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the architecture astronauts are back at it again. instead of spending time talking about solutions, the whole AI space is now spending days and weeks talking ab
by fsndz 1y ago
the architecture astronauts are back at it again. instead of spending time talking about solutions, the whole AI space is now spending days and weeks talking about fun new architectures. smh
https://www.lycee.ai/blog/why-mcp-is-mostly-bullshit https://www.lycee.ai/blog/why-mcp-is-mostly-bullshit
- ramesh31 1y agoThere's a simple reason for that. AI (real AI) is now an engineering problem, not a computer science problem.
- fsndz 1y agoso you are telling me that hallucinations (that by definition happen at the model layer) are an engineering problem ? so if we just spin up the right architecture, hallucinations won't be a problem anymore ? I have doubts
- deleted 1y ago[deleted]
- ramesh31 1y ago>so you are telling me that hallucinations (that by definition happen at the model layer) are an engineering problem ? Yes. Hallucinations were a big problem with single shot prompting. No one is seriously doing that anymore. You have an agentic refinement process with an evaluator in the loop that takes in the initial output, quality checks it, and returns a pass/fail to close the loop or try again, using tool calls the whole time to inject verified/real time data into the context for decision making. Allows you to start actually building reliable/reasonable systems on top of LLMs with deterministic outputs.
- weego 1y agoAnd that's how this will end up stagnating into nothing other than fractured enterprise "standards" There is no evidence that (real AI) is even close to being solved, from a neuroscientific, algorithmic, computer science or engineering perspective. It's far more likely we're going down a dead-end path. I'm now waiting for the rebrand when the ass falls out of AI investment, the same way it did when ML became passé.