Anthropic told investors it could reach operating profitability for the first time in Q2. Quarterly revenue is expected to more than double to about $10.9 billion.
At the same time, reports say Anthropic agreed to pay xAI $1.25 billion per month for compute capacity at the Colossus 1 data center near Memphis.
The deal covers the facilityβs full 300-megawatt capacity and runs until May 2029. In total, the contract could generate more than $40 billion for xAI.
One AI company is becoming profitable by sending billions to another AI companyβs GPUs.
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On this day in 2010: 10,000 Bitcoin were used to buy two pizzas.
Today, theyβd be worth $765 million.
βοΈ @venture
Today, theyβd be worth $765 million.
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Manus founders are reportedly trying to reverse the companyβs sale to Meta after pressure from Chinese authorities.
One option under discussion is raising $1 billion from outside investors to buy the company back. Manus could then be restructured as a Chinese joint venture and eventually listed in Hong Kong.
The startup originally launched in China and later moved operations to Singapore to make a future sale easier.
The twist is that Beijing stepped in when the Meta deal was already near completion. Employees had reportedly moved into Meta offices in Singapore and investors had already received payments.
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On this day in 2002: Netflix went public.
$10,000 invested in the IPO would be worth $7.4 million today.
βοΈ @venture
$10,000 invested in the IPO would be worth $7.4 million today.
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TechCrunch spoke with founders, investors, and finance operators who say many AI startups are stretching the meaning of ARR to boost growth narratives.
The main trick is replacing real ARR with βcontracted ARRβ or annualized projections. In some cases, startups reportedly counted revenue from customers who were not fully onboarded yet, long pilot programs, or contracts that may never convert into payments.
Several investors admitted the practice is common and often tolerated because everyone is chasing the same AI growth story. One VC said some companies report CARR that is 70% higher than actual ARR.
The pressure comes from AI valuations. Investors now expect companies to jump from $1 million to $100 million revenue at record speed.
In AI, revenue headlines are becoming part of the marketing stack.
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Retail traders spent 2026 piling into Nvidia, Tesla, Micron, Sandisk, and other AI infrastructure plays.
The strongest signal came during the DeepSeek panic in January, when Nvidia lost almost $600 billion in market value in one session.
Robinhood users responded with the highest buy-to-sell ratio for Nvidia seen in the last 3 years.
The same pattern showed up across other selloffs. Traders kept buying discounted AI names while taking profits in stocks that had already run hard.
Retail is still playing one trade.
Buy the panic. Hold the AI winners.
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Most investors donβt understand how brutal losses really are.
Down 50%?
You need +100% just to break even.
Down 80%?
You need +400%.
This is why βcheapβ stocks can be dangerous.
And why protecting capital matters just as much as finding winners.
βοΈ @venture
Down 50%?
You need +100% just to break even.
Down 80%?
You need +400%.
This is why βcheapβ stocks can be dangerous.
And why protecting capital matters just as much as finding winners.
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Investor Joseph Jack from OSS Capital projects Anthropic's ARR to jump from $1B in January 2025 to $30B by April 2026, with growth accelerating rather than slowing. Even a conservative slowdown scenario predicts $100B revenue by end of 2026 and $340B in 2027.
Anthropic builds AI models and enterprise software, rapidly expanding its client base. The number of customers spending over $1M annually doubled to 1,000 in under two months, fueling fast scaling and market capture.
Demand for Anthropic's Gemini tokens grew 10x last quarter, far outpacing Alphabet's 60% growth. This rapid adoption narrows the revenue gap, making it likely Anthropic will overtake Alphabet around mid-2028 at $575B revenue.
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Nvidia CEO Jensen Huang says the companyβs next major opportunity is CPUs built for AI agents.
The new chip, called Vera, is described as Nvidiaβs first processor designed specifically for agentic AI. Huang says GPUs will handle the model reasoning, while CPUs will manage the growing workload created by autonomous agents.
According to Huang, Vera opens a $200 billion market for Nvidia. The company has already sold $20 billion worth of these processors this year.
AI agents are creating demand for more than just GPUs now.
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An Uber driver in San Francisco said he was actually a startup founder and asked passenger to sign an NDA before hearing his idea.
βοΈ @venture
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Ferrari stock dropped sharply after the company unveiled Luce, its first fully electric car. Shares in Milan fell about 8% following the presentation.
The Luce was designed with LoveFrom, the studio of former Apple designer Jony Ive. Ferrari says the car opens βa new chapterβ for the brand, but reactions from investors and fans were mixed.
The car starts at around β¬550,000 ($640,000), reaches 100 km/h in about 2.5 seconds, and deliveries are expected to begin later this year.
Analysts said part of the backlash comes from fears that a fully electric Ferrari moves too far away from the companyβs identity built around combustion engines and classic supercar design.
Ferrari spent years building one of the strongest brands in the auto industry.
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Nvidia CEO Jensen Huang publicly warned Super Micro Computer after Taiwanese authorities detained three people accused of using fake shipping documents to move Nvidia-equipped servers into China.
Taiwanese prosecutors raided 12 locations in the islandβs first major semiconductor smuggling crackdown tied to AI hardware exports. The servers were reportedly routed through Hong Kong and Macau.
Huang said Nvidia clearly explains U.S. export rules to partners and placed responsibility on Supermicro to enforce compliance downstream.
The case follows a broader U.S. investigation into a reported $2.5 billion illegal AI hardware pipeline announced earlier this year.
AI infrastructure is becoming part of export control politics now.
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Taiwan and South Korea overtook the UK thanks to chip giants TSMC and Samsung.
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SoftBank owns about 13% of OpenAI and has invested roughly $64.6 billion, mostly not its own cash. It sold $6 billion in Nvidia shares to fund the initial stake without debt.
In March, SoftBank took a $40 billion bridge loan at 8%, paying it to OpenAI but due in a year. In April, it borrowed another $6 billion using its OpenAI shares as collateral.
If OpenAIβs IPO delays or valuation drops, SoftBank risks default and heavy losses. The company is uneasy, but Masayoshi Son ignores warnings.
SoftBank faced a similar fate in 2019 with WeWork, losing $10 billion after a failed IPO. This time, the stakes are 15 times higher.
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In December, Microsoft made a deal with Anthropic and encouraged engineers to use Claude Code. The tool quickly gained popularity among developers.
Now Microsoft plans to cancel its Claude Code license and switch to Copilot CLI. Developers on major products like Windows and Microsoft 365 must move all data from Claude by the end of June.
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The Information estimates Anthropic currently generates at least 35% more annual revenue than OpenAI. Earlier this year, OpenAI led by nearly $1 billion.
Anthropic develops AI models similar to OpenAI's, focusing on large language models and AI safety.
Growth at Anthropic is accelerating while OpenAI sees slowing user growth. This shift could impact their upcoming IPOs.
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The new version improves coding, agent workflows, and reasoning performance while keeping the same pricing: $5 per million input tokens and $25 per million output tokens.
Claude Code now supports dynamic workflows. The model can break large tasks into parts, run parallel subagents, and review results before responding.
Anthropic also says Fast mode for Opus 4.8 is 2.5x faster and 3x cheaper than previous models. The company claims the model is also about 4x less likely to miss bugs in its own code.
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Uber's COO said heavy AI spending is hard to justify as token consumption grows without clear consumer benefits. The company used its annual AI budget in just 4 months.
Nvidia's VP noted their compute costs now exceed employee expenses, showing AI is becoming more expensive than human labor.
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