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Memory-safe. 13% faster on average. ⚡️ The TrueType hinting interpreter in macOS and iOS has been rewritten in Swift, replacing the original C implementation. Pixel-perfect accuracy was validated across 27 million glyphs. And the results:
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💥有消息说：Google Pixel 6月的安全更新，可能会直接跟 Android 17 正式版一起推出来。
Android 17 这次主要是开始“卡死”每个 App 的内存上限：系统会按手机 RAM 大小，给每个 App 设个使用上限，一旦超过就直接杀进程，不再等到整机内存不够才清理。
✅好处就是手机更稳一点，卡顿和发热会少，多任务体验也更顺。
⚠️但代价就是，有些内存管理做得不好的 App，可能更容易被直接干掉，甚至闪退。
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谷歌终于承认部分 #Pixel# 设备出现循环重启问题，用户安装 3 月、4 月或 5 月更新后，启动设备输入 PIN 后就会自动重启。
谷歌现在要求受影响的用户联系客服，而客服给出的解决方案竟然是通过 Fastboot 重置设备，这意味着所有数据都会丢失，用户正在期待谷歌能提供其他能接受的方案。
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Grok Build is pretty good at optimizing my code in one shot.
Prompt:
I want you to optimize it entirely on GPU to speed it up. Measure two metrics: the result must compare with the golden image (CPU) and be nearly identical (PSNR > 40dB), with fast pixels per second.
Make a plan to a) write GPU equivalent code, b) write a benchmark suite to measure PSNR and pixels per second, c) execute various optimization strategies.
Go!
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I have a hypothesis about the current 3D vs non-3D debate.
Perhaps the endgame is that these two paths eventually merge.
Non-3D approaches currently feel incredibly strong. Scale data, scale compute, scale parameters, and surprisingly quickly: 20 → 40 → 60 → 80. Realism improves. Motion improves. Benchmarks improve. But going from 80 → 100 feels fundamentally different. Physical correctness, multiview consistency, object permanence, contact dynamics, and long-horizon reasoning feel much harder.
My intuition is that 0 → 80 is mostly a scaling problem, while 80 → 100 may be a world-state problem. Current large-scale data gives us enormous amounts of observations: pixels, videos, actions. But much less geometry, depth, pose, contact, physical constraints, or object state. As models become stronger, perhaps the bottleneck slowly shifts from “Can models fit the data?” to “Does the data contain enough world state?”
This is why I think 3D matters—not necessarily as the final representation, but as data infrastructure. Multiview capture, simulation, synthetic interaction, counterfactual rollouts, state supervision. These systems don’t simply create more data; they create higher information density data. Which creates an interesting possibility: maybe non-3D systems win early because scaling observations is easy, while 3D systems catch up later because scaling world-state is harder.
And eventually, perhaps the distinction disappears. Sufficiently strong non-3D systems may need to implicitly learn world structure, while sufficiently strong 3D systems must learn appearance, dynamics, and semantics.
Perhaps the real question is not: 3D vs non-3D. But: How do we scale world states.
Before the intelligence scale, the data engine needs to scale first.
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Competing with model giants with 10x more resources, how did we do it? Introducing Unified Layout Models.
We designed a new structured data format for images, based on hierarchical region conditioning. We call this "layouts". Think of it as SVG for pixels.
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You want alpha?
PATTERN RETRIEVAL by @adamilenich is alpha.
A collection of pixelated ASCII characters with each one a memory under pressure.
The project explores how memories persist under pressure. Stored patterns are disrupted by noise, then gradually reconstruct themselves through a process of recall. Presented through CRT-inspired visuals and generative sound, each work loops endlessly between loss and recognition.
The creator, Adam is a builder in the NFT space and he has worked with top brands in web2 and web3 companies like Opensea and Twitter.
This is his first collection.
The collection would be a 478 supply collection with an allowlist price of 0.0069e and a public mint price of 0.1e.
The best way to get in is to explore the site to know more about Pattern Retrieval, then register on the allowlist ( check the link below)
Don’t fade, position and keep close tabs.
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Elon Musk thinks money has an expiration date.
Not the dollar. Not the system.
The concept itself.
Elon Musk: “I think long term… money disappears as a concept.”
Not crashes. Not inflates.
Disappears.
Most people hear that and dismiss it. Musk is the one who said it. And then built around it.
Musk: “You no longer need money as a database for labor allocation.”
Database for labor allocation.
Strip away the mystique and it gets colder.
Money was never wealth.
It was a ledger of what we deny each other.
Every price is a wall. Every balance is a count of what you cannot have yet.
Musk: “If AI and robotics are big enough to satisfy all human needs, then… its relevance declines dramatically.”
His bet is the wall comes down. And unlike the people debating it, he’s building the machines that knock it over.
If machines can make anything, need stops being a negotiation. And the ledger of denial has nothing left to count.
So he reaches for what survives.
Musk: “Energy is the true currency. You can’t legislate energy.”
You can print money. You cannot print power.
Musk: “You can’t just pass a law and suddenly have a lot of energy.”
This is why he built Tesla. Why he built SolarCity. Why every company he touches bends toward energy production, storage, or conversion.
He was never chasing cars. He was chasing the real currency before most people understood what it was.
Every dollar ever printed was a proxy for energy. Every stock. Every bond. A claim on future energy dressed in paper and pixels.
We spent millennia worshipping the proxy and forgot what it was pointing at.
Musk didn’t forget.
Then he scaled it to civilization itself.
Musk: “One way to frame civilizational progress is the percentage completion on the Kardashev scale.”
Kardashev 1. Harness your planet.
Kardashev 2. Harness your star.
Kardashev 3. Harness your galaxy.
Musk: “Things really become energy-based.”
Most founders optimize for quarters. Musk optimizes for Kardashev levels.
Then Nikhil Kamath asked the question that unravels everything.
If we harvest the sun… energy is free too. Infinite. Useless as a store of value.
Money dies of abundance. Then energy dies the same death.
Both were just names for scarcity. Kill scarcity and the names go with it.
We always assumed the destination was getting everything.
Nobody priced what happens after.
What stays scarce when everything is already yours.
The machines can manufacture anything except the thing that actually matters.
Time you don’t get back. A life that still ends. Someone choosing you when they could have chosen anyone.
When nothing has a price, the only thing left with value is you.
A world where everything is free is a world that finally asks what you were for.
Most people have never had to answer.
Musk is already building the world that forces the question.
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One more for the Meowri May pixels. Thought @JennaLynnMeowri would look cute as a hamster, and what better way to make her one than in the Hamtaro style.
