Amin @amin__dev
Software Engineer/Developer/Architecture Lead Developer at @Givethio Blockchain Enthusiastic Joined May 2020-
Tweets168
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Followers150
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Following434
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Likes805
@griffgreen It's the old story, "I have power and want your resources to me mine. You must obey!"
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Amin retweeted
The easiest way for anyone to donate in the @Giveth Causes QF Round? Polygon Accounts - built by @MyUnicornAcct 🦄 💜 With polygon.ac, anyone can start donating in minutes — even if they’ve never touched web3 before… @Gardner explains 👇
Contributor to @SuccinctLabs! 🚀 Made 37 commits to the future of ZK! 💻
Amin retweeted
Governments start wars. Normal people pay the price. This happened a few blocks away from the home of an Iranian friend of mine that works in crypto.
@kristoferlund @bad_alhaji @novahodler @base Haven't heard of it, thanks
Amin retweeted
🚨NOT FINANCIAL ADVICE🚨 Alt Season is here! 🐂 If you are bullish $POL then snipe the upcoming @theqacc token launches today, tomorrow and Monday. 📈 Each token is pegged to the price of POL & will beat the price of POL post DEX listings... as there are no tokens that can be sold in the market for 6 months. ⏫ q/acc tokens are a unique way to wrap your POL with extra upside. @HowToDAObook launches today. @ToDaMoonAI launches tomorrow. @web3packs launches Monday. Follow @theqacc for CAs and launch announcements.
Amin retweeted
15 crypto slang words that every web3 user should know before they ape into anything. And how @theqacc takes each one… and turns it into an opportunity.👇
@dabit3 I think user onboarding is still Web3’s main problem. Until that’s solved, dev tools matter less, especially for senior engineers. Most users don’t see a need for Web3 apps, and businesses still prefer Web2 for practicality.
@sbetamc @PulpSpy @Concordia @GinaCodySchool Congrats man :)
💻 Working on a complex coding task? Don’t expect AI to boost your productivity by much — maybe less than 10%. But where it shines is: ✅ Writing code from scratch ✅ Refactoring ✅ Documentation Use it wisely. #AI #Coding #Productivity mckinsey.com/capabilities/m…
To recap: Create an evaluator Prompt engineer Add RAG if needed Fine-tune only if necessary Stop when it’s good enough. Don’t overdo it. 💡 Use your evaluator to guide decisions, not gut feeling.
Still not good enough? Go for fine-tuning. 🧠 Train a small model using outputs from a big one (like GPT-4). You won’t train a foundation model—but you can teach a small one to specialize. This step needs talent + budget 💸
🚀 Want to get the best out of AI for your business—without burning time or money? Here’s a practical step-by-step playbook (based on @decodingml's excellent guide) to tune and deploy AI efficiently. 🧵👇
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