CHLOE @SantaChloe

$NVDA is expected to beat earnings next Wednesday after market closing. $SMH $SOXL

$AMZN cnbc.com/2025/02/05/ama…

$AMZN Amazon is due to hold an event on February 26

$COIN has the potential for the S&P 500 inclusion. investing.com/news/stock-mar…

$COIN has been oversold after beating earnings. And crypto is doing well.

$COIN Keefe, Bruyette & Woods analysts led by Kyle Voigt raised their price target on Coinbase shares to $305 from $255 while maintaining a Market Perform rating. Canaccord analyst Joseph Vafi increased price target to $400 from $280 while maintaining a Buy rating on the stock

$IBIT $BITX $COIN $MSTR $HOOD

Dyme @CryptoParadyme

a year ago

someone yeeted 700k worth of short term calls 6 minutes before close into $IBIT

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$BITX $IBIT $COIN $MSTR $HOOD $SOFI The three-day CoinDesk Consensus Hong Kong event will begin. The crypto conference marks the first expansion of the Consensus event series beyond North America. consensus-hongkong2025.coindesk.com

$AMD $INTC $SOXL ISSCC 2025 will be held February 16-20, 2025 at the San Francisco Marriott Marquis

$NVDA Bernstein reiterates Nvidia as outperform Bernstein said it sees little impact from tariffs on stocks like Nvidia right now. cnbc.com/2025/02/03/mon…

@realDonaldTrump Please investigate this DeepSeek and ban the app.

@amuse @amuse

a year ago

CHINA: China is illegally using American Ai technology made by $NVDA to build a powerful Ai model called DeepSeek R1. The LLM was released it for free using an open source license. This is a massive blow to US Ai companies like OpenAi and Antropic.

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$SPY $QQQ $NVDA $TSLA $META Deepseek Look, I’m not all about conspiracy theories They published a paper and it looks good Facts: they have 100% lied and own 50,000 H100’s and did something to break our laws Facts: in the paper u can see that they trained the model on 2048 NVDA GPUs and optimized the F out of those chips Now here’s a conspiracy theory and a fact at the same time and I actually think this has a higher mathematical probability when u put the math together… we don’t know if they used the 50,000 H100 super cluster to train a model that told them how to optimize the smaller cluster. Cause that’s literally a feature of AI They could have used the AI from the 50k super cluster to optimize the compression and then used that compression to Optimize the 2k cluster’s AI 🧐🧐🧐🧐🧐🧐🧐🧐🧐 That could have also told them how to reconfigure the actual structure and architecture of the chips forcing areas to work for other areas called Streaming Multiprocessors or as the nerds call it SM’s. Think of it like when the “Starship Enterprise” has to move its rear shields to add to the front shields to focus for a harder defense there Now making those kind of changes at that level kind of make it unstable for people who understand this stuff, it’s unstable because it’s difficult to maintain. This is why for those that remember my deep dives on NVDA I would go deep into CUDA and its importance.,. Well that’s CUDA’s whole thing. They allow u to not have to do all that Mickey Mouse 🐭 crap 💩 to it because you can do all that optimization for programming parallel tasks This makes CUDA more important to the hyperscalers if you understand any of that 🤷‍♂️ This is deep in the weed stuff I didn’t think I’d ever have to get into but you guys have seen me do deep tech dives in this so I have to Something is not exactly as it seems. @elonmusk feels the same Still Deepseek used a ton of NVDA GPU’s and if they’re more successful they will eventually need more of that hardware and if they are even more and more innovative they will want newer hardware that replaces several units for one Jevons Paradox Not financial advice!

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Banana3 @Banana3Stocks

a year ago

$SPY $QQQ $NVDA $META Deepseek Yes they have 50,000 H100’s They claim to have used only 2048 to train their new large language model By having a super cluster of 50k H100’s they could have practiced code and trained a few models to know what to optimize on a smaller cluster

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$NVDA Deepseek is so dumb

Wow. Everyone selling $NVDA for this 😂😂😂😂 yes, market all crashing for ever and ever because of this: THIS:

$SPY $QQQ $NVDA $META Even Deepseek agrees with me 😂 This whole thing is gonna expose a lot of idiots soon! Jevons Paradox 🍌🍌🍌 Not financial advice!

Banana3 @Banana3Stocks

a year ago

$SPY $QQQ $NVDA $META Deepseek Yes they have 50,000 H100’s They claim to have used only 2048 to train their new large language model By having a super cluster of 50k H100’s they could have practiced code and trained a few models to know what to optimize on a smaller cluster

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$SPY $QQQ $NVDA $MSFT $META I don’t care what any of you say about me… I care when one of the smartest human beings on earth 🌍 validates my intellect 🫶💛 Not financial advice!

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Satya Nadella @satyanadella

a year ago

Jevons paradox strikes again! As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can't get enough of. en.m.wikipedia.org/wiki/Jevons_pa…

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$NVDA $NVDL $SOXL $SOXS DeekSeek news is one month old news. Just google it. You will see.

Number of H100 chips bought in 2024: - $MSFT: 450,000 - $META: 350,000 - $AMZN: 196,000 - $GOOG: 169,000 If you believe they couldn’t find the way to make better AI without more chips but a few Chinese engineers did it as a side project, you are too naive. Deepseek was reportedly trained on over 200,000 H100s. Even if Deepseek achieved to match OpenAI with less chips, this isn’t any bearish for chip makers, to the contrary, it is amazingly bullish. If Deepseek really reached this level with just a few thousand chips, can you imagine what could be done with a million chips? Deepseek news, true or false, are amazingly bullish for chip makers, especially for $NVDA.

$NVDA DeepSeek news is nothing new. The news was out one month ago.

$NVDA Is Quietly Building the Future of Quantum Computing Quantum computing is shedding its once-mystical veneer, evolving from theoretical abstraction into a tangible force that promises to reshape industries. At the heart of this metamorphosis sits NVIDIA, quietly but decisively positioning itself as the linchpin of this technological revolution. The company's CUDA Q platform -- a seamless integration of quantum tools, simulators, and infrastructure -- isn’t merely simplifying quantum computing; it’s accelerating its adoption. In a world where quantum possibilities outpace classical systems, NVIDIA is building the bridge that enterprises will rely on to traverse this new frontier. Quantum computing is an inherently intricate dance -- an interplay of nascent hardware, cutting-edge algorithms, and unimaginable computational potential. Yet NVIDIA, leveraging its GPU dominance, has made navigating this complexity more practical than ever. CUDA Q empowers developers to simulate quantum algorithms on NVIDIA GPUs before deploying them to physical Quantum Processing Units (QPUs). This simulation step is indispensable. Real quantum hardware remains costly, constrained, and elusive -- an expensive luxury. By offering a virtual proving ground, NVIDIA enables developers to iterate faster, debug efficiently, and refine their models with precision. In essence, it transforms quantum innovation from speculative science into practical, executable applications. But NVIDIA isn’t climbing this mountain alone. The company has entrenched itself in the cloud infrastructure ecosystem, forging critical alliances with $AMZN AWS, $MSFT Azure, and $GOOGL Cloud. These partnerships are a game-changer. Developers can tap into CUDA Q’s simulators and tools on-demand while accessing physical QPU hardware from $IONQ & $RGTI. This cloud-centric approach democratizes quantum computing, removing cost barriers and opening the floodgates for experimentation. No longer do enterprises need to “own” quantum hardware -- they can rent, test, and iterate. NVIDIA sits squarely in the middle, orchestrating a seamless flow of quantum development from simulation to hardware deployment. The hardware side of quantum computing is an ecosystem unto itself, rapidly diversifying as companies pursue competing architectures. IonQ's ion-trap technology & Rigetti’s superconducting qubits, yet regardless of the underlying qubit technology, the industry’s success hinges on integration -- an area NVIDIA dominates. Simulators, powered by NVIDIA GPUs, provide the classical backbone that quantum systems rely on to scale. The result? A cohesive quantum stack where NVIDIA tools are not just useful but essential for enterprise adoption. The stakes couldn’t be higher. Quantum computing has the potential to unlock capabilities far beyond classical systems, enabling breakthroughs in fields like pharmaceutical modeling, supply chain optimization, and cybersecurity. Theoretical limits no longer feel insurmountable; quantum machines promise computational leaps that redefine what’s possible. But there’s a catch: quantum technology must first become reliable, scalable, and accessible. NVIDIA’s role isn’t to replace QPU providers -- it’s to make quantum computing work. Simulators will remain indispensable, even as quantum hardware matures, because they allow enterprises to prototype, validate, and stress-test quantum algorithms without friction. This strategy mirrors NVIDIA’s dominance in AI. Just as GPUs became the undisputed backbone of AI model training and inference, NVIDIA is now building the same foundational role for quantum computing. CUDA Q isn’t simply a toolkit -- it’s NVIDIA’s declaration that quantum’s future will run through its infrastructure. And as industries begin the first tentative steps into quantum-powered solutions, NVIDIA’s ecosystem provides everything they need -- simulators for experimentation, cloud platforms for scalability, and seamless connections to QPU hardware for real-world deployment. For companies willing to seize the quantum opportunity early, the payoff could be transformative. Quantum-powered breakthroughs will create new winners -- innovators who leverage quantum computing’s potential before the rest of the market catches up. NVIDIA is ensuring its platform is the one those innovators use to get there. The quantum computing boom is still in its infancy, an untapped well of potential that many companies are only beginning to explore. But the trajectory is clear: with NVIDIA at the center, the bridge between quantum possibility and practical application has already been built.