Hi, Community!

Do you think Generative AI can make your life easier? See some potential use cases for GenAI in the latest video from Learning Services:

▶ Generative AI in Use

Hi Community!

How can you create a balanced approach to using Generative AI? Get help from InterSystems experts in the latest video from Learning Services:

⚖ Weighing the Benefits and Risks of Generative AI

Hi Community!

Need an introduction to Generative AI? Learning Services is excited to announce the first video in a new series about GenAI basics:

🧐 What Is Generative AI?

Hey Community!

We're happy to share our newest learning path dedicated to the essentials of GenAI, accessible on the Learning Portal via your SSO:

🤖 Getting Started with Generative AI 🤖

Here is what you can expect:

I try to get a vector from calling GetEmbedding, but i failed to convert it into a vector 

Here is a simplyfied sample class: 

Class User.myclass Extends %Persistent
{Property myVECTOR As %Vector(CAPTION = "Vector");

Property myProperty As %String(MAXLEN = 40) [ Required ];

}

here the GetEmbedding part from User.mymethods:

Looking to get started with generative AI? Try two brand-new learning paths. In Getting Started with Generative AI (2h 45m), learn the basics of interacting with GenAI. Then, try Developing Generative AI Applications (2h) to start developing your own GenAI application. Plus, earn badges for completing each path!

Hi All,
We invite you to join our next Meetup in Boston on June 25 5:30-7:30 pm.
>> RSVP here <<
 

Introduction

ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model as a psychological framework to craft empathetic replies. This article elaborates on the backend architecture and its components, focusing on how InterSystems IRIS supports the system's functionality.

In the previous article, we saw in detail about Connectors, that let user upload their file and get it converted into embeddings and store it to IRIS DB. In this article, we'll explore different retrieval options that IRIS AI Studio offers - Semantic Search, Chat, Recommender and Similarity. 

New Updates  ⛴️ 

• Added installation through Docker. Run `./build.sh` after cloning to get the application & IRIS instance running in your local
• Connect via InterSystems Extension in vsCode - Thanks to @Evgeny Shvarov 
• Added FAQ's in the home page that covers the basic info for new users

Semantic Search

Considering new business interest in applying Generative-AI to local commercially sensitive private data and information, without exposure to public clouds. Like a match needs the energy of striking to ignite, the Tech lead new "activation energy" challenge is to reveal how investing in GPU hardware could support novel competitive capabilities. The capability can reveal the use-cases that provide new value and savings.

Sharpening this axe begins with a functional protocol for running LLMs on a local laptop.

ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model (Hochbaum, Rosenstock, & Kegels, 1952) as a psychological framework to craft empathetic replies.

TL;DR

This article introduces using the langchain framework supported by IRIS for implementing a Q&A chatbot, focusing on Retrieval Augmented Generation (RAG). It explores how IRIS Vector Search within langchain-iris facilitates storage, retrieval, and semantic search of data, enabling precise and up-to-date responses to user queries. Through seamless integration and processes like indexing and retrieval/generation, RAG applications powered by IRIS enable the capabilities of GenAI systems for InterSystems developers.

The introduction of InterSystems' "Vector Search" marks a paradigm shift in data processing. This cutting-edge technology employs an embedding model to transform unstructured data, such as text, into structured vectors, resulting in significantly enhanced search capabilities. Inspired by this breakthrough, we've developed a specialized search engine tailored to companies.

We harness generative artificial intelligence to generate comprehensive summaries of these companies, delivering users a powerful and informative tool.

Hi Community,

Here is a brief walkthrough on the capabilities of IRIS AI Studio platform. It covers one complete flow from loading data into IRIS DB as vector embeddings and retrieving information through 4 different channels (search, chat, recommender and similarity). In the latest release, added docker support for local installation and live version to explore. 

Problem

Do you resonate with this - A capability and impact of a technology being truly discovered when it's packaged in a right way to it's audience. Finest example would be, how the Generative AI took off when ChatGPT was put in the public for easy access and not when Transformers/RAG's capabilities were identified. At least a much higher usage came in, when the audience were empowered to explore the possibilities.  

Motivation

In the previous article, we saw different modules in IRIS AI Studio and how it could help explore GenAI capabilities out of IRIS DB seamlessly, even for a non-technical stakeholder. In this article, we will deep dive into "Connectors" module, the one that enables users to seamlessly load data from local or cloud sources (AWS S3, Airtable, Azure Blob) into IRIS DB as vector embeddings, by also configuring embedding settings like model and dimensions. 

New Updates  ⛴️ 

Hi Community,
In this article, I will introduce my application iris-VectorLab along with step by step guide to performing vector operations.

IRIS-VectorLab is a web application that demonstrates the functionality of Vector Search with the help of embedded python. It leverages the functionality of the Python framework SentenceTransformers for state-of-the-art sentence embeddings.

Application Features

• Text to Embeddings Translation.
• VECTOR-typed Data Insertion.
• View Vector Data
• Perform Vector Search by using VECTOR_DOT_PRODUCT and VECTOR_COSINE functions.
• Demonstrate the difference between normal and vector search
• HuggingFace Text generation with the help of GPT2 LLM (Large Language Model) model and Hugging Face pipeline

Hey Community,

We have more exciting news! The new InterSystems online programming contest dedicated to Generative AI, Vector Search and Machine Learning is starting very soon! 

🏆 InterSystems Vector Search, GenAI and ML Contest 🏆

Duration: April 22 - May 19, 2024

Prize pool: $14,000

Hi Developers!

Here're the technology bonuses for the InterSystems Vector Search, GenAI, and ML contest 2024 that will give you extra points in the voting:

• Vector Search usage - 5
• IntegratedML usage - 3
• Embedded Python - 3
• LLM AI or LangChain usage: Chat GPT, Bard, and others - 3
• Questionnaire - 2
• Docker container usage - 2 
• ZPM Package deployment - 2
• Online Demo - 2
• Implement InterSystems Community Idea - 4
• Find a bug in Vector Search, or Integrated ML, or Embedded Python - 2
• First Article on Developer Community - 2
• Second Article On DC - 1
• First Time Contribution - 3
• Video on YouTube - 3
• Suggest a new idea - 1

See the details below.

Hi all,

As part of the InterSystems Solutionathon we would like to distribute a very quick survey on your thoughts on using AI-driven code documentation for ObjectScript.

https://forms.office.com/r/nSGevGpbTy

Please let us know if you have any further questions!

InterSystems' team is heading to the MIT Hacking Medicine GrandHack 2024, taking place from April 19-21 2024!

MIT GrandHack is a premier event that brings together innovators, entrepreneurs, and healthcare professionals from around the world to collaborate on solving some of the most pressing challenges in healthcare through technology and innovation.

InterSystems is pleased to sponsor and support this event, offering our technology to hackers and presenting the "The GenAI in Healthcare" challenge.

We're excited to see the innovative projects that will arise from this event!

Hey Community,

Watch the latest video on InterSystems Developers YouTube:

⏯ Using Vector Search for Generative AI

What is Unstructured Data?
Unstructured data refers to information lacking a predefined data model or organization. In contrast to structured data found in databases with clear structures (e.g., tables and fields), unstructured data lacks a fixed schema. This type of data includes text, images, videos, audio files, social media posts, emails, and more.

Why Are Insights from Unstructured Data Important?
According to an IDC (International Data Corporation) report, 80% of worldwide data is projected to be unstructured by 2025, posing a significant concern for 95% of businesses. Forbes Article
 

Hi Community!
As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So we need to build a custom ChatGPT AI by using LangChain Framework:
Below are the steps to build a custom ChatGPT:

• Step 1: Load the document 

• Step 2: Splitting the document into chunks

• Step 3: Use Embedding against Chunks Data and convert to vectors

• Step 4: Save data to the Vector database

• Step 5: Take data (question) from the user and get the embedding

• Step 6: Connect to VectorDB and do a semantic search

• Step 7: Retrieve relevant responses based on user queries and send them to LLM(ChatGPT)

• Step 8: Get an answer from LLM and send it back to the user

  For more details, please Read this article

Hi Developers,
Let's meet in-person at our next Developer Meetup in Boston on March 27 5:30 pm!
>> RSVP here <<

Hi Community,

Thank you for participating in our recent mini-contest! We received many great ideas, and we hope you enjoyed the process.

The mastermind of the winning concept will receive 5,000 points, while the astute "investors" in said concept will receive 200 points each.

The Winning Concept: Senior people loneliness

 Loneliness experiences by older people and lack of conversations can negatively impact their mental well-being, concerning their families about difficulties in being able to ask for help on their own.

The Mastermind: Marcelo Dotti

The astute "investors":

Hi Developers,
We will be hosting the first in-person meetup in 2024 in Boston on January 24. Join us to explore the latest trends, tools, and features for innovating with health data.

RSVP here
Presentations:

"Integrate third-party Clinical Decision Support services into the EHR with CDS Hooks" - by Frank Pandolfe, Clinical Product Manager, InterSystems.
"Connecting GenAi into Clinical Workflows" - by Nicholai Mitchko, Manager, Solution Partner Sales Engineering, InterSystems

Hi Community,

Round 2 of the GenAI Crowdsourcing Mini-Contest is here! Everyone can join, even if you missed Round 1. You have $5 million in fantasy funds to invest in up to 5 promising submissions.

🎁 Rewards

• The top-funded submission of Round 1 will emerge victorious.
• The mastermind of the winning concept earns 5,000 points, while 3 astute "investor(s)" backing the winning idea get a chance to receive 200 bonus points each.

Dive into the game, strategically allocate your virtual investments, and aim for maximum returns! Deadline: Dec 31st, 2023

Hi Community,

Round 2 of the GenAI Crowdsourcing Mini-Contest has been extended. The new deadline for all investments is tomorrow - Friday, January 5th.

For more information on round 2, see @Alki Iliopoulou's announcement here.