Heard on the Street – 8/21/2024

Welcome to insideAI News’s “Heard on the Street” round-up column. In this feature, we highlight thought-leadership commentaries from members of the AI industry ecosystem. We cover the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.

InsideAI News on the Move: Join Us at the Premier AI Industry Events!

At InsideAI News, we believe that the best way to stay at the cutting edge of artificial intelligence is by engaging directly with the innovators, thinkers, and leaders driving the industry forward. That’s why we’re thrilled to announce our in-person attendance at some of the most prestigious AI industry conferences this year

Synthetic Data Solves AI’s Biggest Problem

In this contributed article, Kalyan Veeramachaneni, co-founder and CEO of DataCebo, discusses how synthetic data is a useful application of AI technology that is already delivering real, tangible value to customers. More than mere fake data, synthetic data supports data-driven business systems throughout their lifecycle, particularly where ongoing access to production data is impractical or ill-advised.

insideAI News – Media Partner for AI Hardware and Edge AI Summit 2024

insideAI News is pleased to announce being a Media Partner for the upcoming AI Hardware & Edge AI Summit happening Sept. 9-12, 2024 in San Jose, Calif. Editor-in-Chief & Resident Data Scientist, Daniel D. Gutierrez will be attending in-person to keep a pulse on this advancing industry. He will be conducting interviews with some of the movers and shakers from the AI industry ecosystem.

Boomi Discovery Report Reveals More Than Half of Enterprises Invest in GenAI for Integration and Automation 

Boomi™, the intelligent integration and automation leader, announced findings from its Boomi Discovery Report, commissioned by 451 Research. The report, based on perspectives from 650 business and IT leaders across a broad range of industries, outlines how enterprises are using Generative AI (GenAI) to integrate systems and automate processes, and how this has helped their business operations as a result.

Data Science and AI Company KNIME Secures Investment to Accelerate Adoption of Enterprise-Grade AI Governance and ModelOps 

KNIME, one of the leading open-source data science and AI companies, has raised additional funding from its longstanding investor Invus. Since the last announcement, Invus invested another $30M, bringing total funding to $50M. This will allow KNIME, as the only open-source, low-code data science company on the market, to double down on development of its enterprise-grade AI governance and ModelOps capabilities, while continuing to stay ahead of the rapid innovation in the field. 

New Study Puts Claude3 and GPT-4 up Against a Medical Knowledge Pressure Test

Kahun, the evidence-based clinical AI engine for healthcare providers, shares the findings from a new study on the medical capabilities of readily-available large language models (LLMs). The study compared the medical accuracy of OpenAI’s GPT-4 and Anthropic’s Claude3-Opus to each other and human medical experts through questions based on objective medical knowledge drawn from Kahun’s Knowledge Graph.

Revolutionizing Manufacturing: The AI Impact

In this feature article, Daniel D. Gutierrez, insideAInews Editor-in-Chief & Resident Data Scientist, discusses how AI is revolutionizing the manufacturing industry. This revolution promises to enhance efficiency, reduce costs, and improve overall product quality. We explore the multifaceted impact of AI on manufacturing and how it is reshaping the industry’s landscape.

New KNIME Release Helps Enterprises Scale GenAI While Reducing Risk

KNIME, one of the leading open-source data science and AI companies, is announcing a new release to help enterprises securely scale their use of GenAI. The new GenAI features allow organizations to access more AI models, govern which AI models are being used by their data science teams, and ensure no leakage of sensitive data.

MIT News: How to Assess a General-purpose AI Model’s Reliability Before It’s Deployed

Researchers from MIT and the MIT-IBM Watson AI Lab developed a technique to estimate the reliability of foundation models before they are deployed to a specific task. They do this by considering a set of foundation models that are slightly different from one another. Then they use their algorithm to assess the consistency of the representations each model learns about the same test data point. If the representations are consistent, it means the model is reliable.