I'm build open source : Sovereign AI Infra, Deployed in Minutes.
Deliver Private AI in your cloud organization. Everything in full control.
The idea is simple: Its handle of the complexity for AIOps infra like GPU VM provisioning, NVIDIA driver setup, Docker setup, model download, and launching the inference server. User can run any OSS and AI tools inside their cloud.
1) Depend on your own goal. Its wise if you believe in the future, market appreciate ML eng higher than software eng (within same years exp)
2) Yes. I did (> 3 years now)
3) Start find the ML job
Is there an ML engineering practice that isn't focused on building models but more on managing/deploying/scaling models?
Yes. Companies who adopt ML at large scale usually need this.
i.e. can I avoid learning all the maths underneath?
Yes its possible as long as you are focusing on infrastructure. Eg: create/monitoring pipelines, models, etc.
Noted: While you finding job, try to take professional ML engineering certification/program (Google, AWS, Azure, etc) - they will provide you hands-on lab experience with some case studies. The cost is super cheap
I'm building a platform where product managers and engineers can build interaction automation with users using small model. The goal is to help people to build LLM for them without deep expertise in DS/ML, train and host the model in their infrastructure, where no data require to be submitted.
Depend on use case. For me, its very crucial. Context, I'm working on ML and run several processing where usually consume memory up to 1TB at my workstation. Since my RAM only 196GB, this will trigger OOM killer, without Swapfile.
I use HHHL PCI SSD to host my swapfile to withstand with rapid read-write activities
Global distribution is complex. So there is no easy way to do it. Now, what is the option here? Your assumption, around 6 billion of those humans have a bank account. So, we can leverage the bank network to do the distribution.
There is a chance of the same person opening multiple account. Integrating with one bank at a time will help not to do manual transfer and build a centralized database for verification simultaneously. There is no time limit here, I assume this is fine.
How about the rest, the unbankable? Via country social aid. There is a high correlation that the unbankable is similar to under poverty population. With social aid, it will reach them. Cross-check with the central database for verification.
Now, what if the 1 dollar doesn't need in the form of physical money? There are so many alternatives to this. I said, follow on how people spend money.
You can use it to pay each Taxpayer all countries, pay the debt of each person in the bank, and subsidize commodities that the unbankable population consume: data, rice, bread, electricity, vaccine and others thing that people spend. So, understand how unbankable people spend and receive money.
There is a cost of distribution. My rough intuition is probably around 30-40%, if we are looking for precise in-person equal distribution. Yes, that is really expensive, even more for unbankable, because most of them will receive cash.
Thank you for the question @paulluuk. This is a good brain exercise and seems like consulting interview question for me hahaha
Hey OP, I feel relate to your problem as CTO of a startup that is growing fast and requires heavy integration with operation and biz (Seed to Series B in 4 years). My day to day is quite hectic, however, I'm happy to do experiments whether I can contribute or help.
My total experience is 14 years start from eng, project manager, CTO and now handling Product. I have experience managing talents from Asia, India, and Silicon Valley. I spend my time weekly aligning with the biz stakeholders like VP of Operation, Finance, Commercial, HR and of course, my co-founder the CEO :)
You can reach me out at barudevice0 @ Gmail dot com