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Current SBIR Grant Opportunities in AI and Data Analytics

April 2025

Executive Summary

This report provides a comprehensive overview of current Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) grant opportunities available for artificial intelligence (AI) and data analytics technologies as of April 2025. It covers open solicitations across major federal agencies, key focus areas in AI and data analytics, application processes, and timelines. The report is intended to serve as a resource for small businesses seeking federal funding for AI and data analytics innovations.

Introduction

The Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs represent the largest source of early-stage research and development funding for small businesses in the United States. These programs enable small businesses to explore technological potential and provide the incentive to profit from commercialization opportunities. With increa

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BlackRock's Approach to Generative AI and Agentic Systems: A Comprehensive Analysis

April 2025

Executive Summary

This report provides a comprehensive analysis of BlackRock's approach to generative AI and agentic systems, based on publicly available information as of April 2025. As the world's largest asset manager with approximately $10 trillion in assets under management, BlackRock's AI strategy offers valuable insights into how financial institutions are incorporating advanced AI technologies into their operations and investment processes. The analysis examines BlackRock's AI infrastructure, current applications, approach to autonomy, and strategic partnerships, while placing these developments within broader industry context.

1. Introduction

BlackRock, founded in 1988, has consistently positioned itself at the forefront of financial technology innovation, notably through its Aladdin platform which serves as an operating system for investment managers. In recent years, the company has accele

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HL7 FHIR Sources for Synthetic Data

Introduction

This document provides an overview of available sources for synthetic healthcare data in HL7 FHIR format. Synthetic data is invaluable for healthcare IT development, testing, research, and education without the privacy concerns of real patient data.

Vulcan FHIR Accelerator

Vulcan is an HL7 FHIR Accelerator program dedicated to connecting clinical research and healthcare. Their mission is to pursue standardized approaches to healthcare data interoperability that strengthen clinical trials and other categories of clinical research.

Key aspects of Vulcan include:

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AI Alignment and Agentic Hackathons: April-June 2025

Introduction

The first half of 2025 features several significant hackathons and research programs focused on artificial intelligence, with particular emphasis on AI alignment and agentic systems. This document catalogs the major events scheduled between April and June 2025, providing key details for researchers, developers, and enthusiasts interested in contributing to the advancement of safe and beneficial AI.

April 2025

Microsoft AI Agents Hackathon 2025

Dates: April 8-30, 2025

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LangGraph for Fraud Detection: Multi-Agent Approaches and Case Studies

1. Introduction to LangGraph

What is LangGraph?

LangGraph is a module built on top of LangChain to better enable creation of cyclical graphs, often needed for agent runtimes. It's designed to enable the creation of complex agent workflows, supporting diverse control flows including single agent, multi-agent, hierarchical, and sequential patterns.

LangGraph — used by Replit, Uber, LinkedIn, GitLab and more — is a low-level orchestration framework for building controllable agents. LangGraph provides customizable architectures, long-term memory, and human-in-the-loop capabilities to reliably handle complex tasks.

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AI Engineering Bootcamp: Comprehensive Concept Walkthrough

Introduction

Welcome to the AI Engineering Bootcamp! This 10-week intensive program is designed to transform you from a programmer into a certified AI Engineer capable of building production-ready AI applications. The curriculum follows a logical progression through two main phases:

1. Build Phase (Weeks 1-7): Focus on prototyping, concepts, and development
2. Ship Phase (Weeks 8-10): Focus on production deployment and optimization

The bootcamp culminates in a Demo Day where you'll showcase your Certification Challenge project to peers and potentially industry professionals.

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Google's A2A Protocol and OpenTelemetry Alignment

A2A Protocol Overview

Google's Agent2Agent (A2A) Protocol is an open protocol designed to enable communication and interoperability between AI agents across different ecosystems, frameworks, and vendors. Announced in April 2025, A2A provides a standardized way for agents to collaborate regardless of their underlying technologies[1].

Key Features of A2A

• Capability Discovery: Agents publish their capabilities through "Agent Cards" in JSON format, allowing client agents to identify and connect with suitable remote agents[2]
• Interoperability: Enables AI agents to work across different frameworks and vendors[1]

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Ali Arsanjani's Work on A2A, MCP, and OpenTelemetry Integration

Introduction

This research document examines Dr. Ali Arsanjani's contributions to Agent-to-Agent (A2A) Protocol, Model Context Protocol (MCP), and potential connections to OpenTelemetry for AI agent observability. Dr. Arsanjani is the Director of AI/ML Partner Engineering at Google Cloud and has been identified as an author of the A2A protocol.

A2A Protocol Contributions

Dr. Ali Arsanjani has written extensively about the Agent-to-Agent (A2A) protocol, an open standard developed by Google to enable communication between AI agents across different frameworks and vendors. As mentioned in his April 2025 article, he identifies himself as "an author of this protocol" [1].