2026-04-13 00:00:47
Beijing's newly approved 15th Five-Year Plan landed with very little fanfare in the Western press. It should not have. In the 141-page planning document submitted to the National People's Congress in March, the word for lithography machine does not appear once. Neither does wafer fab, extreme ultraviolet, or chip manufacturing. The entire Western vocabulary of the semiconductor war is absent. What took its place is a strategy built on something the West did not expect China to choose: openness.
\ The dominant assumption in Western AI circles has always been that the country with the biggest models wins. More parameters, more compute, more proprietary control. OpenAI, Google, Anthropic — the model is the moat. China looked at that framework and walked in the opposite direction.
\ Since DeepSeek released its R1 reasoning model in January 2025, Chinese companies have repeatedly delivered AI models that match the performance of leading Western models at a fraction of the cost. DeepSeek did not just match competitors. It exposed how much of Western AI spending was structural waste. R1 was trained for approximately six million dollars, compared to roughly one hundred million for GPT-4, using an architecture that activated only 37 billion of its 671 billion parameters per inference. The model was then released under an open MIT licence, free for anyone to download, modify, and deploy.
\ That decision turned out to be a weapon.
\ According to a study of 100 trillion tokens processed through OpenRouter and Andreessen Horowitz, Chinese open-source models went from 1.2 percent of global AI usage in late 2024 to nearly 30 percent within months. Alibaba's Qwen followed the same logic. The Qwen model family had surpassed 700 million downloads by January 2026 on Hugging Face, making it the world's most widely used open-source AI system. These are not niche adoption figures. One partner at Andreessen Horowitz estimated that 80 percent of US startups use Chinese base models to develop derivatives for their businesses. American companies, built on American capital, running their core AI workloads on Chinese infrastructure. The irony is structural and deliberate.
\ Why does this work? Because openness compounds. Frontier labs refine each other's base models, enterprises adapt them for niche applications, and deployment data feeds back into capability improvements. Proprietary models cannot participate in this loop. Every time OpenAI improves GPT-5, that improvement stays inside OpenAI. Every time DeepSeek improves R1, the entire global developer ecosystem absorbs it, builds on it, and sends improvements back. The gap between these two approaches grows with each iteration.
\ The Five-Year Plan encodes this logic formally. A new planning term appears in the document for the first time in Five-Year Plan history: 模芯云用, meaning "model-chip-cloud-application," a four-character compound that places the model layer as the primary strategic layer. Chip production remains a goal. But Beijing is no longer measuring success by semiconductors manufactured. It is measuring success by how deeply computing infrastructure penetrates the economy, with a target of digital economy value-added at 12.5 percent of GDP by 2030.
\ There is a counter-argument worth taking seriously. Proprietary frontier models remain more capable at the absolute cutting edge. GPT-5 can do things that Qwen cannot. The West still leads on the hardest benchmarks. But that argument misunderstands where the real competition is happening. China is not competing for the top of the leaderboard.
\ It is competing to become the default AI infrastructure layer for the developing world, where cost sensitivity and deployment flexibility matter far more than marginal benchmark performance. Singapore, Indonesia, Malaysia — the adoption numbers from Southeast Asia alone suggest this strategy is working faster than most Western analysts predicted.
\ The West built a race around the question of who can train the biggest model. China quietly started running a different race entirely. And by the time most observers noticed, Chinese models were processing 5.16 trillion tokens per week on OpenRouter compared to 2.7 trillion for US models, with four of the five most-used models globally being Chinese.
\ That is not a story about catching up.
2026-04-12 23:43:17
This guide was inspired by challenges encountered while installing the ESP32 library on the Arduino IDE, specifically the error: “Client.Timeout or context cancellation while reading body”. While this issue can be fixed by increasing the connection timeout value, this guide takes a more reliable approach.
It shows you how to set up a stable, efficient ESP32 development environment on a Windows PC without relying on fragile network installs.
After that, a simple example will show you how to use PlatformIO to build and flash firmware onto an ESP32 board.
ESP32 is a development board that stands out with its built-in Wifi client/server, Bluetooth, and compatibility with the Arduino framework. There are different variations of the board, and the developer’s choice depends on the embedded system application.
Below is a list of some popular ESP32 boards to learn more about.
\ There are two types of UART to USB drivers, namely CP210x and CH340. Check the bridge (circled in the photo) to identify the format your board falls under. Usually, a square-shaped bridge requires a CP210x driver, and a rectangular-shaped bridge requires a CH340.
You may download the following drivers:
My board uses the CH340 driver, so I downloaded and installed the driver. 
Visual Studio is an Integrated Development Environment (IDE) that uses code editors, a debugger, and extensibility to enable developers to build applications.
Download VS Code here and get started for free.
Open VS Code and go to the extension section. 
Search for PlatformIO in the search bar and click on it. Install it on the extension page.
| 
| \n 
|
|----|----|
\
Install the C/C++ extension to get the tools needed to program the microcontroller \ 
Install the Clang format to make structuring your code easier. It helps automate indentations, spacing, and brackets.
Activate Clang format by going to file>preferences>settings. Search for format and then change Editor Default Formatter from none to clang format.
Check in Format On Paste and Format On Save.
The PlatformIO icon will appear on your tab. Click on it and go to open under PIO Home. Click on New Project to get started. 
The project wizard window should appear. After naming the project, search for and select the ESP32 board you are using. Mine is the WeAct Studio ESP32C3 Core Board. Leave the framework on Arduino. Click finish and wait a minute for the necessary libraries to be downloaded for the project.
\
The project should be created, and you should see the directory structure. Under the src file find the main.app, which is the starting point for the application we will upload to the board. \ 
The code under the setup function is meant to be executed once when power is supplied to the board. While the loop function executes the code under it continuously.
We will create a test program that makes the ESP32 send some information to the serial monitor.
Firstly, go to platformio.ini and add the code:
monitor_speed = 115200
\ Go to main.app and paste the following code:
#include <Arduino.h>
void setup() {
pinMode(LED_BUILTIN, OUTPUT);
Serial.begin(921600);
Serial.println("Hello from the setup");
}
void loop() {
delay(1000);
digitalWrite(LED_BUILTIN, HIGH);
Serial.printin("Hello from the loop");
delay(1000);
digitalWrite(LED_BUILTIN, LOW);
}
\ Click the build button(pointed by the purple arrow) to compile the code. After compilation is successful, connect the ESP32 development board to the computer using the USB. Immediately after clicking the deploy button(pointed by the orange arrow), hold the boot button on the ESP32 board until the serial monitor shows success.
After deployment, the diode on the ESP32 board should be blinking. While on the serial monitor, the phrase “Hello from the setup” should print first, then “Hello from the loop” should print continuously.
And that’s it!
\
2026-04-12 22:47:20
“If you build it, they will come.”
It’s one of the most quoted lines in startup history. It’s also one of the most destructive, and the reason is simple. Because it sounds right, it feels right, and it is a saying that gives permission to builders to do what they already want to do: build.
In Field of Dreams, the field does work. Of course it does, it’s a movie after all. The players come, then some magic happens, and the story rewards the builder, and it would be a crappy movie if it didn’t. If we want to put it into context and base things on reality, the field is the least important part of the system.
Every marketplace founder thinks they’re building “the field.” You start with the product, the platform, and the infrastructure. However, a two-sided marketplace is not a field; it’s actually much more complex than that, because you have to factor supply to demand, and demand to supply, and keep repeating it over and over until it finally works.
If you break the loop at any point, the whole thing collapses, and most founders find this out the hard way.
Most founders simply build the field and wait for the players to come. Often yelling, “Why aren’t they coming? This is one hell of a field”.
An empty marketplace is worse than no marketplace, because it sends a signal that nothing is happening here. For those familiar with the sitcom Silicon Valley, you will remember this scene where Russ Hanneman steps in at the suggestion of turning on revenue.
\ Russ Hanneman: No. If you go after revenue, people will ask how much, and it will never be enough. The company that was the 100x’er, 1,000x’er becomes the 2x dog. But if you have no revenue, you can say you’re pre-revenue. You’re a potential pure play. It’s not about how much you earn. It’s about what you’re worth. And who’s worth most? Companies that lose money.
\ If someone comes to your marketplace and thinks, “Nothing is happening here.” No sellers, and then buyers leave. If there are no buyers, then sellers never come. If there is no activity, then everyone assumes they’re early, and they exit.
You didn’t build an opportunity; you built and delivered a proof of failure.
Here’s where it gets dangerous. Founders think, “We just need to grow both sides at the same time.” This is clean, logical and wrong. No marketplace in history started balanced, not a single one; they all started unfair.
\
The winners pick a side and go violently on it. They don’t “build the field,” they instead manufacture the game**.**
They broke the loop on purpose and then forced it to restart in their favor.
If you’re early, one side of your marketplace is fake. And by fake, I mean it’s subsidised, scripted, curated, and manually driven. It doesn’t mean your marketplace is flawed; it means you are doing your job. \n
The real version of the quote should have been: “If you build it, nothing else happens.”
Because people don’t come for infrastructure and they aren’t in it for the tech, they come for liquidity, activity, and especially for other people. They come for proof that something is already working.
Well, it sure as hell isn’t the field, not first anyway. You first need to get the first 100 suppliers or the first 1000 users, then obsess over making that side undeniable. You have to make it so damn undeniable that the other side just has to show up. It really is as black-and-white as that.
The movie got one thing right, and it really nailed this part. It wasn’t really about the field but more so about belief. But not the kind founders think, because it’s not “If I build this, they will come,” but instead it’s “If I make one side work so well it looks inevitable, the rest will follow.”
Most founders are standing in a cornfield, polishing a perfect diamond, wondering where everyone is. The smart ones are not building the field; they are already playing the game.
\ \
2026-04-12 22:39:23
When I first started working with market data APIs, it quickly became clear that milliseconds can make the difference between a winning strategy and a missed opportunity. I spent hours chasing latency spikes, only to realize the bottleneck wasn’t in the strategy itself—it was in how the data was fetched and processed.
Optimizing market data APIs isn’t just about choosing the “fastest” provider. It’s about managing requests, handling concurrency, and keeping incoming data clean. Here’s how I approached it.
Before making any changes, I mapped out where latency could creep in:
Knowing these points helped me focus on what really mattered for performance.
Switching from synchronous to asynchronous requests made a noticeable difference. Using Python’s asyncio and aiohttp, multiple API calls can run concurrently without blocking the main thread:
| import asyncio \n import aiohttp \n \n async def fetch(session, url): \n async with session.get(url) as response: \n return await response.json() \n \n async def main(): \n urls = [ \n "https://api.marketdata.com/ticker1", \n "https://api.marketdata.com/ticker2", \n "https://api.marketdata.com/ticker3", \n ] \n async with aiohttp.ClientSession() as session: \n results = await asyncio.gather(*(fetch(session, url) for url in urls)) \n return results \n \n ifname == "main": \n data = asyncio.run(main()) \n print(data) \n \n | |----|
This simple change cut API response times almost in half when handling multiple tickers.
Not all data needs to be fetched in full every second. Many APIs support delta updates, providing only the changes since the last call. Processing batch updates instead of full snapshots significantly reduces bandwidth and parsing overhead.
| # Pseudo-code for delta processing \n lastsnapshot = {} \n for update in apistream: \n for symbol, value in update.items(): \n last_snapshot[symbol] = value # update only the changes \n \n | |----|
For high-frequency tickers, this approach works particularly well, since most values remain unchanged every millisecond.
Heavy data structures can slow down high-frequency processing. I found that using simple dictionaries instead of full pandas DataFrames for each tick keeps processing lightweight:
| ticks = {} \n for tick in api_stream: \n symbol = tick['symbol'] \n ticks[symbol] = tick['price'] \n \n | |----|
Data is only converted into DataFrames or NumPy arrays when calculations require it, keeping per-tick handling fast and memory-efficient.
Optimization without visibility is just guessing. I implemented real-time monitoring of request latency, logging timestamps, API response times, and processing delays. This made it possible to continuously identify bottlenecks.
After these adjustments, the data flow became predictable and fast. I could finally focus on strategy logic and edge cases rather than data handling. One key lesson I learned: efficient market data handling is just as critical as the strategy itself. Ignoring the data layer can mean losing milliseconds—and potentially profits.
\n \n
\
2026-04-12 21:28:53
What does a crypto company do when its 10th birthday lands in the same year as America's 250th?
\ If you are Crypto.com, you book the White House lawn, you partner with the UFC, and you put 14.4 million CRO on the line for the fighters who show up to make history with you.
\ It is the kind of moment that will sit in the company's highlight reel for the next decade. A co-presenting credit on federal executive ground, on a national anniversary, alongside a sport that draws 700 million fans worldwide. There is no second example of a crypto brand reaching this altitude.
UFC Freedom 250 takes place Sunday, June 14, on the grounds of the White House. Crypto.com joins the card as co-presenting partner and is funding a $1 million bonus pool that sits on top of the standard Fight of the Night and Performance of the Night awards UFC President and CEO Dana White hands out after every event. The pool will be paid in CRO, the gas token of the Cronos chain. At the reference rate from April 10, one million dollars converted to roughly 14.4 million CRO.
\
The fight card carries its own gravity. The main event pairs lightweight champion Ilia Topuria, the No. 2 ranked pound-for-pound fighter on earth, against interim lightweight champion Justin Gaethje. The co-main puts former two-division champion Alex Pereira against Ciryl Gane, with Pereira chasing a title in an unprecedented third weight class. Paramount+ holds exclusive United States distribution.
\
Sponsorship deals in sport are usually priced in audience reach. This one should be priced in cultural authority. A crypto exchange standing on the South Lawn on a national anniversary signals that the category has crossed from the periphery into the centre of mainstream American life, and Crypto.com is the brand that planted the flag. For a sector that spent the past three years rebuilding trust, this is the clearest forward indicator yet that the climb is paying off.
\ Crypto.com has been laying the groundwork for years. The UFC partnership began in 2021, when the exchange was named the promotion's first ever Official Fight Kit Partner. A strategic partnership with Trump Media, announced in August 2025, set up a CRO-anchored treasury vehicle that put the token in front of an entirely new investor base. June 14 is the moment those threads converge into one televised frame. For readers new to this, think of the way Visa moved from a niche payment network in the 1970s into the centre of global commerce. Each high-profile placement compounded the next. Crypto.com is running the same playbook on a faster clock.
\
UFC President and CEO Dana White framed the night in fighter terms. White explains,
\
"This is the most historic sporting event in history, and it's a night where every single fight has the potential to be Fight of the Night. Crypto.com is giving fighters the biggest bonus in UFC history, with $1 million on the line. The world will be watching on June 14."
\ Kris Marszalek, Co-Founder and CEO of Crypto.com, anchored the deal to the company milestone. Marszalek explain,
\
"I can think of no better way to celebrate the 10th anniversary of Crypto.com than by making history at the White House. We are humbled to join our long-standing partners at the UFC and serve as co-presenting partner of Freedom 250, an event that transcends sport."
\
Paying the pool in CRO rather than cash turns a marketing line item into an on-chain moment. Every payout creates a public receipt the ecosystem can point to, and every fighter who collects becomes a holder of the token. CoinGecko data places CRO at a market capitalisation around $2.93 billion, ranking it 34th by market value, with a circulating supply of 42 billion tokens.
\ The simplest analogy is an employee stock grant at a growing company. The headline figure is fixed at the moment of announcement, and the upside belongs to the recipient as the asset compounds. Cronos has the rails to back that thesis up. The chain supports up to 60,000 transactions per second, sub second block times, and fees under one cent, and it processes flow for 1.8 million users while plugging into Crypto.com's distribution to more than 150 million accounts worldwide.
\
This is the kind of moment a marketing team builds an entire decade around. A 10th birthday, a national anniversary, the most decorated combat sports brand on the planet, and a venue no competitor will ever match. Crypto.com gets all four in one night, and the fighters who step into the cage walk away with the largest bonus pool in UFC history denominated in a token tied directly to the company's growth. Every party in the room wins, and the broadcast will carry the image into living rooms in more than 210 countries.
\ The forward read is straightforward. June 14 sets a new ceiling for what a crypto brand can credibly attach itself to, and it gives CRO a cultural anchor most tokens never get the chance to earn. The moment lands at exactly the right point in the cycle.
\ Don’t forget to like and share the story!
2026-04-12 21:07:38
This article investigates why geolocation requests in React and React Native apps can hang indefinitely despite granted permissions. The issue stems from a combination of missing timeouts in the API, platform-specific restrictions (like Android battery saver and iOS authorization mismatches), and poor lifecycle management. By implementing manual timeouts, platform-aware logic, robust error handling, and proper cleanup, developers can transform unreliable location retrieval into a stable, user-friendly feature.
