CryptoPepper

Polymarket allows users to bet on when the U.S. military pilot will be rescued.
An F-15E was shot down over Iran, and Polymarket launched a market: Will the U.S. confirm the pilot's rescue on April 3rd or April 4th?
Users can bet Yes or No. Over 63% of the bets are on the pilot not being rescued soon.
Democratic Congressman Seth Moulton was outraged. He wrote on social media: They could be your neighbors, friends, or family. And some are betting on whether they will come back alive.
He called Polymarket a dystopian death market. By the way, he mentioned that Donald Trump Jr. is an investor in

Currently running the latest Google GEMM4 3n E4B model on mobile.
This should be the closest step to a local large model for you. Experience the feeling of open-source unlimited tokens.
Method: Download the Google AI Edge app — download the mobile model you need on demand — just chat.

Houses in the United States are aging collectively.
Seeking Alpha just published a report: The rising costs of home maintenance in the U.S. are increasing financial pressure on homeowners.
The median age of existing homes in the U.S. has exceeded 40 years.
Post-World War II baby boom construction peaks mean those houses are now due for major renovations. Roofs, plumbing, electrical systems, foundations—
Building material prices have not truly fallen since 2020. Labor costs have soared—shortage of blue-collar workers is one of the biggest structural issues in the U.S. labor market.
Finding a re

Kevin Warsh's Fed Chair nomination hearing is scheduled for April 16th.
Trump wants to replace Powell.
Warsh has a solid background: Stanford + Harvard Law School, former executive at Morgan Stanley, and in 2006 became the youngest Federal Reserve Board member in history. He is from the Bush era.
But he faces two obstacles.
First: Senator Thom Tillis publicly said he would not vote. The reason is not opposition to Warsh himself, but a demand that the Department of Justice finish its investigation into Powell first. It’s rare for a Republican to oppose a nomination from his own party in

Anthropic spent $400 million to acquire a company with fewer than 10 employees 🧬
This company is called Coefficient Bio, founded just last year, with a team entirely composed of computational biologists from Genentech.
Spending $400 million on 10 people? Are they crazy?
Not at all. They’re investing in AI + biotech.
Dario (Anthropic CEO)’s ultimate goal is to have Claude participate in drug development. In January, they launched Claude for Life Sciences, integrating research platforms like PubMed and Benchling. Now they’ve also brought people on board.
Basically: AI is no longer jus

The arrival of Generalist AI's GEN-1—robots are really working
At GTC 2026, two robotic arms autonomously completed phone packaging
NVIDIA is building the "Android" for robots, while Generalist provides the "application layer" agile operation model, and Universal Robots supplies the hardware.
Unlike Figure or Tesla Bot, Generalist focuses solely on models, integrating with other hardware. Light assets, rapid iteration.
2026 will be a watershed year for general-purpose robots. Not because of stunning demos, but because the supply chain has taken shape: chips + models + hardware + scenarios, all

A paper made me stop and read for half an hour. S0 Tuning
Core idea: Without changing the model weights, just tuning an initial state matrix can significantly improve the model's coding ability.
On Qwen3.5-4B, using only 48 HumanEval training samples (not 48K, but 48), S0 tuning increased pass@1 by 23.6 percentage points.
Compared to LoRA, S0 outperformed by 10.8 percentage points. p-value < 0.001, statistically significant.
On FalconH1-7B, S0 achieved 71.8%.
This means that after tuning, the model's speed and size remain unchanged, only the "starting position" is better.
For those

Google releases Gemma 4
Sizes of 1B, 13B, 27B, and a dense 31B version. All under the Apache 2.0 license. Commercial use is unrestricted.
This license change is more significant than the model itself. Previously, Gemma used Google's proprietary license with restrictions. Now, with Apache 2.0, it directly competes with Meta's Llama.
Highlights of the model: multimodal — text + vision + audio. The dense 31B version achieved 89.2% on AIME 2026, LiveCodeBench v6 scored 80%, and it has a Codeforces ELO of 2150.
The 27B parameter size is very friendly for local deployment. It can run on a single 409

OpenAI spent money to buy a YouTube talk show.
TBPN, a tech live broadcast program that only started in 2025, has only 58,000 YouTube followers. OpenAI acquired it.
Last year, TBPN's advertising revenue was $5 million. This year, it is expected to surpass $30 million. In less than two years, the program has grown sixfold.
The show airs live every day at 2 PM for three hours. The guest list includes: Sam Altman, Meta executives, Microsoft executives, Palantir, a16z. Bloomberg and CNBC have also appeared.
This is the living room of Silicon Valley's power circle.
After the acquisition,

Alibaba quietly dropped a big move.
CoPaw-Flash-9B — an AI agent model based on Qwen3.5. With 9 billion parameters, it can run on your own computer.
What's so impressive?
It ties with some benchmarks and Qwen3.5-Plus (closed-source large model).
90 billion parameters vs. hundreds of billions, similar scores.
What excites me even more is the CoPaw framework:
- Supports persistent memory (remembers past conversations)
- Multi-channel connectivity (can connect to Feishu, Discord, etc.)
- Local deployment, no API costs
Qwen3.5's architecture is also very powerful — a total of 397B parameters, with

This market is ultimately destroyed by these kinds of manipulative players messing things up.
One day it surges 18 times, then the battle ends in 15 minutes.
Even with contracts or spot trading on Binance, it's hard to escape the fate.
Retail investors with no info edge will only die faster.
Copycats are finished, and the encryption era is over.

I came across a chart titled "AI Tool Collection," divided into over a dozen categories, and it looks really impressive.
Here's a bold statement — you don't actually need that many tools.
The three I actually use every day are:
- Claude: coding + long-form writing + helping it get to know me
- Codex: messing around with stuff
And occasionally, I add three more: Google Stitch for image creation, Whisper for transcription, Claude Artifact for data analysis.
Five tools. That's enough.
So, what's wrong with that chart? It treats "existence" as "usefulness."
One Claude can replace t

Someone is using Transformers to determine whether loops in code can be parallelized.
Sounds very academic? Don’t worry.
First, the background.
Programmers all know that converting a for loop into a parallel execution is the holy grail of performance optimization. But the problem is: if you get it wrong, bugs happen. Traditional methods rely on static analysis, but they fall apart when faced with complex dependency relationships.
This paper does one thing: it feeds code into a Transformer model (yes, the architecture behind GPT) to let AI judge whether "this loop can be safely parallelized."
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