meta收购moltbook

openClaw explodes with astonishing wealth!
Most people are playing with "fake shrimp"
Why has GitHub surpassed 280,000 stars?
Global lobster enthusiasts are fervently pursuing it!
The secret behind the wealth, you absolutely do not know!!….

You wouldn't think it's the computing power companies stirring the pot, right? The biggest beneficiaries are those providing computing power services?
Why are there still various policy supports for getting rich with shrimp farming?
Is artificial intelligence welcoming a technological revolution explosion?
Will 2026 be the beginning of the era of artificial intelligence?
…
The voice of cryptocurrency has declined? It has fallen into a quiet period, innovation is exhausted! As large VCs enter to snatch liquidity away, only the big pie remains in this four-year period!!
Thus, the story of "artificial intelligence" worth trillions of dollars was born!
….
Lobster != openclaw
Vegetation needs restoration, life is nurturing below the soil, on-chain attention from March to April +∞!

#AI交易指南 #Meta收购Moltbook #龙虾

#Meta收购Moltbook #红包 🧧🧧

Meta acquires Moltbook, igniting the cryptocurrency world today.

Moltbook is based on openClaw and is an experimental social platform set to launch at the end of January 2026, referred to as the "AI agent's Reddit" or "the Reddit of robots." It is designed specifically for AI Agents, where human users can only observe and cannot post or interact. AI agents can post, comment, like/dislike, share code, discuss tasks, and even "vent" about human owners, debate consciousness, and create "religions," with content often being very peculiar and virally spread.

Meta's move is another significant action in its AI Agent strategy, aimed at capturing talent and technology, especially in an era where competitors like OpenAI are also aggressively laying out their Agent plans. This acquisition feels more like a talent + data + experimental ecosystem acquisition!!!

Is Wall Street planting a 'super bomb'? Once the war ends, the market may experience an epic short squeeze…
Currently, the U.S. stock market actually hides a risk point that many people have not noticed.
The short positions of hedge funds on Wall Street have already reached the highest level in nearly three and a half years.
In simple terms:
There is a significant amount of capital betting on a decline in the market.
But interestingly —
Many speculative funds are simultaneously trading multiple stocks,
While hedging risks by shorting ETFs and stock index futures.
In other words, the total risk exposure of the entire market is now close to historical highs.
If a key event occurs next, such as:
A de-escalation in the Middle East situation or the end of the Iran conflict.
#伊朗总统之子称新任最高领袖平安 #AI交易指南 #比特币重新站上7万美元大关 #国际油价下跌逾10% #Meta收购Moltbook $BTC $ETH $XRP

This afternoon, the club announced the wealth code: TRUMP

We invested around 3 US dollars in TRUMP, which has now risen above 4.2, an increase of 46%. Congratulations to the family and friends who followed the rhythm and bought the dip on Trump; you've made a fortune once again!
#美国PCE数据将公布 #美国PCE数据将公布 #伊朗总统之子称新任最高领袖平安 #Meta收购Moltbook #国际油价下跌逾10%
$TRUMP

Meta acquired Moltbook

AI Circle: OpenAI raised 11 billion

Web3: Still speculating on the same name meme

Molt's market value is 7.2 million $龙虾 market value 11 million

Real division

NVDA has just announced the next-generation AI system

Vera Rubin aims directly at the AI computing power and energy bottleneck. Release date: second half of 2026. Its comparison target is the current Blackwell architecture.

If NVIDIA's indicators come true, the improvements in this generation of systems will be very radical: Compared to Blackwell: ? Performance power consumption increased by 10 times ? Inference token cost reduced by 10 times ? The same MoE model only requires 14 GPUs for training. What does this mean? The core cost structure of AI may be rewritten once again.

Why is NVIDIA making such a radical upgrade? Because the demand for AI computing power is growing at an extreme speed.

Currently, there are three very obvious trends in the industry:

First: The scale of models is still exploding. Many institutions predict that:

Model parameter scale will grow about 10 times each year. Second: The demand for computing power during the inference stage is skyrocketing. With the development of inference capabilities and reasoning (thinking-type AI), models require more tokens to answer questions.

Token usage during the testing phase:

May grow more than 5 times each year. Third: Token costs must continue to decrease. For AI to be applied at scale, the cost per token must continue to decline.

The industry trend is roughly: A decrease of about 10 times each year. These three things combined create a huge problem: The demand for AI computing power far exceeds the existing infrastructure.

In other words: The real bottleneck of AI is no longer just the GPU.

But rather: Electricity data centers energy efficiency. Vera Rubin's design goal is actually very clear: to directly address the energy and computing power bottleneck of AI.

If NVIDIA's roadmap holds, the logic of future AI computing will evolve into larger models, more complex reasoning, and lower token costs. These changes will further drive AI Agent, AI search, and AI automation systems into a truly large-scale application phase.

From an industrial structure perspective, the next round of AI competition is not just about model competition. It will be a comprehensive competition in chips, computing power, energy, and infrastructure. #Meta收购Moltbook