Anna Ai

This is your sign to start teasing your Black Friday campaign before the big day. I wanted a short ad with a bit of movement, so I created a concept around a stack of papers being blown towards the camera. The product reveal at the end keeps the message simple and clear. Using CapCut PC, I combined product and video references, then refined the footage, transitions, and text through multi-track and timeline editing. BLACK FRIDAY SOON... More about the process: tinyurl.com/2v23rn22 #capcutpc #capcutmarketing #capcutblackfriday #CapCutDidThat

A company matching your ICP isn’t the same as being ready to buy. An expansion permit + new equipment imports? That’s a much stronger signal. @cleanailabs connects these clues to spot B2B buying windows. Selling into manufacturing, legal tech or fintech? Book a demo.

Translation used to feel like a separate step that broke flow. You’d write something, switch tools, paste, fix the tone, then wonder if it still sounded like you. Now the same voice that captured the thought can reshape it for a different language without losing the original intent. I’ve started treating multilingual communication as a default rather than an extra task. The friction disappears, so the conversations happen more often and with less hesitation. That small change compounds across a whole working day.

What if editing videos was as simple as telling AI what to do? I tested CinLink, a local-first AI video assistant that lets you edit footage using natural-language prompts. No complicated timelines. Just describe what you want, from trimming clips and adding subtitles to creating shorts and multilingual versions. And the best part? Your original footage stays on your computer. One video, multiple versions, simple instructions. Here’s how it works 👇

You can know a person's device type if it ends with a question mark and then: s=46 iPhone s=20 Browser s=19 Android You can try it on this tweet

Still sending emails that sound like ChatGPT wrote them? 👀🤖 Meet @lynote_ai 🚀 ✍️ AI Humanizer: Turn robotic AI-generated text into natural-sounding writing. 🔍 AI Detector: Check your emails, essays, and other text for signs of AI-generated content. Two powerful AI tools, one platform! ⚡ 👉 tinyurl.com/4thnwm7v #ad #lynoteai #lynote #aidetector #aihumanizer

🚨 Elon Musk has dropped an unprecedented bombshell—right inside the White House, in front of Donald Trump: 💥🏛️🇺🇸 “From now on, you will no longer need to work for any company... I will make sure everyone on Earth enjoys a celebrity-level lifestyle and income!” Musk is completely challenging the traditional concept of government-provided “Universal Basic Income” (UBI) designed merely for survival, presenting a radical vision of a new form of capitalism. According to Musk, how will everyone become wealthy? 👇 As AI and robots produce goods and services 24/7 without limits, the overall standard of living for all humanity will skyrocket—as if everyone were earning an astronomical salary! Musk confidently declares: “Everyone will have access to better healthcare than I personally receive!” Through the combination of superintelligent AI and precision surgical robots, top-tier medical care could become available to everyone at virtually no cost. AI will handle the thinking, while robots build roads and structures, grow crops, and manufacture products. With forced labor becoming a thing of the past, the phrase “I don’t have enough money to buy what I need” could disappear from the human vocabulary entirely! While 99% of humanity worries that “AI will take their jobs,” Musk envisions a future where “an army of autonomous robots will turn every single person into a king—living a life of total ease!” Bookmark this post to follow the transformation that may lie ahead. 📌

Whenever I feel demotivated i rewatch this... Elon Musk in a living room in 2008, 12 days from bankruptcy, pitching a $109,000 car to people...

Most OCR pipelines pick one parser per document. MiniCPM-OCR Jev makes the case for picking per region. the setup they tested: > MiniCPM-OCR 1.0, Xiaomi OCR and PaddleOCR-VL 1.6 all parse the same PaddleOCR-VL SDK layout crops of OmniDocBench v1.6 > same assembly rules > MiniCPM-OCR Jev flags the low-confidence blocks, which get re-selected from the other two models' outputs result: +0.18 overall for MiniCPM-OCR, +0.25 for PaddleOCR-VL 1.6. no retraining, no new parser, just swapping in better blocks. the routing is the part i like. text from one model, a nasty table from another, one assembled page. the judge doesn't need to know which model is "best", only which output for this crop looks right. open question if you're building this: cost. running three parsers on every block is wasteful. i'd run one, let Jev score it, and only fan out on blocks under threshold. needs its own eval, but that's the version i'd ship. side effect: a parser doesn't have to top the leaderboard to earn a slot. it just has to be good at the regions the others choke on. Hugging Face: MiniCPM-OCR 1.0: huggingface.co/openbmb/MiniC… MiniCPM-OCR Jev: huggingface.co/openbmb/MiniC… GitHub: github.com/OpenBMB/MiniCPM-O…