Why Your Prompts Don’t Belong in Git
#Article #Large_Language_Models #Artificial_Intelligence #Generative_Ai #Prompt_Design #Prompt_Engineering #Python
via Towards Data Science
#Article #Large_Language_Models #Artificial_Intelligence #Generative_Ai #Prompt_Design #Prompt_Engineering #Python
via Towards Data Science
Telegraph
Why Your Prompts Don’t Belong in Git
The hidden cost of storing prompts in your source code The post Why Your Prompts Don’t Belong in Git appeared first on Towards Data Science. Generated by RSStT. The copyright belongs to the original author. Source
Google’s URL Context Grounding: Another Nail in RAG’s Coffin?
#Article #Large_Language_Models #Artificial_Intelligence #Data_Science #Gemini #Programming #Python
via Towards Data Science
#Article #Large_Language_Models #Artificial_Intelligence #Data_Science #Gemini #Programming #Python
via Towards Data Science
Telegraph
Google’s URL Context Grounding: Another Nail in RAG’s Coffin?
Google’s hot streak in AI-related releases continues unabated. Just a few days ago, it released a new tool for Gemini called URL context grounding. URL context grounding can be used stand-alone or combined with Google search grounding to conduct deep dives…
The Math You Need to Pan and Tilt 360° Images
#Article #Math #360_Photo #3d #Vision #Linear #Algebra #Programming #Python
via Towards Data Science
#Article #Math #360_Photo #3d #Vision #Linear #Algebra #Programming #Python
via Towards Data Science
Telegraph
The Math You Need to Pan and Tilt 360° Images
Panning a spherical image is just a horizontal roll, but tilting it vertically is much trickier. Let's see the math! The post The Math You Need to Pan and Tilt 360° Images appeared first on Towards Data Science. Generated by RSStT. The copyright belongs to…
PyCharm : The only Python IDE you need. | The JetBrains Blog:
10 Smart Performance Hacks For Faster #Python #Code
10 Smart Performance Hacks For Faster #Python #Code
The JetBrains Blog
10 Smart Performance Hacks For Faster Python Code | The PyCharm Blog
Learn practical optimization hacks, from data structures to built-in modules, that boost speed, reduce overhead, and keep your Python code clean.