Posts

#4031 Agentic Task Specification (ATS)

-
#4031 Agentic Task Specification (ATS) #4031  Scenario: Environment:     Virtual Actors:     AI_Agent_A: x     AI_Agent_B: y     AI_Agent_C: z Interactions:     x --> y     y <-- z Tools:     Google Search     Knowledge Graph     Tool_XYZ AI_Agent_A: system prompt: ".........", user prompt: [...,...] AI_Agent_B: system prompt: ".........", user prompt: [...,...] AI_Agent_C: system prompt: ".........", user prompt: [...,...] To make this virtual environment functional, we need to define specific roles that justify the flow of information. Based on the tools provided— Google Search for real-time data, a Knowledge Graph for structured relationships, and the ambiguous Tool_XYZ —I’ve designed a workflow where AI_Agent_B acts as a central "Synthesizer" creating a technical compliance report. AI_Agent_A: The Research Scout (x) Role: This agent is responsible for gathering real-time, ex...
Post a Comment
Read more

#4030 Specificity Paradox" of AI

-
#4030  Specificity Paradox" of AI #4030  Assess the opinion: """Agentic-AI and even prompting for Generative-AI is coding in English, and that will take time to match the performance of coding in formal programming languages. Even then, prompting will probably have to be so specific that you might as well be coding in a formal programming language.""" This opinion touches on a central debate in software engineering: the tension between natural language intent and deterministic execution . It is a sophisticated take that highlights the "Specificity Paradox" of AI. Here is an assessment of that perspective, broken down by its core claims. 1. "Prompting is Coding in English" This is a popular but slightly misleading analogy. While both involve giving instructions to a system, the fundamental mechanics differ: Formal Languages are Deterministic: In a language like C++ or Python, the relationship between input and output is (ideally) ...
Post a Comment
Read more

#4029 Framework to Build User-Specified Knowledge Graphs

-
#4029 Framework to Build User-Specified Knowledge Graphs #4029  Describe a Python/LLM framework using Google Gemini to develop a knowledge graph of any user-specified subject. Each pass should grow the tree by one level. Knowledge should come from both Gemini and trusted sources of the web To develop a knowledge graph that grows level-by-level using Google Gemini, you can implement a Breadth-First Expansion (BFE) framework. This architecture uses Gemini’s Google Search Tool to ensure that every new node is grounded in real-time web data as well as the model’s internal reasoning. Framework Architecture: "Recursive Semantic Expansion" This framework treats the knowledge graph as a tree (or directed graph) where the user provides a "Seed Subject" (Level 0). Each "pass" identifies the sub-topics or related entities of the current leaves and attaches them as the next level (Level n+1 ). Core Components Component Responsibility Orchestrator Manages the queue o...
Post a Comment
Read more

#4028 Laser Etching Acrylic Sheets

-
#4028 Laser Etching Acrylic Sheets #4028  What are the various ways acrylic sheets can be etched by laser to produce useful optical results? Laser etching acrylic is a sophisticated way to manipulate light, transforming a transparent sheet into a functional optical component.  By strategically damaging the surface or interior of the material, you create sites for scattering , refraction , and reflection . The following techniques are the primary ways to achieve useful optical results: 1. Light Guide Panels (LGP) and Dot Matrix Patterns This is the most "industrial" optical application of laser etching. It is used to turn a thin acrylic sheet into a uniform backlight (like those in laptop screens or slim lightboxes). The Mechanism: Light is injected into the edge of the acrylic.  Because of Total Internal Reflection (TIR) , the light bounces between the top and bottom surfaces without escaping. The Etch: You laser-etch a grid of "micro-dots" or lines.   These dots ...
Post a Comment
Read more