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10 docs tagged with "AI"

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Agentic AI Frameworks

Explore the transformative potential of Agentic AI frameworks, designed to simplify the development of autonomous systems. Learn about their applications, benefits, and the challenges developers face in this evolving landscape.

Compound AI Systems and DSPy

Examine the evolution of AI systems with a focus on Compound AI and DSPy. Learn how modular architectures enhance control, efficiency, and transparency in AI applications, while exploring the benefits of optimized programming techniques.

Enterprise Workflow Agents

Explore the transformative potential of LLM-powered agents in enterprise workflows, examining their capabilities, challenges, and future directions in enhancing productivity and decision-making.

History and Future of LLM Agents

An insightful analysis of the evolution, current capabilities, and future potential of LLM agents, highlighting their transformative impact on technology and society.

LLM Reasoning: Key Ideas and Limitations

Examine the pivotal role of reasoning in large language models (LLMs), highlighting key advancements, limitations, and practical implications for AI development.

Measuring Agent Capabilities and Anthropic’s RSP

This article examines Anthropic's Responsible Scaling Policy (RSP) and its implications for AI safety and capability measurement, highlighting the advancements in AI technology and the challenges of ensuring responsible development.

Open-Source Foundation Models

This article examines the evolving landscape of open-source foundation models, highlighting the critical role of access in driving innovation, the challenges posed by API-only models, and the opportunities for research and collaboration in the AI community.

The 4 Ps of Marketing: Rewritten for the AI Age

In the AI era, the classic 4 Ps of marketing—Product, Price, Place, and Promotion—demand a modern interpretation. This article analyzes how startups can adapt these foundational principles for innovation and growth, with Notion's journey as a pivotal case study.

Unifying Neural and Symbolic Decision Making

This article examines the integration of neural and symbolic decision-making approaches in AI, highlighting key challenges with LLMs and proposing innovative solutions to enhance reasoning and planning capabilities.