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Artificial Intelligence

Artificial Intelligence
The Frameworks Are Breaking — And So Are the Systems Built on Top of Them
Three converging events reveal a single crisis: our strategic frameworks for managing complexity are failing just as AI systems become too opaque to govern. A five-part essay series exploring solutions launches next week.

Artificial Intelligence
From RAGs to Riches
RAG enhances large language models by connecting them to external, up-to-date data sources, improving accuracy, reducing hallucinations, and enabling cost-effective, domain-specific AI applications without requiring expensive model retraining.

Artificial Intelligence
The Genesis Mission: Where is It Headed?
Trump's Genesis Mission leverages National Laboratories, supercomputers, and federal datasets to accelerate AI-driven scientific discovery. Twenty-four organizations including Anthropic and OpenAI joined. The initiative aims to compress research timelines while maintaining US leadership against China's growing R&D capabilities.

Artificial Intelligence
Orchestrating the Modern Supply Chain
Supply chains must evolve from digitalization to AI-powered orchestration for proactive decision-making. Enterra Solutions' System of Intelligence enables autonomous optimization across planning, execution, and learning, representing supply chain management's future.

Artificial Intelligence
Is Agentic Commerce the Next Big Thing in Retail?
Agentic commerce—AI agents making purchases for consumers—could generate $1-5 trillion by 2030. Though 95% of consumers harbor concerns, retailers must invest immediately in agentic capabilities or risk disintermediation.
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Personal Dispatches: Reflections on today’s society through the lens of Fortune Magazine December 1941

Artificial Intelligence
What Business Leaders Need to Know About Machine Learning in 2022
Machine learning (ML) is a type of artificial intelligence (AI) that allows computers to learn from data and make predictions. Businesses are adopting ML to automate tasks, improve efficiency, and gain new insights from data. There are different techniques for training ML models, including supervised, unsupervised, and reinforcement learning. No-code ML, TinyML, AutoML, and MLOps are emerging trends that make ML more accessible to businesses. By understanding ML, businesses can discover new opportunities to gain a competitive advantage.

Artificial Intelligence
Alright, AI. Explain Yourself
Businesses worry about inaccurate AI outputs. Explainable AI aims to address this by making AI systems transparent, building trust, and ensuring fair and accurate AI decisions.


