This is what “starting” really looks like.
Stop waiting for the perfect time.
Stop waiting for the perfect conditions.
Stop waiting for a magic moment.
Action first, clarity later.
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Stop waiting for the perfect time.
Stop waiting for the perfect conditions.
Stop waiting for a magic moment.
Action first, clarity later.
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It’s one of the largest robotics deployments in history.
Most people missed how fast this happened:
That implies hundreds of thousands of additional units added each year - thousands deployed every week.
This isn’t “cool tech.”
It’s about labor cost, fulfillment speed, and margin expansion.
Every robot:
A bet on $AMZN today is a bet on automation on steroids, not just ecommerce.
The retail margins story hasn’t even started yet.
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This sets a new benchmark for standalone data center size. Catching up on raw scale will take competitors time.
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Define the game you’re playing, and make sure your actions are not being influenced by people playing a different game.
- Morgan Housel
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- Morgan Housel
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After a long IPO drought, Wall Street is preparing for deals that could reset expectations for tech listings.
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Assets under management at BlackRock
Last year, BlackRock recorded a record inflow of new capital.
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Last year, BlackRock recorded a record inflow of new capital.
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Venture Capital
Meta spent $73B on this. ✔️ Subscribe on @venture
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The biggest advantage you can have as an investor is being deeply comfortable with high levels of uncertainty.
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A Bloomberg analysis puts the family’s net worth at about $6.8B. Around $1.4B of that was added from crypto over the past year, making digital assets close to 20% of total wealth for the first time.
Crypto became the main growth engine:
Other parts of the empire moved in the opposite direction:
The family’s balance sheet now moves with crypto markets as much as with property cycles.
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Venture Capital
The timing matters. The exits land while fundraising is ongoing and questions around product direction remain unresolved.
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A controversial story has surfaced around Nvidia and the use of pirated book datasets to train AI models.
In early 2024, a group of authors sued Nvidia, claiming the company trained models on Books3, a known pirated dataset containing hundreds of copyrighted books. Nvidia responded at the time that this fell under fair use.
The case is still ongoing, but a new filing has added fresh detail. Newly revealed correspondence shows contact between an Nvidia employee and Anna’s Archive, a large shadow library hosting pirated books and academic papers.
What the messages show:
The exact scale and payment details are unknown, but reports estimate the dataset at roughly 500 terabytes, potentially millions of books.
The situation may go further. The plaintiffs claim Nvidia likely used other shadow libraries such as LibGen, Sci-Hub, and Z-Library, and may have distributed internal scripts allowing corporate clients to automatically download similar datasets. These claims have not yet been proven.
The lawsuit continues.
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Over the past few days, headlines around OpenAI finances have intensified. The core narrative is simple. Cash burn is accelerating, and the gap between costs and revenue keeps widening.
Here is what the numbers say.
The real issue is not access to capital today. It is scale. If revenue does not grow by an order of magnitude while costs keep compounding, even very large checks only buy time.
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The sale of TikTok’s US business was approved by both the US and Chinese governments. The asset was valued at $14B, with additional fees paid to the US government for brokering the deal.
Ownership after the transaction:
The company will be run by Adam Presser, currently deputy CEO of global TikTok.
Structurally, this resolves years of regulatory pressure. TikTok’s US operations now sit under American control, while the product and brand stay intact.
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OpenAI CFO Sarah Friar said the company is exploring business models beyond subscriptions. The reason is cost. Compute spending keeps rising, and flat fees do not scale with outcomes.
What OpenAI is considering:
The second part is the shift. In some cases, OpenAI would take a share of intellectual property or future revenue. One example mentioned was drug discovery, where an AI-generated molecule could trigger a claim on patent value or sales.
This would not apply to regular users. The focus is enterprise contracts in areas like pharmaceuticals or energy, where AI output has direct commercial value.
The model moves OpenAI closer to revenue sharing based on results, not usage.
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