Be myself. I am what I am

Joined December 2015
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Floating Pisces retweeted

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$NBIS Hidden gem many don’t know about (ClickHouse) So I gained a lot of followers because of this company, and I already explained what Token Factory is and how it is important for $NBIS. However, there is one more asset Nebius owns that many investors either overlook or underestimate its potential. Let me present you: ClickHouse It is an open-source columnar database designed for online analytical processing (OLAP), originally developed by Yandex. To explain it in basic terms, if you store data in databases (most typical transactional databases like PostgreSQL or MySQL), you do it row by row, because, for example, banks often want to search information about a given customer, so they just search for the ID of the customer, and the whole row pops up and they get everything about the customer they care about. But imagine you have 1 billion rows, 50 columns, and you care about, for example, the average spending in the whole database. This is where ClickHouse comes in and uses column-by-column storing. Then, instead of reading 50 billion values, a column-based database might read only 1 billion values. Obviously, the idea is more sophisticated, where ClickHouse developed additional compression algorithms, but for our explanation, this is sufficient, as you now know what ClickHouse does. Importantly, the main advantage is that it often stores data using 5-10x less space than traditional databases. To give you an example, imagine you operate 100,000 GPUs and every second, that GPU sends information such as: - timestamp - GPU ID - temperature - utilization - memory usage 100,000 GPUs -> 1 month = 259,200,000,000 records And now an engineer asks: "What was the average GPU utilization by hour last week?" Instead of going through all rows, the query only needs timestamp and utilization and you save a lot of time. And you know who uses ClickHouse? The biggest players such as OpenAI, Anthropic, Meta, Tesla, Cisco, Alibaba, Spotify and many others. So, now that you get the importance of the company, what if I told you that $NBIS owns approximately 28% of ClickHouse and its valuation is growing rapidly. In May 2025, the company was valued at rougly $6.35B In January 2026, the valuation increased to $15B, which is ~236% increase in 7 months, think about the speed of this. If we would expect the company to "only" double its valuation throughout the whole 2026, we would get to $30B. Implying $NBIS’s stake being worth $8.4B (current market cap is $59B). What’s funny is that many investors have no idea what ClickHouse is and they think it is just some small partner or whatever, but it might soon represent $10B stake for $NBIS. If you have any questions, I am happy to answer them as always. Thanks for reading!
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It was a good one, I guess Thank you @HarryStebbings
Weekend listening: @romanchernin on @20vcFund with @HarryStebbings talking AI infrastructure bubbles, why cheaper compute creates more demand, and why the compute market is nowhere near its ceiling. YouTube or any podcast platform → youtube.com/watch?v=aXAH3bdJ…
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Less than 2 months ago, TD Synnex announced they have reserved over 1000 B300 dedicated instances from $NBIS for distribution to enterprise customers. It is already SOLD OUT, and they are "taking orders and planning for cluster 2.0." crn.com/news/ai/2026/exclusi…
$NBIS @nebiusai X TD SYNNEX NA DEDICATED GPU CLUSTER SOLD OUT! linkedin.com/posts/deanarchi…
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JPM boosts $NOK TP to $21 (prev $14,) cites 'new wins in data center switching add another leg to Nokia's growth (..) and the likely continued growth in optical orders make us positive on order momentum in AI and cloud through ‘26.'
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JUST IN: $NBIS, $RKLB, $ALAB and $CRWV just joined the Nasdaq 100.
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From Goldman Sachs analyst report on $NBIS: "We attended Nebius' Inflection event in San Francisco where we met with CEO Arkady Volozh, COO Ophir Nave, CRO Marc Boroditsky, Chief infrastructure and Product Officer Andrey Korolenko, and Head of IR Gili Naftalovich. Key takeaways include: 1) Agentic Al shifts focus from scale to reliability and cost control, 2) Power procurement and geographic diversification underpin capacity roadmap, 3) Vendor diversity supports CPU availability and mitigates emerging supply constraints, and 4) Differentiated customer offering supports long-term growth ambitions. " GS reiterates Buy with a 12-month price target of $267 (vs $234 prior) Analysts are generally still in the catching up mode
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Nebius wins Best AI Platform & Infrastructure at the National AI Awards 2026. Recognized for best-in-class scalability, innovation across the full AI stack, and proven ability to solve complex infrastructure bottlenecks. #NationalAIAwards
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Today @Citadel has come out and covered the shift toward cheaper AI models This is squarely in line with my thesis x.com/Moshaikh/status/206471…
The most basic way AI could blow up imo. I'm not saying it does but this is the most obvious way I can see it happening - Per seat subscriptions are massively subsidized. The flat fee was priced way below what heavy usage actually costs - For real business use you have to move to the API anyway. Data protections, work integrations and compliance officer approval - On the API you pay metered rates, and businesses are burning credits way faster than the per seat pricing ever led them to expect - This is everywhere right now. Internally for us, Codex users, Uber torching its entire 2026 AI budget in 4 months, the Microsoft comments. Just go try an API I shared more on this here: x.com/Shaughnessy119/status/… - And I don't think most businesses have the money to keep paying increasing API rates without a real change to how they operate (caps needed) - Because they have a cheap alternative. They can reach open source models through any aggregator (OpenRouter, Venice, Baseten, Together) and still get strong privacy. Venice private data centers, or E2EE/TEE serving GLM 5.1. More on open source inference provider raises here: x.com/Shaughnessy119/status/… - And the discount is enormous. DeepSeek V4 codes within a hair of Opus on SWE bench at roughly 1/30th the price, and the cheapest open models run closer to 1/100th - Chinese labs open source frontier grade models. The model is the single biggest cost an inference provider has, and they get it for free - This idea dies if China goes closed source. That is actually bullish web2 AI labs, because if everyone is closed you pay up for the best intelligence. China goes closed source if they are tired of giving away an asset and they want the revenue and data flow to train new models - Is this showing up in web2 AI lab revenue yet? No. Revenue is off the charts. Anthropic went from 9B to 47B run rate in five months - So go forward, what happens? - I think revenue slowly starts leaking to the open source inference providers (see Venice usage, OpenRouter's $113M raise, Baseten is raising at $11B or triple its valuation in three months, on revenue that went from $200M to $600M annualized in a single quarter) - It doesnt move overnight, but it caps the labs ability to raise prices, and margins are already deeply negative. OpenAI is reportedly running near negative 122% - With margins that bad there is no cash flow, so the labs are fully dependent on outside capital to buy GPUs, train models, and keep subsidizing usage (I.e. see Google tapping $80b equity sale, granted 30b for employee RSU taxes. Clearly they think Equity is overvalued or you wouldn't sell it) - The break comes when that capital stops. Pricing is capped so margins cant improve, and the moment investors lose conviction on payback, the whole flow reverses - Why would they lose conviction on payback? Back to the start - the inability to improve margins or get businesses to pay more - This is also limiting, if we start making new drugs with AI or create entirely new businesses, you better believe people will pay up to the max for AI usage
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$VELO: SpaceX’s #1 employees and Impulse Space Founder Tom Mueller highlights Velo3D at their factory floor on the @sourceryy podcast last week. Full video: youtube.com/watch?v=WIORHdlP… (h/t @tb_travis)
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NEBIUS WILL TAKE CARE OF YOU! $NBIS
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Nebius is not a Hyperscaler and not a NeoCloud But an AI First Cloud at Scale Made by engineers for engineers #nebiusinflection
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Actually, the perfect summary. That’s what we do. Build 4 layers of the AI cloud.
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$NBIS Nebius signed a 10-year agreement for a 22MW AI infrastructure deployment at Kao Data’s Harlow campus in the UK. The project will support Nebius AI Cloud and Token Factory services and is part of the company’s previously announced £1.7 billion UK investment.
$NBIS Nebius is investing £1.7 billion to expand AI infrastructure in the UK, with three new $NVDA powered deployments expected to reach 65MW of capacity by 2027. The company is also expanding its London AI R&D hub and building partnerships with universities as it deepens its long-term presence in the region.
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🚨 $NBIS is investing ~£1.7B to expand its AI infrastructure footprint in the UK. Nebius will add three new deployments of NVIDIA’s latest full-stack AI infrastructure, bringing its total UK capacity to 65 MW once fully ramped in 2027. The company launched its first UK Blackwell Ultra deployment in November 2025, so this represents a meaningful expansion of its presence in one of Europe’s most important AI markets. Importantly, this isn’t just capacity built ahead of hypothetical demand. British customers are already running production workloads on Nebius at scale.
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Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor. It’s happening faster than we thought, and the implications deserve greater attention. anthropic.com/institute/recu…
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Jensen: Asian parents' culture, toxic😟 I know they love me, I usually “alright, alright..." 黃仁勳今天說了內心話 一路過來真不容易 “亞洲父母有毒 總是會糾正你“ "我63歲了 他們依然覺得我不夠好“
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$NBIS JUST IN: Famed Billionaire Ron Baron’s Fund Baron Capital Group initiated a position in Nebius in Q1 From Baron Capital: “Nebius is a Big Idea with a remarkable origin story – the company was born from Yandex, popularly known as the “Google of Russia,” which founder Arkady Volozh built into a $30 billion business over 25 years with leading positions in online search, e-commerce, ride-hailing, music streaming, maps, and cloud services. After Russia’s invasion of Ukraine, Volozh divested all Russian assets in the largest corporate exit from Russia in history ($5.4 billion), reconstituting the company as Amsterdam based, Nebius. The company boasts a world-class 1,300-strong team of engineers with decades of experience building large-scale computing systems and a vision to build a leading AI cloud business from first principles – a purpose-built vertically-integrated hardware and software stack optimized for AI workloads. Nebius’ long-term vision requires significant resources to build the physical infrastructure and acquire customers. In the interim, Nebius is strategically and very selectively signing bare-metal GPU deals (renting the data center with the GPUs installed but no software on top of the GPUs) with Microsoft (up to $19 billion) and Meta (up to $27 billion). While there is a range of outcomes on the long-term value of GPUs in a bare-metal model (with the main concern revolving around the rapid depreciation of old GPUs as new more efficient ones are introduced), the useful life of AI accelerators appears to be longer than previously anticipated, as the economic output of GPUs (as measured by token throughput) has been increasing over time as models have improved, meaning project returns get better with age. Dylan Patel of SemiAnalysis explained the dynamic on the Dwarkesh Podcast (March 2026)14: GPT-5.4 from OpenAI generates more tokens on H100s than GPT-4 did, despite being a far more capable model, because newer architectures (such as sparse mixture-of-experts) are more computationally efficient per token. The implication is that an H100 is worth more today than when it was purchased three years ago. For Nebius, this means the residual value of its GPU fleet after long-term contracts expire could be substantially higher than depreciation schedules assume. The rapid growth in AI-demand has also driven H100 one-year rental prices higher by approximately 40% from $1.70 per hour in October 2025 to $2.35 per hour by March 2026 (SemiAnalysis, March 2026),15 even as NVIDIA’s newer Blackwell GPUs entered the market. In our view, as long as incremental AI token demand exceeds the token supply enabled by the new chips produced in a given year, older GPUs retain – and can even gain – value (as long as token throughput increases over time as models improve – despite an increase in intelligence). More importantly, these deals function as a quasi-financing mechanism for the AI cloud buildout. Meta's deal in-particular provides access to investment grade borrowing costs with no equity dilution, while acting as a backstop customer if enterprise demand for the AI cloud doesn't materialize on schedule.” At today's price, we are essentially buying a contracted bare metal business and a portfolio of valuable stakes at a fair price, and getting what could become a very big idea, as one of the world's next great AI cloud platforms with a world-class Founder/CEO and a team of engineers who have succeeded before at an attractive entry point. We have conviction in Nebius' ability to build a large AI cloud business. They are leading the neocloud space in building a full suite of software offerings on their platform, much in line with what the big three hyperscalers have built for cloud workloads, i.e., multi-tenant compute, unified storage, inference-as-a-service, and security certifications, the kind of platform depth that took incumbents years to assemble.” baroncapitalgroup.com/articl…

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