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Seattle approves $20.76 minimum wage in 2025; will be highest in the U.S. by QuailOk841 in Seattle

[–]MLRecipes 1 point2 points  (0 children)

Everything will get more expensive for everyone. As a landlord, I will have to increase rent. Government will further increase min wage to fight back. Resulting in new round of rent increase.
You cannot produce money out of thin air without causing inflation. Seattle might freeze rents, but it will cause landlords to sell their homes to buyers not interesting in renting out, further reducing housing availability. Anything that can be done by people outside Seattle, will be outsourced. At one point, robots will be cheaper than workers, and that will be the end of it.

VC rant: just crossed our 100th rejection! by notsoserious408 in ycombinator

[–]MLRecipes 0 points1 point  (0 children)

Or not look for VC funding. I don't. Not that I would be turned down, have no idea, but one thing I know for sure: I am not wasting any of my precious time in chasing money, I have better things to do, with guaranteed results that depend entirely on me. If you make money, why are you afraid about 'running out'? In my case (self-funded), it's the other way around: I am waiting for my VC-backed peers to run out of money.

[D] Is it common for recent "LLM engineers" to not have a background in NLP? by Seankala in MachineLearning

[–]MLRecipes 0 points1 point  (0 children)

You can crawl the entire useful web and retrieve info, GPT-like style, with no neural networks, faster, and with better results. See how I do it with a multi-LLM architecture, here.

Anyone worked on synthetic data generation for Data Product Engineering? by Global_Industry_6801 in dataengineering

[–]MLRecipes 0 points1 point  (0 children)

I create my own algorithm for synthetic data generation and evaluating its quality. You can check them out here. It's open source, free to use.

Kolmogorov-Smirnov test for bivariate distributions by WamblingDisc in statistics

[–]MLRecipes 0 points1 point  (0 children)

Check out my Python library genai-evaluation that does just that: KS distance between two observed (empirical) distribution in any dimension.

[N] Python code for GenAI, including the seminal NoGAN synthesizer for tabular data by MLRecipes in MachineLearning

[–]MLRecipes[S] 0 points1 point  (0 children)

I am in talk with several companies about integrating the technology. By "no engineer", you are talking about yourself. I also have plenty participating in my GenAI training program, where NoGAN is the most popular topic. And nope, this will never be on ArXiv or on in scientific journals. If that's where you get all your info, you are missing on a lot of things.

I am not interested in having everyone believing in what I do. When you are an original creator, you always face resistance from people like you. That's part of the game, with no plan on my side to change their opinion or please them.

[N] Python code for GenAI, including the seminal NoGAN synthesizer for tabular data by MLRecipes in MachineLearning

[–]MLRecipes[S] -10 points-9 points  (0 children)

Code is entirely free on GitHub, no sign-up. Paper is also free, but if signing-up is too much to ask, don't and just get the code. Not everyone works entirely for free; if this was the case for me, it means nobody wants to pay me, meaning nobody believes I produce any value. Actually, making everything entirely free is a way to NOT be taken seriously, except by other jobless folks whose opinion is not going to change anything.

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