AI Infra2023
Curated learning hub that aggregates roadmaps, tutorials, bootcamps, books, projects, and tool recommendations for learning data engineering and production data infrastructure. Focuses on practical applied learning (projects, interview prep, community links) rather than code libraries.
AI Infra2023
Provides a NumPy-like array framework for building and training ML on Apple silicon, with Python, C/C++, and Swift APIs plus PyTorch-style higher-level modules. Features lazy evaluation, composable AD/vectorization, and a unified-memory multi-device model so arrays can be used on CPU and GPU without explicit copies.
AI Infra2023
A selective State Space Model architecture and PyTorch implementation for linear-time sequence modeling. Hardware-aware, designed for information-dense tasks (e.g. language modeling), with pretrained weights on Hugging Face; requires CUDA-enabled PyTorch.
AI Leaderboard2023
Runs one-command evaluation of vision-language models across 80+ multimodal benchmarks, handling data download, inference, and metric scoring in a single pass. Supports 220+ LMMs; adding a new model means writing one generate_inner() function.
AI Deploy2023
Builds custom AI inference servers in pure Python on top of FastAPI, keeping full control over request logic while batching, GPU autoscaling, streaming, and OpenAI-spec endpoints come built in. Claims a 2x+ throughput edge over plain FastAPI.
AI Infra2023
Provides a PyTorch-native platform for experimenting with and scaling generative AI training, including composable parallelism, checkpointing, float8, logging, and Llama recipes.
AI Infra2023
Triton kernels and PyTorch layers for linear-attention, state-space, and sparse-attention token mixers (GLA, RWKV, Mamba2, GSA) as drop-in replacements for multihead attention. Runs on NVIDIA, AMD, and Intel GPUs with Hugging Face support.
AI Infra2023
Traces how Transformer LLMs route information from input to output, attributing each block's effect to individual attention heads and feed-forward neurons. Click any edge to see what a head promotes or suppresses in vocabulary space.
AI Agent2024
Claude-Mem is a persistent memory compression system built for Claude Code. It automatically captures tool usage observations during coding sessions, generates semantic summaries using Claude's agent-sdk, and injects relevant context into future sessions to maintain continuity of project knowledge.
AI Agent2024
Orchestrates teams of role-based autonomous agents that collaborate on multi-step tasks, plus event-driven Flows for deterministic control. Built from scratch with no LangChain dependency; runs 450M+ agentic workflows monthly.
AI Infra2024
Serves large language and multimodal models with low latency and high throughput using RadixAttention, continuous batching, structured outputs, parallelism, quantization, and broad accelerator support.
AI Agent2024
Curated developer resources that demonstrate building RAG systems, multi-agent workflows, and memory-augmented AI using Oracle AI Database and OCI — includes end-to-end reference apps, notebooks, guides, and workshops for hands-on prototyping.