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yfontana

89 karma · joined June 15, 2024

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yfontana··on Markov chains are funnier than LLMs
LLMs were never very good at directly generating original jokes, for a simple reason: writing a good joke generally starts with finding a good punchline, and then setting it up. An LLM generating token after token will first write a set-up, and then try to shoehorn a punchline into it. Prompt engineering can fairly easily work around this, but just straight-up asking an LLM for a joke never really produced good results on average.
yfontana··on Building data infrastructure that will last
Maybe better recognition of data architecture as a specific domain would help. I'm a data architect, I have a specific set of skills to build and maintain data platforms, but when applying for jobs I'm very often finding myself in 1 of 2 situations.

1) I'm interviewed by software developers / architects, who expect me to have strong knowledge of software development patterns (like OOP patterns or microservices design in webapps). Well I know the basics but not at senior level. That's also not what's actually needed to design and implement a data platform.

2) I'm interviewed by data engineers, and I'm expected to show expert knowledge in data pipelines implementation. That's a lot closer to what I can do, but it's still not the core of my skill set, and it's a bit frustrating not to be judged on that.

yfontana··on Building data infrastructure that will last
In many cases, that means gaining the freedom of creating a huge mess (speaking from experience)
yfontana··on Show HN: Zerox – Document OCR with GPT-mini
My testing was admitedly limited (but focused on cases where GPT-4o was struggling), but in my experience Claude 3.5 also produced fewer hallucinations than GPT when doing OCR with figures / tables recognition. It is of course quite pricey as well.

However both GPT and Claude still struggle with documents that are very heavy on infographics, figures and tables.

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