Pinellas County - 5 mile progression: 5.02 miles, 00:09:03 average pace, 00:45:30 duration
missed all the pace ranges i was aiming for. i did keep the progression alive, but just quicker in each mile. the heart rate was still in a good range thankfully.
#running
Pinellas County - Easy: 5.02 miles, 00:09:55 average pace, 00:49:47 duration
Pinellas County - 5 mile progression: 5.02 miles, 00:09:42 average pace, 00:48:41 duration
kept it easy since it was the first week. the first couple miles took a bit to keep locked on but the rest were fine.
#running
Pinellas County - Base: 5.05 miles, 00:09:18 average pace, 00:46:58 duration
mmm… a chill to the air. had been up since 0230 but just laid in bed. did not head out in the morning because of work but was able to sneak this in between meetings.
#running
Pinellas County - Fartlek: 5.01 miles, 00:09:09 average pace, 00:45:54 duration
from recovery to a fartlek to celebrate the colder weather.
#running
5°C le matin, 27°C l’après-midi. Ce ΔT m’épuise! 😫 #climatechange
Pinellas County - Base: 5.29 miles, 00:09:06 average pace, 00:48:07 duration
beautiful morning. tons of energy. was worried my right calf may give me problems being so tight this morning but thankfully it did not. such a drastic difference from the recent long run.
#running
Pinellas County - Base: 5.03 miles, 00:09:31 average pace, 00:47:52 duration
sprinkled a bit but i missed it unfortunately.
#running
Pinellas County - Base: 5.03 miles, 00:09:39 average pace, 00:48:28 duration
right calf is still a bit tight from the charlie horse. body felt fine otherwise although a bit tough to breathe with the humidity. wore the new mach 5s that came a few days ago and they were a bit tight.
#running
Pinellas County - Base: 5.01 miles, 00:09:33 average pace, 00:47:49 duration
Pinellas County - Base: 5.03 miles, 00:09:34 average pace, 00:48:05 duration
tired legs… bit humid probably because it is now pouring three hours later.
#running
user/bmallred/data/2023-09-06-05-45-28.fit: 5.20 miles, 00:08:51 average pace, 00:46:02 duration
Experts warn ‘green growth’ in high income countries is not happening, call for ‘post-growth’ climate policies
The emission reductions in the 11 high-income countries that have “decoupled” CO2 emissions from Gross Domestic Product (GDP) fall far short of the reductions that are necessary to limit global warming to 1.5°C or even just to “well below 2°C” and comply with international fairness principles, as required by the Paris Agreement, according to a paper published in The Lancet Planetary Health j … ⌘ Read more
HOW ABOUT THEM NOLES? 45-24 over #5 LSU! What a game!
user/bmallred/data/2023-09-04-05-50-26.fit: 5.02 miles, 00:09:22 average pace, 00:47:01 duration
Oh btw all, Fairphone 5 is out https://www.fairphone.com/en/, I remember @jlj@twt.nfld.uk was interested in it! :D
user/bmallred/data/2023-08-21-05-59-03.fit: 5.23 miles, 00:09:06 average pace, 00:47:37 duration
Early here at the moment, 5.45
user/bmallred/data/2023-08-09-05-59-05.fit: 5.02 miles, 00:09:38 average pace, 00:48:23 duration
user/bmallred/data/2023-08-07-05-51-04.fit: 5.45 miles, 00:09:21 average pace, 00:51:01 duration
user/bmallred/data/2023-07-18-04-32-08.fit: 5.94 miles, 00:09:12 average pace, 00:54:41 duration
- 2.4 GHz Wi-Fi: long range, can go through walls, fast but not very fast
- 5.0 GHz Wi-Fi: much shorter range, cannot go very far through walls, quite fast
- Li-Fi: long range (?), cannot go through any walls, very very fast
user/bmallred/data/2023-07-01-05-46-44.fit: 5.01 miles, 00:09:28 average pace, 00:47:28 duration
I just took a PD course for 5 hours. 5 hours! Then the fucking LMS didn’t put any CEU or PDH on the certificate. I’m not doing it again.
user/bmallred/data/2023-06-28-05-47-06.fit: 5.03 miles, 00:09:43 average pace, 00:48:49 duration
user/bmallred/data/2023-06-21-10-14-30.fit: 5.00 miles, 00:09:15 average pace, 00:46:14 duration
Idiots never have 5 friends.
If someone calls me: Idiot!, why should I care about. Surely he is wrong. But if 5 friends call me: Idiot!, maybe they are right.
Most of the can run locally have such a small training set they arnt worth it. Are more like the Markov chains from the subreddit simulator days.
There is one called orca that seems promising that will be released as OSS soon. Its running at comparable numbers to OpenAI 3.5.
@prologic@twtxt.net that would work if it was using shamir’s secret sharing .. although i think its typically 3 of 5 so you get 3, one to the company, and one to the “third party”. so you can recover all you want.. but if the company or 3rd wants to they need one of your 3 to recover.
but still .. if they are providing them then whats the point of trusting they don’t have copies.
I played with nlpodyssey/verbaflow: Neural Language Model for Go today a little bit today…. First I had to download a ~2GB file (the model), then convert that to a format the program verbaflow understands which came out to roughly ~5GB. Then I tried some of the samples in the README. My god, this this is so goddamn awfully slow its like watching paint dry 😱 All just to predict the next few tokens?! 😳 I had a look at the resource utilisation as well as it was trying to do this “work”, using 100% of 1.5 Cores and ~10GB of Memory 😳 Who da fuq actually thinks any of this large language model (LLM) and neural network crap is actually any good or useful? 🤔 Its just garbage 🤣
Exoplanet High-5
⌘ Read more
user/bmallred/data/2023-05-18-05-32-02.fit: 5.18 miles, 00:06:01 average pace, 00:31:07 duration
According to the RedMonk programming language rankings from Jan 2023, Go and Scala are tied at 14th place 😏
1 JavaScript
2 Python
3 Java
4 PHP
5 C#
6 CSS
7 TypeScript
7 C++
9 Ruby
10 C
11 Swift
12 Shell
12 R
14 Go
14 Scala
16 Objective-C
17 Kotlin
18 PowerShell
19 Rust
19 Dart

@abucci@anthony.buc.ci read my new skibloreet about why social meets payments is the next level idea! For just §5 bitshlongs a month on my serfdomage site!
@eldersnake@we.loveprivacy.club interesting, because some people are writing articles declaring the metaverse dead: https://www.businessinsider.com/metaverse-dead-obituary-facebook-mark-zuckerberg-tech-fad-ai-chatgpt-2023-5
user/bmallred/data/2023-05-08-05-42-10.fit: 5.70 miles, 00:06:01 average pace, 00:34:18 duration
user/bmallred/data/2023-04-23-05-31-57.fit: 5.33 miles, 00:09:49 average pace, 00:52:18 duration
Started with

a concept sketch of a full body end-time factory worker on a distant planet, cyberpunk light brown suite, (badass), looking up at the viewer, 2d, line drawing, (pencil sketch:0.3), (caricature:0.2), watercolor city sketch,
Negative prompt: EasyNegativ, bad-hands-5, 3d, photo, naked, sexy, disproportionate, ugly
Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 2479087078, Face restoration: GFPGAN, Size: 512x768, Model hash: 2ee2a2bf90, Model: mimic_v10, Denoising strength: 0.7, Hires upscale: 1.5, Hires upscaler: Latent
user/bmallred/data/2023-04-19-11-00-15.fit: 5.82 miles, 00:06:23 average pace, 00:37:08 duration
user/bmallred/data/2023-04-17-05-34-27.fit: 5.32 miles, 00:08:03 average pace, 00:42:50 duration
Es fascinante el poder de las IA, veremos de aquí a 5 años como va este asunto, jah.
user/bmallred/data/2023-04-06-05-28-56.fit: 5.91 miles, 00:07:08 average pace, 00:42:11 duration
go mills() 😅
So. Some bits.
i := fIndex(xs, 5.6)
Can also be
i := Index(xs, 5.6)
The compiler can infer the type automatically. Looks like you mention that later.
Also the infer is super smart.. You can define functions that take functions with generic types in the arguments. This can be useful for a generic value mapper for a repository
func Map[U,V any](rows []U, fn func(U) V) []V {
out := make([]V, len(rows))
for i := range rows { out = fn(rows[i]) }
return out
}
rows := []int{1,2,3}
out := Map(rows, func(v int) uint64 { return uint64(v) })
I am pretty sure the type parameters goes the other way with the type name first and constraint second.
func Foo[comparable T](xs T, s T) int
Should be
func Foo[T comparable](xs T, s T) int
user/bmallred/data/2023-04-04-05-23-06.fit: 5.88 miles, 00:06:43 average pace, 00:39:26 duration
Tampa Bay seems to be picking up the pace. They beat the Islanders 5-0. Go Lightning!
user/bmallred/data/2023-03-07-12-44-30.fit: 5.03 miles, 00:09:37 average pace, 00:48:20 duration
Pinellas County - Long run: 11.11 miles, 00:10:42 average pace, 01:58:57 duration
surprised i even got out there and did something after a day of drinking and dice with the family last night. not a great rest and worn out. the run went well and stayed out of zones 4 and 5. soaked at the end with the humidity.
#running
user/bmallred/data/2023-03-01-08-52-18.fit: 5.85 miles, 00:11:44 average pace, 01:08:39 duration

