Videos
API Key Security on GitHub: Risks and Best Practices
When you leave here, go on GitHub and just search API key
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DeepSeek just dropped OCR2 Instead of processing images the standard way they built something called Visual Causal Flow that mimics how humans read documents It handles dynamic resolution so it can chew through PDFs fasttheyre claiming parity with their first OCR model but with better accuracy Works with both vLLM for production speed and regular Transformers Supports everything from clean Markdown conversion to layoutfree OCR when documents are messy github opensource
DeepSeq just dropped OCR too
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Ohhhh my god get me out of this!
You probably think because of the beard that I'm really hairy, but, uh, I'm not
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Copy paste this ⬇️ 1. “tell me a story of a day in the life as my future self based off this description” 2. Now write “create a daily schedule for me to follow that will allow me to achieve this life” Enjoy the ride . . . . . . . . . . #entrepreneurship #sales #business #miami #mindset
probably the best chadgpt hack i've seen in the past two years
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Want to improve your storytelling? 👇🏾 EPISODE 1. Start shooting multiple angles of one scene while doing a specific task or action. You don't need multiple cameras, just one. Pay attention to any objects in the frame, and keep them in the same place for continuity. When you edit the video, cut on 'action' as this makes the shot feel seamless. If you haven't grabbed my Simple Shot List Guide yet, comment "guide", and I'll send it over to you! #cinematic #cameraangles #videography #filmmaking #solocreator
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Take data from any website 😲 I wanted to take the entire YCombinator startup directory and analyze it using various tools including LLMs and I couldnt find a way to download or export it until I remembered... Im a Web Developer! I know a few tricks up my sleeve. It was actually super easy because the browser calls for all the data in a single request. No authentication or pagination required. EASY #software #hacks #tipsandtricks #webdevelopment #technology #howto
Let me show you how to take data from a website and use it for your own purposes
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Comment “code” to get the source code. NOTE: it does not include my nodes/workflows — it’s the platform to create your own. #ai #code #creative
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Canva Hack: Add Text Behind a Photo for Magnetic Designs
I run like a ring, I run like a ring, I run like a diamond ring, I run like a finger, I run like...
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Elevate Your Morning ☕️ Say goodbye to unnecessary complexity. The Meraki Espresso Machine seamlessly integrates a grinder, scale, and dual boilers in one sleek design. Why discerning coffee connoisseurs are switching: ⚖️ Built-In Dual Scales: Precision dosing by weight for the perfect shot. 🔥 Dual Boiler System: Uninterrupted brewing and steaming for ultimate control. 🎯 Masterful Control: Temperature and yield precision at your fingertips. Experience perfection with every cup. Order Now.
Everyone asks what the Meraki actually replaces, so let's break it down
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Tax Write-Offs for Homeowners: Save Up to $10,000 This Year
If you're a homeowner and you're not taking advantage of this tax rule you're literally missing...
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New Tax Write-Offs for 2026: Maximize Your Savings
The new tax rules have introduced write-offs that will save people tens of thousands of dollars...
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Moltworker in CloudFlare Tutorial
My name is Confidence, and I'm excited to let you know that ModeBot or OpenClaw now runs on Cloud...
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a bit more advanced tip, with a steeper learning curve #claude #ai
Everyone knows slash commands, but do you know how to use arguments
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Apple’s CLaRa system fundamentally reimagines RAG architecture by solving the semantic similarity problem that plagues traditional retrieval systems. Standard RAG approaches chunk documents, create static embeddings, and hope queries match semantically similar content—a critical flaw that forces workarounds like HyDE and query decomposition. CLaRa eliminates this by transforming documents into Memory Tokens: compressed representations of pure content stripped of filler and syntax, distinct from raw text. The breakthrough lies in its trainable Query Reasoner. Rather than matching queries directly to documents, it generates hypothetical ideal answers and queries against appropriate Memory Tokens. This component learns from the database itself through training runs, continuously improving retrieval accuracy. The system essentially operates as HyDE amplified—hypothetical document embeddings merged with dynamic, learnable retrieval—while running on modest model sizes. Technical highlights: - Memory Tokens replace static chunk embeddings with compressed content representations - Query Reasoner generates ideal answers before retrieval, not after - Direct database-to-reasoner training loop enables continuous optimization - Achieves superior results without requiring massive computational resources
Apple just quietly solved one of the biggest bottlenecks in RAG
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He grew to a Principal Eng (IC8) at Meta then created Claude Code at Anthropic I interviewed Boris Cherny for his full career story, link in bio if you're interested!
Can you explain latent demand
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