I work on a web app that let people file their CA taxes for free. it only has 200K users per year. but hey that is a couple millions intuit doesn't get.
We're a tiny one-stop boutique specialized in machine learning. Our clients are exclusively large organizations because only they can afford our services.
Recently, we started building our "MLOps" platform (https://iko.ai) to reduce the overhead of doing machine learning and the proverbial technical debt that makes makes ML projects so likely to fail and so expensive. This will hopefully lower the barrier to entry as people will be able to use this to deliver value without being in large organizations.
I have been asked time and time again by people I know personally who have small companies how they could hire us to use machine learning, and I was embarrassed time and time again to make them understand they couldn't afford it.
There are many ways to "democratize" the field. Some publish books and courses, others create libraries and frameworks, and we made a system to lower the operational hurdles.
My comment was more than the first two sentences you are referring to.
Here it is again. I wrote:
>Recently, we started building our "MLOps" platform (https://iko.ai) to reduce the overhead of doing machine learning and the proverbial technical debt that makes makes ML projects so likely to fail and so expensive. This will hopefully lower the barrier to entry as people will be able to use this to deliver value without being in large organizations.
>I have been asked time and time again by people I know personally who have small companies how they could hire us to use machine learning, and I was embarrassed time and time again to make them understand they couldn't afford it.
>There are many ways to "democratize" the field. Some publish books and courses, others create libraries and frameworks, and we made a system to lower the operational hurdles.
My point was that the usual hurdles of a machine learning project and the inefficiencies made it almost exclusive to large organizations that could afford it, and we're solving that by building a platform that eliminates these hurdles to make it possible even for small companies and individuals to benefit from and use machine learning without hiring expensive teams or consulting companies such as ours.
This dramatically lowers the barrier to entry and the "activation energy".
How will this make the world better? I ask in earnest, as for the most part I see ML only as a tool to increase profits. Is this making the world a better place or just increasing shareholder value?
We've worked on railway transportation systems to reduce the number of incidents that affect quality of service at best, and endanger people and infrastructure at worst. Predicting events in other types of critical pieces of infrastructure of $10B+ that could lead to catastrophic consequences in terms of lives, devastating environmental damages, etc. We've worked on elderly care in partnership with social workers so the elderly feel less lonely by dispatching caregivers at the right time.
These are the projects we've worked on off the top of my head with obvious benefits to the world. Now, imagine how fast we could have gone had we had our tooling.
For the less obvious projects: we help people live more by reducing mindless, numbing, soul-crushing tasks so that humans do what humans are good at. Think, create things.
It makes learning vim fun[0] and it gives an open-source creator $250/mo[1].
Also it helps me out by giving me extra income that has helped pay down debt.
In Kinobi.asia, We create a service where users can create their own CVs. We handle the formatting, so that you can focus on your content. Our vision is to empower the individuals in SEA region to land into jobs of their dream.
While the service is referral code protected, do chat me up if you love to check it out and use it!
18 comments
[ 2.3 ms ] story [ 52.4 ms ] threadMy contribution is indirect since I don't work on the investment systems themselves.
Also, thank you for doing something to hurt Intuit.
FTFY
Recently, we started building our "MLOps" platform (https://iko.ai) to reduce the overhead of doing machine learning and the proverbial technical debt that makes makes ML projects so likely to fail and so expensive. This will hopefully lower the barrier to entry as people will be able to use this to deliver value without being in large organizations.
I have been asked time and time again by people I know personally who have small companies how they could hire us to use machine learning, and I was embarrassed time and time again to make them understand they couldn't afford it.
There are many ways to "democratize" the field. Some publish books and courses, others create libraries and frameworks, and we made a system to lower the operational hurdles.
Here it is again. I wrote:
>Recently, we started building our "MLOps" platform (https://iko.ai) to reduce the overhead of doing machine learning and the proverbial technical debt that makes makes ML projects so likely to fail and so expensive. This will hopefully lower the barrier to entry as people will be able to use this to deliver value without being in large organizations.
>I have been asked time and time again by people I know personally who have small companies how they could hire us to use machine learning, and I was embarrassed time and time again to make them understand they couldn't afford it.
>There are many ways to "democratize" the field. Some publish books and courses, others create libraries and frameworks, and we made a system to lower the operational hurdles.
My point was that the usual hurdles of a machine learning project and the inefficiencies made it almost exclusive to large organizations that could afford it, and we're solving that by building a platform that eliminates these hurdles to make it possible even for small companies and individuals to benefit from and use machine learning without hiring expensive teams or consulting companies such as ours.
This dramatically lowers the barrier to entry and the "activation energy".
These are the projects we've worked on off the top of my head with obvious benefits to the world. Now, imagine how fast we could have gone had we had our tooling.
For the less obvious projects: we help people live more by reducing mindless, numbing, soul-crushing tasks so that humans do what humans are good at. Think, create things.
[0] https://www.vim.so
[1] https://fastapi.tiangolo.com/#gold-sponsors
In Kinobi.asia, We create a service where users can create their own CVs. We handle the formatting, so that you can focus on your content. Our vision is to empower the individuals in SEA region to land into jobs of their dream.
While the service is referral code protected, do chat me up if you love to check it out and use it!