Mr.Block58

In a few years, every computer and every robot could become a micro Data Center.
Rumor has it that Apple is developing the M7 Ultra, which can support up to 1.5TB of unified memory. While the specifications and launch timeline have not yet been confirmed, the trend is already very clear:
On-device machines will only keep getting more powerful, while models will become smaller and more efficient through quantization, distillation, and sparsification.
Models that today require a Data Center to run may, in a few years, run on a single Mac Studio, AI PC, or even a robot.
In the future, lar

On the first day of its launch, Robinhood Chain directly surpassed Hyperliquid in 24-hour DEX trading volume!
According to the latest data from DefiLlama:
• Robinhood Chain (Lighter): $433.19M
• Hyperliquid: $296.23M
Retail giants @vladtenev + @vnovakovski – this wave of operations is incredibly fierce!
Do you think this trend can continue? Or is it just a launch impact?

Spend $20k to buy this NEO humanoid robot, plus a $90k Nvidia super desktop, total only $110k to have
"Local AI + Robot" 👀
It won't complain, won't ask for leave, won't demand overtime pay, and can help you with housework, moving things, and caring for the elderly 24 hours a day.

Too powerful... #FIFA
Pharaoh power!!!

1/ 🧠 Why can future personal AI computers (like the NVIDIA DGX Spark) really compete with data centers?
Not because desktops are powerful enough to replace the cloud, but because AI's "demand structure" is splitting—
Training stays in the cloud, inference returns to the local.
2/ Key Breakthrough 1: FP4 Rewrites the Rules
A 70B parameter model requires 140GB of memory in FP16;
Switch to FP4 → only 35GB.
A desktop with 128GB unified memory can run a model that previously required 8 H100s.
Accuracy loss? It's almost negligible with QAT (Quantization-Aware Training).
3/ Key Break

Google AI Brain Drain!😱
In the past week, 4 key personnel have left:
• Jonas Adler: Gemini core, AI coding expert → Anthropic
• Alexander Pritzel: Key figure in Gemini training → Anthropic
• Arthur Conmy: Gemini post-training and alignment expert → Anthropic
• Addy Osmani: 14-year senior leader in Chrome/Cloud AI
Although Google pays high salaries, the temptation of equity from Anthropic's nearly 1 trillion valuation + upcoming IPO is too strong!
Silent threat 😱

why there isn’t a search tab for @ManusAI connector?

Taiwanese Stocks
from the beginning of the year to now

According to The Economist, U.S. Senator Mark Warner revealed: NSA Director Joshua Rudd personally told him that Anthropic's AI model Mythos broke through almost all of NSA's classified systems during authorization testing in just "a few hours," rather than the traditional several weeks.
This was not an external hacker intrusion, but NSA's own red team testing Mythos, with shocking results!
At the same time, the U.S. government has imposed export controls on top-tier models like Mythos and Fable, and Anthropic has further globally shut down the models.
AI's cyberattack capabilities have

Wow, @arena is made by someone from Taiwan?
Recently, the AI coding leaderboard is really worth watching 👀
But I think the focus is no longer on "who is number one."
What truly matters is: the top AI models are becoming less and less rare. 🧠⚡️
In the past, everyone thought AI would be a winner-takes-all game:
GPT-4 far ahead,
other models can only catch up.
But now, looking at leaderboards like Arena, the top models are getting more crowded. Claude, OpenAI, Google, GLM, Qwen, Kimi, and various open-source and closed-source models are all within the same capability range. The El

Assuming 1.1 trillion dollars ($1.1 Trillion):
💰 Spend 1 million dollars per day
→ Takes 3,014 years
💰 Spend 10 million dollars per day
→ Takes 301 years
💰 Spend 100 million dollars per day
→ Takes 30 years
💰 Spend 1 billion dollars per day
→ Also takes 3 years