Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world. Phone Number: +1-650-246-9381 Email: [email protected]
228 Park Avenue South New York, NY 10003 United States
Website: Publisher: https://towardsai.net/#publisher Diversity Policy: https://towardsai.net/about Ethics Policy: https://towardsai.net/about Masthead: https://towardsai.net/about
Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-François Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
Towards AI Cover
Logo:
Towards AI Logo
Areas Served: Worldwide Alternate Name: Towards AI, Inc. Alternate Name: Towards AI Co. Alternate Name: towards ai Alternate Name: towardsai Alternate Name: towards.ai Alternate Name: tai Alternate Name: toward ai Alternate Name: toward.ai Alternate Name: Towards AI, Inc. Alternate Name: towardsai.net Alternate Name: pub.towardsai.net
5 stars – based on 497 reviews

Frequently Used, Contextual References

TODO: Remember to copy unique IDs whenever it needs used. i.e., URL: 304b2e42315e

Resources

Unlock the full potential of AI with Building LLMs for Production—our 470+ page guide to mastering LLMs with practical projects and expert insights!

Publication

Why LLM Patterns Are the Key to Enterprise Success — And Why Ignoring Them is a Mistake
Artificial Intelligence   Data Science   Latest   Machine Learning

Why LLM Patterns Are the Key to Enterprise Success — And Why Ignoring Them is a Mistake

Last Updated on November 3, 2024 by Editorial Team

Author(s): David Sweenor

Originally published on Towards AI.

This member-only story is on us. Upgrade to access all of Medium.

In nature, patterns are everywhere — you just have to look. Photo by author David E. Sweenor

As the generative AI aura begins to fade, organizations realize that the technology is not the panacea they once thought. To move beyond tinker-toy prototypes to enterprise-grade AI systems is challenging, to say the least. McKinsey estimates that only 11% of organizations have adopted generative AI at scale.[1] Organizations are hoping to automate tasks, optimize processes, and improve overall productivity are excited about the potential. The excitement is certainly justified — AI can generate content, retrieve critical information, and summarize large corpora of data at a scale and speed unmatched by human labor. However, there’s a critical oversight many enterprise leaders are making: without a structured understanding of AI patterns, these initiatives are likely to fail.

Generative AI is not a one-size-fits-all solution. In order for AI to improve organizational productivity, it must be deployed using specific frameworks — AI patterns — that align the technology with the company’s use cases. There are five key AI patterns that, when applied correctly, offer a clear pathway to improving efficiency, decision-making, and automation: Author, Retriever, Extractor,… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓