GUIDE: FREE Irys (✧ᴗ✧) INTERACTIONS ($20M) ⏰ Time: 10... seconds 🆓 Cost: $0 Deploy Irys Storage CLI with EasyNode: > Go to > Select Irys > Choose free 2-week plan Like & RT to share 💜🔁show more

Video content is the future of business! I've built... a 13 step Video Sales Letter (VSL) Guide 🎥 -> 💰💰💰 It's Free for 48 hours! To get it: 1, Like & RT 2, Reply " guide " 3, Follow me so I can DMshow more

🚨FREE SMALL BATCH GIVEAWAY🚨 1. Follow 10 toes 🏃🏾‍♂️💰... 2. RT & comment which of these 4 strains you’d like to try most 3. Tag SB you’d share it with 4 winners and each one will get one of these for free! Winners will be chosen Friday!show more

I'm starting on a new project #buildinpublic 🤠 ✅... ahrefs sub 📚 initial keyword research 🆕 .com domain name But this is different. Why? I'm starting with SEO & marketing, then fleshing out the product afterwards. It's been a busy morning already thanks to Ahrefs. From the learnings of grandmaster sensei — I will be using my other projects for backlinks & focus on SEO instead of adding as an afterthought. The plan: ------------------------- [hacks explained further down] 1. keyword research 2. more keyword research [HACK #1] 3. content plan 4. choose topics, subtopics & post outline using long-tail keywords found in 1. & 2. [HACK #2] 5. landing page, blog & initial marketing 6. barebone MVP 7. blog with content hubs [HACK #3] 8. initial backlinks [HACK #4] 9. marketing & launch 10. talk to users & iterate while SEO is slowly cooking in the background (hopefully by the time the product matures SEO is booming) ... 🔁 continue to fill in posts according to the content plan. then back to 1 & 2. more long-tail posts & create free tools to improve ranking + increase no. of backlinks. Hack #1 --------- Explore keywords for "result intent" SEO. Figure out guides & tutorials for keywords with DR long tail ones. Create structure for internal links, e.g.: /generic-topic-keyword (links to all posts) ➡️/more-specific-subtopic-keyword (links to child posts) ➡️➡️/very-specific-post-1 ➡️➡️/very-specific-post-2 etc. Hack #3 --------- Create hubs for generic keywords with links to subtopics and long-tail posts. The hubs themselves should be somewhat informative but mostly an overview. => My crazy idea: before I have the content, add external links to authoritative sources for each specific post. I'll slowly write my own content to replace those and move the links inside the post. Hack #4 --------- Use my other projects to write posts on the new product and link to it to get a decent domain ranking fast. Launch on PH with a beta, mostly for the good backlink. Add repos with md files to Github, Gitlab, Bitbucket etc. for some easy backlinks. 🤠 Crazy enough to work, right?* *to note: I've validated the idea and am somewhat sure people will pay for it. But, I'd still like to shorten each step to minimize my risk & ship fast. Thinking: 1 week research, 1 week dev, 1 week marketing, 1 week content. What could go wrong? :Dshow more

🚨🚨SILVER GIVEAWAY TIME🚨🚨 It is time to do another... silver giveaway! Woohoo!! This is your chance to win another piece of silver jewlery made from the one and only JesterJum so here we go with giveaway #2 😃 Huge congrats to our last winner Supersonic Redhead🛫! She can attest to the quality of the pieces I make! This is a solid 925 silver, one of a kind wolf ring inspired by House Stark from Game of Thrones. This giveaway will last for 5 days, so the winner will be randomly chosen and announced next week on 4/16 @ 9pm CST To enter for a chance to win, you must: 1) Follow Jum 2) Like this post 3) Repost this post 4) Leave a comment (any comment you like) Each individual is only allowed 1 entry so multiple comments will not give you multiple entries. Multiple accounts per person will be disqualified — play fair! Entries from duplicate or spam accounts won't count. At the end of the week, all eligible individuals will be put into Grok and Grok will choose a random winner! This is a chance to get a 100% FREE silver ring, and with silver at an all time high, you don't want to miss this chance! **This giveaway is in no way sponsored, endorsed, or administered by Xshow more

[Commission - Scene1 - Kissing/Opening Scene] Sound ON 🔊... [NSFW] 🌱🏛️ This commission has like near on just one minute of kissing (≧∀≦) kissing is a pain to animate and very time consuming… (*´-`) so if you like this content please consider reposting/retweeting （╹◡╹）it’s free and helps out a ton. One of the NSFW scenes have already been posted, I’ll share only previews of what’s to come now until the project is finished. It’ll be up on p@treon for public release within a week and a half, give or take. //Commission details// Total length: 3minutes+ VA: Definitely Not Ty 🔞 Scene 1: Domestic, kissing & makeout Scene 2: Rough sex in mating press pos & over the couch Scene 3: surprise… (*ﾟ∀ﾟ*) Length animated as of 6/2/2024: 1min, 30 secs+ ╰(*´︶`*)╯♡ If you like my works please consider supporting or commissioning me~ Average work time for a commission is between 3-8 weeks, any delays are compensated with further bonus content (о´∀`о) this can be bonus renders (images) or up to a 15 second animation for free at no extra charge (๑˃̵ᴗ˂̵) If you’re interested, my commission sheet is in my bio! Takes a quick five minutes to look over and will help me build up an idea for your commission. It has checkboxes and selection for position, ship choice (free choice, just write it) and I’ll respond to your form via email or provided contact to discuss any further details and the payment plan~ （╹◡╹） My payments are split, so no need to worry about paying it all in bulk~ Aaanyway, enough rambling from me! Video tags: #nsfw #haikaveh #nsfwhaikaveh #haikavehnsfw #genshin #yaoi #genshinyaoi #gayporn #nsfwanimation #animationnsfw #genshinimpact #genshinimpactnsfw #nsfwgenshinimpact #genshinimpactshow more

[INTEREST CHECK] Based on the poll results from last... time, most participants agreed with having a summer outdoor party 🎉 Please note that the target location has been changed due to schedule availability conflicts with our initial options. The entire resort will be rented exclusively for us, so rest assured that the venue will be private for all attendees on the event day. If you check the photos of the resort, please be informed that the inflatable obstacle course is not included in the venue. This will be rented separately and set up on the day of the event. We would also like to extend our gratitude to JLCENTERFLARES for sponsoring the finger foods. Kindly see the tentative date and location below, and feel free to share your thoughts. ❤️ 📅 Date: April 25 ⏰ Time: 11:00 AM – 10:00 PM 📍 Location: Villa Viella, Bacolor, Pampanga (approx. 2 hours from Metro Manila) 💸 Registration Fee: ₱1,200 Inclusions: • Entire venue (including Simple JL Land, pool access, function hall, and gazebo) — EXCEPT rooms • Simple lunch • Finger foods (sponsored by JLC) • Dinner • Inflatable obstacle course • Freebies Additional possible inclusions may also be announced once the registration form is released. 📝 Please be informed that there will be an additional cost should you wish to avail the shuttle service. For those messaging or planning to message us regarding sponsorship, please note that we will only respond through our official account. #AHOF #아홉 #AHOF_JL #제이엘show more

IF I WAS FORCED to build a $20K/month AI... creative agency using nothing but Photoshop, starting from 0, here's exactly what I would do in steps: The production setup (Days 1–3) 1. Download the Higgsfield plugin inside Photoshop — takes 5 minutes 2. You now have: sketch-to-image, layer decomposer, mockup studio, relight, upscale, face swap, character swap, background removal, AI stylist — all in 1 tool 3. Old creative agency workflow: designer + photographer + editor + 3–5 day turnaround 4. New workflow: 1 person, Photoshop, 30 minutes per deliverable The offer (Days 3–7) 5. Pick 1 niche — ecom brands, real estate agents, or course creators all need visuals constantly 6. Build a simple offer: "10 ad creatives delivered in 24 hours — $500" 7. Old agencies charge $2,000–$5,000/month for the same output 8. Your cost to deliver: $0 beyond the plugin. Pure margin. 9. Create 3 sample mockups using the tool — drop a product image in, generate 9 variations, pick the best 3 10. That's your portfolio. Built in under 1 hour. Cost: $0. The client machine (Days 7–20) 11. Go on X and search "[niche] + need a designer" or "[niche] + creatives" 12. DM 50 people per day — "I'll make you 3 free ad creatives in 24 hours, no catch" 13. Deliver them in 30 minutes using the plugin 14. 50 DMs/day × 14 days = 700 outreach messages 15. Conservative 3% conversion = 21 people see the free work 16. Close 5 of them at $500 = $2,500 in week 3 The scale (Days 20–30) 17. Upsell every client to a $1,500/month retainer — 10 creatives/week, unlimited revisions 18. 1 client per day in Photoshop takes 45 minutes max 19. 10 retainer clients × $1,500 = $15,000/month 20. Add 3 one-off clients at $500/month = $1,500 21. Add a $997 "AI creative system" course teaching other people this exact workflow = $3,000+/month from 3 sales The math: 50 DMs/day × 30 days = 1,500 outreach messages 3% book a call = 45 calls 40% close at $1,500/month retainer = 18 clients 18 × $1,500 = $27,000/month recurring Time per client per day: 45 minutes Total daily work: 4–5 hours Every mockup — AI. Every restyle — AI. Every layer rebuild — AI. Every variation — AI. No photographer. No designer and no reshoot. Start it here. 👇show more

Met my girlfriend's parents for the first time. Her... dad asked what I do for work. I said I build trading systems. He said like Wall Street? I said no. 6 AI agents. They work while I sleep. He laughed. So robots are making you money? I did not argue. I opened my laptop. Showed him the terminal. 6 agents running. 47 mispriced markets caught in the first week alone. His face changed. That is not gambling. That is automation? Exactly. Then I showed him how it works. Built the whole thing in 6 hours. Agent 1: Monitoring Runs 24/7. Watches Polymarket for mispriced markets. Spots an anomaly. Writes to memory and pings me on Telegram instantly. Agent 2: Research Parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I check my phone. Agent 3: Trading Reads the research agent memory. Sees the market has not reacted yet. Acts. Execution tool in gateway mode with a whitelist. No full access on a live server. Agent 4: Watchdog Heartbeat every 5 minutes. Monitoring running. No errors. Positions up to date. Something breaks. Immediate Telegram message. All of this. One Gateway. One config file. Isolation via per-agent scope. The token trick: stopped dumping everything into one file. Critical rules in bootstrap. Markets, patterns, past trades in memory. Semantic search pulls it when needed. Token spend dropped 3x. From $0.40 per request to $0.13. First week running: → 47 mispriced markets caught before Polymarket adjusted → Average entry edge 8 to 12 cents per position → Watchdog fired 3 times and caught a broken RPC before it cost me anything The whole system is plain text files. Open an editor. Change one line. Agent behaves differently. No deploy. No build. Her dad went quiet. Then he asked can you teach this? Her mom asked for the setup guide. I built the entire framework. Six agents. Full deployment. Memory architecture. Telegram alerts. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the 6-agent system this week. Start with $200. Scale on evidence.show more

I just built a Claude skill that writes 20... Meta ad hooks in 60 seconds 🤯 Give it your product, your audience, and your best-performing angles → it writes hooks across 10 proven frameworks, each one targeted at a specific customer pain point. All inside Claude Cowork. Perfect for DTC brands and agencies who are still writing hooks from scratch every time they need new creative — staring at a blank doc, scrolling competitors for inspiration, and recycling the same 3 angles because you ran out of ideas two weeks ago. If you're launching Meta Ads and your hook writing process looks like this — open a Google Doc, try to remember what worked last time, write 5 hooks that all sound the same, run them, 4 flop, go back to the doc, repeat ... This skill replaces the entire process: → You give it your product name, key benefits, and target customer → It writes hooks across 10 frameworks: problem-solution, curiosity gap, bold claim, social proof, before/after, us vs them, question, contrarian, urgency, and storytelling → Each hook targets a specific pain point — not generic "Shop now" copy → Generates 2 variations per framework so you have options to test → Outputs everything organized by framework with notes on when to use each one → Takes about 60 seconds No blank page. No recycling the same 3 angles. No writing 5 hooks that all sound like the same ad. What you get: → 20 hooks across 10 proven frameworks, ready to drop into your ads → Each hook written for a specific customer pain point, not a generic audience → Framework labels so you know which hook type you're testing → A reusable skill — run it for every new product, every new campaign, every new angle sprint → Works from a product brief — no API connection, no CSV export, no setup beyond installing the skill One product brief. 20 hooks. 60 seconds. I put together the full skill file plus a playbook showing how to install it, customize the frameworks, and run your first hook sprint. Want it for free? > Like this post > Comment "HOOKS" And I'll send it over (must be following so I can DM)show more

How to make money on the weather using Polymarket... I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto—focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( – $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > ( - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > ( — Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules >Tropical Tidbits ( - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high >Climate Reanalyzer ( - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities >Windy ( - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online ( - 100+ years of historical location data NOAA Weather Prediction ? >Center ( - short forecasts for precipitation, anomalies. Climate Prediction Center ( - long-term ENSO, droughts >Open-Meteo ( - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. >OpenWeatherMap ( = Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. >Visual Crossing Weather ( - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities >WeatherAPI. com ( - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha informationshow more

How to make money on the weather using Polymarket... I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto-focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( - $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > - Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules > - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high > - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities > - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online - 100+ years of historical location data NOAA Weather Prediction > - short forecasts for precipitation, anomalies. Climate Prediction Center - long-term ENSO, droughts > - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. > - Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. > - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities > - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha informationshow more

after consistently booking 100 b2b calls/mo from linkedin inbound... funnels... i sat down with Lara Acosta and gave away our ENTIRE playbook in a 1-hour interview → every system → every framework → every DM script for context, a post with 40 comments booked me 4 qualified calls last week a single question in the DMs booked a client 72 calls in 26 days and one lead magnet batch generated 7,000 comments across 4 variations in this interview i break down exactly how all of it works... here's what's inside: → why i think content pillars are dead and what replaced them (awareness stage positioning: problem unaware, pain aware, solution aware) → the lead magnet system we run at 100 per week across all client accounts (what makes a good one, why 50 pages of text is a waste, and why the best lead magnets right now are all Claude/AI related) → the DM conversion framework that turns a free resource into a booked call in 3-5 messages ("hey, what caught your attention?" → discover the pain → drop a case study → assume the yes with a specific date and time) → why engagement doesn't equal revenue and what actually does (30k followers with low engagement booking 10x more calls than before because the conversion infrastructure changed) → the trend jacking strategy that makes dead accounts go viral overnight (spot it on X in the morning, build the resource by noon, post on linkedin by evening) → how to get your first case study using pay-for-results instead of free trials → the competitor analysis shortcut for never running out of content ideas → why the linkedin algorithm conversation is 90% excuse and 10% useful like + comment "POD" and i'll send you the full interview (must be following + RT for priority access)show more

This guy cracked the code on AI-powered fashion ecommerce... using synthetic face technology and now pulls $50,000 to $150,000 per month from two Shopify stores without paying a single real model. He got tired of watching DTC fashion brands burn $20,000 monthly on photoshoots while their competitors tested 40 product angles in the same timeframe, so he built a system that generates hyperrealistic fashion content using his gaming PC and real-time AI masks instead of studios, contracts, or casting calls. His monthly profit hit $150,000 last month from just 2 stores and organic TikTok traffic, while traditional fashion brands cap out at $30K after paying models $400 to $800 per shoot and studio rentals of $200 to $500 per session. Here is the exact breakdown: → Real-time synthetic face technology becomes the only tool you need, but most people butcher the setup by skipping motion sync calibration in the first 30 seconds → Product selection comes first, and if you mess this up nothing saves it. Stick to women's accessories (bags, sunglasses, jewelry) because that is where organic TikTok engagement lives → Avatar casting is not random. You build one consistent AI face that repeats across all content so your audience recognizes the "model" and trusts the brand continuity → You are picking who your customer projects onto, not who looks expensive. That is your positioning baked into the face → Motion capture runs before generation, and this is what kills the uncanny valley effect that destroys watch time in 4 seconds → You mirror your own gestures through webcam: wave, chin tap, finger point, shoulder dance. The AI mask tracks every micro-movement and applies it to the generated face in real time → Batching is the move 94 percent skip: same outfit base, multiple product swaps, one recording session. No re-shooting, no model schedules, no usage rights negotiations → The system generates 3 to 5 TikToks before lunch, while traditional brands test 2 per week and wonder why their conversion rates are stuck at 0.8 percent The economics are stupid: each video costs him $0 in talent fees, pulls 1.5 million views organically, converts at 0.03 percent into 450 orders at $45 to $60 retail with $30 to $45 margin per sale. That is $15,750 profit per viral video, while fashion brands pay $1,200 per shoot and net $3,000 after ads. The key move nobody talks about: you cannot skip the motion synchronization test. If you generate the AI face without mirroring your own natural gestures first, the avatar moves like a mannequin. The blinks lag. The smile timing breaks. The whole thing screams "synthetic face technology" and your hook rate dies at 1.1 seconds. His system records him doing the exact dance trend first, so the AI mask inherits human timing, natural head tilts, and spontaneous energy that reads as a real creator showing off a product find, not a rendered advertisement. One accessories store generated 10 variants of the same handbag reveal in 18 minutes with different outfits, different backgrounds, different trend audios, and found the winner in 72 hours without spending $6,000 on influencer gifting. They were previously paying $800 per UGC creator and burning $4,800 per week on content that plateaued at 40K views. Now they spend $0 for 10 variants and their cost per acquisition dropped from $62 to $18. UGC agencies now panic because their entire margin was built on talent scarcity, and this removes the human bottleneck. The outfit changes between clips like a wardrobe filter. The lighting matches bedroom setups. The hand gestures sync with beat drops. No casting call. No model release. No location permits. Just a webcamera, a real-time AI mask, and the discipline to batch-test product angles before you commit ad spend to one creative.show more

How do you get the biggest SKR airdrop allocation... with the least effort? 📱🪂 Not everyone has time to grind Seeker activity every day. But everyone wants a solid SKR airdrop when Season 2 ends. Here are 5 ways to maximise your activity with minimal effort 👇 1️⃣ SKR Staking ✅ One of the strongest passive actions in Season 2 👉 Zero ongoing effort after setup 👉 Stake inside Seed Vault Wallet (Activity tab) 👉 Or at ✅ Compounds every 48h automatically 👉 Unstaking cooldown is only 48h - never locked in 👉 Strong loyalty signal 👉 Counts directly toward Onchain Activity ✅ Passive SKR accumulation + inflation rewards 👉 One setup, long-term impact for the next airdrop 2️⃣ Daily Use ✅ Already done if Seeker is your main phone ✅ Secondary device? One simple habit 👉 Open Seed Vault Wallet + 3–4 apps once a day 👉 Takes under 60 seconds 👉 Full “Daily Use” bar from this alone ✅ No grinding required 👉 Consistency over 7 days beats any single burst 👉 Fits into any routine 3️⃣ dApp Exploration ✅ 10 minutes a week is enough 👉 Open dApp Store → browse Featured or New 👉 Download 1–3 apps → open each → connect wallet ✅ No deep usage required 👉 The tracker rewards discovery 👉 Fills the “ New Things “ bar weekly 4️⃣ Onchain Activity ✅ 30-day rolling window 👉 Regularity beats volume ✅ Minimum effective dose: 1–3 txns per day 👉 Micro Jupiter swap: 0.01 SOL or less 👉 One swap, seconds of effort 👉 Do it from your pocket ✅ Bar climbs steadily without grinding 👉 Small consistent txns outperform sporadic bursts 👉 Cost is near zero 5️⃣ DePIN Background Apps ✅ Install once, runs 24/7 👉 No daily action needed 👉 Each generates on-chain activity automatically 👉 Also counts toward dApp Exploration ✅ Four apps to install from the dApp Store 👉 UpRock - share bandwidth, earn $UPT 👉 Roam - hotspot sharing, earn $ROAM 👉 WeatherXM - weather data, earn $WXM + 25% station discount 👉 Helium Mobile ☁️ - free Zero plan (3GB/100min/300 texts) + Cloud Points ✅ Passive activity across multiple bars simultaneously 👉 Extra token rewards on top of SKR 👉 Setup: ~10 min total, zero effort after 6️⃣ Overview ✅ The full routine is simple 👉 Daily: open wallet + optional micro swap 👉 Weekly: install 1–3 new dApps 👉 Forever: SKR staked + 4 DePIN apps running ✅ Avoid automation tools 👉 Diagnostics flag patterns - manual only ✅ Season 2 rewards consistency, not bursts 🔚show more

introducing a new, very fun, LLM benchmark- the Game-of-Life... Bench! the rules are simple: given an 8x8 grid following Conway's game of life rules, the goal is to create an initial pattern with at most 32 cells that can last the longest number of turns before dying/repeating. some results to highlight (with caveats detailed below): - gpt 5.1 lasts the longest with a 106 step run - claude models are really bad at this! they refuse to reason about this task and score < 25 points - deepseek r1 is the best open model with 102 steps. why? because i wanted to create a benchmark that has (i think) no practicality, but is still fun to look at, cheap, and still measures something interesting. i also am a big fan of the game of life. its absurdly simple rules leading to intractability is extremely cool to me. also, i saw a lot of work with LLMs trying to "predict" the next state in Conway's game of life, I think game-of-life bench is more fun because it's pretty open ended and only asks the LLM for the initial state. I also think this could be an RL env? but idk why you would ever train on this task haha i don't think this is a "serious" benchmark because it doesnt measure anything practical, but i still think it's a hard benchmark exactly because you can't predict what happens with your initial state many turns into the future; this is why i was initially expecting all LLMs to be bad at it, but turns out, some are clearly better than the others (the ordering may surprise you!) reminder: this is still a work-in-progress; (1) i am gpu-poor so could only do 10 runs for each model, even though total running cost is relatively low. maybe with some more credits i can run more seeds for each model. (2) i handpicked models which i think are at the frontier right now, plus some others that were on my mind. so, if you'd like to see a model on here, let me know. (3) i currently only do an 8x8 grid because i thought that by itself would be pretty hard for current LLMs, but of course we can increase grid sizes! (4) the coolest thing is, i dont think we can calculate the max possible number of states (yay undecidability!) you can go without repeating, so this is essentially a no-ceiling task, which is pretty cool! again, i did this mostly out of a desire to make LLMs do something fun. if this keeps me entertained for a few more days, i'd likely release a blog post on it. if it keeps me entertained for a week (and someone sponsors me), i'll put more work into it :P lastly, this is fully open sourced, so feel free to run this on your own!show more

A Citadel quant sat down next to me at... Verve on Gough and asked why my laptop had four terminals open I was scanning Polymarket. Four panes. Each one a different agent. He was killing time before a flight. Saw the screens. "Is that a multi-agent setup on prediction markets. Who's orchestrating" Claude. One prompt per agent. They don't share memory. Only a queue file. He pulled up a chair. "Walk me through. I do this for equities at work. I want to see your agent separation" Agent 1 is the scanner. I piped raw JSON from the official Polymarket CLI straight into Claude and told it to score every live market on three things. Edge against my probability estimate. Book depth on both sides. Hours to resolution. Thresholds kill 93% of markets before the brain ever sees them. Edge under 7 cents gone. Depth under $500 gone. Under 4 hours to resolution gone. Over 168 gone. 487 live markets collapse to 35. "Seven cents is your transaction cost buffer" Yes. Below that the gas and spread eat the trade. A green fill popped. +$52 on a BTC dominance market. "And the brain" Agent 2. Runs four checks on every survivor. Base rate from history. News in the last six hours. Whether any of the 47 top wallets are currently holding. And a disposition check - is the crowd making a known cognitive error. Three out of four must agree. Otherwise drop it. 86 million trades. I let Claude rank every wallet with 100+ fills and a 70%+ win rate. It returned 47 names in four minutes. Top 20 wallets made more than the bottom 13,000 combined. "Concentration like that means the signal is there. Most retail books look like a normal curve. Yours looks like power law" Kelly sizing does the rest. Capped at quarter Kelly. If f-star goes negative the trade dies no matter how confident I feel. "Overbet once and the bankroll is gone. You respect that. Good" Agent 3 is execution. Three strategies pulled out of a 53k line Typescript repo. Arbitrage across related markets. Convergence when price moves toward my estimate. Whale copy with a 60 second delay on the 47 wallets. Two agents agree full position. One agent only half. Disagreement no trade. "What did you cut" Sports. 52% win rate. Already priced in before the scanner flags it. Markets under $50k in depth. Slippage makes every edge a coin flip. Holding to settlement. The top wallets exit at 73% of max profit every time. I copied that. Agent 4 watches exits. Three triggers. Target hit at 85% of expected move. Volume spike 3x the ten minute average. Thesis stale 24 hours with no movement. "91% of the smart wallets exit before resolution. That's the trade" Yeah. Being right is not the same as being profitable. Setup: Claude API $20 Hetzner VPS $5 Four repos free Total $25 a month $200 seed. 27 days ago. $14,300 now. 271 trades. 74% win rate. Sharpe 2.47. Copy here: "How long did the build take" Two weekends. One to wire the scanner and the CLI. One to get the agents talking through the queue file. He watched the volume exit trigger fire on a Fed cut market. Position closed at 0.71. +$184. "Nobody at my shop runs four agents on their own money. We run eight on the firm's. You got the same structure on a laptop for the price of a sandwich a month" He asked for the repos. I sent them. He messaged me from the gate. "Publishing this tomorrow. My PM is going to ask me why I didn't do it first" I told him his PM already has a Bloomberg. That's the problem.show more

This is my "feel the AGI" moment: I used... GPT-5.6 Sol to train my own autocorrect model that outperforms GPT-5.6 Sol (wtf??) I have no ML background. I have no idea what I'm doing. I just kept pushing Sol until it spat out a SOTA model. And I spent $0. The motivation: Years of talking to AI have made me terrible at typing. Rather than fix my skill issue, I decided to throw more AI at it. My idea was: instead of autocorrect that interrupts my flow, I want to type fast with mistakes and have AI clean it up after. I wanted the smallest local model possible, for speed, for battery life, for science! So I decided to train my own. Inspired by Andrej Karpathy’s autoresearch, I ran Codex /goal with this setup: pick an experiment, try it, record the results to a doc, throw it out if it fails, and plan the next experiment without repeating failures. I gave a few examples that had to pass, tight latency targets, and let it run. Sol did some amazing things. First, it scanned benchmarks and shortlisted base models: Qwen 3.5, Gemma 4, Liquid LFM 2.5. It found a dataset on HuggingFace for typed text. Then it built a simulator for fingers striking a Mac keyboard, modeling the physical layout with a Gaussian distribution around each key. It simulated striking the wrong key, wrong order, fat-fingering, etc. With the models + data + simulator, it fine-tuned using MLX right on my MacBook. It had a working prototype within an hour! But accuracy was pretty poor. — Problem 1: Tokenization Sol read papers, ran tests, and identified that the tokenizer was the bottleneck. Tokenization makes typos hard for the model to see, so it memorizes mappings instead of using its language priors. Sol tried ByT5, Google’s tokenizer-free byte-level LLM. This made a big improvement, but the model is old and lacked the knowledge needed to reach Sol performance. Sol dug deeper and realized a tokenizer-free model isn’t needed; instead, it used T5Gemma, an encoder-decoder model. This can understand the input deeply before producing output, and furthermore, Sol could post-train the encoder to improve performance. This gave a much higher ceiling. — Problem 2: Loss function Now the model was correcting some typos perfectly, but ignoring most. Sol realized that standard cross-entropy loss was teaching the model to avoid edits, because the vast majority of characters in the training data were left unmodified. The fix was wild: Sol wrote a custom loss function that byte-aligns the source and target strings, uses a dynamic programming algorithm to compute the minimum edits between the two, then weights correct edits much higher than copies. After a lot of tuning, this dramatically improved accuracy. — Problem 3: Autoregression One failure mode remained: if the model made a mistake, it couldn’t backtrack. It could only predict the next token. Teaching it to “think” like a reasoning model would solve this, but would be far too slow. Sol found a beautiful solution: instead of greedily predicting the next token, beam search over all possibilities. This parallelizes the exploration instead of one linear chain-of-thought. At the end, choose the path with highest cumulative log probability. This worked great, but made the experience worse, since the user wouldn’t see progress until the whole search was done. To fix this, Sol made a clever observation: after each search step, the longest common prefix among surviving branches is guaranteed to appear in the final result, so it can be displayed immediately. As the search progresses, weaker paths are dropped and the prefix grows, so the user sees continuous progress. Sol built all this as a custom MLX pipeline that does the parallel decoding on the MacBook GPU, with just ~40ms TTFT. It’s crazy fast and entirely local. — Final eval (error reduction rate, higher is better): - Apple autocorrect: 49.66% - GPT-5.6 Luna: 82.47% - GPT-5.6 Terra: 87.64% - GPT-5.6 Sol: 90.56% - Our model (1.7B): 91.02% Final cost: - 1 quota reset (thanks Tibo) - $0 (And yes, I verified there's no cheating. In fact, we test words scrubbed from the training data to prove the model isn’t memorizing) There were a ton more details and tangents I could write about: contrastive learning, GRPO, DPO, dynamic masking, and more. Sol is a fascinating and creative model. It blew my mind so many times. Don’t let a lack of experience stop you: Sol makes AI experiments accessible to anyone!show more

Real Benefits of Staying Overnight at Accor’s Mercure Ba... Na Hills 🏰☁️ Save Time • Save Money • Experience the REAL Ba Na Hills If Ba Na Hills, Vietnam 🇻🇳 is on your itinerary, do NOT do it as a day trip. An overnight stay at Mercure Ba Na Hills French Village completely changes the experience — and most people miss this 👇 ⸻ 🚡 World’s most unique hotel access — arrive by cable car with luggage This is the ONLY hotel where you reach your hotel room via cable car — with your luggage 🎒🧳 Your stay literally starts with a scenic cable car journey over the lush green forest, waterfalls and through the clouds ☁️ No roads. No buses. Just views and vibes. ⸻ ✨ Ba Na Hills at night = pure magic After sunset 🌄, it feels like you’re staying above the clouds ☁️ Silent streets, misty castles, and unreal vibes — something day visitors never see. 🚶‍♂️ Post 4:30 PM = Ba Na Hills becomes yours Once the day crowd leaves: • Empty streets • Quiet castles • Peaceful photo spots 📸 • Zero chaos ⸻ 🚡 VIP Cable Car access (Huge hidden benefit!) ✔️ Mercure guests get VIP / priority entry into cable cars ✔️ Private cable cars for your family only ✔️ No queues at all ⏳ Day visitors wait 60–90 minutes EACH side, and 10–15 people are packed into one cable car. This benefit alone saves hours. ⸻ 🎢 Fantasy Park with ZERO crowds 🗓️ Friday–Sunday: Open till 7 PM in the evening while day visitors leave by 4:30 PM. Unlimited FREE Rides, games, and 4D/5D shows — repeated multiple times 🎮🎠 No queues. No rush. Full fun mode 😍 ⸻ 🎿 Alpine Coaster Happy Hours = Double Win at this Gravity Based Roller Coasters 🎢, Most Popular at Ba Na 💰 Pay just VND 50k (instead of VND 80k) ⏰ 4:30–5:30 PM | 8:30–9:30 AM 🚫 Almost no waiting 🌫️ Evening mist rides on mountains = unforgettable ⸻ 🌉 Golden Hand Bridge — crowd-free access The iconic Golden Bridge is accessible ONLY to Mercure guests from 6 AM–8 AM Till ~9 AM, there are very few people — perfect for photos & serenity 📸 ⸻ 🚡 30% discount on Cable Car + ALL attractions if purchased at Mercure check-in, The two-way Cable Car tickets includes 👇following on all days on your Stay ✔️ All cable cars (up, down & internal) ✔️ All funiculars 🚆 ✔️ Unlimited Fantasy Park & Moon Castle games ✔️ 4D / 5D / 7D & 360° movies ✔️ Flying Eye Theatre ✔️ Indoor & outdoor bumper cars ✔️ All rides ✔️ Sun Castle & Moon/Lunar Castle ✔️ Le Jardin D’Amour, Pagoda & Love Garden 🌸 ✔️ Thác Thần Mặt Trời waterfall & Golden Horse Statue ✔️Except Alpine Coasters & 10D Show, everything is Free, unlimited times 🤩 Most day visitors don’t even realise what they miss. ⸻ 💡 Bottom Line: Ba Na Hills is NOT meant to be rushed. You need time to feel the vibe and explore peacefully. After staying there, I honestly wished I had booked 2 nights instead of 1. 🏰 A night stay at Mercure Ba Na Hills isn’t just about the hotel — it unlocks the best version of Ba Na Hills. 🔖 Save this post 🇻🇳 Stay tuned for more Vietnam travel & credit-card-optimised travel tips. 📘 Visit SpendWisely Blog: Detailed credit card reviews & guides 👉 Some links may be referral links in the above post. It supports the page without any cost to you. #creditcard #spendwisely #creditcardsshow more