Cognilytica Insights
This week we share part 4 of our 6 part newsletter on Prompt Engineering Best Practices. Make sure to check out part 1
, part 2
, and part 3
if you haven’t already!
Prompt Engineering Best Practice #4: Using Plugins
?? Sometimes what you need from a Large Language Model (LLM) based generative AI solution can only go so far. LLMs are limited by their training data, their inability to access your documents and data, and limitations on what they can do with text-based prompts and data.
?? This is where Plugins come in to enhance LLM capabilities.
Plugins for Large Language Models (LLMs) are additional tools or extensions that enhance the LLM's capabilities beyond its base functions. These plugins can access external databases, perform specific computations, or interact with other software and APIs to fetch real-time data, execute code, and more. In essence, plugins significantly expand the utility of LLMs, making them more versatile and effective tools for a wide range of applications. They bridge the gap between the static knowledge of a trained model and the dynamic, ever-changing information and capabilities of the external world.?
Here’s why they’re becoming increasingly popular:
- Access to Real-time Information: LLMs are trained on vast datasets that become static once training is complete. Plugins allow these models to access up-to-date information from the web or other data sources, keeping responses relevant and timely.
- Specialized Knowledge and Skills: By integrating plugins, LLMs can perform specialized tasks like solving complex mathematical problems, generating code, or providing translations with expertise that might not be fully developed in the base model.
- Interactivity and Dynamic Content: Plugins enable LLMs to interact with other applications and services, allowing for dynamic content generation, automation of tasks, and enhanced user interactions. For example, a plugin could let an LLM book appointments, send emails, or even play games with the user.
- Customization and Personalization: Developers and users can tailor the capabilities of LLMs to their specific needs through plugins. This means businesses and individuals can use the same base model but customize it with plugins to serve niche markets or personal preferences.
- Improved Performance and Efficiency: Some tasks may be beyond the scope of the base LLM or require computational resources that are more efficiently handled externally. Plugins can offload these tasks to specialized services or databases, improving the overall performance and speed of the LLM.
Understanding and utilizing these plugins can significantly enhance the efficiency, effectiveness, and adaptability of your tasks and projects. Below is an overview of types of plugins or tools that could be conceptualized as plugins for LLMs, their uses, and why project managers might find them valuable:
???? Code Execution Plugins:
- Use: Allows LLMs to run code snippets, returning real-time execution results.
- Why: Enables dynamic code generation and testing within conversations, ideal for software development projects.
?? Data Analysis and Visualization Plugins:
- Use: Performs complex data analysis and generates visual reports directly from datasets.
- Why: Provides instant insights from data, supporting data-driven decision-making.
?? Real-time Collaboration Tools Integration:
- Use: Integrates with tools like Slack, Asana, or Trello to manage tasks and communications.
- Why: Allows for seamless project management and team communication within the LLM interface.
?? Calendar and Scheduling Plugins:
- Use: Manages calendars, schedules meetings, and sets reminders.
- Why: Automates scheduling tasks, saving time and reducing conflicts.
?? Enterprise Application (CRM, ERP, etc.) Integration:
- Use: Accesses customer data, logs interactions, and provides personalized customer insights. Connects with financial software to track budgets, expenses, and financial forecasts.
- Why: Enhances integration with data, engagement and personalization of services.
?? Translation and Localization Plugins:
- Use: Provides real-time translation services and localizes content for different regions.
- Why: Expands the global reach of projects and teams by breaking down language barriers.
?? Cloud Storage Access Plugins:
- Use: Retrieves and stores files directly from cloud storage solutions
- Why: Streamlines file management and access without leaving the LLM interface.
?? External Database Querying Plugins:
- Use: Performs queries on external databases to retrieve or update information in real-time.
- Why: Enables dynamic data retrieval and manipulation for up-to-date information access.
?? AI Model Training and Deployment Plugins:
- Use: Facilitates on-the-fly training and deployment of machine learning models.
- Why: Allows for custom model development and integration within projects.
There are hundreds of different plug-ins and many different ways to use them and have them provide help.?
?? Stay subscribed for the part 5 in our series next week where we explore another best practice in prompt engineering: “Hack and Track”: how do you use a spreadsheet or other method to track what prompts work well as you experiment with different possibilities.
?? In Case you Missed it… Insights from Cognilytica Podcasts & Content
- ?? {Featured Forbes Article} Advancing The Use Of AI To Improve Healthcare - The healthcare industry grapples with the best way to apply AI to deliver results and quality to patients, care providers, support staff, and all aspects of the industry. How will the use of AI improve healthcare and provide a hyperpersonalized experience in the years ahead? [Read here
]
- ?? {Featured Forbes Article} Keeping AI Projects In Check: Scoping AI Projects - For AI projects to be successful, there needs to be a combination of a larger vision for AI and quick projects that allow organizations to ensure real-world value. [Read More
]
- ?? {Featured Podcast} ?Prompt Engineering Best Practices: Using a Prompt Pattern [AI Today Podcast] - Prompts are natural language instructions for an LLM provided by a human so that it will deliver the desired results you’re looking for. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer dig into using a prompt pattern. [Listen here
]
- ?? {Featured Podcast} Prompt Engineering Best Practices: What is Prompt Chaining? [AI Today Podcast] - To improve the reliability and performance of LLMs, sometimes you need to break large tasks/prompts into sub-tasks. Prompt chaining is useful if the LLM is struggling to complete your larger complex task in one step. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss prompt chaining. [Listen here
]
?? The Most Important AI Stories from the Past Week You Should Know:
- ???? {AI Strategic Plans} - Texas is replacing thousands of human exam graders with AI: An “automated scoring engine” that utilizes NLP is being rolled out by the Texas Education Agency (TEA) to grade open-ended questions on the State of Texas Assessments of Academic Readiness (STAAR) exams. It’s expected to save $15–20 million per year by reducing the need for temporary human scorers. And, Texas plans to hire just under 2,000 graders this year compared to the 6,000 required in 2023.[Read More
]
- ?? {AI Adoption} - AI-operated fighter jet will fly Air Force secretary in a test of military's future drone warplanes: Drone warfare has quickly expanded from the sidelines of combat to one of its primary weapons. The US Air Force is betting a large part of its future air warfare on a fleet of more than 1,000 autonomously operated combat aircraft. [Read More
]
- ??? {Augmented Intelligence} - AI makes retinal imaging 100 times faster, compared to manual method: Researchers at the National Institutes of Health have enhanced a cell imaging technique using AI, speeding up the process by 100 times and improving image contrast by 3.5 times. This advancement will aid in better evaluating age-related macular degeneration (AMD) and other retinal diseases. [Read More
]
?? Events and Opportunities to Hear from Cognilytica
- THIS WEEK April 17, 2024: PMI New York City Chapter “How to Run Successful AI Projects and Avoid Failure” Virtual / Online session, 6-7pm EST [Register here
]
- THIS WEEK ? April 18, 2024: FORUM: Women Making an IMPACT, Empowering Women in AI - virtual/ webinar, 1pm EST [Register here
]
- April 23, 2024: PMI Tulsa, OK Chapter: “The Hidden Secret of AI Success: A PMI Approach” Virtual / Online session 12:00-1:00pm CST [Register here
]
- April 29, 2024: PMI Saudi Arabia Chapter: “How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session -? 7PM-8PM Saudi Time (10AM-11AM Eastern Time) [Register here
]
- May 2, 2024: PMI Austin, TX Chapter: “The Future is Now:? Essential AI Skills Every Project Manager Must Have”, Professional Development Day 2024, In-person presentation, 7:30am - 16:00pm CT ?[Register here
]
- May 7, 2024: PMI Delaware Valley Chapter: “How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session -? 6:30PM-8PM Eastern Time [Registration opening soon]
- May 8, 2024: PMI Southwest Ohio Chapter: “How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session, 6:30-7:30pm Eastern Time [Register here
]
- May 15, 2024: Designing Maryland's AI Future Summit, 8:30am-4:30pm, Fort Washington, MD [Registration opening soon]
- May 21, 2024: PMI New Jersey Chapter: “What you need to know, today, to successfully run and manage AI projects”, Virtual / Online session -? 6:30PM-8PM Eastern Time [Registration opening soon]
- July 10, 2024: PMI Madrid, Spain Chapter: “Best Practice Methods for Successful AI Projects”, Virtual / Online session - 7:00 - 8:00 PM Spanish time? [Registration opening soon]
- July 10th, 2024: PMI San Francisco Chapter: “Successful approaches to running AI Projects - Avoiding the Top Reasons why AI Projects Fail”, Virtual / Online session -? 6-7:30 pm PST [Registration opening soon]
- July 17, 2024: PMI Northern Alberta Chapter: “The hidden secret of AI success: a PM approach” Virtual / Online session? 6-8pm MT [Registration opening soon]
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?? Move Forward with AI Best Practices - Training & Certification
Cognilytica’s AI best practices & Trustworthy training and certification continues to be in high demand. Haven’t yet enrolled in a certification or training? What’s holding you back?
- ?? CPMAI v7 - Get Certified with comprehensive AI & ML Project Management Training. Includes: AI Fundamentals, AI Applications, Managing Data for AI, Data Preparation for AI, ML Algorithms, Generative AI, CPMAI Methodology, and Trustworthy AI. [Enroll now
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