
Ask HN: What angle of startups or AI isn't covered by YouTube creators? - scotthtaylor
I&#x27;ve just started creating content on YouTube and want to know from the HN audience what you think is lacking from the videos and creators that are currently on YouTube?<p>And I say startups and AI specifically as I&#x27;ve started and sold a few startups previously. And now help lead an AI&#x2F;ML team within a large asset manager manage ~$320 billion across a number of asset classes.
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sneeuwpopsneeuw
(This is my first comment on hacker news) but I would like to see more content
targeted to people who know how to program but don't know the slang and words
in this specific field. For example Sebastian Lague did a great tutorial on
machine learning
[https://www.youtube.com/watch?v=bVQUSndDllU](https://www.youtube.com/watch?v=bVQUSndDllU)
I would love to see something like this but from the angle lets pick a random
programming language and lets program this together from scratch.

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keiferski
In general, most content on YouTube is a bit pedestrian. I would like to see
more serious academic resources referenced, longer and more in-depth videos,
and better production values. Something like _Every Frame a Painting_ but for
other topics.

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Jugurtha
Everything. The state of YouTube content on ML is similar to what the state of
software engineering _would_ be if there were only videos on "Hello, world!"
_or_ conference talks about awesome products demoed on "Hello, world!"
problems.

Practically none of the content creators seem to have ever executed a project
that used ML, or worked in an ML team, and those who are doing that
professionally don't do YouTube videos, except for talks in conferences that
they _did_ something, not really _how_ they did it.

I think you are in a great position and can do a lot of good by showing how
_you and your team_ execute a project from _start_ to _finish_.

Seasons and episodes. One season per project. One episode every week or two
that addresses the problems solved, and how. I want to look at your screen and
listen to conversations and brain-storming. How do you do ML, in long form
videos from the field, not some bullshit 5 minutes videos with sentences like
"then you only have to deploy your model". How do you collaborate on a
project, how do you choose metrics that translate to the real world, how do
you retrain your models, how do you do workload management, how do is your
private cloud, do your ML practitioners have self service infra for training,
how do you do self service deployment, manage data and access, how do you test
data is not tainted, deploy and expose models, embed models.. How do you
collaborate. How do you track knowledge, decisions, and assumptions and
hypotheses.

For example, if you could take papers like _" The ML Test Score: A Rubric for
ML Production Readiness and Technical Debt Reduction"_[^1] or _" Hidden
Technical Debt in Machine Learning Systems"_[^2] and show how _your team_ is
dealing with each point, it would be great content.

All the thing that anyone who has spent a day in the real world knows isn't
covered by 99% of the content online because the people doing it are either
too busy, consider it competitive advantage, or don't know it even exists (had
people working at FAANG try our internal platform, and they don't even deal
with these problems because they're in "research" and they have teams of ops
they can offload their notebook to).

[^1]:
[https://static.googleusercontent.com/media/research.google.c...](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/aad9f93b86b7addfea4c419b9100c6cdd26cacea.pdf)

[^2]: [https://papers.nips.cc/paper/5656-hidden-technical-debt-
in-m...](https://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-
learning-systems.pdf)

~~~
vanboxel
I don't often self-promote, but my channel, DanDoesData, hosts the long-form
type of series you may be looking for. Every video is a hour of live-stream
where I research, design, and implement the model on the fly, explaining my
thought process along the way.

One of my longest and most "real-world" projects was a (relatively simple)
self-driving car based on single camera input. I used this model for a self-
driving PowerWheels race. It later served as a starting point for a small
autonomous RC car.

Here's the start of that playlist, but I've put together several projects.
Working on a GAN for fake startup names right now.

[https://www.youtube.com/watch?v=meU1fXXIAOQ&list=PLFxrZqbLoj...](https://www.youtube.com/watch?v=meU1fXXIAOQ&list=PLFxrZqbLojdJIMff4WzpXpk1G2pEa3jAb)

