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Want to reverse the source of a JS app? Typical unminifiers struggle with statement sequencing, JSX lowering, and other bundler/minifier shenanigans like (0, m.f)(xx) Pionxzh's Wakaru unpacks modules, formats the code, then runs AST transforms to recover intent, recovering readability where possible. Demo video 👇

Herrington Darkholme

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11,570 views • 4 months ago •via X (Twitter)

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This app has racked 500K installs using this UGC format. This is one of the best app growth strategies I’ve seen by this language fluency ai app. The video got 9.9M views 990K likes The app is doing: $500K MRR $6M ARR With formats like: “why tf is English so hard 🥀” …then seamlessly transitions into the app demo. I studied and reverse-engineered all of their UGC and content marketing strategies. Then I built a complete UGC system that lets you replicate the same growth framework, create viral concepts consistently, and scale your app much faster without guessing what to post. If you want to know how they grew so quickly and replicate their success… Comment “VIRAL” and I’ll send the full guide (must be following so I can DM).

This app has racked 500K installs using this UGC format. This is one of the best app growth strategies I’ve seen by this language fluency ai app. The video got 9.9M views 990K likes The app is doing: $500K MRR $6M ARR With formats like: “why tf is English so hard 🥀” …then seamlessly transitions into the app demo. I studied and reverse-engineered all of their UGC and content marketing strategies. Then I built a complete UGC system that lets you replicate the same growth framework, create viral concepts consistently, and scale your app much faster without guessing what to post. If you want to know how they grew so quickly and replicate their success… Comment “VIRAL” and I’ll send the full guide (must be following so I can DM).

Daniel

16,811 views • 1 month ago

This app has raked 79.5M installs and 415K paying users with this UGC format This is one of the best app ideas I’ve ever seen This video got 7.2M views The app is doing $38.2K per day $1.15M per month $13.7M per year With formats like this “I found a way to interact with my long distance sister” then shows app demo I studied & researched all thier UGC and content marketing strategies and format. If you want to know how they did it in a short period of time and replicate thier success Comment “VIRAL” and I’ll send the full guide (must be following so I can DM)

This app has raked 79.5M installs and 415K paying users with this UGC format This is one of the best app ideas I’ve ever seen This video got 7.2M views The app is doing $38.2K per day $1.15M per month $13.7M per year With formats like this “I found a way to interact with my long distance sister” then shows app demo I studied & researched all thier UGC and content marketing strategies and format. If you want to know how they did it in a short period of time and replicate thier success Comment “VIRAL” and I’ll send the full guide (must be following so I can DM)

Daniel

75,677 views • 2 months ago

Building SPA-like experiences with Next.js (6) You can lose connection mid-session and your app waits it out, then picks back up the moment you reconnect. With the experimental (!) 𝚞𝚜𝚎𝙾𝚏𝚏𝚕𝚒𝚗𝚎 flag, a failed navigation, fetch, or Server Action stays pending instead of throwing, then retries automatically. The 𝚞𝚜𝚎𝙾𝚏𝚏𝚕𝚒𝚗𝚎() hook lets you show a reconnecting bar while it waits. Because Partial Prefetching keeps the App Shell on the client, you always have something to show offline. And, if a route's content was prefetched, that's available too. Live demo, source code, and docs below ↓

Building SPA-like experiences with Next.js (6) You can lose connection mid-session and your app waits it out, then picks back up the moment you reconnect. With the experimental (!) 𝚞𝚜𝚎𝙾𝚏𝚏𝚕𝚒𝚗𝚎 flag, a failed navigation, fetch, or Server Action stays pending instead of throwing, then retries automatically. The 𝚞𝚜𝚎𝙾𝚏𝚏𝚕𝚒𝚗𝚎() hook lets you show a reconnecting bar while it waits. Because Partial Prefetching keeps the App Shell on the client, you always have something to show offline. And, if a route's content was prefetched, that's available too. Live demo, source code, and docs below ↓

Aurora Scharff

17,420 views • 1 month ago

NEED SUGGESTIONS for community, do drop in your suggestions😊 We are trying to improve the readability of articles. At present most of the blog DSA sites have lengthy articles which you read via scrolling. It looks daunting when you start with it. At TakeUforward, we are trying to change this, and help out users with an easier way to navigate and read. We want the logic to be something as you can see in the video.. the design is just a rough one, and is no where close to what we want it to be. The typical article will have problem statement, examples, followed by this sticky bar, which helps us to navigate, and ease out reading.. You can feel free to suggest more changes we can do, or some design recommendations. We can hire someone for this, but I will prefer recommendations from people who use it rather than someone who does not. RT for good Karma ♥️

NEED SUGGESTIONS for community, do drop in your suggestions😊 We are trying to improve the readability of articles. At present most of the blog DSA sites have lengthy articles which you read via scrolling. It looks daunting when you start with it. At TakeUforward, we are trying to change this, and help out users with an easier way to navigate and read. We want the logic to be something as you can see in the video.. the design is just a rough one, and is no where close to what we want it to be. The typical article will have problem statement, examples, followed by this sticky bar, which helps us to navigate, and ease out reading.. You can feel free to suggest more changes we can do, or some design recommendations. We can hire someone for this, but I will prefer recommendations from people who use it rather than someone who does not. RT for good Karma ♥️

Striver | Building takeUforward

13,937 views • 3 years ago

Code Interpreter in ChatGPT is incredible! Took me 5 mins to make this game. You can make your own game assets with any AI generator and then ask GPT-4 with Code Interpreter to write code. If you have any problems you can ask it to fix the errors. 1. Write this prompt: "write p5.js code for Asteroids where you control a spaceship with the mouse and shoot asteroids with the left click of the mouse. If your spaceship collides with an asteroid, you lose. If you shoot down all asteroids, you win! I want to use my own textures for the spaceship and for asteroids." 2. Go to Openprocessing website create and save sketch (you'll need to save it before uploading any texture files). Copy paste code from GPT-4 3. Generate texture files and remove backgrounds, for example in Clip Drop 4. Replace names of files with your filenames 5. Run the program 6. If something doesn't work ask GPT-4 to fix it (you can copy an error and paste in GPT-4) like you would ask a human programmer 7. To learn a bit of programming write these prompts to GPT-4: "Act as my programming teacher. Tell me an algorithm of Asteroids game in detail and make names of functions and explain what each of these functions will do. Don't write the code just yet." and then " Can you describe the algorithm overall for a 10-year-old child"

Code Interpreter in ChatGPT is incredible! Took me 5 mins to make this game. You can make your own game assets with any AI generator and then ask GPT-4 with Code Interpreter to write code. If you have any problems you can ask it to fix the errors. 1. Write this prompt: "write p5.js code for Asteroids where you control a spaceship with the mouse and shoot asteroids with the left click of the mouse. If your spaceship collides with an asteroid, you lose. If you shoot down all asteroids, you win! I want to use my own textures for the spaceship and for asteroids." 2. Go to Openprocessing website create and save sketch (you'll need to save it before uploading any texture files). Copy paste code from GPT-4 3. Generate texture files and remove backgrounds, for example in Clip Drop 4. Replace names of files with your filenames 5. Run the program 6. If something doesn't work ask GPT-4 to fix it (you can copy an error and paste in GPT-4) like you would ask a human programmer 7. To learn a bit of programming write these prompts to GPT-4: "Act as my programming teacher. Tell me an algorithm of Asteroids game in detail and make names of functions and explain what each of these functions will do. Don't write the code just yet." and then " Can you describe the algorithm overall for a 10-year-old child"

Kris Kashtanova

1,675,286 views • 3 years ago

one of my favorite ways to use claude code skills right now - combining remotion with claude-in-chrome for motion video creation. the workflow is addictive. the clip you see here was produced with minimal prompting effort let me know if you would like me to write a full break down of this process. you describe to claude code what you want, claude code writes the remotion components, opens the remotion studio (via browser) with claude-in-chrome, sees the actual rendered output, and iterates on it in real time. need the arrows pointing to the center of the bubbles instead of the edge? just say it. need the layout shifted to the center? say it. claude sees the preview, adjusts the code, re-renders. then when you're happy you tell claude code to render the final video. but skills are what make this possible. remotion knowledge + browser automation + the taste to iterate visually. no copy pasting screenshots back and forth. no "can you try moving it 10px to the right" over chat. it just looks and fixes. this is the kind of workflow that makes you realize how much further claude code can go beyond just writing code in a terminal. i didn't touch any code while working on the clip you see if you haven't tried combining skills together like this - start experimenting. the skills combos is where the magic is at.

one of my favorite ways to use claude code skills right now - combining remotion with claude-in-chrome for motion video creation. the workflow is addictive. the clip you see here was produced with minimal prompting effort let me know if you would like me to write a full break down of this process. you describe to claude code what you want, claude code writes the remotion components, opens the remotion studio (via browser) with claude-in-chrome, sees the actual rendered output, and iterates on it in real time. need the arrows pointing to the center of the bubbles instead of the edge? just say it. need the layout shifted to the center? say it. claude sees the preview, adjusts the code, re-renders. then when you're happy you tell claude code to render the final video. but skills are what make this possible. remotion knowledge + browser automation + the taste to iterate visually. no copy pasting screenshots back and forth. no "can you try moving it 10px to the right" over chat. it just looks and fixes. this is the kind of workflow that makes you realize how much further claude code can go beyond just writing code in a terminal. i didn't touch any code while working on the clip you see if you haven't tried combining skills together like this - start experimenting. the skills combos is where the magic is at.

elvis

46,494 views • 6 months ago

The pilot was unable to recover the aircraft from the roll, and by the time he realized what was happening, he was already too close to the ground. If the jet had a higher thrust-to-weight ratio, it might have had a better chance of recovering. Delta wings rely heavily on high angles of attack to generate lift at low speeds. This results in: High induced drag Significant vortex drag Rapid energy loss during turns Keeping the nose up to maintain a high angle of attack also reduces the pilot’s ability to see the ground, limiting situational awareness. Altitude warnings are then the primary source of awareness, but during airshows pilots often disregard these alerts because they know they will be performing low-altitude maneuvers. This is one reason we saw no ejection from the Tejas. Being at low speed, low altitude, in an under powered jet, operating a delta-wing aircraft under high drag and vortex drag, and having the nose slightly up, thereby reducing forward and downward visibility, means the flawed design of Indian Tejas contributed to the Tejas crash. I have frame freezed in the video where any other jet would have successfully got out of this roll but Tejas crashed. The machine betrayed the man and a pilot was lost. I will place the blame of Tejas crash on politics and designers.

The pilot was unable to recover the aircraft from the roll, and by the time he realized what was happening, he was already too close to the ground. If the jet had a higher thrust-to-weight ratio, it might have had a better chance of recovering. Delta wings rely heavily on high angles of attack to generate lift at low speeds. This results in: High induced drag Significant vortex drag Rapid energy loss during turns Keeping the nose up to maintain a high angle of attack also reduces the pilot’s ability to see the ground, limiting situational awareness. Altitude warnings are then the primary source of awareness, but during airshows pilots often disregard these alerts because they know they will be performing low-altitude maneuvers. This is one reason we saw no ejection from the Tejas. Being at low speed, low altitude, in an under powered jet, operating a delta-wing aircraft under high drag and vortex drag, and having the nose slightly up, thereby reducing forward and downward visibility, means the flawed design of Indian Tejas contributed to the Tejas crash. I have frame freezed in the video where any other jet would have successfully got out of this roll but Tejas crashed. The machine betrayed the man and a pilot was lost. I will place the blame of Tejas crash on politics and designers.

Irves

310,169 views • 9 months ago

CCleaner used to be the default way to keep a Windows machine fast. Then it got bought, stuffed with ads and bundled crapware, and in 2017 one release was compromised and shipped malware to over 2 million people. Millions still install it every month because nothing else has really replaced it. So, a team called AdventDev just built a free, open-source replacement. It's called Kudu. Open the app and you get one dashboard for the whole machine. > System cleaner for temp files, logs, caches, and crash dumps. > Browser cleaner across every major browser. > Gaming cleaner for launcher and shader caches. > Registry cleaner for broken and orphaned entries. > Startup manager that shows the actual boot impact of each program. > Disk analyzer with an interactive treemap, so you can see where 40GB quietly disappeared to. > Debloater that rips Windows bloatware out. > Program uninstaller that also removes the leftovers other uninstallers leave behind. Then it does the parts CCleaner never did. A malware scanner with signature matching, heuristic analysis, and Windows Defender integration. A privacy shield that lets you flip 30+ Windows privacy settings from one screen: telemetry, ad ID, Cortana, tracking. Secure delete that overwrites files with random data before removing them, so nothing can recover them later. There's a real-time performance monitor with per-core CPU, memory, disk, network, and S.M.A.R.T. drive health. A one-click restore point before every clean, so you can roll back. Scheduled scans. A CLI mode for people who don't want a GUI. Support for 30 languages. Native app for Windows, macOS, and Linux. Intel and Apple Silicon builds. No ads, no upsells, no telemetry, no account. The cleaning rules are plain JSON files, so if your favorite app isn't covered yet, you can add support for it without writing a line of code. MIT license. 100% Open Source. Repo:

CCleaner used to be the default way to keep a Windows machine fast. Then it got bought, stuffed with ads and bundled crapware, and in 2017 one release was compromised and shipped malware to over 2 million people. Millions still install it every month because nothing else has really replaced it. So, a team called AdventDev just built a free, open-source replacement. It's called Kudu. Open the app and you get one dashboard for the whole machine. > System cleaner for temp files, logs, caches, and crash dumps. > Browser cleaner across every major browser. > Gaming cleaner for launcher and shader caches. > Registry cleaner for broken and orphaned entries. > Startup manager that shows the actual boot impact of each program. > Disk analyzer with an interactive treemap, so you can see where 40GB quietly disappeared to. > Debloater that rips Windows bloatware out. > Program uninstaller that also removes the leftovers other uninstallers leave behind. Then it does the parts CCleaner never did. A malware scanner with signature matching, heuristic analysis, and Windows Defender integration. A privacy shield that lets you flip 30+ Windows privacy settings from one screen: telemetry, ad ID, Cortana, tracking. Secure delete that overwrites files with random data before removing them, so nothing can recover them later. There's a real-time performance monitor with per-core CPU, memory, disk, network, and S.M.A.R.T. drive health. A one-click restore point before every clean, so you can roll back. Scheduled scans. A CLI mode for people who don't want a GUI. Support for 30 languages. Native app for Windows, macOS, and Linux. Intel and Apple Silicon builds. No ads, no upsells, no telemetry, no account. The cleaning rules are plain JSON files, so if your favorite app isn't covered yet, you can add support for it without writing a line of code. MIT license. 100% Open Source. Repo:

Brady Long

149,822 views • 1 month ago

The entire timeline is filled with talks on sentient and all, but I love being as informative and precise as possible on pressing issues. Let’s quickly talk about @SentientAGI’s Recursive Open Meta Agent (ROMA); ROMA is an open-source meta-agent framework used to build high performance multi-agent systems. ROMA serves as the conductor in a mass choir, or a captain of a ship . The captain gives commands for the other subordinates to follow to ensure efficiency on all sides. In this like manner, it provides a hierarchical tress system where the parent agents break down complex tasks to create simpler subtasks that are then passed on to children nodes. A family tree has the parents above, likewise the same tree analogy works here, but that’s not all that makes it stand out The results and solutions gotten by these child nodes are then aggregated together and there’s an up flow of results sent back up to the parent nodes. And at the center of it all is ROMA engineering and making sure all is running smoothly without break or fail. Are you really bullish on Sentient and the future of AGIs?

The entire timeline is filled with talks on sentient and all, but I love being as informative and precise as possible on pressing issues. Let’s quickly talk about @SentientAGI’s Recursive Open Meta Agent (ROMA); ROMA is an open-source meta-agent framework used to build high performance multi-agent systems. ROMA serves as the conductor in a mass choir, or a captain of a ship . The captain gives commands for the other subordinates to follow to ensure efficiency on all sides. In this like manner, it provides a hierarchical tress system where the parent agents break down complex tasks to create simpler subtasks that are then passed on to children nodes. A family tree has the parents above, likewise the same tree analogy works here, but that’s not all that makes it stand out The results and solutions gotten by these child nodes are then aggregated together and there’s an up flow of results sent back up to the parent nodes. And at the center of it all is ROMA engineering and making sure all is running smoothly without break or fail. Are you really bullish on Sentient and the future of AGIs?

OHJAY ⭕️ || 🇬🇧

23,521 views • 11 months ago

This app uses AirDrop to send files from your Android phone to your Macbook! Yes, it actually uses AirDrop. That means you don't have to install ANYTHING on your Mac to send files from your Android phone! Here's a video of a Galaxy Z Flip 5 AirDropping a file to a Macbook running macOS Ventura 13.5.1. (Thanks to u/FragmentedChicken for testing this app for me and sharing the video!) A few months ago, Twitter user @Linus13499209 brought an app called WarpShare to my attention. WarpShare is an app made by the developers of MoKee, an AOSP-based custom ROM that was popular in China. Since MoKee wasn't as popular outside of China, it seems the existence of their WarpShare app slipped under the radar. I was skeptical about whether it would work at all. Grishka, the developer of NearDrop, an open source port of Google's Nearby Share to macOS, told me that they were under the assumption that AirDrop requires the use of AWDL (Apple Wireless Direct Link, Apple's proprietary WiFi-based protocol) to communicate both ways. However, it seems that AWDL is only required for your Android phone to be discoverable by your Mac (ie. to send files from your Mac to your Android phone) but not the other way around. Because of this, though, WarpShare only supports sending files from Android to Mac but not vice versa. Your Mac also needs to have AirDrop discoverability set to "everyone" for this to work, as "contacts-only" requires Apple-signed certificates. Plus, it also doesn't support sending files from Android to iPhones or iPads, even when "everyone" mode is enabled. Still, if you find other Android --> Mac file sharing options to be lackluster, give WarpShare a try! The fact that it works at all is incredible, which is why I'm sharing this news here. If you want to download WarpShare on your Android device, you'll need to compile the app from its source code. If you're a Patron/X subscriber, however, I will share my compiled APK with you. WarpShare source code:

This app uses AirDrop to send files from your Android phone to your Macbook! Yes, it actually uses AirDrop. That means you don't have to install ANYTHING on your Mac to send files from your Android phone! Here's a video of a Galaxy Z Flip 5 AirDropping a file to a Macbook running macOS Ventura 13.5.1. (Thanks to u/FragmentedChicken for testing this app for me and sharing the video!) A few months ago, Twitter user @Linus13499209 brought an app called WarpShare to my attention. WarpShare is an app made by the developers of MoKee, an AOSP-based custom ROM that was popular in China. Since MoKee wasn't as popular outside of China, it seems the existence of their WarpShare app slipped under the radar. I was skeptical about whether it would work at all. Grishka, the developer of NearDrop, an open source port of Google's Nearby Share to macOS, told me that they were under the assumption that AirDrop requires the use of AWDL (Apple Wireless Direct Link, Apple's proprietary WiFi-based protocol) to communicate both ways. However, it seems that AWDL is only required for your Android phone to be discoverable by your Mac (ie. to send files from your Mac to your Android phone) but not the other way around. Because of this, though, WarpShare only supports sending files from Android to Mac but not vice versa. Your Mac also needs to have AirDrop discoverability set to "everyone" for this to work, as "contacts-only" requires Apple-signed certificates. Plus, it also doesn't support sending files from Android to iPhones or iPads, even when "everyone" mode is enabled. Still, if you find other Android --> Mac file sharing options to be lackluster, give WarpShare a try! The fact that it works at all is incredible, which is why I'm sharing this news here. If you want to download WarpShare on your Android device, you'll need to compile the app from its source code. If you're a Patron/X subscriber, however, I will share my compiled APK with you. WarpShare source code:

Mishaal Rahman

1,290,491 views • 3 years ago

A good technical LLM interview question: Your LLM chatbot takes 12s before it generates the first token, and the users are complaining. So you move the model onto a GPU with 3x the computing power. The time to first token barely improves. Why did this happen? (answer below) Latency in an LLM app is a placement problem disguised as a model problem. If you profile the 12 seconds, the model's prefill itself may only account for around 1.5 seconds of it. So halving the prefill step saves just 750ms out of 12000, which is under 7%. The rest is spread across stages that never touch the GPU. The request first travels to whatever region the app runs in, and a cross-continent round trip could cost over a second before any code executes. Then the request handler starts. On a container-based serverless platform under load, this adds several seconds of cold start, paid before auth, rate limiting, or prompt assembly even begins. Retrieval adds its own hop, and the response streams back across the same distance. Optimizing a stage that was already fast cannot alter the latency that's majorly affected by other stages. Those other stages are slow for a structural reason. An LLM app runs two workloads that want opposite machines. - The request path is short, spiky, and needs to sit close to users - Inference is long-running, GPU-bound, and billed hourly, whether requests arrive or not. So the actual decision is not which model to run, but where each of these two workloads runs. There are three options, each with its own tradeoffs: > A dedicated GPU box removes inference cold starts, but it bills around the clock and lives in one location, so distant users wait out the round trip on every request > Container-based serverless scales to zero, but the request path pays a cold start, and most of these platforms have no GPU behind them. > Edge runtimes start in under a millisecond, because a WebAssembly module carries no OS or container image to boot. They handle the request path well and cannot hold a model. So the answer is not to pick one, but to split the app across two of them. The request path runs close to users, and inference runs on a dedicated GPU it calls into. That also explains the failed upgrade. More compute made a stage that was already fast faster, and left the 10.5 seconds around it untouched. To actually learn how it's done in practice, Akamai's GitHub has a reference implementation for each half. - vllm-on-lke serves Qwen2.5-7B-Instruct behind an OpenAI-compatible endpoint on one RTX 4000 Ada GPU in Linode Kubernetes Engine, with Terraform creating the cluster, both firewalls, and the GPU operator in one apply. - akamai-functions-llm-chatbot covers the front, where a WebAssembly API checks a KV cache and only calls the GPU-backed instance on a miss. Both are available on Akamai’s new Developer Hub, alongside their tutorials and code samples. It also links to Edge Case, their Discord, where four developer advocates architect and deploy a production app live every other Wednesday. If you create a new Akamai Cloud account, you can also get $300 in credits for joining. Join here: That said, this post treats generation as a single 1.5s block, but that block has its own structure, and knowing it well tells you whether a model is slow to start or slow to stream. I wrote a first-principles walkthrough of it, covering the prefill and decode split, KV caching, and where the time actually goes inside each one. Read it below. Thanks to Akamai Cloud for partnering today!

Avi Chawla

21,423 views • 17 days ago

ANTHROPIC'S LEAD ENGINEER ACCIDENTALLY LEAKED HIS PERSONAL OBSIDIAN VAULT. INSIDE - NO CODE, NO PROMPTS. JUST A SCHEMATIC OF HIS OWN MIND, BUILT LIKE A NEURAL NETWORK 8,893 nodes. 4,729 links. A $10-a-month app opens Obsidian. 21 inputs, 10+ hidden layers, ReLU activation. First layer 64 neurons, then 37, then 22, all the way to the output. Thousands of connections firing in real time this isn't a concept diagram from a blog - it's a living brain that actually runs decisions inside the company. 9,000 documents, each its own knowledge space, all interconnected he makes around $2M a year for putting markdown files into the right folders. The company building the best AI in the world manages its internal knowledge with the same app a college freshman uses for lecture notes. hasn't written a single line of infrastructure for any of it. three years of discipline and one open Obsidian tab you're reading this on a device where you could open the same Obsidian tonight and start building your own vault

ANTHROPIC'S LEAD ENGINEER ACCIDENTALLY LEAKED HIS PERSONAL OBSIDIAN VAULT. INSIDE - NO CODE, NO PROMPTS. JUST A SCHEMATIC OF HIS OWN MIND, BUILT LIKE A NEURAL NETWORK 8,893 nodes. 4,729 links. A $10-a-month app opens Obsidian. 21 inputs, 10+ hidden layers, ReLU activation. First layer 64 neurons, then 37, then 22, all the way to the output. Thousands of connections firing in real time this isn't a concept diagram from a blog - it's a living brain that actually runs decisions inside the company. 9,000 documents, each its own knowledge space, all interconnected he makes around $2M a year for putting markdown files into the right folders. The company building the best AI in the world manages its internal knowledge with the same app a college freshman uses for lecture notes. hasn't written a single line of infrastructure for any of it. three years of discipline and one open Obsidian tab you're reading this on a device where you could open the same Obsidian tonight and start building your own vault

chewa

1,210,811 views • 2 months ago

At the age of thirteen, in the late 1940s, Thomas Fogarty, newly bereft of his father, found himself employed at Cincinnati’s Good Samaritan Hospital, sorting supplies and learning the rhythms of the place from the ground up. With time and a certain doggedness, he moved from the stockroom to the operating room, working his way up to the role of scrub technician, where he stood at the surgeon’s elbow, handing over instruments. Back then, the approach to removing blood clots from an artery was crude and perilous. It was a bit like a ritual sacrifice—that involved slicing the artery wide open in a procedure that could easily stretch over nine hours and leave the patient with incisions from the abdomen down both legs. The outcome, more often than not, was dismal. Many didn’t survive, many others ended up with amputations. It was during those hours at the operating table, observing the struggle of clot removal, that Fogarty began to wonder if there might be a way to make the process a bit less medieval. He retreated to his garage with little more than a length of tubing, a surgical glove, and an idea. There, he crafted a tool so simple that it verged on the audacious. He started with a urethral catheter, flexible yet sturdy enough to navigate through a clot. To the end of the catheter, he attached a tiny balloon made from the finger of a latex glove. Once past the clot, the balloon could be inflated with saline from the other end of the tube, expanding it to the width of the artery and then pulled back—bringing the clot along with it. The device was so simple, so staggeringly clever, that when he demonstrated its use, the surgeons were equal parts gobsmacked and irritated. With it, clot removal (embolectomy) was no longer a barbaric ritual but a neat, almost gentlemanly procedure. Like removing a cork from a bottle. Thomas Fogarty went on to become a cardiovascular surgeon. That little embolectomy catheter he dreamt up became the very first minimally invasive surgical device. Here’s a video showing how it’s done: through a small incision in the groin, under local anesthesia.

At the age of thirteen, in the late 1940s, Thomas Fogarty, newly bereft of his father, found himself employed at Cincinnati’s Good Samaritan Hospital, sorting supplies and learning the rhythms of the place from the ground up. With time and a certain doggedness, he moved from the stockroom to the operating room, working his way up to the role of scrub technician, where he stood at the surgeon’s elbow, handing over instruments. Back then, the approach to removing blood clots from an artery was crude and perilous. It was a bit like a ritual sacrifice—that involved slicing the artery wide open in a procedure that could easily stretch over nine hours and leave the patient with incisions from the abdomen down both legs. The outcome, more often than not, was dismal. Many didn’t survive, many others ended up with amputations. It was during those hours at the operating table, observing the struggle of clot removal, that Fogarty began to wonder if there might be a way to make the process a bit less medieval. He retreated to his garage with little more than a length of tubing, a surgical glove, and an idea. There, he crafted a tool so simple that it verged on the audacious. He started with a urethral catheter, flexible yet sturdy enough to navigate through a clot. To the end of the catheter, he attached a tiny balloon made from the finger of a latex glove. Once past the clot, the balloon could be inflated with saline from the other end of the tube, expanding it to the width of the artery and then pulled back—bringing the clot along with it. The device was so simple, so staggeringly clever, that when he demonstrated its use, the surgeons were equal parts gobsmacked and irritated. With it, clot removal (embolectomy) was no longer a barbaric ritual but a neat, almost gentlemanly procedure. Like removing a cork from a bottle. Thomas Fogarty went on to become a cardiovascular surgeon. That little embolectomy catheter he dreamt up became the very first minimally invasive surgical device. Here’s a video showing how it’s done: through a small incision in the groin, under local anesthesia.

Ambarish Satwik

49,730 views • 1 year ago

INTRODUCTION TO THE STOCK MARKET The stock market is a place where individuals and institutions buy and sell ownership in companies (called shares or stocks). When you buy a share, you’re essentially buying a small piece of that company and participating in its growth, profits, and risks. People invest in the stock market to grow wealth over time, earn dividends, protect against inflation, and build long-term financial security. Unlike short-term trading, investing focuses on patience, discipline, and owning quality businesses. --- INTRODUCTION TO THE NIGERIAN STOCK MARKET (NGX) The Nigerian Exchange Group (NGX) is Nigeria’s official stock exchange, where publicly listed Nigerian companies trade their shares. It hosts banks, telecoms, industrial firms, consumer goods companies, oil & gas firms, and more. Through the NGX, everyday Nigerians can own parts of companies like banks, manufacturing firms, telecom operators, and other major businesses driving the economy. Returns come from: Capital appreciation (share price increases) Dividends (cash payouts from profits) The NGX is regulated, structured, and accessible to both local and foreign investors through licensed platforms. --- HOW TO GET STARTED INVESTING IN NGX (TWO SIMPLE WAYS) Today, you don’t need to walk into a stockbroking office. You can get started fully online using digital investment platforms. Below are two popular and easy options that I personally use; --- 1) GETTING STARTED WITH BAMBOO Bamboo Bamboo is a digital investment app that allows Nigerians to invest in Nigerian stocks (NGX) and foreign stocks. Steps to get started: 1. Download the Bamboo app from the App Store or Google Play. 2. Create an account with your email and phone number. 3. Complete KYC verification Input your BVN Provide personal details 4. Fund your wallet via bank transfer. 5. Search for Nigerian stocks listed on NGX and place your first buy order. 👉 Referral code: ngxinvestor Bamboo is beginner-friendly and suitable for people who want a simple interface and access to both local and global markets. When done with registration to buy stocks on Bamboo,select the " Invest " icon on the bottom part of the screen,you will see that you can invest in USD or Naira assets,click on Naira,then select NG stocks,search for the stock of your choice and buy --- 2) GETTING STARTED WITH I-INVEST i-invest I-Invest is an official platform that allows Nigerians to invest in Nigerian stocks, Commercial Papers,Mutual Funds,USD Bonds etc... Steps to get started: 1. Visit the I-Invest website or download the app on App Store or Google Play. 2. Create an account 3. Complete required KYC documentation: BVN Valid ID Bank details Proof of Address etc... 4. Fund your account. 5. Start buying NGX-listed stocks directly through the app. 👉 Referral code: 22406 I-Invest is ideal for investors who want more Investment options because you can also invest in fixed deposit notes, commercial papers,USD Bonds ,life insurance etc.. After registration to buy shares ,click on " Invest " then select " Equities " ,then search the company of your choice then select "buy equities" --- FINAL NOTES FOR BEGINNERS Start small and grow with experience. Focus on learning before chasing quick profits. Invest in businesses you understand. Think long-term, not overnight success. The most important step is starting — clarity and confidence come with time and consistency. The first video is for bamboo Bamboo The second video is for I-Invest i-invest Please if anyone has any more questions please comment and I'll try to reply,and if you can DM I'll appreciate if you guys can use my referral codes

INTRODUCTION TO THE STOCK MARKET The stock market is a place where individuals and institutions buy and sell ownership in companies (called shares or stocks). When you buy a share, you’re essentially buying a small piece of that company and participating in its growth, profits, and risks. People invest in the stock market to grow wealth over time, earn dividends, protect against inflation, and build long-term financial security. Unlike short-term trading, investing focuses on patience, discipline, and owning quality businesses. --- INTRODUCTION TO THE NIGERIAN STOCK MARKET (NGX) The Nigerian Exchange Group (NGX) is Nigeria’s official stock exchange, where publicly listed Nigerian companies trade their shares. It hosts banks, telecoms, industrial firms, consumer goods companies, oil & gas firms, and more. Through the NGX, everyday Nigerians can own parts of companies like banks, manufacturing firms, telecom operators, and other major businesses driving the economy. Returns come from: Capital appreciation (share price increases) Dividends (cash payouts from profits) The NGX is regulated, structured, and accessible to both local and foreign investors through licensed platforms. --- HOW TO GET STARTED INVESTING IN NGX (TWO SIMPLE WAYS) Today, you don’t need to walk into a stockbroking office. You can get started fully online using digital investment platforms. Below are two popular and easy options that I personally use; --- 1) GETTING STARTED WITH BAMBOO Bamboo Bamboo is a digital investment app that allows Nigerians to invest in Nigerian stocks (NGX) and foreign stocks. Steps to get started: 1. Download the Bamboo app from the App Store or Google Play. 2. Create an account with your email and phone number. 3. Complete KYC verification Input your BVN Provide personal details 4. Fund your wallet via bank transfer. 5. Search for Nigerian stocks listed on NGX and place your first buy order. 👉 Referral code: ngxinvestor Bamboo is beginner-friendly and suitable for people who want a simple interface and access to both local and global markets. When done with registration to buy stocks on Bamboo,select the " Invest " icon on the bottom part of the screen,you will see that you can invest in USD or Naira assets,click on Naira,then select NG stocks,search for the stock of your choice and buy --- 2) GETTING STARTED WITH I-INVEST i-invest I-Invest is an official platform that allows Nigerians to invest in Nigerian stocks, Commercial Papers,Mutual Funds,USD Bonds etc... Steps to get started: 1. Visit the I-Invest website or download the app on App Store or Google Play. 2. Create an account 3. Complete required KYC documentation: BVN Valid ID Bank details Proof of Address etc... 4. Fund your account. 5. Start buying NGX-listed stocks directly through the app. 👉 Referral code: 22406 I-Invest is ideal for investors who want more Investment options because you can also invest in fixed deposit notes, commercial papers,USD Bonds ,life insurance etc.. After registration to buy shares ,click on " Invest " then select " Equities " ,then search the company of your choice then select "buy equities" --- FINAL NOTES FOR BEGINNERS Start small and grow with experience. Focus on learning before chasing quick profits. Invest in businesses you understand. Think long-term, not overnight success. The most important step is starting — clarity and confidence come with time and consistency. The first video is for bamboo Bamboo The second video is for I-Invest i-invest Please if anyone has any more questions please comment and I'll try to reply,and if you can DM I'll appreciate if you guys can use my referral codes

Emmanuel Essien

20,510 views • 8 months ago

Colmap 4.0 was very recently released, so it inspired me to do some work to better understand it and its new capabilities with Rerun. I want to really understand how Colmap, and in particular, pycolmap, works outside of just calling it via the CLI. So my goal is to use the low-level pycolmap API to log every part of the pipeline. The explicit goal is to have an alternative to the SQLite database that I can utilize. Instead of SQLite, I want to try logging everything directly to rerun and use RRD. This means I can have deep inspectability and still save the features/matches/2D view geometry, but be able to view it directly in rerun. I think this is one of the superpowers that rerun provides; data and visualizations are deeply integrated. As I'm often working with sequential data (videos), I'm going to specifically focus on four things: 1. Monocular Video Simple: Calls high-level APIs such as pycolmap.extract_features, pycolmap.match_sequential, pycolmap.incremental_mapping. These are basically identical to the CLI options and provide a good baseline. 2. Monocular Video Streamed: Take the above high-level APIs and break them down to their iterator version, logging each component in a streamed manner. This way, I can stream the intermediate features to rerun while the extraction/matching/mapping is happening. 3. Rig with unknown calibration: <- WHAT THE VIDEO SHOWS This is probably the most interesting version and the first one I've been working on. It allows one to set a rig between known sensors, such as in VR/AR devices, leading to much better reconstructions with multiple cameras. This is the case where we don't know the calibration a priori, so we have to run a reconstruction twice: once as a normal Colmap reconstruction with no rig constraints, use this to generate the constraints, and then do it again with the newly found rig. 4. Rig with known calibration: This is the RoboCap example, where we have a pre-calibrated set of sensors, so we don't need to run the two reconstructions and also gain better matching between cameras, both spatially and temporally. Again, this leads to a much better reconstruction! Along with all this, GLOMAP has become a first-class global mapper, making it super easy to use directly within pycolmap! I'm excited to do more with this and compare it to things like pycuvslam, vipe, and other alternatives.

Colmap 4.0 was very recently released, so it inspired me to do some work to better understand it and its new capabilities with Rerun. I want to really understand how Colmap, and in particular, pycolmap, works outside of just calling it via the CLI. So my goal is to use the low-level pycolmap API to log every part of the pipeline. The explicit goal is to have an alternative to the SQLite database that I can utilize. Instead of SQLite, I want to try logging everything directly to rerun and use RRD. This means I can have deep inspectability and still save the features/matches/2D view geometry, but be able to view it directly in rerun. I think this is one of the superpowers that rerun provides; data and visualizations are deeply integrated. As I'm often working with sequential data (videos), I'm going to specifically focus on four things: 1. Monocular Video Simple: Calls high-level APIs such as pycolmap.extract_features, pycolmap.match_sequential, pycolmap.incremental_mapping. These are basically identical to the CLI options and provide a good baseline. 2. Monocular Video Streamed: Take the above high-level APIs and break them down to their iterator version, logging each component in a streamed manner. This way, I can stream the intermediate features to rerun while the extraction/matching/mapping is happening. 3. Rig with unknown calibration: <- WHAT THE VIDEO SHOWS This is probably the most interesting version and the first one I've been working on. It allows one to set a rig between known sensors, such as in VR/AR devices, leading to much better reconstructions with multiple cameras. This is the case where we don't know the calibration a priori, so we have to run a reconstruction twice: once as a normal Colmap reconstruction with no rig constraints, use this to generate the constraints, and then do it again with the newly found rig. 4. Rig with known calibration: This is the RoboCap example, where we have a pre-calibrated set of sensors, so we don't need to run the two reconstructions and also gain better matching between cameras, both spatially and temporally. Again, this leads to a much better reconstruction! Along with all this, GLOMAP has become a first-class global mapper, making it super easy to use directly within pycolmap! I'm excited to do more with this and compare it to things like pycuvslam, vipe, and other alternatives.

Pablo Vela

30,070 views • 5 months ago

📜In Code We Trust: Crypto #DeFi's Game Changer: The Rise of The world's first #Bitcoin-native decentralized exchange, Orders.Exchange's LP is launched! In the past, DeFi has been susceptible to vulnerabilities like code errors, rug pulls, and potential attacks, raising security concerns in EVM-compatible blockchains. On the other hand, the Bitcoin DeFi landscape has been relatively uncharted territory, with limited options for fully on-chain trading. But that's where steps in, offering a unique approach that distinguishes it from DeFi in the old days. Let's delve into the key differentiators: 1⃣A Smart-contract-like Trading on Bitcoin Native Network: operates natively on the Bitcoin network, eliminating the need for layer-2 solutions or the Lightning Network. This simplifies the process and brings smart-contract-like functionality to Bitcoin. 2⃣AMM VS DIMM introduces the P-LP (PSBT Liquidity Pool), a zero-risk liquidity pool solution. Your assets remain in your account without the need to lock them. Unlike Ethereum's AMM mechanism, employs DIMM (Decentralized Instant Market Maker), eliminating the reliance on a mathematical formula for token prices. This ensures that the number of tokens you provide remains constant during liquidity provision, no more TVL, Slippage, and Impermanent Loss. 3⃣Trust and Openness: is trustless, meaning the platform cannot independently sign and seize your assets at the code level, ensuring a secure and decentralized liquidity pool on the Bitcoin network. It's also open-source and interoperable with other networks with the nostr protocol👉 The future of DeFi is here, and it's happening on the Bitcoin network. Join us as we embark on this journey👇

📜In Code We Trust: Crypto #DeFi's Game Changer: The Rise of The world's first #Bitcoin-native decentralized exchange, Orders.Exchange's LP is launched! In the past, DeFi has been susceptible to vulnerabilities like code errors, rug pulls, and potential attacks, raising security concerns in EVM-compatible blockchains. On the other hand, the Bitcoin DeFi landscape has been relatively uncharted territory, with limited options for fully on-chain trading. But that's where steps in, offering a unique approach that distinguishes it from DeFi in the old days. Let's delve into the key differentiators: 1⃣A Smart-contract-like Trading on Bitcoin Native Network: operates natively on the Bitcoin network, eliminating the need for layer-2 solutions or the Lightning Network. This simplifies the process and brings smart-contract-like functionality to Bitcoin. 2⃣AMM VS DIMM introduces the P-LP (PSBT Liquidity Pool), a zero-risk liquidity pool solution. Your assets remain in your account without the need to lock them. Unlike Ethereum's AMM mechanism, employs DIMM (Decentralized Instant Market Maker), eliminating the reliance on a mathematical formula for token prices. This ensures that the number of tokens you provide remains constant during liquidity provision, no more TVL, Slippage, and Impermanent Loss. 3⃣Trust and Openness: is trustless, meaning the platform cannot independently sign and seize your assets at the code level, ensuring a secure and decentralized liquidity pool on the Bitcoin network. It's also open-source and interoperable with other networks with the nostr protocol👉 The future of DeFi is here, and it's happening on the Bitcoin network. Join us as we embark on this journey👇

Rachel.metaid

101,524 views • 2 years ago

Most recent diffusion language model research (that I’ve seen) seems to be using masking as the noising process. It looks like, however, most closed-source models (Google Gemini Diffusion and possibly Inception Labs’ Mercury) use a different noising process, where instead of masking tokens, they replace them with different tokens (either with a random token or a semantically similar token). I wondered how they were getting such high throughput with the latter noising process, since I believed that optimizing inference with KVCache approximation would be more difficult (for various reasons). I visualized this noising process with tiny-diffusion and compared it to normal unmasking, and was very surprised to see how fast the generation “settles” into a reasonable output, and then only slightly refines afterwards, requiring much fewer steps in total. Unmasking (where tokens are never remasked, the typical implementation) is inherently limited in generation speed by the fact that an increase in tokens decoded per step leads to more errors due to the mismatch between individual and marginal token probability distributions we sample from. The token replacement noising process seems to have a much different set of characteristics. Because we sample each token per step, every token makes “progress” towards the final output each iteration (in addition to *potentially* giving other tokens more information in future steps). Generally, masking has outperformed other noising processes, which is probably why most research focused on it (using smaller models). But the paper referred to in the retweet shows that random replacement as a noising process may scale better as model size increases. Big labs might have noticed these results much earlier (due to having drastically more training resources and being able to test larger models), which may explain the discrepancy in the choice of noising process. I’m gonna test this with larger models, since tiny-diffusion only has 10M parameters.

Most recent diffusion language model research (that I’ve seen) seems to be using masking as the noising process. It looks like, however, most closed-source models (Google Gemini Diffusion and possibly Inception Labs’ Mercury) use a different noising process, where instead of masking tokens, they replace them with different tokens (either with a random token or a semantically similar token). I wondered how they were getting such high throughput with the latter noising process, since I believed that optimizing inference with KVCache approximation would be more difficult (for various reasons). I visualized this noising process with tiny-diffusion and compared it to normal unmasking, and was very surprised to see how fast the generation “settles” into a reasonable output, and then only slightly refines afterwards, requiring much fewer steps in total. Unmasking (where tokens are never remasked, the typical implementation) is inherently limited in generation speed by the fact that an increase in tokens decoded per step leads to more errors due to the mismatch between individual and marginal token probability distributions we sample from. The token replacement noising process seems to have a much different set of characteristics. Because we sample each token per step, every token makes “progress” towards the final output each iteration (in addition to potentially giving other tokens more information in future steps). Generally, masking has outperformed other noising processes, which is probably why most research focused on it (using smaller models). But the paper referred to in the retweet shows that random replacement as a noising process may scale better as model size increases. Big labs might have noticed these results much earlier (due to having drastically more training resources and being able to test larger models), which may explain the discrepancy in the choice of noising process. I’m gonna test this with larger models, since tiny-diffusion only has 10M parameters.

nathan (in sf)

40,440 views • 7 months ago

I didn’t expect Blitz to become my favorite feature in Fetra AI… but after seeing it generate multiple viral video concepts in seconds, I kept coming back to it. Instead of giving you just one idea and hoping it works, Blitz generates several different concepts based on video formats that have already proven to perform. It makes finding a strong direction so much easier. Then I tried Viral Remix. I uploaded a trending video and a single product photo, within a minute it recreated the entire concept around my brand. It genuinely felt like the video had been made for my product from the start. I also spent some time testing AI Influencers. It’s like having a UGC creator available whenever you need fresh content without organizing a new shoot every time. I haven’t explored everything yet, but Business DNA—which learns about your brand from your website before creating contentand Social Growth Manager, which helps keep your content workflow organized, both look really promising. My biggest takeaway? What stood out wasn’t just how much time it saved. Starting with formats that have already worked gives you a much better chance of creating content people actually want to watch. 👇 Full process in the first reply—all it takes is one product photo to turn a proven video format into your own branded video.

Aryan Rakib

43,338 views • 26 days ago

i wanted to tell you how we made the visuals for nerve-bloom i did it with Natalia Kleszczewska and Natalie Liu . Natalia Kleszczewska is a painter , she painted the creatures and the backgrounds . Natalie Liu is a computer graphics director , she shaped the digital dimension of the work . my role in it was a creative director , bringing in the singer-songwriter tradition , where emotionally precise things happen inside the structure of a song . i guided colour pallettes , textures and the environments the music happens in . to make this possible , during the process , natalia often had to paint many shapes and sizes , different textures and layers of colours . natalie then developed the visuals, designing and overseeing CGI elements , and finding ways for the digital to sit organically alongside Natalia’s world . and include my dramaturgy and creative direction. we spent 7 months talking and working together , dedicated to relish in the craft of blending hand-made visuals with digital experimentation , 3D design and commit it to physical display technology . a lot of time was spent on researching different tools and techniques to find what worked best at each stage in the song . like i’ve done before , i wanted to merge old things with tech , giving it soul & a meaning . to paint a painting is an analog craft but computer programming is craftmanship too !! and both can co-exist , .....encouraging each other to bloom even further towards a mutual world . there is a tradition in pop music for the mucisian to choose a video director . in the art world , this is called “curation” , but where we came from , it was natural that the musician would have strong opinions on what your song needed , which mood , colours , textures & storyline . today this is called “creative director” and it is something we didn’t credit ourselves with in the 90s , but i am starting to understand this better now . i don´t think of me as a visual artist . because my heart is music . everything i do comes from a sonic point of view . this is something i have called “sonic symbolism” , sound made visual , a reverse synesthesia . when you listen to a song for the first time , it is like swallowing a whale , you need to feel the whole musical sculpture in one go . the structure of a song has always been extremely important to me : what shape it is . this is part of the craft of being a singer-songwriter ........... we are tune sculpturors ....... since i am talking about the visuals for nerve bloom it is impossible to not mention the avatars in my music videos . they have replaced the storyteller with anattempt to connect to the more universal element of music , through animation, avatars , puppetry both digital and analog . for me they are marionettes in a puppet-theatre , hopefully in a similar realm as the jungian archetypes ( which we all can act out the characteristics of ...) .... i feel nerve-bloom is a natural continuation .... an animated avatar archetype singing you a song ––––– Avatars, animation and archetypes: Nerve Bloom (remix) – on display at Listasafn Íslands / National Gallery of Iceland until September 20th 2026. The production of this film was made possible with the generous support of #bottegaveneta.

björk

1,407,808 views • 3 months ago