ALLPCB
OpenAI Sora: a new AI model for video generation
Technical overview of OpenAI's Sora and its video generation capabilities, core machine learning foundations, and potential impacts on production workflows and society.
10 Key Moments in AI History
A concise technical review of AI history covering 10 pivotal milestones—from Dartmouth and perceptron to deep learning breakthroughs and the rise of large models.
Four Methods for Fine-Tuning Large Models
Technical overview of large-model fine-tuning and PEFT approaches, covering prompt/prefix tuning, P-tuning v2, AdaLoRA, adapter/LoRA methods and standard training workflow.
Popular LLM Inference Stacks and Setups
Survey of LLM inference stacks covering throughput, latency and cost; explains hardware constraints, KV cache, quantization, paged/grouped attention, and practical optimizations.
Why GPUs Are Suited for AI: AI Server Supply Chain Analysis
Technical overview of AI servers, GPU/CPU architectures, training vs inference, compute demand and market estimates, including H100/A100 performance and China server market
Five Core Network Requirements for Large AI Models
Network requirements for large-model GPU training: RDMA-based bandwidth, ultra-low latency, stability, and automated deployment for scalable multi-GPU clusters.
How to Achieve a Trillion-Transistor GPU
Analysis of semiconductor advances enabling AI scale: 3D integration, CoWoS/HBM packaging, silicon photonics and energy-efficient trends toward trillion-transistor GPUs.
Memory Interface Chips for AI Servers
Technical overview of AI server interconnects and components: DGX H100 architecture, PCIe switches and Retimers, and DDR5 memory interface chip trends.
AI and Machine Learning on Low-Power Microcontrollers
Technical overview of TinyML on MCUs: frameworks, model optimization (quantization, pruning), accelerators, toolchains, and deployment guidance for embedded systems.
VCS Verification Flow with VSO.ai
Overview of Synopsys VSO.ai integration into VCS and its AI-driven verification methods to accelerate coverage convergence, infer coverage, and reduce redundant regressions.
Deploy DeepSeek LLM on ELF 2 (RK3588) Development Board
Guide to converting and deploying the DeepSeek LLM on Rockchip RK3588 using RKLLM-Toolkit: environment setup, cross-compilation, model conversion and board deployment.
Common Deep Learning Methods for Small Object Detection
Survey of techniques for small object detection and face detection: image pyramids, FPNs, data augmentation, anchor strategies, SNIP/SNIPER training and context modeling.
AI-RAN Alliance Advances AI Integration in RAN
Overview of the AI-RAN Alliance formed at MWC 2024, its goals to integrate AI into radio access networks for 5G/6G, edge AI deployment, and contrast with OpenRAN.
AIGC basics and industry applications
Overview of AIGC and ChatGPT: technologies, industry chain, applications in text/image/video, e-commerce impact, and prompt engineering best practices.
Fourier Transform Fundamentals and Machine Learning Uses
Explains Fourier transform fundamentals, FFT use in signal processing and machine learning, and Python time-series examples for frequency-domain feature extraction.
EASY EAI Nano-TB (RV1126B) AIoT Board Data Sheet
Technical overview of the EASY EAI Nano-TB AIoT mainboard (RV1126B): quad-core Cortex-A53, up to 3 Tops NPU, dual MIPI CSI, MIPI DSI, dual GbE, WiFi 6, USB, GPIO, Linux SDK.
Visualization Techniques for Machine Learning
Guide to machine learning visualization techniques covering model structure, performance plots (ROC, confusion matrix), feature importance, and practical analysis.
AI in Image Super-Resolution and Upscaling
AI super-resolution and upscaling: GPU and transfer-learning advances, training-data limits, and applications in satellite, medical, gaming, and video-conferencing.
AI Smart Safety Helmet: Passive to Active Protection
Overview of AI smart safety helmet integrating AI vision, vital-sign and environmental sensors for real-time monitoring, alerts, positioning and intelligent management.
OpenAI's Defense Against LLM Attacks
OpenAI's study unveils an instruction hierarchy to boost LLM security against attacks like prompt injections, enhancing model safety.