Experiment ⬇️ „Dubai is empty“ When I post a... picture or video, I have already left, for my security When I post, I make sure I choose a moment and angle, with no faces visible or edit them out of the content, for their security For the same security reasons, the UAE doesn’t want us to film and post sensitive footage People like to make up stories and look for faults, here is an experiment: A teacher writes down: 1+1=2 2+2=4 3+3=6 4+4=8 5+5=9 Every student raises their hand and points out the last mistake, instead of pointing out that 4/5 calculations are correct At the end, we are all human and must protect each other, instead of making each other vulnerableshow more

So I have been trying to do my own... take on the 4-2-1-3. but it is not for my play style. Will try some more, later on. For now I ended up with a 5-2-1-2 that I like a lot. And it’s surprisingly good against the 4-2-1-3. Anyone wants to test? 🔥🏴‍☠️show more

In 2026 there are 3 types of people left... on Polymarket. I have been all 3 and only one of them stopped losing money. Type 1: programmers. They write bots, make $11K to $120K a month. They are 2% of the platform. I tried to become one of them. Lasted two weeks and one broken script. Type 2: people who found type 1 and copy their trades. No code, no servers, no sleepless nights. They are 5%. Type 3: everyone else. Trading by hand, trusting their gut, and steadily handing money to the first two types. They are 93%. I sat here for 4 months and lost $1,800. The most frustrating part is that all the information is right there. The blockchain shows every trade from every wallet. I stared at it for 4 months and kept trading on my own. To become type 1 you need months of coding. To become type 2 you need to stop believing you are special. The team at PMX built a tool that copies the best wallets automatically: I did not get smarter. I just stopped being type 3.show more

Last post on this I'd appreciate if people took... the time to read it and share it because I think when people listen they deserve credit but TRNSMT have done more than that I complained about the disabled situation TRNSMT Festival and I think the fact that they listened and made changes is the kind of progressive attitude we need towards disabled facilities. I wasn't complaining to come across as some sort of Karen, it just genuinely would've been a health and safety risk. So I think it's only right that I commend them for the work they've done with the platform this year. The platform has many key things that I think make it the best at any festival I've been at. 1.Clear marked out lanes for people to move out to the toilets and back to their seat to avoid congestion and create space 2. A bar for disabled people beside the platform this is amazing. 3. Toilets well spaced out as well as a changing places toilets for people who more severe disabilities beside the platform. 4. Plenty of space in the toilets. 5. It's huge and you feel really close to the stageshow more

ermmm I got 2 more babies xD i had... to go back and get the other sisters they’re all from the same litter i felt so bad :c but once they’re all 3 bonded with my 4 older female rats im going to do a big cage upgrade and they’ll all be in the same one! but this is two of the new babies the other one is shy and sleepy 😴 ill try to take a pic of all 3 of them later! so the video is 2 of 3 of the new babies, and the 2nd pic is their cage until they bond with my adult rats and get a bit bigger, in which case by then i will be moving all of 7 (YES now SEVEN hahah) of my female ratties to the big big cage next to my older pack of 4 girls’s cage (u can see champagne -the albino- and oreo-the one below) saying hello in pic 4 :3 and what’s crazy is that the current rat cage for my 4 older girls is a pretty good size, so moving all of them to the larger cage is going to be crazy for them, im gonna make it like a rat theme park hahashow more

I really learnt from the best If your content... is averaging 700 views it’s of two things 1. It’s either you did not warm up your account well to the hashtag you are posting with 2. You have a general content problem , you need to find content that has been pushed in the last 1 month max and post I have 4 iPhones , 3 iphone 8 and 1 iPhone 7 , I post content on all everyday been doign this for the past 2 years I use the iPhone 7 to post for one of my brands And I use the 3 iPhone 8 to post for one brand The most important thing is , find what works for one phone and spread it across others It took me years to learn this One big lesson, don’t tell your vpn to X , you will hate yourself , not telling people the vpn I am using so they don’t overcrowd it If you post a content in your main niche, you should be averaging 1k+ - 5k+ views Trust me it’s a lot of work I also started posting on instagram and YouTube and they work differently , don’t post the same video content on both without observing hashtags I also posted on lemon8 , one of my post average 10k+ views Daily I get around 50 users , I have gone viral several times, one of my biggest virality is 700k+ views I really want to buy more iPhone 7 and 8 , It costs me arround $50-70 for each locally here Recently I have been thinking of how do I get clippers locally to do this and train them but it looks like it’s hard because you have to train them Taking advice from the legend Alex Nguyen I have not made a lot but trust me , it works This is proof from one of the apps , we ask during onboarding where they find usshow more

MLP in PyTorch by hand ✍️ ~ 7 steps... walkthrough below Goal: fill in every blank in the PyTorch code to build a multi-layer perceptron. 1. Given Let us start with a code template on the left and the network it is supposed to build on the right. Every blank in the code can be worked out from the picture. 2. Linear layer We count: 3 features in, 4 features out. So the weight matrix is 4 by 3. There is an extra column for the biases, which means bias = T. 3. ReLU Let us apply the activation. ReLU crosses out the negatives, so -1 becomes 0. 4. Linear layer The input size is 4, because that is what the previous layer put out. The output size is 2. A 2 by 4 weight matrix, and this time no extra column, so bias = F. 5. ReLU We cross out the negatives again. 6. Linear layer Two features in, five out. A 5 by 2 weight matrix, with a bias column, so bias = T. 7. Sigmoid Let us finish. Sigmoid squashes the raw scores (3, 0, -2, 5, -5) into probabilities between 0 and 1. You have just implemented a three-layer deep neural network by hand. ✍️ == Story == Three years ago I gave this exercise to my students, to connect the code to the math. They found it odd. Every other AI course they were taking lived inside a Jupyter notebook, and here I was handing out paper. Three years later, my colleagues are the ones rushing to move their materials to paper. The exercise has not changed. Paper still asks the one thing a notebook lets you skip: do you actually understand what the code is doing? If you can tell me why the weight matrix is 4 by 3, and why bias is F on the second layer, you understand nn.Linear better than someone who has been copy-pasting it for a year. 💾 Save this post! #AIbyHand #PyTorch #DeepLearningshow more

There is a state park by me that closes... when the sun goes down for safety reasons. I always see people find a way in there to do what they need to do. No matter what they do mayor be add a gate or even have more law enforcement, there’s no stopping it. These people are sitting in their car. They see people walking in and out of the woods while they are sitting there eating and chatting. The people going in and out look so out of place, like they are in a zombie apocalypse. If I saw people just struggling in and out of the woods, looking dirty, no flashlights at all. I would think they are up to something. Especially for the hikers making their way back and hearing rumbling and voices I would be creeped out too.show more

This happened at country pop star Morgan Wallen’s concert... Friday night in Pittsburgh, Pennsylvania. A fan handed her phone to a security guard. The security guard was standing with her face to the crowd and her back to the stage and was filming Morgan. Morgan comes over and crouches down and gives the phone camera a look, walks away, then comes back and grabs the phone out of the security guard’s hands and then turns around and chucks the phone off the stage. A lot of people are upset with Morgan, I get it, but many people pointed out that the security guard wasn’t doing her job. They said when you sign up for the job, the job entails making sure that you are enforcing no videoing. I personally have never seen a venue employee or security guard, whatever she was, film the performer for a fan. But, depending on the venue, and looking at Morgan’s policies, he allows videoing, not sure about the venue though. Why chuck the phone? 🤯 Do you think the security guard is to blame or do you think Morgan was just acting like a jerk by tossing that fan’s phone?show more

Goodluck to those competing in day 4 of closed... quali for gc. So many great teams and I’m excited to see the matches and who makes it out of their pods. With a lot being on the line today for each team I hope no matter the result you are all able to have no regrets at the end!show more

For 6 months I woke up at 5 AM... to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:show more

The Eagles certainly loved their marine concepts on Drive... #4. 3 different variations — Fish (Guppie), Bass, and Ocean — of the same inside-out LB squeeze read, all work about as well as you’d expect. I have my own diagrams of these with the reads laid out for Covers 1-5, FZ, and 3x1 concepts but can’t get them to load.show more

1. I thought this was a direct response not... a public post 2. I didn’t know it was a video thought it was a picture 3. The note is backwards 4. No one believes it’s actually me for some reason 5. Follow me pls @ _ chipfatshow more

I built a PDF compression tool instead of paying... for it. It's funny because the more I get into AI, the more I realize how much I've stopped spending on SaaS subscriptions. Here are 5 things I used to pay for: 1/ PDF Compression → $9/mo 2/ Remove BG → $35/mo 3/ Typefully → $12.5/mo 4/ Link Shortener → $10/mo 5/ Color Palette Generator → $5/mo I've already replaced half of these with AI, and they're way better because they are personal and custom. No weird features or ads. Everything is hosted locally so I'm not uploading my data to random servers. I truly believe AI is changing the way we interact with SaaS entirely. More and more people will just build their own tools instead of purchasing generic subscriptions. It's easier because you just tell AI what problem you have, and it automatically comes up with a custom solution for you. I am already starting doing it. In a few months, I'll have my own "Home" hub where I have a bunch of custom apps working for me. All powered by AI. Pretty exciting!show more

This is a question I think quite a lot... of people are wondering about. Right now, I’m hiring students to handle the newer phones, post content, and create content every day. For the TikTok accounts that are already trusted, have been running for a long time, and have a high follower count, I automate them using my own internal tools. Currently, I only handle the first steps myself: buying new phones → warming them up → making the first posts. After that, I hand the phones over to the students I hire to continue creating and posting content. Then, once I feel the accounts are strong enough, I move them into automation. And right now, I’m traveling with my family in Da Nang. This time I’m here with my family and want to spend all my time with them, so I won’t be meeting anyone while I’m here. 🏝️ I always aim to build everything in an automated way, or avoid doing things I don’t enjoy by hiring people to handle them for me.😌show more

I just want to take a moment to say... thank you to everyone. We fight, we argue, and I know some of you get mad at my tweets sometimes🤣🤣 but at the end of the day, it's all love, no hate. I truly appreciate each and every one of you for sticking around and for your support. Thanksgiving is all about gratitude and today l'm feeling extra grateful for all of you. Let's keep lifting each other up even when we don't always agree and we don’t need to agree🤣🤣 I'm ending this thanksgiving with love in my heart, and I want you to know I love you all❣️ #Grateful #Thanksgivingshow more

Meloni - So here, you can see the main... part of Rome. Almost all is visible here in Rome. Hundreds and hundreds of churches here. From here, I can count: 1 2 3 4 5 6 7 8 9... Vishwaguru - Khikhi khikhi khikhi khikhi Khikhi khikhi.. 🤷‍♂️show more

🚨UPSET ALERT🚨 Arkansas Tech Baseball takes down No.3 UCM... in extras by the score of 4-3! Sawyer Duddleston and Cole Dawson had 2 hits each. Jack Rector allowed just 3 hits and a run with 8 Ks over 5. The Arkansas Tech bullpen gave up just 2 hits and 1 earned run in their 7 innings of work. Doubleheader scheduled for tomorrow, we'll see who comes out on top. #D2Baseballshow more

I went from ZERO($0) to 5 figures in less... than 5 months The year 2024 was a defining year for me and a lot of my friends. This story is one I should have told since but was waiting for the right time It all began in August after losing a cumulative of $20,000. That was literally all I had left with me and was down to less than $300. They say it all begins when you are down to your last 1 million and funny how I didn't even have up to a million Over the course of several days I began asking myself questions as to what I would have done with the money. I could have given my parent their dream house or gotten a car for myself, my mum and started my Agric business. Well, that was how Anxiety started with heavy palpitations and a pulse of 130 Not to bore you, allow me explain step by step as to how I bounced back 1) God - I wont lie to you, God and Prayers are very important in this WEB3. We have very few Normal people on here as this space is toxic enough to destroy you and your mental health 2) Network - See, I know all your idolos are telling you to grind hard which is factually correct but the real profits in this life are from who you know. Check SAYRAAH #WID 📈📉📊 content on networking for more information 2) Excellence - One little lesson I've learned from life is that excellence in itself is not restricted to a particular sphere but its a way of life. I strongly believe the reason all my clients refer me like their lives depend on it is because I handle my job with a unique style of excellence. Starting from my personal page to my clients jobs and even mannerisms 3) Hard work - This aspect has been misused so much. Hard work although very vital must be accompanied with a lot of smart work for you to have results. Scripture shows us that there is a possibility for two people to engage in similar work while they get different result. The one with the smaller result was termed a FOOLISH MAN and the one with better results was called a WISE MAN. The difference is in the knowing, you need to learn how to actually work hard 4) Voice out - Make sure you always voice out when you are not doing as much as you are supposed to. I have a lot of my guys that I tell intricate stuffs about my money-making journey and everyone puts heads together to ensure we all make money I might sound like aspire to perspire but the reality is, bouncing back is difficult but I want you to know that your hard work will eventually pay off I could have just said GOD DID but I know there's someone out there that might need this. Don't stop and don't settle, your future will thank you for it Over the next few days, I would be sharing some opportunities I recently found that I'm sure will print you money. Stay gluedshow more

Batch Normalization by hand ✍️ ~ 7 steps walkthrough... below Batch normalization is common practice for improving training and achieving faster convergence. It sounds simple. But it is often misunderstood. 🤔 Does batch normalization involve trainable parameters, tunable hyper-parameters, or both? 🤔 Is batch normalization applied to inputs, features, weights, biases, or outputs? 🤔 How is batch normalization different from layer normalization? So I drew and calculated one entirely by hand. Goal: normalize a mini-batch of 4 examples to mean 0 and variance 1, then let the network scale it back. = 1. Given = A mini-batch of 4 training examples, each with 3 features. = 2. Linear layer = Let us multiply by the weights and add the biases. Batch norm sits after this, which answers the second question: what gets normalized is features, not inputs, weights or biases. = 3. ReLU = We apply the activation, and -2 becomes 0. Negative values are suppressed before any statistic is taken. = 4. Batch statistics = Let us compute the sum, mean, variance and standard deviation, one row at a time. A row is a feature and the four columns are the four examples, so every number here measures one feature against the rest of the batch. That is the "batch" in batch normalization, and it is exactly what layer normalization does not do. The statistics are rounded to whole numbers, which is what keeps the rest of the page doable in pen. = 5. Shift to mean 0 = We subtract the mean, in green. The four values in each feature now average to zero. = 6. Scale to variance 1 = Let us divide by the standard deviation, in orange. Each feature now has variance one, whatever scale it arrived at. = 7. Scale and shift = We multiply by a linear transformation and pass the result on. The diagonal and the last column are trainable, so having just forced every feature to mean 0 and variance 1, we hand the network the means to undo it. The outputs: Mean of each feature = [2, 1, 2] Std dev of each feature = [1, 1, 2] To the next layer = [2, -2, 2, 0], [-3, 3, 6, -3], [2, 0, 1, 2] The answers: 🤔 Both. The scale and shift are trainable, the statistics are not. Epsilon and the momentum on the running statistics are the hyper-parameters, and one mini-batch by hand needs neither. 🤔 Features, after the linear layer, not inputs, weights or biases. 🤔 Batch norm measures across the batch, one feature at a time. Layer norm measures across the features, one example at a time. 💾 Save this post!show more