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#Generative AI (GenAI)

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Generative AI refers to algorithms and models in artificial intelligence that are capable of generating new data or content that is similar to existing data. These models are trained on large datasets and learn to generate new examples that mimic the patterns and characteristics of the original data.

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.

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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.

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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

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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

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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.<--break->

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Hey Community,

Watch the latest video on InterSystems Developers YouTube:

⏯ Using Vector Search for Generative AI

https://www.youtube.com/embed/IapbO3j1Qmw
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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.

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We all know that having a set of proper test data before deploying an application to production is crucial for ensuring its reliability and performance. It allows to simulate real-world scenarios and identify potential issues or bugs before they impact end-users. Moreover, testing with representative data sets allows to optimize performance, identify bottlenecks, and fine-tune algorithms or processes as needed. Ultimately, having a comprehensive set of test data helps to deliver a higher quality product, reducing the likelihood of post-production issues and enhancing the overall user experience.

In this article, let's look at how one can use generative AI, namely Gemini by Google, to generate (hopefully) meaningful data for the properties of multiple objects. To do this, I will use the RESTful service to generate data in a JSON format and then use the received data to create objects.

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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

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Artificial Intelligence (AI) is getting a lot of attention lately because it can change many areas of our lives. Better computer power and more data have helped AI do amazing things, like improving medical tests and making self-driving cars. AI can also help businesses make better decisions and work more efficiently, which is why it's becoming more popular and widely used. How can one integrate the OpenAI API calls into an existing IRIS Interoperability application?

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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

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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

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Introduction

This article aims to explore how the FHIR-PEX system operates and was developed, leveraging the capabilities of InterSystems IRIS.

Streamlining the identification and processing of medical examinations in clinical diagnostic centers, our system aims to enhance the efficiency and accuracy of healthcare workflows. By integrating FHIR standards with InterSystems IRIS database Java-PEX, the system help healthcare professionals with validation and routing capabilities, ultimately contributing to improved decision-making and patient care.

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Artificial intelligence is not limited only to generating images through text with instructions or creating narratives with simple directions.

You can also make variations of a picture or include a special background to an already existing one.

Additionally, you can obtain the transcription of audio regardless of its language and the speed of the speaker.

So, let's analyze how the file management works.

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Article
· Nov 27, 2023 2m read
Generative AI for image creation

Currently, many digital artists use generative AI technology as a support to accelerate the delivery of their work. Nowadays it is possible to generate a corresponding image from a text sentence. There are several market solutions for this, including some available to be used through APIs. See some at this link: https://www.analyticsvidhya.com/blog/2023/08/ai-image-generators/.

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Introduction

InterSystems would like to optimize IRIS to take advantage of modern CPU instruction set extensions. That’s great for product performance, but how do you know if your CPU will still be supported for new IRIS builds? Here’s how to know your CPU’s microarchitecture family as well as how to find out your CPU’s specific instruction set extensions.

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Hi Community

In this article, I will introduce my application IRIS-GenLab.

IRIS-GenLab is a generative AI Application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS to demonstrate Machine Learning, LLM, NLP, Generative AI API, Google AI LLM, Flan-T5-XXL model, Flask Login and OpenAI ChatGPT use cases.

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Hi Everyone,

Join us at the online Developer Roundtable to discuss Generative AI Use Cases in Healthcare on August 31, 10 am ET.
Learn Use Cases + Reference Architecture in Healthcare, and witness the demo of LLMs. We will have time for Q&A and open discussion as usual.

Speaker: @Nicholai Mitchko , Manager, Solution Partner Sales Engineer, InterSystems

Background: Nicholai runs a team of 10 solution engineers at InterSystems that help healthcare companies design, develop, and deliver solutions at enormous scale. In his free time, Nicholai works on large language models, including developing his own models which appear on the Huggingface OpenLLM leaderboard.

See the recording on our YouTube channel:

https://www.youtube.com/embed/S4UgMHPJyqA
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FHIR has revolutionized the healthcare industry by providing a standardized data model for building healthcare applications and promoting data exchange between different healthcare systems. As the FHIR standard is based on modern API-driven approaches, making it more accessible to mobile and web developers. However, interacting with FHIR APIs can still be challenging especially when it comes to querying data using natural language.

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With rapid evolution of Generative AI, to embrace it and help us improve productivity is a must. Let's discuss and embrace the ideas of how we can leverage Generative AI to improve our routine work.

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Our next Developer Meetup will take place on July 26, 17:30 pm at the CIC Venture Café in Cambridge.

Join us to learn Generative AI Use Cases + Reference Architecture in Healthcare, witness the demo of LLMs in Healthcare and share your thoughts on the topic.

RSVP here

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