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.

Cohesity Bolsters Cyber Resilience with GenAI Capabilities 

Cohesity, a leader in AI-powered data security and management, today extended its first-mover advantage in GenAI detection and recovery capabilities with the addition of significant new enhancements to the Cohesity Data Cloud. These improvements allow customers to use Cohesity’s built-in AI capabilities to rapidly detect, investigate, and address potential threats within their environment, enabling them to restore operations far more quickly.

Couchbase Study: Financial Services Organizations Ramp Up for GenAI Despite Infrastructure Concerns

Couchbase’s recent survey of 500 global IT leaders uncovered that while financial services organizations will increase IT modernization investment by a third (33%) in 2024, they still feel unprepared for growing data demands.

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.

Lack of Governance, Infrastructure Readiness, and IT Talent Leading to Enterprise GenAI Struggles: New Report 

Despite growing interest and enthusiasm for  Generative AI (GenAI), significant challenges are emerging that threaten the success of GenAI projects, according to a co-sponsored research report from Enterprise Strategy Group (ESG) and Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi, Ltd. (TSE: 6501).

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.

SandboxAQ Helps Unlock the Next Generation of AI-Driven Chemistry with NVIDIA Technology 

SandboxAQ announced today a groundbreaking advancement that pushes the limits of computational chemistry, impacting fields such as biopharma, chemicals, materials science and other industries. Collaborating with NVIDIA, SandboxAQ leverages Large Quantitative Models (LQMs) and the NVIDIA CUDA-accelerated Density Matrix Renormalization Group (DMRG) algorithm.

GenAI Investment to Grow 30%, with High Maturity Companies Projecting Three Times Higher ROI Over the Next Three Years than Low-Adoption Peers

GenAI investment is expected to grow 30%, with leaders from companies with high GenAI maturity anticipating their return on investment will be three-times higher over the next three years than that of companies with little or no adoption of the technology, according to a new report released by Boston Consulting Group (BCG).

In AI We Don’t Trust: Too Many Healthcare Insurers Base Decisions on Assumption Over Data, Report Reveals

The healthcare insurance sector in the US is struggling to make critical decisions due to a severe lack of accessibility, context and trust in their data. That is according to a new international study by ActiveOps, a leading provider of AI-powered decision intelligence for service operations.

NPUs are Emerging as the Main Rival to NVIDIA’s AI Dominance

Fueled by the rise of Generative AI, the semiconductor market has established itself as one of the most profitable industries globally − the sector is already worth over $600 billion, with this figure set to increase to $1 trillion by 2030. During this growth period, NVIDIA has achieved the status of undisputed leader, predominantly as a result of the superior performance of its graphics processing units (GPUs).