Search:
Match:
3 results
business#ai adoption📝 BlogAnalyzed: Jan 19, 2026 14:30

Breaking Free: Driving Enterprise-Wide AI Adoption!

Published:Jan 19, 2026 14:19
1 min read
AI News

Analysis

IBM's new service model is a game-changer! It's designed to help companies leapfrog from AI pilot projects into full-scale enterprise integration. This exciting approach promises to unlock the full potential of generative AI.
Reference

The article highlights the crucial shift from AI pilot programs to full-scale enterprise adoption.

The AI paradigm shift most people missed in 2025, and why it matters for 2026

Published:Jan 2, 2026 04:17
1 min read
r/singularity

Analysis

The article highlights a shift in AI development from focusing solely on scale to prioritizing verification and correctness. It argues that progress is accelerating in areas where outputs can be checked and reused, such as math and code. The author emphasizes the importance of bridging informal and formal reasoning and views this as 'industrializing certainty'. The piece suggests that understanding this shift is crucial for anyone interested in AGI, research automation, and real intelligence gains.
Reference

Terry Tao recently described this as mass-produced specialization complementing handcrafted work. That framing captures the shift precisely. We are not replacing human reasoning. We are industrializing certainty.

Technology#Machine Learning📝 BlogAnalyzed: Dec 29, 2025 08:20

Industrializing Machine Learning at Shell with Daniel Jeavons - TWiML Talk #202

Published:Nov 21, 2018 16:32
1 min read
Practical AI

Analysis

This article summarizes a podcast episode featuring Daniel Jeavons, General Manager of Data Science at Shell. The discussion centers on Shell's application of machine learning (ML) within its operations. Key topics include the evolution of analytics and data science at Shell, focusing on Internet of Things (IoT) applications, edge computing, federated ML, and digital twins. The conversation also delves into the data science process at Shell and the significance of platform technologies for the company. The article highlights the practical application of ML in a large industrial setting, offering insights into challenges and strategies.
Reference

In our conversation, we explore the evolution of analytics and data science at Shell, discussing IoT-related applications and issues, such as inference at the edge, federated ML, and digital twins, all key considerations for the way they apply ML.