Preston McCauley

I often find more active communities in Discord, specifically those related to AI and edge technologies. The best way to find these communities is to look for the latest popular GitHub projects in a specific field. Then, identify what the community is excited about, join the conversation, and start chatting. This is a great way to learn so much more. You can quickly engage and learn about the latest developments in any field. This will drive your discussions and help you connect with people passionate about technology, innovative approaches, and problem-solving.

Your primary goal should be understanding data architecture and how humans expect to use and interact with it. I'm building amazing things with AI, but it all starts with understanding the goals, objectives, and data I'm about to use. As AI technology advances, it's important to remember that data analysis, architecture, and information skills are at its core. These skills are not just theoretical but crucial in discerning what is true and false when working with complex AI systems. Understanding the foundations of data of all types will be your path forward. They are the building blocks and act as gateways to everything to come.

As a UX teacher, I am often asked these questions. The best advice is to diversify your skills and portfolio. Create full examples across the UX process in a variety of industries. Push yourself to move beyond just wires, prototypes, and research. Expand to understand strategy, as this is a key element necessary in AI evolution. Refine your understanding of how to solve, and specifically think about why you are designing the solution, what problems you are solving, and why your solution solves these problems precisely. Always look to learn the latest cross-functional skills, as that helps you stay up with rapidly changing markets

If you want to find the best tools to experiment with. It would be best to start with LM Studio / GPT4ALL, which accesses many local models and allows you to experiment with techniques. You should join the myriad of discord servers dedicated to AI. Then it would be best if you looked at the top GitHub projects. Next, take a look at the hugginface website. Lastly, I highly recommend product hunt. These four places have the most activity in the space, and I check them daily. Then, I would dig into more of the enterprise-level systems like vertexAI, Anthropic, and Bedrock. These tools speed up a lot of process-level flows. The AI space is rapidly changing, so new techniques are constantly evolving.

Step 1. Create a list of known markers for facial points. This could be with open cv. This means asking the ai what patterns might exist if the data set was diverse in x or y. This will lead you down a path to understand what new approaches could be taken, next I would proceed to isolate techniques for improving the core data set, perhaps there are other aggregate markers that generative AI attached to open cv can see if they two are connected together, emotional cues, but also voice inflection. That’s how I would begin. Check out this article to discover techniques I use https://medium.com/@uidesignguide/utilizing-artificial-intelligence-for-hypothetical-problem-solving-and-critical-thinking-strategies-a604ff986abd

The goal is going to change dependent upon what my objective is with my model. I’m actively building specialist based models where I can rotate out wide array of corpus topics. I’ll be sharing a lot more on this soon. I also designed a model to evaluate bias and truth validity, that is currently patent pending. Truth and facts in data train sets is so important https://medium.com/@uidesignguide/utilizing-artificial-intelligence-for-hypothetical-problem-solving-and-critical-thinking-strategies-a604ff986abd In the meantime check out my latest article on my profile about using fine tuned AI”s to approach hypothetical problem solving.