https://playcanvas.com/supersplat/editor?load=https://raw.githubusercontent.com/willeastcott/assets/main/iceberg.ply&camera.debug=false&show.bound=false&show.grid=false

https://github.com/david-rhodes/GSOPs

https://www.linkedin.com/posts/davidarhodes_gsops-gaussiansplatting-3dgs-activity-7250970758321975296-k7f7

https://player.style/

https://peterszasz.com/engineering-managers-guide-to-effective-annual-feedback

The main goals of a regular, written feedback cycle are:

• Recognition, support for self-reflection and personal growth
• Alignment with team- and company needs
• Documentation

These promote:

• Recognize Achievements: Use the feedback process to boost morale and support self-reflection.
• Align Goals: Ensure individual contributions match company objectives.
• Document Progress: Keep a clear record of performance for future decisions.
• Prepare Feedback: Gather 360-degree feedback, focus on examples, and anticipate reactions.
• Strength-Based Approach: Focus on enhancing strengths over fixing weaknesses.
• Deliver Feedback Live: Engage in discussion before providing written feedback.
• Follow-Up: Use feedback to guide future goals and performance improvement.

GIL 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

1. 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.
2. 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.
3. 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.
4. 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

1. 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.
2. 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.
3. 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.
4. 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

https://www.linkedin.com/posts/bengunsberger_ai-podcasts-notebooklm-activity-7247492413705871361-JVnM

https://notebooklm.google/

Listen to the podcast in the post

“I just created a AI-Generated podcast by feeding an article I write into Google’s NotebookLM. If I hadn’t make it myself, I would have been 100% fooled into thinking it was real people talking.”

(more…)

https://venturebeat.com/ai/apple-releases-depth-pro-an-ai-model-that-rewrites-the-rules-of-3d-vision/

The model is fast, producing a 2.25-megapixel depth map in 0.3 seconds on a standard GPU.

https://github.com/apple/ml-depth-pro

https://arxiv.org/pdf/2410.02073