Its almost a given considering how fast this field moves. Also, what kind of workflow structure would someone have that a single specific model is the only one that would perform acceptably?
Great story. Reminded me what my professional nightmare would look like. But, I think at the end it started to thin out its allegorical premise when it started including SWE terms like Kanban and retros.
Almost all of these don't apply to diabetes science. Its just the unfortunate nature of the average populace collapsing the complicated nature of scientific work and real human issues into problems that affect "science". Also, bad actors that want to twist the uncertainity of certain scientific areas into fake news.
This was my first thought. Why would you use a cloud provider to store MP3s? There are plenty of cheap local options that don't paint a giant target on your back.
I feel like its another symptom of dying health institutions. These kinds of beliefs also lead people down other ridiculous roads.
I've seen the thought process of someone go from:
- replacing seed oils with animal-based oils
- arguing against the role of LDL in increased CVD and events
- building a more animal-centric and meat-heavy diet
- using "looks-maxxing" terminology to describe their diet and associated beliefs around that diet
- digging deeper into that subculture and believing our ancestors only ate meat
- why do we eat plants or "goy-slop"? well because of [x]
- extreme pseduo-science about other topics
From a technological prespective, we all know that social media accelerates this thought pipeline by feeding people certain content. I also feel like Instagram orders comments in a certain way to specifically engage an individual user. Like making sure they see either a statement they'd agree with OR vehemently disagree with. This is regardless of the number of likes.
If you are not practicing an activity consistently, you'll forget some of the finer grained aspects. When I'm coding, I subconsciously create a continuous logic map. Having someone or something just generate (and generate so quickly) destroys that and makes it easier for bugs to slip through.
These systems have provided incorrect data, and law enforcement often misuse that data to stalk, attack, and wrongfully arrest innocent people. Privacy matters to everyone - especially for ones who don't care about privacy.
Isn't that already being done to a certain extent with things like chili? They add TVP to supplement the meat, and people see it as a very negative thing.
What do you mean by overstating? It has really good protein numbers. The protein itself has an evenly balanced amino acid profile (or in other words - a "complete" protein). It has a good amount of calcium, iron, and low fat. You can technically make it yourself and there's numerous ways of cooking and flavoring it.
On top of that, there seems to be a pervasive misconception of the effectiveness of plant vs animal-based protein on things like muscle growth. Older studies showed that plant-based proteins had lower digestibility scores via metrics like PDCAAS. In turn, people interpolated that muscle growth would be lower. Some early studies comparing the two protein sources on muscle synthesis didn't do gram-for-gram comparisons and that increased the misconception. Newer studies are showing that, if you match the protein amount at or above the 1-1.6 g/kg for muscle growth, you will get the same level of muscle growth.
I feel like it'll take another 5 years for this "bio-availability" myth to die out.
Great work and love the detailed breakdown. This is kind of tangential, but it reminded me of this work: https://arxiv.org/pdf/2310.12973 (Frozen Transformers in Language Models are Effective Visual Encoder Layers).
The paper puts out an interesting hypothesis that these LLM-derived transformer layers have the ability to "refine" any set of learned tokens, even in different modalities. I wonder if what you're seeing here is related?