<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>AILinkDeepTech</title><description>Technical blog on Artificial Intelligence, Embodied Intelligence, Robotics, Computer Vision, 3D Reconstruction, LLMs, and AGI.</description><link>https://ailinkdeeptech.com/</link><item><title>Proximal Policy Optimization (PPO) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/ppo_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/ppo_algo/</guid><description>A PyTorch implementation of Proximal Policy Optimization (PPO) with a clipped surrogate objective, shared actor-critic network, Gaussian policy, and value/entropy losses.</description><pubDate>Wed, 14 Oct 2026 00:00:00 GMT</pubDate></item><item><title>Soft Actor-Critic (SAC) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/sac_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/sac_algo/</guid><description>A PyTorch implementation of Soft Actor-Critic (SAC) with a stochastic squashed Gaussian policy, twin Q-networks with target networks, automatic temperature tuning, and a replay buffer for continuous control.</description><pubDate>Thu, 24 Sep 2026 00:00:00 GMT</pubDate></item><item><title>Neural Radiance Fields (NeRF) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/nerf_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/nerf_algo/</guid><description>A PyTorch implementation of Neural Radiance Fields (NeRF): positional encoding for positions and view directions, MLP with skip connections, density/color prediction, stratified sampling, and volumetric rendering.</description><pubDate>Tue, 01 Sep 2026 00:00:00 GMT</pubDate></item><item><title>Rotary Position Embedding (RoPE) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/rope_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/rope_algo/</guid><description>A PyTorch implementation of Rotary Position Embedding (RoPE): inverse frequency buffer, precomputed cos/sin cache, query/key rotation, and shape verification.</description><pubDate>Sun, 02 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Multi-Agent Embodied Systems: CTDE, Shared 3DGS Maps, and Foundation Model Coordination</title><link>https://ailinkdeeptech.com/articles/multi-agent-embodied-systems-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/multi-agent-embodied-systems-2026/</guid><description>Master multi-agent embodied systems: CTDE reinforcement learning, shared 3DGS maps, dynamic role allocation, and heterogeneous robot team deployment.</description><pubDate>Fri, 17 Jul 2026 10:00:00 GMT</pubDate></item><item><title>World Models for Embodied AI: Recurrent State Space Models (RSSM), Latent Dynamics, and Model-Based MPC</title><link>https://ailinkdeeptech.com/articles/world-models-embodied-ai-tutorial-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/world-models-embodied-ai-tutorial-2026/</guid><description>Master World Models for Embodied AI: Recurrent State Space Models (RSSM), latent dynamics, model-based MPC planning, and VLA policy integration in PyTorch.</description><pubDate>Fri, 17 Jul 2026 10:00:00 GMT</pubDate></item><item><title>Stable Diffusion (DDPM): Minimal PyTorch Implementation</title><link>https://ailinkdeeptech.com/research/stablediffusion_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/stablediffusion_algo/</guid><description>A minimal PyTorch implementation of a Denoising Diffusion Probabilistic Model (DDPM): sinusoidal time embeddings, U-Net with skip connections, forward noising, reverse denoising, and ancestral sampling.</description><pubDate>Wed, 24 Jun 2026 00:00:00 GMT</pubDate></item><item><title>NeRF: Neural Radiance Fields, Differentiable Volume Rendering, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/nerf/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/nerf/</guid><description>Master NeRF (Neural Radiance Fields): 5D radiance fields, differentiable volume rendering, Fourier positional encoding, hierarchical sampling, and PyTorch.</description><pubDate>Mon, 22 Jun 2026 12:36:00 GMT</pubDate></item><item><title>Training Qwen3-VL-8B Vision with GRPO: Multimodal Policy Optimization and Reward Engineering</title><link>https://ailinkdeeptech.com/cookbook/qwen3_vl_8b_vision_grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_vl_8b_vision_grpo/</guid><description>Train Qwen3-VL-8B Vision with GRPO: multimodal policy optimization, two-tier visual reward functions, and 16-bit LoRA under 15GB VRAM.</description><pubDate>Thu, 18 Jun 2026 12:00:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen3.5-4B Vision with Unsloth: High-Precision Multimodal SFT on 10GB VRAM</title><link>https://ailinkdeeptech.com/cookbook/qwen3_5_4b_vision/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_5_4b_vision/</guid><description>Fine-tune Qwen3.5-4B Vision using Unsloth: 16-bit LoRA optimization, multi-modal patch projection, and Q4_K_M GGUF edge deployment on consumer GPUs.</description><pubDate>Thu, 11 Jun 2026 11:37:00 GMT</pubDate></item><item><title>Vision-Language-Action (VLA) Models for Robotic Manipulation: Architecture, Rectified Flow Matching, and Sim-to-Real Deployment</title><link>https://ailinkdeeptech.com/articles/vision-language-action-vla-model-robotic-manipulation-tutorial-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/vision-language-action-vla-model-robotic-manipulation-tutorial-2026/</guid><description>Master Vision-Language-Action (VLA) models: continuous Flow Matching action heads, cross-embodiment datasets, Action Chunking, and Isaac Lab sim-to-real.</description><pubDate>Thu, 11 Jun 2026 10:00:00 GMT</pubDate></item><item><title>Transformer Encoder Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/transformer_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/transformer_algo/</guid><description>A compact PyTorch implementation of a Transformer encoder with multi-head self-attention, sinusoidal positional encoding, feed-forward layers, residual connections, and padding masks.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate></item><item><title>Fine-Tuning FLUX.2 Klein with Kohya_ss: Edge MMDiT LoRA Training, Flow Matching, and VRAM Optimization</title><link>https://ailinkdeeptech.com/cookbook/flux2_klein_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/flux2_klein_lora/</guid><description>Train FLUX.2 Klein LoRA on 8GB GPUs using Kohya_ss: compact 4B MMDiT flow matching, CLIP-L conditioning, latent caching, and ComfyUI deployment.</description><pubDate>Wed, 03 Jun 2026 06:15:00 GMT</pubDate></item><item><title>Training Qwen3.5-4B-Vision with GRPO: Multimodal Policy Optimization and Reward Engineering</title><link>https://ailinkdeeptech.com/cookbook/qwen3_5_4b_vision_grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_5_4b_vision_grpo/</guid><description>Train Qwen3.5-4B Vision with GRPO: multimodal policy optimization, two-tier visual reward functions, and 16-bit LoRA under 15GB VRAM.</description><pubDate>Mon, 01 Jun 2026 12:00:00 GMT</pubDate></item><item><title>Fine-Tuning OpenAI gpt-oss-20B with Unsloth: 4-bit MoE QLoRA and Harmony Chat Templates</title><link>https://ailinkdeeptech.com/cookbook/gpt-oss-fine-tuning/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/gpt-oss-fine-tuning/</guid><description>Fine-tune OpenAI gpt-oss-20B MoE using Unsloth on 16GB GPUs: 4-bit QLoRA, Harmony chat templates, channel separation, and SFTTrainer pipeline.</description><pubDate>Sat, 30 May 2026 07:20:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen3-VL-8B Vision with Unsloth: Multimodal LoRA and LaTeX OCR</title><link>https://ailinkdeeptech.com/cookbook/qwen3_vl_8b_vision/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_vl_8b_vision/</guid><description>Fine-tune Qwen3-VL-8B Vision on LaTeX OCR tasks with Unsloth: 4-bit NF4 QLoRA, multimodal token collation, and GGUF export under 8.5GB VRAM.</description><pubDate>Wed, 27 May 2026 12:03:00 GMT</pubDate></item><item><title>Video Generation Foundation Models: 3D DiT Architectures, Flow Matching, and Spatiotemporal Attention</title><link>https://ailinkdeeptech.com/articles/video-generation-foundation-models-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/video-generation-foundation-models-2026/</guid><description>Master Video Generation Foundation Models: 3D Diffusion Transformers, continuous Flow Matching, 3D VAE compression, and open-source PyTorch pipelines.</description><pubDate>Thu, 21 May 2026 10:00:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen3.5-0.8B Vision with Unsloth: Sub-3GB Multimodal Edge Alignment</title><link>https://ailinkdeeptech.com/cookbook/qwen3_5_0_8b_vision/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_5_0_8b_vision/</guid><description>Fine-tune Qwen3.5-0.8B Vision on VQA tasks using Unsloth: BF16 LoRA optimization, multi-modal token alignment, and GGUF edge deployment under 3GB VRAM.</description><pubDate>Tue, 19 May 2026 11:13:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen3.5-2B Vision with Unsloth: Document VQA and 16-bit LoRA Alignment</title><link>https://ailinkdeeptech.com/cookbook/qwen3_5_2b_vision/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_5_2b_vision/</guid><description>Fine-tune Qwen3.5-2B Vision on document VQA using Unsloth: 16-bit LoRA optimization, multi-modal OCR token alignment, and GGUF export under 5GB VRAM.</description><pubDate>Mon, 18 May 2026 11:30:00 GMT</pubDate></item><item><title>OpenClaw: Architecture, Gateway Routing, Sandboxed MCP Skills, and Multi-Channel Deployment</title><link>https://ailinkdeeptech.com/articles/openclaw-self-hosted-personal-ai-agent-complete-2026-tutorial/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/openclaw-self-hosted-personal-ai-agent-complete-2026-tutorial/</guid><description>Master OpenClaw: self-hosted gateway routing, Docker sandbox isolation, SKILL.md progressive disclosure, MCP servers, and multi-channel messaging deployment.</description><pubDate>Sat, 16 May 2026 10:00:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen3-4B-Thinking with Unsloth: DeepSeek-R1 Distillation and Dual-Mode Inference</title><link>https://ailinkdeeptech.com/cookbook/qwen3_4b_thinking/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_4b_thinking/</guid><description>Fine-tune Qwen3-4B-Thinking on DeepSeek-R1 CoT traces with Unsloth: OpenMathReasoning alignment, thinking-mode toggles, and GGUF multi-quant export.</description><pubDate>Fri, 15 May 2026 13:20:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen3-14B Reasoning and Conversational Modes with Unsloth</title><link>https://ailinkdeeptech.com/cookbook/qwen3_14_reasoning-conversational/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_14_reasoning-conversational/</guid><description>Fine-tune Qwen3-14B dual-mode reasoning and chat: 75/25 mixed-dataset distillation, 4-bit QLoRA, and GGUF multi-quant export on 12GB VRAM.</description><pubDate>Fri, 08 May 2026 12:00:00 GMT</pubDate></item><item><title>Training gpt-oss-20B with GRPO: Multi-Objective Reinforcement Learning</title><link>https://ailinkdeeptech.com/cookbook/gpt-oss-20b-grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/gpt-oss-20b-grpo/</guid><description>Train gpt-oss-20B MoE using GRPO: AST sandboxing, anti-reward hacking, 4-bit QLoRA, and execution benchmark reward engineering.</description><pubDate>Sun, 03 May 2026 12:49:00 GMT</pubDate></item><item><title>Fine-Tuning FLUX.1 Dev with Kohya_ss: MMDiT LoRA Training, Flow Matching, and ComfyUI Workflow</title><link>https://ailinkdeeptech.com/cookbook/flux1_dev_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/flux1_dev_lora/</guid><description>Master FLUX.1 Dev LoRA fine-tuning with Kohya_ss: MMDiT joint attention, Flow Matching velocity loss, text encoder freezing, and ComfyUI deployment.</description><pubDate>Fri, 01 May 2026 06:14:00 GMT</pubDate></item><item><title>Microsoft TRELLIS: Structured 3D Latents (SLAT), Rectified Flow Transformers, and Unified Multi-Format 3D Generation</title><link>https://ailinkdeeptech.com/articles/trellis-structured-3d-latents-text-to-3d-microsoft-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/trellis-structured-3d-latents-text-to-3d-microsoft-2026/</guid><description>Master Microsoft TRELLIS: Structured 3D Latents (SLAT), Rectified Flow Transformers, and unified decoding into 3D Gaussian Splats, NeRFs, and meshes.</description><pubDate>Mon, 27 Apr 2026 10:00:00 GMT</pubDate></item><item><title>Training SDXL LoRA with Kohya_ss: Dataset Curation, Loss Formulation, and Rank Tuning</title><link>https://ailinkdeeptech.com/cookbook/sdxl_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/sdxl_lora/</guid><description>Train high-fidelity SDXL LoRAs with Kohya_ss: latent diffusion objective, cross-attention projection tuning, multi-aspect bucketing, and ComfyUI deployment.</description><pubDate>Wed, 22 Apr 2026 06:13:00 GMT</pubDate></item><item><title>Training Qwen3 4B with GRPO: Two-Stage Reasoning Alignment and Reward Engineering</title><link>https://ailinkdeeptech.com/cookbook/qwen3_4b_grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_4b_grpo/</guid><description>Train Qwen3-4B with GRPO on 16GB GPUs: two-stage format pre-tuning, 4-tier composite reward shaping, rsLoRA, and vLLM acceleration.</description><pubDate>Tue, 21 Apr 2026 12:52:00 GMT</pubDate></item><item><title>Training Qwen3-8B-FP8 with GRPO: Native 8-Bit Reinforcement Learning on Single GPUs</title><link>https://ailinkdeeptech.com/cookbook/qwen3_8b_fp8_grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_8b_fp8_grpo/</guid><description>Train Qwen3-8B in native FP8 precision using GRPO reinforcement learning: memory-efficient policy updates, multi-tier reward functions, and 20GB VRAM execution.</description><pubDate>Tue, 21 Apr 2026 12:42:00 GMT</pubDate></item><item><title>Hunyuan3D-2: High-Resolution Text-to-3D, Flow-Matching DiT, and 2K PBR Texture Synthesis</title><link>https://ailinkdeeptech.com/articles/hunyuan3d-2-tencent-high-resolution-text-to-3d-image-to-3d-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/hunyuan3d-2-tencent-high-resolution-text-to-3d-image-to-3d-2026/</guid><description>Master Tencent&apos;s Hunyuan3D-2: explore the decoupled Hunyuan3D-DiT shape generator, Hunyuan3D-Paint 2K PBR texture synthesis, and Blender pipeline.</description><pubDate>Fri, 17 Apr 2026 10:00:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen3-4B-Instruct with Unsloth: Instruction Alignment and Response Masking</title><link>https://ailinkdeeptech.com/cookbook/qwen3_4b_instruct/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen3_4b_instruct/</guid><description>Fine-tune Qwen3-4B-Instruct with Unsloth: response-only loss masking, 4-bit QLoRA, memory profiling under 8GB VRAM, and GGUF multi-quant export.</description><pubDate>Wed, 15 Apr 2026 12:00:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen-Image 20B with AI-Toolkit: uint3 Quantization, ARA Adapters, and Flow Matching</title><link>https://ailinkdeeptech.com/cookbook/qwen_image_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen_image_lora/</guid><description>Train 20B Qwen-Image LoRA on 24GB GPUs using AI-Toolkit: uint3 quantization, Accuracy Recovery Adapters (ARA), Flow Matching, and ComfyUI deployment.</description><pubDate>Mon, 13 Apr 2026 07:00:00 GMT</pubDate></item><item><title>Multi-Modal Agents: VLA Architectures, Flow Matching, and Isaac Lab Deployment</title><link>https://ailinkdeeptech.com/articles/multimodal-agents-text-vision-action-embodied-intelligence-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/multimodal-agents-text-vision-action-embodied-intelligence-2026/</guid><description>Master multimodal embodied agents: Vision-Language-Action (VLA) backbones, flow-matching continuous control, hierarchical memory, and Isaac Lab sim-to-real.</description><pubDate>Sun, 12 Apr 2026 10:00:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen2.5-Coder-1.5B for Tool Calling: Hermes Schema Alignment with Unsloth</title><link>https://ailinkdeeptech.com/cookbook/qwen2_5_coder_1_5b_tool_calling/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen2_5_coder_1_5b_tool_calling/</guid><description>Fine-tune Qwen2.5-Coder-1.5B for tool calling using Unsloth: Hermes JSON schema formatting, 4-bit QLoRA, multi-tool dispatch, and edge deployment.</description><pubDate>Fri, 10 Apr 2026 13:07:00 GMT</pubDate></item><item><title>Training LTX-2 Character-Consistent Video LoRA: In-Context Conditioning (IC-LoRA) and ComfyUI Deployment</title><link>https://ailinkdeeptech.com/cookbook/character_consistent_character_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/character_consistent_character_lora/</guid><description>Master LTX-2 Character-Consistent Video LoRA training: in-context conditioning (IC-LoRA), paired dataset curation, YAML configs, and ComfyUI deployment.</description><pubDate>Fri, 03 Apr 2026 07:50:00 GMT</pubDate></item><item><title>Fine-Tuning FLUX.2-dev with AI-Toolkit: MMDiT LoRA Training, Flow Matching, and Prodigy Optimization</title><link>https://ailinkdeeptech.com/cookbook/flux_2_dev_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/flux_2_dev_lora/</guid><description>Master FLUX.2-dev LoRA fine-tuning with AI-Toolkit: MMDiT flow matching, dataset curation, Prodigy adaptive optimization, and ComfyUI deployment.</description><pubDate>Fri, 03 Apr 2026 07:00:00 GMT</pubDate></item><item><title>Fine-Tuning Qwen-Image-Edit-2511 with AI-Toolkit: Paired MMDiT LoRA Training and Flow Matching</title><link>https://ailinkdeeptech.com/cookbook/qwen_image_edit_2511_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/qwen_image_edit_2511_lora/</guid><description>Train Qwen-Image-Edit-2511 LoRA using AI-Toolkit: paired MMDiT datasets, qfloat8 quantization, Diff Output Preservation, and ComfyUI deployment.</description><pubDate>Fri, 03 Apr 2026 07:00:00 GMT</pubDate></item><item><title>Accelerating Mixture-of-Experts Fine-Tuning: Unsloth Faster MoE, Split LoRA, and Grouped GEMM</title><link>https://ailinkdeeptech.com/cookbook/faster-moe/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/faster-moe/</guid><description>Accelerate MoE LLM fine-tuning with Unsloth Faster MoE: torch._grouped_mm, Triton fused kernels, Split LoRA memory optimization, and benchmarks.</description><pubDate>Mon, 30 Mar 2026 10:38:00 GMT</pubDate></item><item><title>HunyuanVideo: 13B Video DiT, Flow Matching, and 3D VAE Latent Compression</title><link>https://ailinkdeeptech.com/articles/hunyuanvideo-tencent-text-to-video-generation-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/hunyuanvideo-tencent-text-to-video-generation-2026/</guid><description>Master Tencent&apos;s HunyuanVideo: 13B parameter flow-matching DiT, Causal 3D VAE compression, MLLM text conditioning, and PyTorch deployment.</description><pubDate>Tue, 17 Mar 2026 10:00:00 GMT</pubDate></item><item><title>Real-Time 3D Gaussian Splatting: Mathematical Derivations, CUDA Rasterization, and PyTorch Training</title><link>https://ailinkdeeptech.com/articles/real-time-3d-gaussian-splatting-tutorial-2026-5/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/real-time-3d-gaussian-splatting-tutorial-2026-5/</guid><description>Master 3D Gaussian Splatting from scratch: anisotropic covariance decomposition, spherical harmonics, tile-based CUDA rasterization, and PyTorch training.</description><pubDate>Mon, 16 Mar 2026 10:00:00 GMT</pubDate></item><item><title>Text-to-3D Gaussian Splatting: Score Distillation Sampling, Diffusion Priors, and PyTorch Training</title><link>https://ailinkdeeptech.com/articles/text-to-3d-gaussian-splatting-diffusion-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/text-to-3d-gaussian-splatting-diffusion-2026/</guid><description>Master Text-to-3D with Gaussian Splatting: Score Distillation Sampling (SDS), diffusion guidance, differentiable gsplat rendering, and PyTorch pipelines.</description><pubDate>Tue, 10 Mar 2026 10:00:00 GMT</pubDate></item><item><title>Training Llama 3.2 (3B) with GRPO and LoRA: Multi-Reward Reasoning RL</title><link>https://ailinkdeeptech.com/cookbook/advanced_llama3_2_3b_grpo_lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/advanced_llama3_2_3b_grpo_lora/</guid><description>Train Llama 3.2 (3B) with GRPO and LoRA: multi-reward optimization, SFT format warm-up, cosine similarity scoring, and PyTorch deployment.</description><pubDate>Sun, 01 Mar 2026 13:02:00 GMT</pubDate></item><item><title>Hermes Agent by Nous Research: Architecture, Self-Improving Loops, and MCP Integration</title><link>https://ailinkdeeptech.com/articles/hermes-agent-nous-research-self-improving-ai-agent-2026-tutorial/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/hermes-agent-nous-research-self-improving-ai-agent-2026-tutorial/</guid><description>Master Hermes Agent by Nous Research: explore the closed learning loop, hierarchical memory, progressive skill discovery, and multi-backend MCP integration.</description><pubDate>Thu, 19 Feb 2026 10:00:00 GMT</pubDate></item><item><title>GS-SLAM + VLA: Real-Time Gaussian Splatting SLAM with Vision-Language-Action Models for Robotic Manipulation</title><link>https://ailinkdeeptech.com/articles/gs-slam-vla-robotic-manipulation-tutorial-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/gs-slam-vla-robotic-manipulation-tutorial-2026/</guid><description>Deploy GS-SLAM with VLA models for robotic manipulation: 3D Gaussian spatial grounding, cross-attention feature fusion, and closed-loop control.</description><pubDate>Wed, 18 Feb 2026 10:00:00 GMT</pubDate></item><item><title>Scaffold-GS: Structured 3D Gaussians, Sparse Voxel Anchors, and Model Compression</title><link>https://ailinkdeeptech.com/articles/scaffold-gs-structured-3d-gaussians-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/scaffold-gs-structured-3d-gaussians-2026/</guid><description>Master Scaffold-GS: sparse voxel anchor grids, shared neural MLP predictors, view-dependent LOD rendering, and 10x-100x Gaussian splat compression.</description><pubDate>Wed, 11 Feb 2026 14:00:00 GMT</pubDate></item><item><title>Scaling LLM Pretraining with DeepSpeed and Megatron-LM: 3D Parallelism, ZeRO-3, and Multi-Node Systems</title><link>https://ailinkdeeptech.com/cookbook/deepspeed_megatron/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/deepspeed_megatron/</guid><description>Master distributed LLM pretraining (13B–70B+) with DeepSpeed and Megatron-LM: 3D Parallelism (TP/PP/DP), ZeRO-3, FP8 TransformerEngine, and multi-node NCCL.</description><pubDate>Tue, 03 Feb 2026 08:10:00 GMT</pubDate></item><item><title>Training Llama 3.2 1B with FP8 Quantization and GRPO Reinforcement Learning</title><link>https://ailinkdeeptech.com/cookbook/llama_fp8_grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/llama_fp8_grpo/</guid><description>Train Llama 3.2 1B using hardware FP8 quantization and GRPO: 4-layer reward shaping, vLLM weight sharing, and 60% VRAM reduction.</description><pubDate>Sun, 01 Feb 2026 13:30:00 GMT</pubDate></item><item><title>Training Llama 3.1 8B with GRPO: Reasoning Alignment and 5-Tier Reward Shaping</title><link>https://ailinkdeeptech.com/cookbook/llama3_1_8b_grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/llama3_1_8b_grpo/</guid><description>Train Llama 3.1 8B with GRPO using Unsloth on a single 16GB GPU: 5-tier composite reward functions, 4-bit QLoRA, XML reasoning, and vLLM acceleration.</description><pubDate>Sun, 11 Jan 2026 12:30:00 GMT</pubDate></item><item><title>Gaussian Splatting SLAM (GS-SLAM): Real-Time Dense Mapping and Tracking with 3DGS</title><link>https://ailinkdeeptech.com/articles/gaussian-splatting-slam-gs-slam-real-time-dense-mapping-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/gaussian-splatting-slam-gs-slam-real-time-dense-mapping-2026/</guid><description>Master Gaussian Splatting SLAM (GS-SLAM): real-time pose tracking, incremental Gaussian mapping, loop closure, and PyTorch deployment on RGB-D streams.</description><pubDate>Sun, 11 Jan 2026 10:00:00 GMT</pubDate></item><item><title>Training DeepSeek-R1 Distilled Qwen3 (8B) with GRPO: Multi-Objective RL</title><link>https://ailinkdeeptech.com/cookbook/deepseek_r1_0528_qwen3_8b_grpo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/cookbook/deepseek_r1_0528_qwen3_8b_grpo/</guid><description>Train DeepSeek-R1 distilled Qwen3 (8B) using GRPO: multi-signal reward functions, group advantage normalization, and single-GPU fine-tuning.</description><pubDate>Thu, 01 Jan 2026 13:00:00 GMT</pubDate></item><item><title>4D Gaussian Splatting for Dynamic Scenes: Canonical Fields, HexPlane Deformation, and Real-Time Rendering</title><link>https://ailinkdeeptech.com/articles/4d-gaussian-splatting-dynamic-scenes-tutorial-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/4d-gaussian-splatting-dynamic-scenes-tutorial-2026/</guid><description>Master 4D Gaussian Splatting: canonical space formulation, HexPlane vs. MLP deformation fields, real-time PyTorch training, and robotics digital twins.</description><pubDate>Fri, 19 Dec 2025 09:00:00 GMT</pubDate></item><item><title>3D Gaussian Splatting for Embodied AI &amp; Robotics: Real-Time Perception, Grasp Planning, and Sim-to-Real</title><link>https://ailinkdeeptech.com/articles/3d-gaussian-splatting-embodied-ai-robotics-2026/</link><guid isPermaLink="true">https://ailinkdeeptech.com/articles/3d-gaussian-splatting-embodied-ai-robotics-2026/</guid><description>Deploy 3D Gaussian Splatting in robotics: real-time scene reconstruction, Mahalanobis collision checking, 6-DoF grasp planning, and sim-to-real transfer.</description><pubDate>Wed, 17 Dec 2025 11:30:00 GMT</pubDate></item><item><title>LTX-2 Architecture: Asymmetric Dual-Stream Audio-Video DiT and Flow Matching</title><link>https://ailinkdeeptech.com/research/ltx-2/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/ltx-2/</guid><description>Master LTX-2: asymmetric dual-stream video/audio DiT, 1D/3D RoPE alignment, cross-modality adaLN, multimodal guidance (CFG/STG), and PyTorch pipelines.</description><pubDate>Sat, 13 Dec 2025 00:00:00 GMT</pubDate></item><item><title>Direct Preference Optimization (DPO) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/dpo_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/dpo_algo/</guid><description>A PyTorch implementation of Direct Preference Optimization (DPO): a small LSTM language model, a preference dataset, and a DPO trainer that optimizes a policy against a frozen reference via the sigmoid logistic DPO loss on chosen/rejected pairs.</description><pubDate>Mon, 01 Dec 2025 00:00:00 GMT</pubDate></item><item><title>Group Relative Policy Optimization (GRPO) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/grpo_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/grpo_algo/</guid><description>A PyTorch implementation of Group Relative Policy Optimization (GRPO): a Group-relative RL approach that partitions sorted trajectories into groups, weights group-relative advantages, and applies clipped surrogate updates with PPO-style ratios.</description><pubDate>Mon, 24 Nov 2025 00:00:00 GMT</pubDate></item><item><title>Deep Deterministic Policy Gradient (DDPG) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/ddpg_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/ddpg_algo/</guid><description>A PyTorch implementation of Deep Deterministic Policy Gradient (DDPG): an Actor that outputs tanh-bounded deterministic actions, a Q-value Critic over state-action pairs, a replay buffer, target networks with soft updates, and a smoke test that exercises action selection and a short training loop.</description><pubDate>Sat, 22 Nov 2025 00:00:00 GMT</pubDate></item><item><title>LLaVA (Large Language and Vision Assistant) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/llava_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/llava_algo/</guid><description>A PyTorch implementation of LLaVA: a ResNet-50 vision encoder, a Transformer-based language model, a custom cross-attention fusion layer, and an enhanced tokenizer for image-grounded text generation.</description><pubDate>Sun, 09 Nov 2025 00:00:00 GMT</pubDate></item><item><title>Diffusion Transformers (DiT): Architecture, adaLN-Zero Modulation, and Latent Scaling Laws</title><link>https://ailinkdeeptech.com/research/diffusion_transformer/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/diffusion_transformer/</guid><description>Master Diffusion Transformers (DiT): latent patchification, adaLN-Zero conditioning, multi-modal MMDiT joint attention, scaling laws, and PyTorch pipelines.</description><pubDate>Wed, 05 Nov 2025 00:00:00 GMT</pubDate></item><item><title>Diffusion Transformer (DiT) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/diffusiontransformer_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/diffusiontransformer_algo/</guid><description>A PyTorch implementation of the Diffusion Transformer (DiT): a patch-embedded Vision Transformer with sinusoidal timestep conditioning, multi-head self-attention, MLP blocks, and a transposed-conv head that predicts the image-space noise.</description><pubDate>Tue, 04 Nov 2025 00:00:00 GMT</pubDate></item><item><title>Deep Q-Network (DQN) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/dqn_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/dqn_algo/</guid><description>A PyTorch implementation of Deep Q-Network (DQN): a Q-value MLP, a replay buffer, an ε-greedy agent with target network, Bellman loss update, and a CartPole-v1 training/test loop using Gymnasium.</description><pubDate>Sat, 01 Nov 2025 00:00:00 GMT</pubDate></item><item><title>Low-Rank Adaptation (LoRA) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/lora_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/lora_algo/</guid><description>A PyTorch implementation of Low-Rank Adaptation (LoRA): low-rank A/B matrices wrapped around a frozen linear layer, scaled by alpha/rank, with shape, freezing, and rank-property tests.</description><pubDate>Mon, 27 Oct 2025 00:00:00 GMT</pubDate></item><item><title>Denoising Diffusion Probabilistic Model (DDPM) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/diffusion_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/diffusion_algo/</guid><description>A PyTorch implementation of a Denoising Diffusion Probabilistic Model (DDPM): a linear-beta forward diffusion, a reverse sampling loop, a time-conditioned UNet denoising network, and a training-free smoke test that forward-diffuses, predicts noise, and samples images.</description><pubDate>Mon, 20 Oct 2025 00:00:00 GMT</pubDate></item><item><title>FlashAttention Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/flashattention_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/flashattention_algo/</guid><description>A PyTorch implementation of FlashAttention-style multi-head attention: a softmax-scaled dot-product attention block, a tiled/blocked variant that processes sequence chunks for memory efficiency, and basic shape tests.</description><pubDate>Sun, 19 Oct 2025 00:00:00 GMT</pubDate></item><item><title>Mixture of Experts (MoE) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/moe_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/moe_algo/</guid><description>A PyTorch implementation of the Mixture of Experts (MoE) layer with a top-k gating network, multiple expert MLPs, and weighted expert outputs for sparse expert routing.</description><pubDate>Fri, 17 Oct 2025 00:00:00 GMT</pubDate></item><item><title>ControlNet Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/controlnet_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/controlnet_algo/</guid><description>A minimal PyTorch ControlNet implementation: a control encoder with conv blocks, residual skip connections, channel attention, and a zero-initialized projection that adds residual control features into a backbone so that the model behaves as identity at init.</description><pubDate>Thu, 09 Oct 2025 00:00:00 GMT</pubDate></item><item><title>Denoising Diffusion Implicit Model (DDIM) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/ddim_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/ddim_algo/</guid><description>A PyTorch implementation of a Denoising Diffusion Implicit Model (DDIM) sampler: a UNet denoiser with GELU time conditioning, an eta-controlled stochastic-to-deterministic reverse process on a sub-sequence of timesteps, and a smoke test that verifies noise addition, model output, sampling shapes, and deterministic reproducibility.</description><pubDate>Wed, 08 Oct 2025 00:00:00 GMT</pubDate></item><item><title>Denoising Diffusion Probabilistic Model (DDPM) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/ddpm_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/ddpm_algo/</guid><description>A PyTorch implementation of a Denoising Diffusion Probabilistic Model (DDPM): a UNet denoiser with sinusoidal-free linear time conditioning, a linear-beta forward diffusion, an iterative reverse sampling loop, and a smoke test that verifies noise addition, model output, and sampling shapes.</description><pubDate>Sun, 21 Sep 2025 00:00:00 GMT</pubDate></item><item><title>PagedAttention: Virtual-Memory KV Cache Management, Continuous Batching, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/pagedattention/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/pagedattention/</guid><description>Master PagedAttention: virtual memory KV cache paging, block tables, prefix caching (CoW), continuous batching, memory fragmentation math, and PyTorch kernels.</description><pubDate>Thu, 18 Sep 2025 00:00:00 GMT</pubDate></item><item><title>DeepSeek Architecture Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/deepseek_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/deepseek_algo/</guid><description>A PyTorch implementation of the DeepSeek-style architecture: RMSNorm pre-norm blocks, a multi-head latent attention module, a Mixture-of-Experts (MoE) feed-forward router, and a stack of DeepSeek blocks with token-level residual paths.</description><pubDate>Tue, 09 Sep 2025 00:00:00 GMT</pubDate></item><item><title>DDIM (Denoising Diffusion Implicit Models): Non-Markovian Sampling and Probability-Flow ODEs</title><link>https://ailinkdeeptech.com/research/ddim/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/ddim/</guid><description>Master DDIM (Denoising Diffusion Implicit Models): non-Markovian sampling, probability-flow ODE derivations, deterministic inference, and PyTorch pipelines.</description><pubDate>Fri, 05 Sep 2025 00:00:00 GMT</pubDate></item><item><title>Vision Transformer (ViT) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/visiontransformer_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/visiontransformer_algo/</guid><description>A PyTorch implementation of the Vision Transformer (ViT) with patch embedding, learnable class token and position embeddings, multi-head self-attention, MLP blocks, and classification head.</description><pubDate>Thu, 04 Sep 2025 00:00:00 GMT</pubDate></item><item><title>Vision Transformer (ViT): Patch Embedding, Self-Attention, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/vision_transformer/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/vision_transformer/</guid><description>Master the Vision Transformer (ViT): patch projection, class tokens, multi-head self-attention over patches, DeiT augmentation, and PyTorch implementations.</description><pubDate>Mon, 01 Sep 2025 00:00:00 GMT</pubDate></item><item><title>LLaMA Transformer Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/llama_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/llama_algo/</guid><description>A from-scratch PyTorch implementation of the LLaMA-style Transformer: RMSNorm, Rotary Position Embeddings (RoPE), GQA-style multi-head attention with causal mask, SwiGLU MLP, and a stack of pre-norm decoder layers.</description><pubDate>Wed, 27 Aug 2025 00:00:00 GMT</pubDate></item><item><title>RoPE (Rotary Position Embedding): Mathematical Foundations, Complex Rotations, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/rope/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/rope/</guid><description>Master RoPE (Rotary Position Embedding): complex rotation algebra, relative distance invariance proof, long-context scaling (YaRN), and PyTorch kernels.</description><pubDate>Mon, 11 Aug 2025 00:00:00 GMT</pubDate></item><item><title>DDPM: Denoising Diffusion Probabilistic Models, ELBO Derivation, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/ddpm/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/ddpm/</guid><description>Master DDPM: forward and reverse Gaussian Markov chains, closed-form ELBO derivation, noise-prediction parameterization, and PyTorch training pipelines.</description><pubDate>Tue, 05 Aug 2025 00:00:00 GMT</pubDate></item><item><title>3D Gaussian Splatting (3DGS) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/3dgs_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/3dgs_algo/</guid><description>A PyTorch implementation of 3D Gaussian Splatting from scratch: per-Gaussian learnable positions, scales, quaternions and RGBA, 3D covariance via R S Sᵀᵀ, projection to 2D via the perspective Jacobian, splat-based alpha compositing over a pixel grid, and a smoke test that checks initialization, symmetry/orthogonality of covariances, and the rendering output shape and value range.</description><pubDate>Mon, 04 Aug 2025 00:00:00 GMT</pubDate></item><item><title>Diffusion Models: Mathematical Foundations, Score Matching, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/diffusion/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/diffusion/</guid><description>Master diffusion models: forward Markov perturbations, reverse ELBO derivations, score-based SDE unifications, and production PyTorch training pipelines.</description><pubDate>Fri, 01 Aug 2025 00:00:00 GMT</pubDate></item><item><title>Asynchronous Advantage Actor-Critic (A3C) Implementation in PyTorch</title><link>https://ailinkdeeptech.com/research/a3c_algo/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/a3c_algo/</guid><description>A PyTorch implementation of Asynchronous Advantage Actor-Critic (A3C): a shared Actor-Critic network with a softmax policy head, multiple Worker processes that collect CartPole trajectories, compute n-step returns and advantages, and sync gradients into a global model, plus a greedy test harness that runs the trained policy in render mode.</description><pubDate>Sun, 20 Jul 2025 00:00:00 GMT</pubDate></item><item><title>4D Gaussian Splatting (4DGS): HexPlane Spatiotemporal Neural Fields and Dynamic Splatting</title><link>https://ailinkdeeptech.com/research/4dgs/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/4dgs/</guid><description>Master 4D Gaussian Splatting (4DGS): HexPlane spatiotemporal neural fields, canonical deformation fields, and real-time dynamic novel view synthesis.</description><pubDate>Thu, 10 Jul 2025 12:37:00 GMT</pubDate></item><item><title>3D Gaussian Splatting (3DGS): Differentiable Tile Rasterization and Explicit Radiance Fields</title><link>https://ailinkdeeptech.com/research/3dgs/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/3dgs/</guid><description>Master 3D Gaussian Splatting (3DGS): covariance matrix decomposition, tile-based differentiable rasterization, adaptive density control, and real-time CUDA pipelines.</description><pubDate>Fri, 04 Jul 2025 12:35:00 GMT</pubDate></item><item><title>LLaVA: Visual Instruction Tuning, Cross-Modal Projection, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/llava/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/llava/</guid><description>Master LLaVA: visual instruction tuning, 2-stage cross-modal projection, CLIP/SigLIP feature alignment, AnyRes scaling, and PyTorch VLM pipelines.</description><pubDate>Tue, 10 Jun 2025 00:00:00 GMT</pubDate></item><item><title>Stable Diffusion: Latent Diffusion Models, Cross-Attention U-Net, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/stable_diffusion/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/stable_diffusion/</guid><description>Master Stable Diffusion: latent diffusion models (LDM), perceptual VAE compression, cross-attention U-Net, classifier-free guidance, and PyTorch pipelines.</description><pubDate>Sun, 25 May 2025 00:00:00 GMT</pubDate></item><item><title>LoRA (Low-Rank Adaptation): Mathematical Foundations, Rank SVD Dynamics, and PyTorch PEFT Architecture</title><link>https://ailinkdeeptech.com/research/lora/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/lora/</guid><description>Master LoRA (Low-Rank Adaptation): low-rank matrix decomposition, intrinsic rank analysis, QLoRA NF4 quantization, DoRA, and PyTorch PEFT pipelines.</description><pubDate>Mon, 21 Apr 2025 00:00:00 GMT</pubDate></item><item><title>ControlNet: Zero-Convolution Architecture and Spatial Conditioning in Diffusion Models</title><link>https://ailinkdeeptech.com/research/controlnet/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/controlnet/</guid><description>Master ControlNet: zero-convolution weight initialization, trainable U-Net copy architecture, multi-condition composition, and PyTorch training pipelines.</description><pubDate>Sat, 05 Apr 2025 00:00:00 GMT</pubDate></item><item><title>3D Transformers: Point Clouds, Sparse Voxels, Vector Attention, and PyTorch Architecture</title><link>https://ailinkdeeptech.com/research/transformer3d/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/transformer3d/</guid><description>Master 3D Transformers: vector self-attention on point clouds, sparse voxel hashing, 3D Swin windowing, relative positional bias, and PyTorch architectures.</description><pubDate>Fri, 04 Apr 2025 00:00:00 GMT</pubDate></item><item><title>Llama Architecture: RMSNorm, SwiGLU, RoPE, GQA, and PyTorch Implementation</title><link>https://ailinkdeeptech.com/research/llama/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/llama/</guid><description>Master Llama architecture: RMSNorm pre-normalization, SwiGLU activations, RoPE relative embeddings, Grouped-Query Attention (GQA), and PyTorch pipelines.</description><pubDate>Sat, 15 Mar 2025 00:00:00 GMT</pubDate></item><item><title>The Transformer Architecture: Scaled Dot-Product Attention, Multi-Head Projections, and PyTorch Engine</title><link>https://ailinkdeeptech.com/research/transformer/</link><guid isPermaLink="true">https://ailinkdeeptech.com/research/transformer/</guid><description>Master the Transformer: scaled dot-product attention, multi-head projections, sinusoidal &amp; RoPE encodings, Pre-LN vs Post-LN stability, and PyTorch engines.</description><pubDate>Mon, 10 Feb 2025 00:00:00 GMT</pubDate></item></channel></rss>