LLM to Google Sheets - An LLM Demo

Groq
27 Dec 202304:14

TLDRIn the demo, Mark Heaps, VP of Brand and AI Evangelist at Grock, showcases the integration of AI into daily life with the Alpha release of Lama 70 billion. He demonstrates how to generate a list of sports winners from 1970 to 2020, format it into a table and CSV for easy integration with tools like Google Sheets or Microsoft Excel. The goal is to inspire users to think creatively about how AI can be utilized in their work and personal life.

Takeaways

  • 😀 The presenter, Mark Heaps, is the VP of Brand and AI Tech Evangelist at Grock.
  • 🔍 Mark demonstrates a demo using the Alpha release of LLM with 70 billion parameters running on Grock's LPU inference engine.
  • 🤖 The LLM is capable of performing Google searches and can be integrated into everyday life for various applications.
  • 📝 A prompt is used to generate a list of winners for the NBA, NFL, and NHL finals from 1970 to 2020, showcasing the model's access to internet-trained information.
  • ⚡ The model generates the list at a speed of 271.77 tokens per second per user, highlighting its efficiency.
  • 📊 Formatting controls are available to make the information more glanceable, such as converting the list into a table format.
  • 📋 The table format organizes the information in a clear and concise manner, making it easier to read and understand.
  • 🔄 Another prompt is used to format the information as a CSV, allowing for easy import into programs like Microsoft Excel or Google Sheets.
  • 📋 The CSV format uses comma separation and quotations, which is standard for spreadsheet applications.
  • 📁 The presenter shows how to copy the results and save them as a CSV file, which can then be imported into spreadsheet software.
  • 📊 After importing into Google Sheets, the information is separated into columns, allowing for further manipulation and analysis.
  • 💡 The demo encourages viewers to think creatively about how they can use the LLM to generate and format information for their own needs.

Q & A

  • Who is the speaker in the video and what is his role at Groq?

    -The speaker is Mark Heaps, who is the VP of Brand and AI Tech Evangelist at Groq.

  • What is the purpose of the demo presented by Mark Heaps?

    -The purpose of the demo is to show how to integrate the capabilities of Groq's Alpha release of Lama 70 billion model into everyday life and to inspire users with its potential applications.

  • What is the specific prompt that Mark Heaps pasted into the system to generate a list?

    -The prompt is to make a list of all the winners each year of the NBA Finals, the NFL finals, and the NHL finals from 1970 to 2020.

  • How does the LLM handle the request for information that is not readily available on the internet?

    -The LLM has been trained on information from the internet up to a certain point, and it uses this training to generate the requested list.

  • What is the speed at which the LLM generated the list of sports winners?

    -The LLM generated the list at a speed of 271.77 tokens per second per user.

  • How does the Groq interface help in making the generated information more glanceable?

    -The Groq interface provides formatting controls that can be activated through prompts, allowing the user to format the information as a table.

  • What is the purpose of formatting the generated list as a CSV?

    -Formatting as a CSV allows the user to easily copy and paste the information into a text editor, save it, and then import it into programs like Microsoft Excel or Google Sheets.

  • How does the LLM handle the request to format the information as a CSV?

    -The LLM takes the list or table and formats it with comma separation and quotations, which is common for a CSV file.

  • What is the process of importing the CSV file into Google Sheets as described in the demo?

    -The process involves going to Google Sheets, selecting 'Import', 'Upload', browsing for the CSV file, and then opening the data to have it separated into its own columns.

  • What are some potential applications of the LLM's capabilities as suggested in the demo?

    -Potential applications include asking for information about states' population data, rainfall, agricultural exports, shipping channels, wildlife, and then formatting it for use in various office applications.

  • How can users access the Alpha chat demo mentioned in the video?

    -Users can access the Alpha chat demo by visiting gro.com.

Outlines

00:00

🤖 AI Demo Introduction

Mark Heaps, VP of Brand and AI Tech Evangelist at Grock, introduces a demo of the Alpha release of Lama, an AI model running on Grock's inference engine. He addresses a question about integrating AI into everyday life and presents a prompt to generate a list of winners for NBA, NFL, and NHL finals from 1970 to 2020, showcasing the AI's speed and accuracy in retrieving and presenting data.

📊 Formatting AI Output

After generating the list, Mark demonstrates how to enhance the readability by using Grock's interface to add formatting controls. He uses a prompt to format the list into a table, making the information more glanceable and easier to digest, which could be useful for responding to emails or customer inquiries.

🔄 Converting Data to CSV

To further integrate the AI-generated data into everyday applications, Mark shares a prompt to format the list as a CSV, which can be copied and pasted into a text editor and then imported into spreadsheet software like Microsoft Excel or Google Sheets. This step shows how AI can be used to prepare data for analysis and reporting in common office applications.

Mindmap

Keywords

💡LLM

LLM stands for Large Language Model, which is a type of artificial intelligence that can understand and generate human-like text based on the data it has been trained on. In the video, the presenter uses an LLM to generate a list of sports winners, demonstrating its ability to retrieve and format information.

💡Google Sheets

Google Sheets is a web-based spreadsheet program offered by Google within the Google Drive service. It is used for data organization, calculations, and data analysis. The script shows how information generated by the LLM can be imported into Google Sheets for further manipulation and use.

💡Integration

Integration in this context refers to the process of combining different systems or technologies to work together. The video demonstrates the integration of an LLM with everyday tools like Google Sheets, showing how AI can be seamlessly incorporated into daily workflows.

💡Alpha release

An Alpha release is a version of a product that is still in development and is made available for testing purposes. The video script mentions the 'Alpha release of Lama 70 billion,' indicating that the LLM being demonstrated is in an early testing phase.

💡Grock

Grock is mentioned as the company responsible for the LLM and its inference engine. The term refers to the organization that developed the technology showcased in the video, highlighting the company's role in AI and machine learning advancements.

💡Inference engine

An inference engine is a component of an expert system that uses reasoning to derive conclusions from a set of asserted facts or rules. In the video, the presenter mentions that the LLM is running on Grock's inference engine, which is responsible for the model's fast performance.

💡Formatting

Formatting in the context of the video refers to the process of arranging data in a specific structure or layout. The script describes how the LLM can format information as a table or CSV, making it more readable and easier to import into other applications.

💡CSV

CSV stands for Comma-Separated Values, a file format used to store tabular data, such as a spreadsheet or database. The video shows how the LLM can output information in CSV format, which can then be copied and pasted into a text editor and imported into spreadsheet programs like Excel or Google Sheets.

💡NBA Finals

The NBA Finals is the championship series for the National Basketball Association (NBA) and the conclusion of the league's postseason. The video script uses the NBA Finals as an example of the type of information that the LLM can retrieve and list.

💡Token

In the context of the video, a token refers to a unit of text, such as a word or punctuation mark, that the LLM processes. The script mentions the speed at which the LLM generates tokens, indicating the model's efficiency in text generation.

💡Meta

Meta is the parent company of Facebook and is known for its investment in AI research and development. The script mentions that the LLM has been trained by Meta's AI division, highlighting the company's role in advancing AI technologies.

Highlights

Introduction to a demo by Mark Heaps, VP of Brand and AI Tech Evangelist at Grok, showcasing the integration of AI into everyday life.

Demonstration of Grok's Alpha release of Lama 70 billion, running on Grok's LPU inference engine.

Addressing a question about integrating AI with Google searches and everyday tasks.

Using a simple prompt to generate a list of winners of NBA, NFL, and NHL finals from 1970 to 2020.

Explanation of the AI model's training on internet information up to a certain point by Meta's AI division.

Showcasing the speed of AI generation at 271.77 tokens per second per user.

Adding formatting controls to Grok's interface to improve the glanceability of the generated information.

Transforming the list into a formatted table for easier readability.

Using a prompt to format the information as a CSV for import into spreadsheet applications like Microsoft Excel.

Highlighting the ability to copy and paste AI-generated results directly into a text editor.

Removing comments from the AI-generated CSV for cleaner data entry into spreadsheets.

Importing the CSV file into Google Sheets and demonstrating the separation of data into columns.

Emphasizing the potential for AI to generate and format data on a wide range of topics, from states' population to wildlife.

Encouraging users to think differently about how they can use the AI chat demo for various applications.

Invitation to visit gro.com for the Alpha chat demo and other AI integrations.

Closing remarks by Mark Heaps, expressing excitement for future demos and AI applications.