The White House Meets with 7 Big Tech Companies – Releases Commitments on Managing AI

The White House has just announced that that it accepting pledges from a number of high-profile tech companies for the safe development of AI. The Fact Sheet for today’s meeting can be found here. Seven companies — Google, Microsoft, Meta, Amazon, OpenAI, Anthropic and Inflection — convened at the White House today to announce the voluntary agreements.

The Rise of Intelligent Apps in Finance

In this contributed article, Rohit Gupta, CEO and Founder, Auditoria.AI, discusses how the future of finance hinges delicately on the ability to adapt. Unfortunately, the finance department is often the last stop on the progress tour – and sometimes overlooked altogether. Optical Character Recognition (OCR) and Robotic Process Automation (RPA) are two of the most common automation tools in corporate finance today. While both tools serve a specific purpose – RPA is programmed to execute high-volume, repeatable tasks, and OCR helps extract structured data in an automated fashion – as standalone solutions, they no longer pull their weight.

Generative AI Report: DaaS Startup Facteus Launches Mobius

Welcome to the Generative AI Report, a new feature here on insideBIGDATA with a special focus on all the new applications and integrations tied to generative AI technologies. We’ve been receiving so many cool news items relating to applications centered on large language models, we thought it would be a timely service for readers to start a new channel along these lines. The combination of a large language model, fine tuned on proprietary data equals an AI application, and this is what these innovative companies are creating. The field of AI is accelerating at such fast rate, we want to help our loyal global audience keep pace.

Generative AI Report: Pilot Taps OpenAI to launch Pilot GPT

Welcome to the Generative AI Report, a new feature here on insideBIGDATA with a special focus on all the new applications and integrations tied to generative AI technologies. We’ve been receiving so many cool news items relating to applications centered on large language models, we thought it would be a timely service for readers to start a new channel along these lines. The combination of a large language model, fine tuned on proprietary data equals an AI application, and this is what these innovative companies are creating. The field of AI is accelerating at such fast rate, we want to help our loyal global audience keep pace.

Money Laundering Finally Meets Its Match – Federated Learning Will Change the Game

In this contributed article, Laurence Hamilton, Chief Commercical Officer, Consilient, discusses the next generation federated learning solution for financial crime detection. Such a solution will help enable banks and other financial institutions to detect high-risk entities and behaviors by sharing insights across different data environments and organizations.

Analysis of 145 Generative AI Startups IDs Opportunities to Remedy Pain Points in Healthcare and Life Sciences

Generative AI technology could deliver industry-changing improvements in healthcare delivery and life sciences productivity, efficiency and patient outcomes and presents a massive untapped opportunity for entrepreneurs and investors, according to a new market analysis by Justin Norden of GSR Ventures, Jon Wang, and Ambar Bhattacharyya of Maverick Ventures.

The Problem with ‘Dirty Data’ — How Data Quality Can Impact Life Science AI Adoption

Jason Smith, Chief Technology Officer, AI & Analytics at Within3, highlights how many life science data sets contain unclean, unstructured, or highly-regulated data that reduces the effectiveness of AI models. Life science companies must first clean and harmonize their data for effective AI adoption.

How NLP Can Provide Deeper, Actionable Data Insights for All Healthcare Stakeholders

In this contributed article, Anoop Sarkar, PhD, Chief Technology Officer, emtelligent, discusses how providing clinicians with the most accurate and relevant information about a patient at the point of care requires a collaboration between AI-powered medical NLP and clinicians with deep medical knowledge. These collaborations will fulfill the promise of medical NLP.

USGIF Releases New White Paper: The Evolving Role of Synthetic Data in GEOINT Tradecraft 

Recent advancements in AI have created many opportunities in the GEOINT field, not only by improving imagery analysis techniques, but also by creating synthetic training data for AI algorithms to work more efficiently and accurately. Prior to the innovation of synthetic training data, human inputs would be needed for training AI algorithms.

How Synthetic Data can be Created and Utilized for a Wide Range of Use Cases in Healthcare

In this contributed article, Jonah Leshin, Head of Privacy Research at Datavant, discusses how we have seen a rapid increase in the digitization and standardization of health data. With this groundwork laid, more recently, there have been concerted efforts to connect siloed health data sources in support of more impactful use cases. Synthetic data serves as a powerful complementary tool for the analyses that these use cases require, bringing us closer to maximizing data utility within the healthcare ecosystem.