CryptoPepper

Google released a paper called TurboQuant, and within 24 hours, the community had ported it to llama.cpp.
What did TurboQuant do? It compressed the KV cache of large models to 3 bits, reducing memory usage by a factor of 6, and sped up inference by 8 times on H100.
The key point is—no retraining needed, no fine-tuning required, and no loss of accuracy. This is one of the reasons chip stocks plummeted.
Samsung and SK Hynix dropped over 6% in Seoul, and Micron fell 6.9% in the US stock market.
The market's concern is—if each model can use 6 times less memory, doesn’t that reduce the demand for H

Meta has laid off another 700 people.
This is the second round in 2026. In January, they cut 10% of Reality Labs, and this time it's sales, recruitment, and global operations.
Zuckerberg's words: "Projects that used to require a large team can now be handled by a talented individual."
At the same time, Meta's capex budget this year is between $115 billion and $135 billion, all invested in data centers.
Layoffs plus heavy investment in AI infrastructure.
This is the standard operation for big tech companies in 2026.
It's not that they don't need people anymore; the type of people th

Because I have personally trained systematically for 10 years, I consider this basic common sense, and many people may not know it.
The post below from KeKeLi has gone viral, so I’m sharing it here for everyone to see.
1) The basic principle of strength training/muscle building is "approach the current muscle limit—cause slight damage to the body—spontaneous repair—muscle growth—repeat."
It can be simply understood as pushing the muscles to the limit, and they will grow.
2) In this process, your body first consumes resources and then replenishes, ultimately resulting in growth.
So you need to

"Is AXTI the new king of US stocks?"
I see posts like this on Xiaohongshu every day. Just change the ticker and keep shouting.
They keep trying to make you believe in the light—damn, there's so much of it.
Most people can't explain in one sentence what this company actually does.
AXTI makes compound semiconductor substrates. You've probably never even heard of it, right?

OpenAI Shut Down Sora
Launched with great fanfare in September last year, it hit the top spot on the App Store. Six months later, it was shut down.
Official statement: "Focusing computing power to world simulation research and robotics."
Translation: Too expensive to run, couldn't retain users.
That big deal with Disney? Three months, contract terminated.
Attention AI video creators: If OpenAI can't afford to sustain a product line, how long do you think your video AI startup will last?

<>One command to bridge WeChat with any AI (please star us on GitHub 🌟)
<> One command to connect WeChat with any AI
🤖 Multiple AI backends Claude Code CLI · Gemini CLI · Codex CLI · OpenAI API · Anthropic API
🖼️ Image understanding Send images, AI directly analyzes content (vision models)
🎙️ Speech recognition Built-in ASR + local Whisper dual fallback
🎬 Video analysis ffmpeg frame extraction + Whisper audio transcription, comprehensive video understanding
📄 File parsing PDF · Word · Excel · PPT · EPUB · code files fully supported
⚡ Streaming output AI replies with real-time typewriter

# Brief Review of the So-Called "AI Auto-Iteration to Find Optimal Strategy" GitHub Project
If you understand the basics, you can skip this—this is just marketing nonsense.
**Key Issues:**
1. **Sharpe 20.6, max drawdown 0.3%—almost certainly overfitted.** This literally cannot happen in reality. Even the Medallion Fund wouldn't claim a Sharpe ratio of 20. This is a red flag.
2. **All 103 experiments evaluated on the same data segment, without accounting for funding rates or maker/taker fees.** The backtest is incomplete and unrealistic.
3. **The git reset/keep mechanism just uses "history" as

Drinking with the local human resources bureau director and discussing the pandemic:
"Do you know how many supply trucks a town coordinating 300,000 people needs during a pandemic?
It's not dozens of 2-ton trucks, but hundreds of them—one truck per minute. Now imagine scaling that up to 3 million people and how many supply trucks would be needed.
I used to think it was all amateur hour, but now I really don't dare think that way anymore."

Alibaba's profits plummet 67%
Why? Massive AI investments. Cloud business grows slower
Breaking it down:
First level: Alibaba is all-in on AI. It's an investment, which means losses
Second level: Slower cloud growth indicates Chinese enterprises' cloud adoption growth has peaked
Third level: Actually bullish for US AI stocks—competitors are burning cash to catch up, proving NVDA's moat is even deeper
I don't care if Alibaba's stock falls or rises.
What I care about is: Chinese AI companies collectively burning cash → chip demand surges → NVDA benefits. People who understand the supply chain ma