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... 12:14
QWQ could be the BEST local AI model for coding, but only if you know how to prompt it.

GosuCoder

1+ months ago 3K views

Recent explorations of the qwq model have revealed significant potential in enhancing coding efficiency. Adjusting prompts to emphasize urgency led to faster and more substantial code generation, drastically reducing processing time from extensive delays to manageable periods. Experimentation with alternative prompting techniques unlocked improvements in model performance, showcasing the importance of effective interaction with these AI systems. This approach not only optimizes coding tasks but also establishes a framework for integrating AI models into workflows in a timely manner, transforming the coding process into a more productive endeavor.
04:37 - 05:11

Exploring urgency in prompts to reduce processing time led to quick, accurate outputs.

Machine Learning Tech & Hardware
... 16:
RAG vs. CAG: Solving Knowledge Gaps in AI Models

IBM Technology

1+ months ago 18K views

Large language models struggle with knowledge when information falls outside their training set. Two techniques to address this are Retrieval-Augmented Generation (RAG) and Cache-Augmented Generation (CAG). RAG queries an external knowledge base to fetch relevant information before generating answers, while CAG preloads all information into the model’s context for immediate access. RAG offers scalability and better data freshness management, whereas CAG provides faster response times but is limited by context window size. Each method has its unique advantages, making them suitable for different applications and environments.
01:41 - 01:50

CAG preloads the complete knowledge base into the context window for access.

IBM Natural Language Processing (NLP) Education
... 26:52
DAY-2 | AI Assisted DevOps | Prompt Engineer Explained In 30 Minutes

Abhishek.Veeramalla

1+ months ago 3K views

Prompt engineering is crucial for optimizing AI model outputs, particularly in DevOps environments. This entails enhancing user inputs—called prompts—to elicit desired results from AI models. Different prompting techniques, such as zero-shot, few-shot, and multi-shot prompting are explored, highlighting their practical applications in real-world scenarios. Effective prompting can significantly reduce costs associated with AI model utilization. By providing structured and specific prompts, users can achieve outputs that align closely with organizational requirements, thereby streamlining workflows and maximizing productivity in AI-assisted DevOps tasks.
05:24 - 05:30

Cost optimization in organizations can be achieved through effective prompting.

Machine Learning Education
... 22:7
Build AI AGENTS 3x Faster with this Prompt Agent

Simon Scrapes | AI Agents & Automation

1+ months ago 2K views

Build AI agents three times faster with an effective prompting agent, simplifying the complex and time-consuming process of writing prompts. Through a template, the method streamlines prompt creation, ensuring comprehensive outputs that reduce rework and enhance productivity. By answering targeted clarification questions, a user can refine a broad prompt into a detailed, functional instruction set for an AI agent. This structured approach not only speeds up the prompt-building process but also increases the quality of outputs, resulting in more efficient AI solutions tailored to specific tasks.
04:20 - 05:10

Generating prompts tailored to specific tasks improves overall AI output quality.

Machine Learning AI Startups
... 4:34
The Top AI Prompt Writing Tips You Must Know About

Bernard Marr

1+ months ago 2K views

Creating effective AI prompts relies on context, role assignment, and structured formatting. Clear directives increase AI output quality, with techniques like demonstrating styles and limiting output parameters. Adjusting creativity levels based on task type and using iterative design produces better results. Effective prompts include context, specific roles, explicit goals, stylistic guidance, and exclusions. Constant refinement and attention to AI reasoning enhance the development of high-quality AI-generated content.
01:23 - 01:26

Using examples to illustrate style improves AI writing quality.

Natural Language Processing (NLP) Education
... 23:54
This new AI prompting technique REDUCES token usage SIGNIFICANTLY

GosuCoder

1+ months ago 3K views

My company utilizes numerous API calls to OpenAI and Claw, primarily for building prompts. Encountering challenges during prompt creation led to the investigation of Chain of Draft, which focuses on optimizing thought processes for enhanced results with local models. This approach demonstrates that prompt engineering can both reduce costs and improve accuracy. Various experiments, including a standard house problem and a math problem, reveal trade-offs in token usage and accuracy across different models, ultimately showcasing the value of careful prompt design in leveraging AI models effectively.
01:51 - 02:19

Testing Chain of Thought shows a trade-off between tokens used and answer accuracy.

Natural Language Processing (NLP) Education
... 9:7
1000+ FREE EVERGREEN A.I. PROMPTS!🤯

Philip Anders

1+ months ago 4K views

A new, massive library of print-on-demand and T-shirt design prompts is available for free access. This library, introduced by My Designs for Dream AI, allows users to explore and view successful prompts used across various AI models like DALL-E 3 and Ideogram V2. Users can filter and research different AI models' results, copy prompts, and analyze generation styles. Techniques to scale and repurpose successful prompts facilitate the creation of multiple unique designs. A public setting option allows users to share their images and prompts, reducing costs while increasing collaborative opportunities within the community.
01:45 - 02:02

Different AI models yield diverse aesthetics and design quality.

MyDesigns Text generation Education
... 7:46
AI Isn't the Problem. YOUR prompts Are!

Dr. Liz Moyer

1+ months ago 1K views

This video provides a solution for users frustrated with vague AI responses by introducing the prompt canvas tool, designed to enhance interactions with AI models like ChatGPT. It outlines a practical framework for creating clear and effective prompts, particularly in the context of military relocation (PCS). The speaker engages the audience with a live demonstration of using the prompt canvas to generate useful checklists, focusing on ensuring smooth military moves. Additionally, there's a cautionary note about an ineffective AI training program that the speaker recommends avoiding.
04:59 - 06:26

Creating a detailed checklist for military relocation using AI.

Natural Language Processing (NLP) Education
... 7:46
AI Isn't the Problem. YOUR prompts Are!

Dr. Liz Moyer

1+ months ago 1K views

This video provides a solution for users frustrated with vague AI responses by introducing the prompt canvas tool, designed to enhance interactions with AI models like ChatGPT. It outlines a practical framework for creating clear and effective prompts, particularly in the context of military relocation (PCS). The speaker engages the audience with a live demonstration of using the prompt canvas to generate useful checklists, focusing on ensuring smooth military moves. Additionally, there's a cautionary note about an ineffective AI training program that the speaker recommends avoiding.
04:59 - 06:26

Creating a detailed checklist for military relocation using AI.

Natural Language Processing (NLP) Education