Freelancers using Kapwing in Ocoee

Freelancers using Kapwing in OcoeeFreelancers using Kapwing in Ocoee

Projects People

Paul N.

Ocoee, USA

Shopify customizer & Ecommerce Consultant

6: Followers

Shopify customizer & Ecommerce Consultant

Cover image for ⛰🏃‍♂️💨🔥 Prometheus took fire for it's greatest and worst ...

⛰🏃‍♂️💨🔥 Prometheus took fire for it's greatest and worst power: it can make more of itself.🔥🔥🔥 FireBuilder is intended as an offline first page builder SPA, no servers (deployed on github), with export features and intended to be able to deploy to github itself; using either PATs or PKCE auth methods. Try it out https://paulnewton.github.io/firebuilder/ (https://paulnewton.github.io/firebuilder/)And builder.io preview url (https://262df3c9d6494d4e9131ae39984e8558-main.projects.builder.my)A simple hallmark of great tools is the ability to make more. So this is one of the first things I do with code AI's see how far of an MVP it can make of builder.io Fusion did a pretty good job, nearly a oneshot w/ ~25 tokens. That allowed me time to go off and be creative with the intro video for the story of prometheus as an intro.

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This ones a bit meta , if your running low on time to make a presentation video for your FLORA technique, #FLORATechnique. I made one to quickly make an explainer vid by providing it some screenshots and a description of your technique / software. Give it an overview screenshot and 4 supplementary screens. And you get 30 seconds of 5 separate 6 seconds videos with narration you can download and merge or edit. See attached compiled video few sample of what it outputs, the last bit on the compiled video is seedance being seedance 🤪 Try it here: https://app.flora.ai/techniques/explainer Here's an example process with ffmpeg command to do that last part quickly: Create an input file list (inputs.txt) listing all video clips names in order , note the file prefix is literal as are the quotes: file 'clip1.mp4' file 'clip2.mp4' file 'clip3.mp4' Then this ffmpeg command: ffmpeg -f concat -safe 0 -i inputs.txt -i audio.mp3 -c:v copy -c:a aac -map 0:v:0 -map 1:a:0 -shortest output.mp4 Parameters Explanation, -f concat -safe 0 -i inputs.txt: Uses the concat demuxer to read the list of files. -i audio.mp3: Inputs the single audio file. -c:v copy: Stream copies the video (fast, no re-encoding). -c:a aac: Re-encodes audio to AAC for better compatibility with MP4. -map 0:v:0 -map 1:a:0: Takes the video from the first input (concat) and audio from the second input. -shortest: Ends the output file when the shortest input (likely the audio) finishes.

Cover image for Bespoke is a Generative Personalization

Bespoke is a Generative Personalization Engine using @FLORA , made as a technique #FLORATechnique. Bespoke does product customization AND personalization. Customized products visuals for customers tailored to them with their preferences & additional addons (e.g. engraving, monogram) . Run it here -> https://app.flora.ai/techniques/bespoke It lets you make rapid fire customized products visual previews for customers tailored to them with their preferences & additional addons (e.g. engraving, monogram). Send personalized products visuals that are more than an stock overlay slapped on an image. Real integrated imagery tailored for customers with additional addons with less design time (e.g. engraving,monogram,wordmark or logo ) . Personalization based on customer buyer history to automatically set combos of intrinsic product options (like colors materials) the a customer would likely prefer. Just provide the flow with: Static asset of product without customization Static asset of product WITH examples of customization. Product data (variants, skus, etc; structured or not) Customer behavior data (purchase history, view interests, etc; structured or not) The system synthesizes new customizations based on the inputs. What that means is you may only need to mock up on product ONCE. For example mockup the initials P.N. in color,size etc, and let the system generate all the other possible combinations when needed. Basic Customization Use Cases Monogram / Embroidery - Text input: customer provided initials , or name Apparel example: shirt without monogram shirt with monogram or embroidery monogram Travel: luggage identification Engraving / - Text input: customer provided message Jewelry example: ring with engraving on the inside of the ring Business: nameplates Footwear: Custom conversation shoe builder choosing the color of the laces, the sole, custom logo lockup utilizing the customers name or initials, material. Toys: XTREME customizable action figures, or dollhouses. Where the accessories, clothing, and personality traits are chosen for the buyer by the buyer. Personalization use cases Personalized onboarding of the purchase in upsells, mails and ads that incorporate the customizations and personalization's in outreach specific to that customer while staying on brand. Present products automatically fit for a customer based on the user's history, behavior, and demographics. Industry use cases of personalization: Apparel: Sizes, materials, fit(tight, loose), brand preferences, seasonal etc Footware: Type, Sizes, materials, fit, accessories(laces,cleanwipes) Jewelry: Maker, Toys: toy line, character-personality(gruff soldier , glam unicorn 🦄✨) (aka recommendation engines: "Because you bought X, you might like Y") It's a double whammy when a business chooses to use a Bespoke Technique to get customers something unique to them. and yeah i know the thumb on the technique page is missing the embroidery 😉

AI Arena is for the community if your spending time in flora.ai (http://flora.ai) content creation flipping through text models to pick one I built a utility technique to save some clicks and time by taking the shotgun approach 🔫💥💥💥💥💥💥💥💥💥💥💥💥💥💥. AI arena lets users prompt multiple generative models at once to evaluate output for quality,testing,debugging, or curiosity. See multiple generated outputs right inside your flora workflow quickly. So you can run all the samples on the canvas with a few clicks, then pick the best one for your case, or even pipe all the outputs to your own downstream evaluators. A multi model curiosity technique for anyone ideating, or iterating a creative generative workflow. 🤔 In comes in two flavors for the Text-To-Text AI arena technique on flora:: all(except o3deepseek*) https://app.flora.ai/techniques/ai-arena (https://app.flora.ai/techniques/ai-arena)and core https://app.flora.ai/techniques/ai-arena-core-text-to-text (https://app.flora.ai/techniques/ai-arena-core-text-to-text)Core uses Uses (💸8 • ⚡8s) Claude Sonnet 4.6{balanced} (💸8 • ⚡6s) Gemini 3 Flash{speed} (💸26 • ⚡12s) GPT-5.1{analysis} picked for the mid range models from each provider at reasonable token cost. *o3deepseek is 900 credits and takes 10 minutes to run Should I build the image and video versions into this too 🤔 , upgoat if this type of technique will save you time every day on flora.

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