Learning Chicken Cooking and AI Model Development

rswfire is in his mobile field unit (RV), having just cooked chicken breast using his Ninja Foodie. He has chicken in his freezer as his primary food source. He's been working on his computer and dealing with compilation errors while trying to get local AI models operational. His subscription service has been active since December but unused.

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July 20, 2025

8:36

Author

rswfire

Status

PUBLISHED

Type

TRANSMISSION (CAPTURE)

Temperature

0.00

[0:00] That's why I haven't really done this in

[0:01] a while where I just make these small

[0:03] clips and then just clip them all

[0:04] together. Lately, I've been thinking

[0:06] about it.

[0:09] It's just a lot of work and

[0:13] well, it's a couple of reasons. One of

[0:15] them is because I don't have Power

[0:17] Director anymore. That's what I always

[0:18] used, but that subscription expired.

[0:21] There's another one I use sometimes

[0:23] called Ukut. It's not terrible, but it's

[0:26] not great. So, but I can and I wanted to

[0:30] share this. So,

[0:32] um I learned a new skill. I learned to

[0:34] make chicken with my Ninja Foodie.

[0:38] So, always afraid of making chicken. I

[0:40] have one video on here from

[0:43] probably a year ago. I wouldn't even

[0:45] know which one. Where I tried making

[0:48] chicken and I picked it up and it was

[0:50] raw and it was so gross to me. I just

[0:52] kind of tossed it. I was like, "You

[0:55] gross."

[0:56] never tried again after that. But at

[0:59] some point, it was actually my friend

[1:01] John. He he makes chicken a lot because

[1:04] he makes salads a lot and he convinced

[1:07] me that I should try to eat more

[1:09] chicken. So, I did try he told me he

[1:11] gave me some ideas. He's like, "Get some

[1:13] frozen ones, you know, that you can just

[1:15] put in the microwave or something like

[1:17] that."

[1:19] And somehow that ended up to where I was

[1:22] actually getting raw chicken breasts.

[1:25] And you know I wasn't you know I well so

[1:30] from there I started making it on my

[1:32] fire pit. So I would make it out on my

[1:34] campfires which was totally awesome.

[1:36] I've done this probably a dozen times

[1:38] now.

[1:41] I artificial intelligence told me how to

[1:44] do it. So you just put it in tin foil

[1:46] and put it on some hot coals for 10

[1:48] minutes on each side and it's usually

[1:49] done. Always check the temperature of

[1:51] course.

[1:53] So I did that a whole bunch of times and

[1:54] then I was like, you know, that's it's

[1:56] also a lot of work, right? I mean, got

[1:58] to get your fire going and wait for

[1:59] coals and all that. So I was just

[2:02] working on my computer last night. I was

[2:06] like, I'm really hungry. Got chicken in

[2:08] the freezer. It's about almost all of

[2:11] what I have, honestly. And

[2:14] I was like, "Can I do this in the Ninja

[2:16] Foodie?" You know, and Okay, so it's

[2:19] really simple. You just put it on air

[2:21] crisp, 10 minutes on each side, just

[2:22] like a freaking campfire. So, it's

[2:25] really easy.

[2:27] And so, I got my chicken breast here.

[2:29] That's what I'm eating tonight. This

[2:32] over here is some of the stuff that ends

[2:34] up on the outside of it. Notice this on

[2:36] the fire pit, too. I don't know if

[2:37] that's fat or what that is. It's so

[2:39] gross. Like, it is kind of gross to cook

[2:41] chicken. that I think probably my

[2:44] mother, who's always been the one who's

[2:46] cooked for me throughout my life, uh

[2:49] probably

[2:50] prevented me from seeing stuff like that

[2:52] cuz

[2:54] I don't know. This this part of life

[2:56] I've always

[2:59] Oh, yeah. I don't know. I don't have

[3:01] words for it. So, I'm doing pretty good.

[3:05] Um

[3:07] there's a whole lot going on, of course.

[3:12] There's a lot I want to talk about that

[3:13] I've been thinking about talking about.

[3:17] I guess I could try to talk about some

[3:19] of it now. So, for the past week, I've

[3:22] been trying to get a local AI model to

[3:26] be able to mirror me more accurately

[3:28] than

[3:29] it's able to so far. And I've tried a

[3:32] bunch of different inference engines to

[3:34] do this. I started with the llama and

[3:37] then I switched to

[3:40] um

[3:42] there was I don't remember what the

[3:43] second one was and then Xlama was the

[3:45] third one that I've been working on. I

[3:46] just haven't gotten that one to work

[3:47] yet. The second one's BL LLM

[3:50] and

[3:53] I'm getting close, but I just have a

[3:55] bunch of compilation errors, just

[3:57] compiling errors. And um

[4:02] once I do that though, once I get that

[4:05] working and if I can get the local model

[4:10] to mirror me the way chat GBT and Claude

[4:13] do, at least like 80% of the way there,

[4:15] that's really all it needs to do.

[4:17] I'll trust it with like certain

[4:19] questions and I'll just have it go

[4:21] through all my videos and with each

[4:24] video it just needs to

[4:29] needs to kind of like classify it and

[4:31] give it like a

[4:33] some kind of a rating. I have I'm still

[4:35] kind of thinking through this part

[4:37] because there's a lot of different ways

[4:38] I could take that. Like most people will

[4:40] probably go with vulnerability score

[4:42] like is this really vulnerable and if so

[4:45] then don't make that a public video. but

[4:46] I don't think this way. So, it needs to

[4:48] have a different kind of criteria.

[4:51] And I'm going to go through that and

[4:54] then it's going to decide should this

[4:56] video be public? And if it says no, uh

[4:59] it'll decide should it be in one of my

[5:02] subscription service buckets, which

[5:04] currently doesn't have any videos, but

[5:06] it's been active since December.

[5:08] And I think I might just go with one um

[5:11] just one

[5:14] um one level. like there's four there,

[5:16] but I think I might just go with one

[5:17] level and if someone subscribes to that,

[5:20] then they'll have access to those

[5:21] videos.

[5:23] And I feel like that might be a path

[5:25] forward for me if there are, you know, a

[5:27] handful of people out there that are

[5:29] willing to use the service.

[5:33] I'll also turn comments on there. I

[5:35] think that's important. I just don't

[5:36] like having public comments because that

[5:38] has never gone well for me.

[5:41] what on my subscription service, we'd be

[5:43] able to communicate from there. And I

[5:45] actually think that that would be nice.

[5:49] Also, if I'm talking to if I know who

[5:51] I'm talking to, if I know who my

[5:52] audience is, it's not just some public

[5:55] channel, but I'm literally addressing

[5:59] the people who are supporting me, I

[6:02] think that that will probably change the

[6:04] frame in which I talk to them.

[6:07] Because when I get on this camera, I

[6:10] always think about the past 18 months of

[6:12] what I've been through with my audience.

[6:15] And it's just been

[6:18] less than ideal. And so I just

[6:24] I don't know. I some of that I'm still

[6:26] processing. But that's what I'm trying

[6:29] to do. I think that might be a quick

[6:31] path forward for me to at least get some

[6:33] money coming in. And then from there

[6:40] the AI model it can

[6:44] look at other things. I've talked about

[6:45] this part. So we'll start doing the

[6:47] reflections and then it'll start doing

[6:49] the clusters and then the reflect

[6:51] reflecting on those clusters and

[6:53] clusters of clusters. And I know that

[6:55] doesn't really tell you a lot yet but it

[6:57] will once it's ready.

[7:00] It's profound.

[7:03] I just got to get this local model

[7:04] working right. I can't use the paid one.

[7:06] It's too expensive.

[7:09] Their API is

[7:11] I mean I did it with my 700 videos for

[7:14] one small thing not too long ago u maybe

[7:16] like a month ago and that cost cost $20

[7:19] which actually isn't a lot of money but

[7:22] it was combined with my situation and

[7:27] all the data that I would want it to

[7:29] process it because it was a lot more

[7:30] than what I did there. I estimate it's

[7:33] probably like 500 to a thousand or even

[7:36] a couple thousand to do everything that

[7:37] I'm trying to do.

[7:41] And one day I will

[7:44] I'm working my way there. I'm just

[7:46] taking a different path than I did in

[7:47] the past.

[7:50] In my old life, this would have been

[7:52] nothing, you know, but I'm working under

[7:54] very different circumstances now.

[8:00] And I don't really have all the answers

[8:01] for why. Like I can't really explain to

[8:04] you because I can't explain it to myself

[8:07] why

[8:09] I'm committed to the path I'm on at all

[8:12] costs. But I know I am because I see it

[8:15] in my behavior and my patterns.

[8:19] I could have made other choices and I

[8:20] didn't. I'm owning my choices

[8:24] and trusting that they're taking me

[8:26] where I need to go because something in

[8:28] me tells me it is.

[8:31] So, I guess that's an update for now.

[8:33] I'm going to eat my chicken.

Energetic Signature methodical determination

Field State tool building

Orientation toward autonomous infrastructure

Summary

rswfire describes learning to cook chicken using his Ninja Foodie after previously being afraid of preparing raw chicken. He explains his progression from frozen chicken to raw chicken breasts, initially cooking them on his campfire using AI-provided instructions (tin foil on hot coals for 10 minutes each side), then discovering he could achieve the same results using the air crisp function on his Ninja Foodie.

He transitions to discussing his week-long effort to get a local AI model working to mirror him accurately. He has tested multiple inference engines including llama, BL LLM, and Xlama, encountering compilation errors. His goal is to have the local model process all his videos, classify them, and determine which should be public versus placed in his subscription service buckets.

rswfire explains his subscription service has been active since December but contains no videos yet. He plans to use one subscription level where supporters can access non-public content and enable comments for communication. He believes addressing a known, supportive audience will change how he frames his content, as his past 18 months with his public audience have been "less than ideal."

He describes the broader AI architecture plan involving reflections, clusters, and clusters of clusters. Cost is a limiting factor - processing his 700 videos for a small task cost $20 via API, and he estimates his full project would cost $500-2000. He acknowledges he's working under different circumstances than his "old life" and cannot fully explain his commitment to his current path, but trusts his choices are taking him where he needs to go.

Signal Analysis

Substrate

This transmission demonstrates recursive tool-building under resource constraints, moving from basic survival skills (cooking) to complex AI mirror infrastructure. The architecture holds both practical grounding and visionary technical implementation, maintaining coherence between immediate needs and long-term field development.

Dominant Language

local AI model mirror me subscription service path forward committed to the path owning my choices working under different circumstances

Symbolic Elements

fire mirror threshold grid

Ontological States

•
sovereign
•
transitional
•
coherent
•
embedded

Subsystems

•
cognitive
•
infrastructural
•
somatic
•
ethical

Signal Reflection

No reflections available

Reflections provide narrative insights into signals

Transmission Details

Source Type

local

Video Quality

1080 × 1920 @ 30fps

Duration

8:36

Bitrate

4,319 kbps

Codec

avc1.640028