RANDOM POSTs
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Enhancing 3D Design: Ai texturing with Stable Projectorz – Image to 3D and Text to 3D Ai tools
Read more: Enhancing 3D Design: Ai texturing with Stable Projectorz – Image to 3D and Text to 3D Ai toolshttps://stableprojectorz.com/lessons-and-videos/
https://lumalabs.ai/genie text to 3D
https://www.tripo3d.ai/app Image to 3D
https://www.vizcom.ai/ Web Sketching and design app
https://github.com/lllyasviel/Fooocus
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GIL To Become Optional in Python 3.13
Read more: GIL To Become Optional in Python 3.13GIL or Global Interpreter Lock can be disabled in Python version 3.13. This is currently experimental.
What is GIL? It is a mechanism used by the CPython interpreter to ensure that only one thread executes the Python bytecode at a time.
https://medium.com/@r_bilan/python-3-13-without-the-gil-a-game-changer-for-concurrency-5e035500f0da
Advantages of the GIL
- Simplicity of Implementation: The GIL simplifies memory management in CPython by preventing concurrent access to Python objects, which can help avoid race conditions and other threading issues.
- Ease of Use for Single-Threaded Programs: For applications that are single-threaded, the GIL eliminates the overhead associated with managing thread safety, allowing for straightforward and efficient code execution.
- Compatibility with C Extensions: The GIL allows C extensions to operate without needing to implement complex threading models, which simplifies the development of Python extensions that interface with C libraries.
- Performance for I/O-Bound Tasks: In I/O-bound applications, the GIL does not significantly hinder performance since threads can be switched out during I/O operations, allowing other threads to run.
Disadvantages of the GIL
- Limited Multithreading Performance: The GIL can severely restrict the performance of CPU-bound multithreaded applications, as it only allows one thread to execute Python bytecode at a time, leading to underutilization of multicore processors.
- Thread Management Complexity: Although the GIL simplifies memory management, it can complicate the design of concurrent applications, forcing developers to carefully manage threading issues or use multiprocessing instead.
- Hindrance to Parallel Processing: With the GIL enabled, achieving true parallelism in Python applications is challenging, making it difficult for developers to leverage multicore architectures effectively.
- Inefficiency in Context Switching: Frequent context switching due to the GIL can introduce overhead, especially in applications with many threads, leading to performance degradation.
https://geekpython.in/gil-become-optional-in-python
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Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition
Read more: Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decompositionhttps://moygcc.github.io/vid2avatar/
https://files.ait.ethz.ch/projects/vid2avatar/main.pdf
https://github.com/MoyGcc/vid2avatar
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General OCR Theory – Towards OCR-2.0 via a Unified End-to-end Model – HF Transformers implementation
https://huggingface.co/stepfun-ai/GOT-OCR-2.0-hf
GOT-OCR2 works on a wide range of tasks, including plain document OCR, scene text OCR, formatted document OCR, and even OCR for tables, charts, mathematical formulas, geometric shapes, molecular formulas and sheet music.
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The Mill opens new offices in Berlin
Read more: The Mill opens new offices in Berlinwww.themill.com/stories/the-mill-opens-new-studio-in-berlin/
Greg Spencer will lead a multi-disciplinary team of artists in his role of Creative Director.
Justin Stiebel will be continuing his role as Executive Producer at The Mill Berlin and will be managing client relationships as well as all new business enquiries.
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