cost of ownership (TCO).

Also Read: Intel Challenges Nvidia Dominance with New Gaudi 3 AI Chip

Samsung Unveils Fastest-Ever LPDDR5X DRAM Chip, Revolutionizing AI Applications

Future Prospects

The introduction of Samsung’s LPDDR5X DRAM chip marks a significant milestone in the evolution of AI-enabled devices. The demand for on-device AI is continuously growing across various sectors, including smartphones, wearable devices, robots, and autonomous vehicles. This intensifies the need for high-performance, high-capacity memory chips. Market projections indicate a substantial increase in demand for mobile DRAM chip capacity. This underscores the importance of innovations like Samsung’s LPDDR5X chip in meeting future technological demands.

Our Say

Samsung’s unveiling of the LPDDR5X DRAM chip represents a paradigm shift in memory technology. It offers unmatched speed, capacity, and energy efficiency tailored for the AI-driven future. As Samsung continues to push the boundaries of innovation, we anticipate further advancements that will reshape the AI landscape.

Follow us on Google News to stay updated with the latest innovations in the world of AI, Data Science, & GenAI.

K.C. Sabreena Basheer
K.C. Sabreena Basheer

Sabreena Basheer is an architect-turned-writer who's passionate about documenting anything that interests her. She's currently exploring the world of AI and Data Science as a Content Manager at Analytics Vidhya.

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