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My worry with AI is that even though it is very impressive and useful in many ways for real world applications, the Hype may end up making it another crypto.

My worry with AI is that even though it is very impressive and useful in many ways for real world applications, the Hype may end up making it another crypto. Crypto was a great promise when it was invented and one can make the argument that it could have so many real world uses but it failed to live upto that expectation and one of the reasons is that it was over hyped way too quickly and ultimately became a tool for get rich quick, speculation, scams, dark web payments etc. AI is already much better with its use BUT the hype is dangerous and we need to be careful. I see a lot of people starting "X-GPT.com" apps and touting 10K MRR in 2 months and what not. THis is what worries me. Every Tom, Dick and Harry is starting yet another AI tool. It can't be because they are so excited. It is because they see it as the new Crypto to get rich quick. Overall, I think that AI is the new Crypto unfortunately not because it has no real world application (it does and is lot better than crypto) but because of the hype and everyone trying to cash in on it.

scarface_74 3y ago
I use ChatGPT to help me quickly write simple AWS SDK based helper scripts. I’ve also recently been involved in designing a DevOps /Docker deployment pipeline for a customer. They use Java and I haven’t used Java in decades. Before I would have just done my POC using a Python or Node container and rely on the fact that they knew Java well enough to get the concepts. But I used Java and started the chain of questions “answer all question based on talking to someone who doesn’t know Java. Explain everything step by step.” In both cases, ChatGPT will usually get me 99% there. But I have to keep trying things and giving it the error messages and iterating. Of course there is the hallucination issue. On the other hand, I’ve done a lot of work professionally with old school chatbots integrated with web pages and call centers where the only intelligent component is that we could parse out parts of speech (nouns, verbs, adjectives, etc) and only search on those. I would never recommend putting an LLM style chatbot in front of a customer. When I work with customers - especially in the government - the questions and answers are heavily vetted before being put in production. They would never take a chance that either the customer could jailbreak the chatbot and have it say something and trigger a political argument about “bias” or that it would give incorrect information about a government benefit.
- Roark66 3y ago
  Watch out, I'm doing devops too and I've caught chatgpt on such obviously stupid behaviors it hurts to even think about it. It's not just hallucinations problem (edge cases or doing unusual stuff). It seems to give answers that are 100% incorrect and when told so says "of course you're right, here is the right answer". The only stuff I'd use it for is if I already know exactly how to write the script and I'm just using it to type it for me quickly because I don't remember if aws_instance is the correct spelling or aws-instance in terraform...
  - scarface_74 3y ago
    Exactly. But with code, it’s easy enough to prove correctness just by running it. That being said, the one bug I find consistently with ChatGPT is that with the AWS APIs, all list type methods pagínate and you have to account for that. Python/boto3 have built in paginators and it doesn’t. This an insidious bug because things will work correctly in a dev account with only few resources. But will fail in hard to debug ways in production. What’s even worse is that ChatGPT “knows” the pattern and will correct itself once you say something like “This won’t work with more than 50 roles/ec2 instances, etc”
  - mullingitover 3y ago
    My trick is to get second and third opinions - sometimes ChatGPT gets it wrong, but bard is right, or 3.5 is right when 4 is wrong. So I just copy the same question to all available chatbots and compare. Asking them to provide sources for the answers is also a good way to keep them honest.
    - scarface_74 3y ago
      With code in particular the only thing I use it for, the source of truth is running the code and testing for corner cases. I usually know what the right answer is. It can just get to it faster. I may not know always know the correct API or CloudFormation/CDK/Terraform syntax. But if it gets it wrong, I can read the docs and correct it. Providing sources doesn’t usually help. ChatGPT consistently makes up sources.
eric_cc 3y ago
> crypto.. failed You realize it’s still here, adoption is increasing, utility is increasing, etc Just because it’s not a hype cycle does not mean it’s dead or even close to dead.
- codegeek 3y ago
  "adoption is increasing, utility is increasing" Genuinely curious. Where ? Remember it's been 15 years already. Few anecdotal examples are not good enough.
  - eric_cc 3y ago
    Bitcoin
throwuwu 3y ago
I’m not even remotely concerned about an AI bubble, in fact the faster it can inflate and pop the better. An AI hype winter would be as comfortable as a tropical vacation with the current tech that’s available. We could build and research in peace without endless media FUD and hit pieces.

scarface_74 3y ago

I use ChatGPT to help me quickly write simple AWS SDK based helper scripts. I’ve also recently been involved in designing a DevOps /Docker deployment pipeline for a customer. They use Java and I haven’t used Java in decades. Before I would have just done my POC using a Python or Node container and rely on the fact that they knew Java well enough to get the concepts. But I used Java and started the chain of questions “answer all question based on talking to someone who doesn’t know Java. Explain everything step by step.” In both cases, ChatGPT will usually get me 99% there. But I have to keep trying things and giving it the error messages and iterating. Of course there is the hallucination issue. On the other hand, I’ve done a lot of work professionally with old school chatbots integrated with web pages and call centers where the only intelligent component is that we could parse out parts of speech (nouns, verbs, adjectives, etc) and only search on those. I would never recommend putting an LLM style chatbot in front of a customer. When I work with customers - especially in the government - the questions and answers are heavily vetted before being put in production. They would never take a chance that either the customer could jailbreak the chatbot and have it say something and trigger a political argument about “bias” or that it would give incorrect information about a government benefit.

Roark66 3y ago
Watch out, I'm doing devops too and I've caught chatgpt on such obviously stupid behaviors it hurts to even think about it. It's not just hallucinations problem (edge cases or doing unusual stuff). It seems to give answers that are 100% incorrect and when told so says "of course you're right, here is the right answer". The only stuff I'd use it for is if I already know exactly how to write the script and I'm just using it to type it for me quickly because I don't remember if aws_instance is the correct spelling or aws-instance in terraform...
- scarface_74 3y ago
  Exactly. But with code, it’s easy enough to prove correctness just by running it. That being said, the one bug I find consistently with ChatGPT is that with the AWS APIs, all list type methods pagínate and you have to account for that. Python/boto3 have built in paginators and it doesn’t. This an insidious bug because things will work correctly in a dev account with only few resources. But will fail in hard to debug ways in production. What’s even worse is that ChatGPT “knows” the pattern and will correct itself once you say something like “This won’t work with more than 50 roles/ec2 instances, etc”
- mullingitover 3y ago
  My trick is to get second and third opinions - sometimes ChatGPT gets it wrong, but bard is right, or 3.5 is right when 4 is wrong. So I just copy the same question to all available chatbots and compare. Asking them to provide sources for the answers is also a good way to keep them honest.
  - scarface_74 3y ago
    With code in particular the only thing I use it for, the source of truth is running the code and testing for corner cases. I usually know what the right answer is. It can just get to it faster. I may not know always know the correct API or CloudFormation/CDK/Terraform syntax. But if it gets it wrong, I can read the docs and correct it. Providing sources doesn’t usually help. ChatGPT consistently makes up sources.

eric_cc 3y ago

> crypto.. failed You realize it’s still here, adoption is increasing, utility is increasing, etc Just because it’s not a hype cycle does not mean it’s dead or even close to dead.

codegeek 3y ago
"adoption is increasing, utility is increasing" Genuinely curious. Where ? Remember it's been 15 years already. Few anecdotal examples are not good enough.
- eric_cc 3y ago
  Bitcoin

throwuwu 3y ago

I’m not even remotely concerned about an AI bubble, in fact the faster it can inflate and pop the better. An AI hype winter would be as comfortable as a tropical vacation with the current tech that’s available. We could build and research in peace without endless media FUD and hit pieces.