𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛)

Cryptocurrency Enthusiast, Austrian Economics Reader, Blogger, Author Co-Founder @MkulimaExports(

[𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛) @dmutanga]

I just published
https://t.co/RhUAXrPEQU

[𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛) @dmutanga]

How to grab onto an England victory https://t.co/4iafC398T5 via @politico

[𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛) @dmutanga]

@Dominovito @BulawayoForever https://t.co/Vf23YNbvHT

[𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛) @dmutanga]

@Dominovito @BulawayoForever Demise of the apartheid regime? Apart from Cuba, which other African armies took the opportunity to give the enemy a mortal wound?
As for the Rhodesian military, it is argued to be one of the most effective in history
https://t.co/3ZvJe5RrDc

[𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛) @dmutanga]

@Dominovito @BulawayoForever The problem with X is that history is reduced to point-scoring. We approach it with a bias that we wish to portray. Was the war in Angola not the death knell of the apartheid regime? War needs money, and through this misadventure, South Africa bled its coffers, leading to

[𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛) @dmutanga]

Once upon a time, there were NFTs...

[Ricardo @Ric_RTP]

Mark Zuckerberg is bankrupting a $22 billion startup because they refused to sell to him.

The company is Kalshi.

They run the largest prediction market in the US. Users bet real money on real-world outcomes.

Last year, prediction markets did $28 billion in monthly volume across the industry.

This month, they did $220 BILLION.

The sector literally 8x'd in a single year.

Bernstein now projects the entire prediction market industry will hit $1 TRILLION by 2030.

Zuckerberg saw the growth curve coming. Last year, when Kalshi was valued at only $2 billion, he sat down with founder and CEO Tarek Mansour to discuss buying the entire company.

Mansour said no.

Kalshi went on to raise at $11 billion in December. Then $22 billion in March. It is now pursuing a $40 billion round and openly weighing an IPO.

Zuckerberg's response:

He walked back to Meta headquarters, took every piece of information he learned in that meeting, and directed a small internal team to build a Kalshi clone from the ground up.

Meta's version is called Arena. It uses Llama to generate the questions. Every one of Meta's 3.5 billion daily users will get access.

And here's where the plan gets ruthless...

Meta is deliberately launching with play money. That single decision lets Zuckerberg dodge every gambling regulator on Earth while he trains billions of users to bet on prediction markets.

Meanwhile Kalshi is spending millions fighting state gambling laws, the CFTC, an Illinois sports tax, a Minnesota felony statute, and the Department of Justice.

Kalshi is the crash test dummy. Meta is the getaway driver.

The moment the regulatory war is settled, Zuckerberg flips the switch. Arena becomes a real-money market, and 3.5 billion users are already trained to use it. Kalshi's user base of a few million cannot compete.

This is the exact playbook Meta ran on Snapchat in 2016 when Instagram Stories launched. It is the exact playbook they ran on TikTok in 2020 when Reels launched. It is the exact playbook they ran on Twitter in 2023 when Threads launched.

The FTC took Meta to court over this pattern last year and called it "buy or bury." The judge sided with Meta. So the playbook is legally protected.

Tarek Mansour walked into a meeting with the most predatory copycat in tech history and gave him the entire pitch deck for the fastest growing product in Silicon Valley.

Six months later, Zuckerberg is executing on that intel while Mansour is stuck defending his company in courts across America.

Kalshi survived Zuckerberg's offer. But it probably will not survive Zuckerberg's clone.

Meta ended Q1 with $81 billion in cash. That is enough to buy every prediction market company on Earth six times over. Zuckerberg is choosing to STEAL them instead because he can, and because the courts already gave him permission.

The next 12 months will decide whether Kalshi becomes a $50 billion IPO or a cautionary tale about what happens when a founder says no to Meta.

What do you think?

[Sony Thăng @nxt888]

Multipolarity doesn't mean Western people will become poor.

It means they will become normal.

It means a Congolese engineer and a German engineer will negotiate on terms that reflect their actual value rather than the legacy of who colonized whom.

It means the dollar will be one currency among several rather than the rent the whole world pays to America for existing.

It means European countries will have to make foreign policy based on actual relationships rather than the assumption that their preferences automatically constitute the international consensus.

Normal.

The horror with which this prospect is greeted, the language of civilizational threat, of decline, of loss, tells you everything about how far from normal the current arrangement actually is.

And who it's normal for.

[Victoria Falls International Financial Centre @VFIFC_ZW]

VFIFC is Africa’s first purpose-built International Financial Centre. A transparent, USD-based gateway for global finance.

[Pushmeet Kohli @pushmeet]

The future of Math is mathematicians and AI agents working together.

Very pleased to introduce @GoogleDeepMind's AI co-mathematician: a multi-agent system designed to actively collaborate with human experts on open-ended research mathematics.

Mathematicians testing the agent across areas as diverse as group theory, Hamiltonian systems, and algebraic combinatorics have reported impressive results.

In autonomous mode evaluation on the rigorous FrontierMath Tier 4 problems, AI co-mathematician scored an unprecedented 48% — a new high score among all AI systems evaluated.

[Geoffrey Hinton @geoffreyhinton]

I just watched an amazingly good lecture by Adam Brown about the future impact of AI on physics
https://t.co/EjiKpoiKZr

[Yoshihiro Shibata @shiba_8ro]

noteの #Onshape 導入ガイドを更新しました。 Onshape(オンシェイプ)はWebブラウザ内で操作するクラウドベースの3DCADで、400万人を超えるユーザーが居ます。Windowsに限らずMac・iPad、Linuxなどマルチプラットフォームで個人でも団体でも無償で利用ができます。
https://t.co/Cik6fA8pFg

[EVA Robotics Lab / EVARL @UTokyo @evarl_utokyo]

EVARL@UTokyoのアカウントを作りました！フォローよろしくお願いします！

[Yoshihiro Shibata @shiba_8ro]

ﾏｶﾍﾞｪ氏は一生モジュラー型ロボットやってる印象

[𝕾𝖍𝖚𝖒𝖇𝖆𝕭𝕿𝕮(🌜,🌛) @dmutanga]

https://t.co/2nTkcpUNIC

[Russell Straub @russellstraub]

The next AI data center may not be a data center.

Sky Fusion is turning qualified homes into secure, behind-the-meter inference nodes.

We're using @8090_Factory's Software Factory to accelerate our MVP with AI — building fast, minimizing technical debt, and designing for full scalability from day one. 🚀

@chamath

[Zy @ZyMazza]

It is not. The saying originates from a time when kettles were polished metal, and pots were cast iron. The pot, seeing its own reflection in the shiny tin kettle, calls the kettle black.

[Yuchen Jin @Yuchenj_UW]

GLM-5.2 is the open-source Claude moment.

The demand we’re seeing at Databricks is astonishing. The world is going to see massive adoption of oss LLMs.

Also, more companies will shift toward post-training their own models on top of oss models and owning the weights.

[Ricardo @Ric_RTP]

This is the moment Chinese AI beat American AI.

One of the largest public crypto companies in the world just DUMPED OpenAI and Anthropic.

Coinbase switched to open-weight Chinese models from Zhipu and DeepSeek, and shaved nearly 50% off the company's internal AI spending.

The numbers are absolutely ridiculous:

Running the same enterprise workload through Anthropic's Claude costs $4,811. Running it through Zhipu's GLM 5.2 costs $544. That's a 9x price difference for equivalent output.

OpenAI's GPT-5.5 sits in the middle at $3,357. DeepSeek's V4 lands at $1,071. Moonshot's Kimi at $948.

On the actual benchmarks: Zhipu's GLM 5.2 scored 62.1 on SWE-bench Pro, the gold standard for coding. OpenAI's GPT-5.5 scored 58.6.

One AI researcher called GLM 5.2 "at least as good as Opus 4.8 and GPT 5.5." Another called it "the first open model that can really compete with closed-source systems."

The Chinese models are not just cheaper but they are now also beating American models on the benchmarks American companies pay $4,811 per workload for.

Coinbase did the math first and reacted - more companies will certainly follow.

Now watch what happens to the IPO timeline:

Anthropic confidentially filed for an IPO targeting October at a $965 billion valuation. OpenAI followed days later with its own confidential filing.

Both companies built their financial models on the assumption that they could keep charging enterprise prices that are 9 to 33x what Chinese competitors charge for the same task.

Brian Armstrong publicly proved customers WILL leave.

45% of companies are now spending over $100,000 per month on AI, up from 20% last year. Every one of those customers is one quarterly budget review away from dumping American AI.

OpenAI has reportedly already started preparing major token price cuts.

Anthropic is expected to follow.

And here's the thing...

The export controls were supposed to CRUSH Chinese AI.

The US government banned American AI chips, restricted model weights, blacklisted Alibaba and Baidu as Chinese military companies, and just banned Anthropic's flagship model from every foreign national on the planet. The entire premise of the American AI valuation bubble is that Washington can keep China two generations behind.

But Chinese labs responded by building cheaper, more efficient models on inferior hardware and pricing them at one ninth the cost of the American alternative.

And now American companies are voting with their checkbooks.

The dominant American labs are valued at nearly $2 trillion combined on the assumption that their pricing power is durable. Coinbase proved it is not, and every customer doing a year-end budget review will be looking at the same math.

For investors, the question here is what happens to the Anthropic IPO at $965 billion when the company is being forced to cut prices to defend share against open-weight Chinese models that score higher on the benchmarks.

For everyone else, the bigger question is what happens when Washington spent four years and billions of dollars trying to contain Chinese AI, and the only thing that actually shifted in the end was American customers.

[Marc Andreessen 🇺🇸 @pmarca]

Many smart people/AI insiders are saying GLM-5.2 is the first Chinese AI model to match and often beat the American big lab public AI models with no compromises. Incredible timing given current events.

[Dustin Ogle @DustinOgle33]

The catch: Most AI bills are still going up. Because People aren't routing to cheaper and capable models, the edge isn't which AI you buy.

It's that you stop using one.

Full breakdown - https://t.co/MNKwxdwAqE

[Xiaoyin Qu @quxiaoyin]

with Chinese open source models starting to dominate, we will see a booming self-training period where people can finally post train their models often and fast.