Sid

@sidshekhar

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11226 Followers

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Using AI today involves making a choice between a plethora of different LLM models available to trial. Through the course of building Gina, we evaluated 6+ models on complex tasks like token swaps, bridging, and fetching market updates. Wrote up some findings on what we learned about speed, accuracy, and which models handle multi-step actions well in our latest post. Your weekend read if interested in practical insights and real-world data on model performance :) https://paragraph.xyz/@askgina/from-conversation-to-execution-lessons-learned-evaluating-6-llms-for-gina

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What's your terminal of choice

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Building @askgina.eth

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If X is for mogging, Farcaster is for ....

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if only it could reference dune dashboards https://www.perplexity.ai/search/can-you-give-me-a-deep-dive-on-VHD.RpMVRRKH980LkbxlMw#0

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Ok banger metaphor

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Inb4 yet another layer 4 built on dfinity

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At least someone needs to move the needle on post-slab smartphone form factor

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If a tree fell in the forest and it wasn't written about, did it really fall.. (In the eyes of an llm)

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If anything the democratisation of cheap llm inference (available privately) all the more pushes me to write more. Inner monologue/random mental chatter/as well as other more salient stuff.

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ggwp Load the sovereign wealth fund inflows https://x.com/tier10k/status/1890444834051076373?s=19

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We're in a token production industry. Only makes sense to serve the core use case.

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lovable < replit < cursor in order of dev involvement + advanced capability possible. Just different levels of vibe coding

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Love this. Next up: replit!

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A rarified 5 potatoes sticking around in the $1b+ club.

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TIL! Those are not too shabby as far as cups go tbf

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