klotz: pytorch* + python*

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  1. The article details “autoresearch,” a project by Karpathy where an AI agent autonomously experiments with training a small language model (nanochat) to improve its performance. The agent modifies the `train.py` file, trains for a fixed 5-minute period, and evaluates the results, repeating this process to iteratively refine the model. The project aims to demonstrate autonomous AI research, focusing on a simplified, single-GPU setup with a clear metric (validation bits per byte).

    * **Autonomous Research:** The core concept of AI-driven experimentation.
    * **nanochat:** The small language model used for training.
    * **Fixed Time Budget:** Each experiment runs for exactly 5 minutes.
    * **program.md:** The file containing instructions for the AI agent.
    * **Single-File Modification:** The agent only edits `train.py`.
  2. This project guides you from data inspection and preprocessing to crafting an end-to-end application for aircraft localization based on crowdsourced air traffic control communication data (ADS-B). It utilizes Apache Spark, Modin, ensemble methods, TabNet, Apache Kafka, Flask, and Leaflet.js.
  3. Train your neural network in TensorFlow or PyTorch, and run it inside CircuitPython using a single line of Python code.
  4. Learn how to design, develop, deploy and iterate on production-grade ML applications.
  5. This is the code repository for Causal Inference and Discovery in Python, published by Packt. Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more.
  6. oLLM is a Python library for running large-context Transformers on NVIDIA GPUs by offloading weights and KV-cache to SSDs. It supports models like Llama-3, GPT-OSS-20B, and Qwen3-Next-80B, enabling up to 100K tokens of context on 8-10 GB GPUs without quantization.
  7. Lambda Stack is an all-in-one package that provides a one line installation and managed upgrade path for deep learning and AI software, ensuring that you always have the most up-to-date versions of PyTorch, TensorFlow, CUDA, CuDNN, and NVIDIA Drivers.
  8. • This is an MCU-based vision AI module powered by Arm Cortex-M55 and Ethos-U55, supporting TensorFlow and PyTorch frameworks.
    • It has a standard CSI interface, onboard digital microphone, and SD card slot.
    • Compatible with XIAO series, Arduino, Raspberry Pi, and ESP dev board.
    • Supports off-the-shelf and custom AI models from SenseCraft AI, including Mobilenet V1, V2, Efficientnet-lite, Yolo v5 & v8.
    • Can be used for industrial automation, smart cities, transportation, smart agriculture, and mobile IoT devices.
  9. This article explains why Convolutional Neural Networks (CNN) are useful for function identification in reverse engineering, and provides a Python implementation using PyTorch to identify the start of functions in binaries.
  10. 2024-04-19 Tags: , , , , by klotz

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