Hacker Newsnew | past | comments | ask | show | jobs | submit | charlesischuck's commentslogin

Location: Menlo Park CA Remote: only if consulting Willing to relocate: no Technologies: full stack deep learning Résumé/CV:

Hi I'm Charles. Good at whatever I am currently interested in. I'm looking for consulting work or just a chat if you're looking for advice.

I'm currently interested in full stack deep learning systems for customized LLM work.

Before that I fully designed large scale distributed AI systems for AI researchers.

Before that I led a team for image analysis in a cancer research company.

Before that, I redesigned their instrument and firmware.

Did a lot of electronics before that.

  Email: Curt.Charles.EE@gmail.com


You should read how the infrastructure of gpt works. In peak times you response quality will drop. Microsoft has a few whitepapers on it.

Ideal output is when nobody elese is using the tool.


I have built large scale distributed gpu (96gpus per job) dnn systems and worked on very advanced code bases.

GPT4 massively sped up my ability to create this.

It is a tool and it takes a lot of time to master it. Took me around 3-6 months of every day use to actually figure out how. You need to go back and try to learn it properly, it's easily 3-5x my work output.


Visual design work, coding, messaging, strategy, and law consulting.

Using it for basically every component of my startup.

Image generation and image interpretation means I may never hire a designer.


There's a startup in my coworking space that is doing exactly this.

They are based in menlo park, exactly as you describe it they are doing. Not sure how good it is but they're trying.

If anyone cares about the name reply and I'll get it tomorrow when I go in.


Would be great to know their name! Thanks in advance


https://www.multion.ai/

Sorry for late reply


Good luck getting that lol


A top end gpu now to make you competitive cost 20-50k per gpu.

To train a top model you need hundreds of them in a very advanced datacenter.

You can't just plug gpus into standard systems and train, everything is custom.

The technical talent required for these systems is rare to say the least. The technical talent to make a model is also rare.

I trained a few foundation models with images, and I would NEVER buy any of them. These guys are on a wildly different scale than basically everyone.


You pay for the system not the gpu with AWS.

It's absolutely worth the money when you look at the whole picture. Also lambda labs never has availability. I actually can schedule a distributed cluster on AWS.


> It's absolutely worth the money when you look at the whole picture.

That highly depends on many things. If you run a business with a relatively steady load that doesn't need to scale quickly multiple times per day, AWS is definitely not for you. Take Let's Encrypt[1] as an example. Just because cloud is the hype doesn't mean it's always worth it.

Edit: Or a personal experience: I had a customer that insisted on building their website on AWS. They weren't expecting high traffic loads and didn't need high availability, so I suggested to just use a VPS for $50 a month. They wanted to go the AWS route. Now their website is super scalable with all the cool buzzwords and it costs them $400 a month to run. Great! And in addition, the whole setup is way more complex to maintain since it's built on AWS instead of just a simple website with a database and some cache.

[1] https://news.ycombinator.com/item?id=37536103


We built a tool for lambda labs and other clouds that launches a specific instance whenever it becomes available and notifies you. We poll Lambda Labs for availability every 3 seconds. Would this be something that would be useful for you?


Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: