Today It's Q&A Time - AIxC: 75
+ Applying CMF and New SREFs for Paid Subscribers
Hey all, welcome to #75! I thought I’d take time today to highlight and answer a lot of great questions that come up on Linkedin. Ones that I think will help provide some clarity as to how Ai impacts our creative work.
If you have any questions our inbox is always open,
Hector & the AIxC Team
01 / Q&A
How do we know if we’re not getting results because the tool isn’t capable or because of lack of skills?
This is a great question and it’s a tough one. The answer is that it’s hard to know with certainty without investing a fair amount of time. One week isn’t enough, let alone one day or one hour.
I have two suggestions, aimed at two mindsets.
For those who enjoy testing and tinkering, set time aside to “play” with these tools. No focus on ROI, just a focus on learning. If you’re a leader at an org, find those individuals that have this mindset and give them that space. I can’t stress enough the no ROI focus. Not yet.
For everyone else, be friends with the tinkerers. Ask them to show you what they’re working on and what they’re learning. Make your investment of time more about gathering filtered learnings.
There is no shortcut to answer this question. It’s a case by case basis and it simply takes time and effort to be able to accurately answer it.
02 / Q&A
Ai seems like it’s just for pretty pictures online. How does it work for real world application?
Another great question, probably one of the biggest ones.
The answer we’ve found is that it generally looks one of two ways.
1. Traditional with Sprinkles of Ai
This is the majority of how Ai looks in the real world. An Ai enhanced project that when you zoom out, looks almost exactly the same as our traditional process. It’s when you zoom in that you see there are opportunities to inject Ai efforts for gains in depth, breadth or speed.
The big takeaway here is that the more experience you have with Ai, the more opportunities you will spot, upstream, downstream and everywhere in between.
These are incremental gains that add up.
2. Ai Redefined
In the minority are Ai implementations where you begin to rethink the entire process, or large portions of it.
These are harder to come by but they have the potential to be exponential in nature. They require a lot of dead ends and they require time to prove. They’re tough because you have to question everything.
These opportunities will become more and more common over time as tool progress continues to open new doors.
My Closing Thoughts
My closing thoughts on this topic are to start with option 1. Avoid thinking that Ai has to be everywhere and instead focus on easy wins - areas where you can get some small incremental gains. Do that for a while and get some wins under your belt. Option 2 will come in time.
03 / Q&A
What tools do you recommend for design?
Like every other question, it’s not an easy one to answer, but some thoughts that will hopefully help.
Ai is like learning a new language. Once you’re fluent, you can talk to all of the tools.
The right tool, then, is the one that you will start using today. Just pick one and start talking the language.
Tools with more built-in capability (closer to all-in-one) will give you a better opportunity to learn more of the language, versus tools that do one thing.
A lot of tools have free or low cost options, start there if cost is an issue. Or pay for a higher level plan. For some folks, paying helps keep them logging in the time.
Open source tools are great but require a heavy lift to start. If you have the time, by all means go the route of SD/Flux/Comfy. For most people, closed-model tools will get you up and running (and learning the language), much sooner.
04 / FOR PAID SUBSCRIBERS
Applying CMF
For paid subscribers we have new content in the lab on applying CMF and a few new SREF codes.
Sign up below for access to the AIxC R&D Lab board and the detailed breakdown. Link and password behind the paywall.