JAMIL BARRAGE

Founder and Chief Investment Officer, 2XL Capital Partners.

[Toad Capital @rich_toad]

Tiger Management thought he was applying for IT support.

He launched his hedge fund in 1999. Months later, the Nasdaq fell 75%. Not exactly ideal timing.

Philippe Laffont wasn’t supposed to be a hedge fund manager. He studied computer science at MIT and wanted to work in tech. When Apple said no, he went to Chile for six months, learned Spanish, and basically fished all day.

Then he moved to Spain and ended up in a basement office at his wife’s family business with nothing to do. So he started reading stock listings in the International Herald Tribune.

He bought Microsoft, Intel, and Dell.

When he came back to the U.S., he had no finance background and no Wall Street network. He worked unpaid at mutual fund just to learn the language of finance.

He hustled for a shot and a friend got him two minutes with Julian Robertson and said exactly what he wanted: to pick tech stocks at Tiger.

That bet on himself worked.

After a few years at Tiger Management as the telco and tech analyst, Laffont started Coatue with $45M — without Julian backing him — right before the dot-com collapse.

The firm survived. Then it evolved. Then it became one of the most influential tech investors in the world.

Full story of Coatue Management: https://t.co/UH27PBugIB

[zerohedge @zerohedge]

Trump trying to pump Micron

[Bob Elliott @BobEUnlimited]

The Chinese extended malaise in a single picture. And getting even worse in recent months.

[Leonardo Otero @Leonardootero61]

essa é talvez a melhor entrevista com um trader que eu já vi, esse vídeo é só um trecho. é fácil encontrar a completa na internet. quem ainda não assistiu, recomendo muito!

[Xiaoyin Qu @quxiaoyin]

China's AI strategy: 1. Government invests in Deepseek, subsidizing labs to open source everything. 2. Building nuclear and data centers everywhere fast to lower inference cost, regulating it like electricity. 3. Making sure people learn AI fast, especially government officials must know how to use AI. US's AI strategy: stock price going up and to the right. Export control. Takes forever to build a data center because of permits and regulation. It's time to change.

[Vivi @vivilinsv]

我特别喜欢和欣赏的一位连续创业者 @quxiaoyin 晓音，这两天在 X 上火起来了。

她提出一个很尖锐的判断：中国开源模型会持续获得市场份额，甚至可能成为美国 AI 生态的“最坏情境”之一—如果中国模型不仅占据 model layer，还逐步适配华为等国产芯片，叠加美国数据中心建设速度不够快，那么 AI 竞争就不只是模型之争，而是模型、芯片、算力、成本和生态的系统性竞争。

这个观点被 @a16z 创始人 Marc Andreessen @pmarca 转发后，引起AI 圈大规模讨论。

我自己的看法是：open source / open-weight models 的重要性会越来越高。它们给企业带来更低成本、更强可控性、本地部署、私有数据微调，以及对单一闭源 API 供应商的议价能力。尤其当 AI 成本越来越高、地缘政治和合规限制越来越复杂时，开源模型会成为很多企业的战略选项。

但现在说谁会最终胜出，还太早。

闭源模型仍然在 frontier capability、稳定性、工具链、企业服务、安全合规、生态集成和品牌信任上有明显优势。未来更可能不是“开源打败闭源”或者“闭源统治一切”，而是一个混合格局：最前沿能力仍由少数闭源巨头推动，而大量应用层、企业层、本地化和成本敏感场景，会越来越依赖开放模型。

真正的竞争，可能不只是模型本身，而是谁能掌握完整生态：模型能力、推理成本、芯片适配、开发者社区、企业工作流、数据闭环和信任机制。

无论你是否完全同意晓音的判断，这都是一个值得认真讨论的问题：AI 的未来，到底会集中在少数闭源平台里，还是会被开放生态重新分散？

最后也想私心推荐一下晓音。她不仅是非常成功的连续创业者，也特别热心、真诚、善良，长期在分享创业和 AI 相关的高质量内容。欢迎大家关注她的视频号「曲晓音 - 创业脱口秀」，也可以关注她最新的创业项目 @tycoonai。😇

[Xiaoyin Qu @quxiaoyin]

if US bans open source because China is leading, then
1. impossible to enforce(you just need to download a zip for weights)
2. Increases the cost of using AI for US companies and consumers, while China leads in enterprise and consumer adoption which drives GDP growth and productivity gains
3. Gives away market share to China for countries who don't follow the ban(which will be many)
Banning open-source might benefit labs, but only in the short-term, as they will lose long term regardless. It will harm independent neoclouds, enterprises and consumers. Because you forcefully drive up the cost of using intelligence by 100x compared to China, and if everyone in China and ROW can afford the good-enough intelligence but only not in the US, will this benefit US in the long run?

[Peter DiCarlo @pdicarlotrader]

Last time this setup appeared on $NOW, price moved +44% in one month.

It is back again. And I am not taking this trade.

In today’s video I cover:
• The current setup using my rules based framework
• The exact levels I am watching
• Why I am standing aside here despite the same signal

Full breakdown here 👇

[Bloomberg @business]

In the China tech space, Baidu is now a full-stack player in the AI industry. As the maker of its own chips, AI model (Ernie), cloud system and a self-driving car business (Apollo Go), the tech giant is a very desirable company to work for.

On this episode of the Odd Lots podcast, Baidu CFO Henry He joins @TheStalwart and @tracyalloway to discuss how the company uses AI to evolve its own organizational structure and attract new talent. Listen at https://t.co/RqFaugaTL4 or watch at https://t.co/fcjUvfje6d.

[Brian Coughlin @EquityBrian]

Baidu’s chip unit Kunlun is reportedly targeting a $50B valuation for its Hong Kong IPO.

$BIDU owns about 58% of it.

That stake alone would be worth roughly $29B, while Baidu’s entire market cap is only around $37B

https://t.co/7nTcb6mqH6

[Damir Akaza @Damir_Akaza]

Larry Robbins, founder of Glenview Capital with around $5.6 billion in assets under management, presented nine companies across three market categories at the Sohn 2026 conference

"Forty-one stocks in the S&P doubled in a year, while almost a third fell in a rising market, we've never seen this kind of dichotomy"

The man who pitched Teva and Global Payments a year ago, and both worked out, explains in ten minutes which beaten-down stocks with turnaround potential to step into and which doubled names are still cheap

bookmark it and you'll learn how a manager of serious capital plays this fragmented market ↓

[Thomas J. Hayes @HedgeFundTips]

Be in the know. 14 key reads for Monday… #StockMarket
https://t.co/xCZT4GTNnY

[Chubby♨️ @kimmonismus]

The worst-case scenario for the United States is becoming increasingly realistic, and I will briefly explain why.

@quxiaoyin raised many valid points, and I agree with her. First of all:

-China certainly does not place such strong emphasis on open source because it cares so deeply about humanism, but because it is a strategy to attract many users, gain market share, put pressure on US models, and also because the models are increasingly being trained on Huawei hardware (think of DeepSeek 4), allowing China to host the entire stack domestically.

-But the underlying logic is far more important: The United States is still building too few data centers to meet future demand. @ChrisGillett wrote an outstanding analysis on this, which I shared a week ago. In short, based on SemiAnalysis data, demand is greater than what is currently being built in terms of data centers.

-Even more importantly, however, the United States lacks sufficient energy and grid capacity. This is a problem that will become much more severe in the near future. China, by contrast, is addressing the issue through a massive expansion of its energy supply. Solar capacity: in 2025 alone, China installed as much solar capacity as the United States did in 10 to 15 years. China is also building 36 nuclear power plants, significantly more than the United States, and is installing them faster.

-In addition, China is managing to become more independent through Huawei chips, even though the country still lags far behind NVIDIA. But here, China is betting on quantity rather than quality.

In short: China is a real threat in the AI race, and the situation for the United States is becoming increasingly precarious. This is also the main reason why China is to be kept away from SOTA LLMs at all costs, so as not to jeopardize the lead under any circumstances.

[Xiaoyin Qu @quxiaoyin]

Deepseek is funded by Chinese Government VC directly in their most recent funding round. Chinese models will continue to be better, faster, cheaper and open. Meanwhile US models are export controlled, expensive, and not open. Why do you think US will win with this strategy? It's time to change strategy.

[Whale Insider @WhaleInsider]

JUST IN: 🇨🇳 Ex Meta PM and AI founder Xiaoyin Qu says “American and European enterprises will ditch OpenAI and anthropic and adopt Chinese models.”

[Poe Zhao @poezhao0605]

Baidu's chip unit Kunlun is reportedly targeting a $50 billion valuation for its Hong Kong IPO. Baidu's total market cap is $36 billion. A subsidiary worth 40% more than the company that owns 58% of it.

The math creates a logical paradox. If Kunlun is worth $50 billion, Baidu's stake is worth $29 billion. That leaves the rest of Baidu -- search advertising, AI cloud, Apollo Go robotaxi, iQiyi, and $28 billion in cash -- with an implied value close to $7 billion. For a company generating $32 billion in quarterly revenue. The market is either wildly overpricing Kunlun or severely underpricing everything else inside Baidu.

[Xiaoyin Qu @quxiaoyin]

Why do you think hosting Chinese open source models on your own GPUs is less trustworthy and secure than giving away your data to anthropic and being shut down access at any time because they think you are doing something they consider “not safe”?

[Podcast Alpha @PodcastAlphaX]

Micron at $60. Micron at $1,200. Visser is still buying.

Jordy Visser @jvisserlabs held this thesis from the start and still says the second derivative scares people who do not read the call.

Earnings growth slows from 400% to maybe 50% year-on-year. That is a slower rate of growth, not a reversal. Memory is the bottleneck, and the bottleneck commands the premium.

His call: Micron reaches a $2T market cap within a year. He sold too early and now holds Marvell as the adjacent play.

The full deceleration-vs-collapse case: https://t.co/3uBnyBSjWD

Source: Anthony Pompliano Podcast - https://t.co/2XyjaZKO6i

[Fareed Zakaria @FareedZakaria]

The relationship between the US and Israel is growing increasingly strained. Will it bounce back, or is it altered forever? I discussed with Jake Sullivan in part 2 of our conversation:

[Cassandra Unchained @michaeljburry]

No paywalls!
Two free recent articles-
The Heretic’s Guide to AI’s Stars Part III:
(AI Demand, Offshore Financing, etc)
https://t.co/0QxhGcXbLT
Software & Payments Stocks Part II: Productivity Tools and Cybersecurity
(Part 2 of 6)
https://t.co/yEl65szBsM