About
👋 Hi, I'm zane, a Data Analyst and AI Researcher with over two years of experience in a major tech company. I'm passionate about uncovering insights from data and applying cutting-edge AI technologies to solve real-world problems. 🌍 I'm on a journey to become a digital nomad and independent developer, aiming to launch products globally. My goal is to transform innovative ideas into practical solutions that benefit users worldwide. 🚀 I believe technology can change everything, and I'm excited to share my journey here. If you're interested in data analysis, AI, or the digital nomad lifestyle, let's connect and explore the future together! ✨
Work
Indie maker at Meta
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🔥 Roast my idea: drop your ideas and get brutally honest feedback 🔥
It's simple. Drop your next big idea and get some brutally honest but hopefully valuable feedback. The rules are:
Drop your idea, you don't have to go super in depth but give a sentence or two about what it is and does.
Get roasted, duh
Roast someone else's.
That way we create a cycle of feedback
What's your monthly LLM bill? How Much Are You Really Spending.
We re a data company that recently interviewed over 60 large enterprise VPs and 70+ startup engineers and CTOs. Here s what s intriguing: Despite the massive hype around Large Language Models (LLMs), some of the largest tech enterprises (5k+ employees) report LLM bills of less than $1000 per month. Meanwhile, some startups are burning through over $100k on LLMs like OpenAI, Claude, or even self-hosting models like LLaMA. Is this a case of enterprises being cautious, or are they simply seeing through the LLM hype that startups are buying into? Are you spending big on LLMs, or are you getting by with cheaper alternatives like LLaMA-CPP and other quantized models that run on CPUs? As a prelaunch team, we started with running llama cpp on a macbook to $500-$1k monthly openai bills over the past 6 months. How much are you spending and what are your cost saving tricks!?