3 ms·

The AI "hype-train" exists because people really want to find a way to make AI useful. It was a big technological advancement that is now in search of a purpose

The AI "hype-train" exists because people really want to find a way to make AI useful. It was a big technological advancement that is now in search of a purpose. The same thing happened with blockchain, not a ton came out of it except Bitcoin and clones, but AI is much easier to imagine a use for. The market is throwing attention and money at these AI products because one might end up being truly useful as a product. You should be rewarded for your efforts in exploring the product space, trying things out, creating real value through application/product engineering. I'll also say that you aren't ripping anyone off. Google / OpenAI want you to find product/market fit so they can rip you off right back. They are essentially outsourcing that work. Get your bag while you can.

gigaflop 3y ago
I'm not an AI enthusiast by any means, but can still get behind this all. If OP can productize and suddenly make an extra $1k/mo, more power to them. When you boil everything down, most code can technically be recreated by any skilled-enough individual(s). Sometimes, an Enterprise License for some software saves a company enough money relative to the cost of building in-house to where they just want to sign a check and be given an API key, in order to focus on things they're naturally better at. That's why I have a job. People want coded stuff, without hiring the coding people. My company allows another company to sign a dotted line, and get access to developer braintime.
deleted 3y ago
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Malcolmlisk 3y ago
AI is useful as today. I, for example, I'm finishing a project where the company I work for wanted to extract some data from bills and documentation. The thing is, in my later company I did a project with OCR and deep learning and it was quite useful. But this time, since we don't really need to tabulate the data, just extract some info here and there, what we did is to attach an LLM after the OCR extraction with an API. So right now we are getting a big improvement and flexible queries of information we are required to extract from bills and documentation, with an easy solution and not that heavy or costly. And I'm taking into notes that usually what we are talking about is llms as AI. But in the other hand, my last project for this company was an energy demand and allocation time series with auto-training in case it detects a huge chunk of error in the last statistics stracted from the model compared to the reality. This project was complex but it impacted the company positively with millions of euros in earnings. So, yeah. Statistics and programming works. Usually when we talk we do refere llms as AI, but there are other situations where just "classic" data science is useful and more than enough.
- mvdtnz 3y ago
  Very alarming to hear you're using LLMs to extract and report billing data. LLMs are frequently wrong, you will be getting incorrect and often totally fabricated data. I hope you're not using this information to bill customers or generate any kind of financial documents.

gigaflop 3y ago

I'm not an AI enthusiast by any means, but can still get behind this all. If OP can productize and suddenly make an extra $1k/mo, more power to them. When you boil everything down, most code can technically be recreated by any skilled-enough individual(s). Sometimes, an Enterprise License for some software saves a company enough money relative to the cost of building in-house to where they just want to sign a check and be given an API key, in order to focus on things they're naturally better at. That's why I have a job. People want coded stuff, without hiring the coding people. My company allows another company to sign a dotted line, and get access to developer braintime.

deleted 3y ago

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Malcolmlisk 3y ago

AI is useful as today. I, for example, I'm finishing a project where the company I work for wanted to extract some data from bills and documentation. The thing is, in my later company I did a project with OCR and deep learning and it was quite useful. But this time, since we don't really need to tabulate the data, just extract some info here and there, what we did is to attach an LLM after the OCR extraction with an API. So right now we are getting a big improvement and flexible queries of information we are required to extract from bills and documentation, with an easy solution and not that heavy or costly. And I'm taking into notes that usually what we are talking about is llms as AI. But in the other hand, my last project for this company was an energy demand and allocation time series with auto-training in case it detects a huge chunk of error in the last statistics stracted from the model compared to the reality. This project was complex but it impacted the company positively with millions of euros in earnings. So, yeah. Statistics and programming works. Usually when we talk we do refere llms as AI, but there are other situations where just "classic" data science is useful and more than enough.

mvdtnz 3y ago
Very alarming to hear you're using LLMs to extract and report billing data. LLMs are frequently wrong, you will be getting incorrect and often totally fabricated data. I hope you're not using this information to bill customers or generate any kind of financial documents.