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The Pros and Cons of Artificial Intelligence in the Construction Industry

For our next #tipoftheweek we're diving into conversational data collection and exploring how AI can streamline your construction projects. Don’t miss out on discovering the latest iFormBuilder features that can revolutionize your workflows! https://buff.ly/3AJcyXy #constructiontech #datacollection #aisolutions #constructionmanagement

A lot of things have been going around in the world of LLMs, primarily you will hear these 3 - Prompt Engineering, Retrieval Augmented Generation (RAG), and Fine-tuning. Before delving into depths of each its very important to know how they vary and which to use when. I came across this video - https://lnkd.in/dM47szmj which expains it very nicely. Prompt Engineering: Involves crafting prompts that guide the model's responses. Prompts may include priming, audience considerations, handling errors, and formatting. Dynamic content in prompts can be adjusted based on user inquiries. Knowledge is explicitly provided in the prompt for the model to generate relevant responses. Retrieval Augmented Generation (RAG): Introduces external data sources to the model's prompts. Involves setting up a database with information in vector format for efficient retrieval. Allows dynamic knowledge retrieval during runtime to enhance the model's responses. Enables the model to answer specific queries by pulling in relevant information from the database. We have done a type of RAG implementation in a medium blog here - https://lnkd.in/d_WmT7Gy Fine-Tuning: Fine-tuning involves training a base model on specific examples to modify its behavior. Useful for teaching intuition and incorporating specific writing styles, tones, and formatting. Can enhance model performance with a smaller dataset, contrary to misconceptions. We have done a medium blog on finetuning - https://lnkd.in/dgky-a9X Integration of Techniques: These techniques can be used together. Fine-tuning augments generation capabilities, allowing the model to learn from examples. The combination of RAG and fine-tuning can provide more consistent and accurate results. There's no need to choose between RAG and fine-tuning; they can complement each other. #llm #rag #nlp #largelanguagemodels #generatieveai

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Something I’m really excited about is video within LLMs. You can drop a video into an LLM tool, and the LLM can do mind-boggling things with it. People aren’t thinking enough about what this means in terms of the task categories that can now be augmented with multi-modal models. An idea I’ve been playing around with is: Can you use video capabilities to optimize the quoting process for Electricians and other home services? I built a small prototype where I went from a 2-minute iPhone video of me sharing project details for an EV charger installation at my house -- to a detailed quote (including labor, materials, project phases, etc.) in under 10 minutes. I've attached the detailed quote pdf to this post for you to check out. All generated with LLMs and a bit of prompting: https://lnkd.in/gKBGBhMm I wrote more details on how I did this here on my site: https://lnkd.in/gR4y93Mc And did an 8-minute video walkthrough here on YouTube: https://lnkd.in/gYETHNC3 Some people still think AI and LLMs are all hype. They are not. It's an entirely new set of tools which -- if applied prudently on real problems that exist -- can make a huge difference. I think the world is going to look a lot different in a few years, and I'm thrilled to be on the leading edge of that. What are you or your company building that could use tools or expertise in the AI / LLM eco-system? What ideas do the above concepts raise for you? I'm always eager to hear from you, and what you're trying to accomplish / what problems you have. Maybe we can find a way to work together

6 Best Prompt Engineering Tools in 2024 #Ardenresourcing #engineering #BestPromptEngineeringTools

How to limit errors and speed up the #construction cost estimate process with the help of Artificial Intelligence (AI) https://bit.ly/3GHE5Zg

Exciting times in the construction industry! The title says it all "AI in Construction Has Landed" – AI has officially arrived. So proud of how Miller-Davis Company is embracing the transformative potential of AI! My favorite takeaway from the article: "But construction is inherently reliant on the vast institutional and individual knowledge, something that AI cannot replace." This highlights how critical human expertise is in construction. AI is just a powerful ally that enhances our processes. The fusion of technology and human knowledge is the key to building a brighter future!

What if construction specifications were adapted so contractors could find what they need, right when they need it - in the field or office? Steven Solloway walks us through what that looks like for SpecGPT. #specifications #AI #artificialintelligence #SpecGPT #finditfast https://lnkd.in/g8b5VX8Z