Search Results
24 results for “compute”
AI in Malaysian Manufacturing
Artificial intelligence adoption in Malaysian manufacturing covers predictive maintenance, computer vision quality control, demand forecasting, and supply-chain optimisation across the electronics, automotive, and food sectors.
AI in Malaysian Retail
AI in Malaysian retail encompasses the deployment of machine learning, computer vision, and natural language processing across Malaysia's retail sector, including e-commerce platforms, brick-and-mortar stores, and omnichannel retail operations.
AI in the Malaysian Palm Oil Industry
The application of artificial intelligence, computer vision, robotics, and predictive analytics to oil palm cultivation, harvesting, milling, and supply chain traceability in Malaysia.
AI PC
A personal computer equipped with a dedicated Neural Processing Unit (NPU) designed to accelerate on-device artificial intelligence workloads locally, without requiring cloud connectivity, for tasks such as image generation, speech recognition, and language model inference.
Artificial Intelligence
Artificial intelligence (AI) is the simulation of human intelligence processes by computer systems, encompassing learning, reasoning, problem-solving, perception, and language understanding.
Computer Vision
Computer vision is the field of artificial intelligence that enables machines to interpret and act upon visual information from the world — including images, video, and depth data.
Convolutional Neural Network
A convolutional neural network (CNN) is a type of deep neural network that uses convolutional layers to automatically learn spatial hierarchies of features from grid-structured data, most commonly images.
DeepSpeed
DeepSpeed is an open-source deep learning optimisation library developed by Microsoft that enables efficient distributed training and inference of large-scale neural networks through memory and compute optimisations.
Face Recognition
Face recognition is a biometric technology that identifies or verifies individuals by analysing facial features from images or video, widely used in security, banking, and immigration.
Image Segmentation
A computer vision task that partitions an image into meaningful regions by assigning a class label to every pixel, enabling pixel-level understanding of visual scenes.
KV Cache
A KV cache (key-value cache) is a memory optimisation used in transformer inference that stores pre-computed key and value tensors from the attention mechanism, eliminating redundant recomputation when generating tokens sequentially.
Mixture of Experts
Mixture of Experts (MoE) is a machine learning architecture in which a model routes each input to a small subset of specialised sub-networks called experts, enabling large model capacity at a fraction of the compute cost.
Natural Language Processing
Natural language processing (NLP) is the subfield of AI concerned with enabling computers to understand, interpret, manipulate, and generate human language in both text and speech form.
Neural Scaling Laws
Neural scaling laws are empirical relationships describing how the performance of neural networks improves predictably as a function of model size, dataset size, and compute budget, enabling principled resource allocation for AI training.
Object Detection
Object detection is a computer vision task that involves identifying the location and category of one or more objects within an image or video frame, producing bounding boxes and class labels for each detected instance.
Optical Character Recognition
A computer vision technology that converts images of typed, handwritten, or printed text into machine-readable digital text, increasingly powered by deep learning and transformer-based vision models.
Parameter-Efficient Fine-Tuning
A family of techniques that adapts a pretrained language or vision model to a downstream task by training only a small fraction of its parameters, dramatically reducing compute, memory, and storage requirements compared to full fine-tuning.
Pose Estimation
Pose estimation is the computer vision task of detecting and tracking the position and orientation of human bodies, hands, or objects from images or video, typically by locating keypoints such as joints.
Prompt Caching
Prompt caching is an inference optimisation technique that stores precomputed key-value representations of repeated prompt prefixes, reducing latency and token processing costs for applications with stable system prompts or long shared contexts.
Reasoning Models
Reasoning models are large language models trained to generate extended internal deliberation before producing a final answer, using test-time compute to improve accuracy on complex tasks such as mathematics, coding, and multi-step logic.
Residual Network
A deep convolutional neural network architecture introduced by Microsoft Research in 2015 that uses skip connections to enable training of very deep networks, winning the ImageNet challenge with a top-5 error rate of 3.57%.
Speech Recognition
Speech recognition, or automatic speech recognition (ASR), is the technology that enables computers to identify and transcribe spoken language into text using acoustic models, language models, and deep learning architectures.
Transfer Learning
Transfer learning is a machine learning technique in which a model pre-trained on one task or dataset is adapted for a different but related task, enabling high performance with significantly less data and compute than training from scratch.
Vision Transformer
The Vision Transformer (ViT) is a deep learning model that applies the transformer architecture originally designed for NLP directly to sequences of image patches, achieving state-of-the-art results on visual recognition tasks.