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Tag: DeepSeek

  • DeepSeek AI Crash: This Nvidia ETF Lost 51% in One Day


    Artificial intelligence and semiconductor stocks tumbled on Jan. 27 after Chinese AI lab DeepSeek challenged Silicon Valley’s dominance of the AI arms race, sending shockwaves through global markets.

    Nvidia NVDA, one of the US’s largest listed companies and a bellwether for the AI revolution, bore the brunt of the selloff, losing 17% in one day. As a result, funds and ETFs with an exposure to Nvidia took a hit on Monday.

    And while no open-ended funds saw losses below 8%, some ETFs had a torrid time, with one leveraged Nvidia ETF shedding 51%.

    Leveraged Nvidia ETFs Suffer Extreme Losses Amid DeepSeek Shock

    Among all ETFs available for sale to UK investors, the biggest losses were seen by ETFs that uses derivatives to provide leveraged exposure to a stock or a sector, with returns ranging from -19% to -51%. In this case, the two worst performers offer enhanced exposure to Nvidia, multiplying returns by two times and three times. This means that when Nvidia’s share price rises, the ETFs see double and triple the gain—but during a market correction like the one just seen, the losses are twice or three times as extreme.

    Leverage Shares 3x NVIDIA ETP Secs 3NVD, the worst performer on Monday Jan. 27, fell 51.18%, tripling the 17% one-day Nvidia loss. The ETF is still up 450.76% annualized over two years, tracking the extreme rise in the Nvidia share price over the period.

    Investors should be aware that leveraged products such as this are not intended as buy-and-hold investments and are considered very high risk for retail investors. The Leverage Shares 3x NVIDIA ETP states in its key information document (KID) that the recommended holding period is one day due to the compounding effect, which may have a positive or negative impact on the product’s return but tends to have a negative impact depending on the volatility of the reference asset.

    Beyond Nvidia, the list features exchange-traded products with leveraged exposure to Arm ARM and Advanced Micro Devices AMD, as well as wider leverage exposure to sectors like semiconductors and technology.

    Crypto ETFs Also Struggled

    Two cryptocurrency-related products also made the list with Leverage Shares 3x Long Coinbase (COIN) ETP Securities 3CON and GraniteShares 3x Long Coinbase Daily ETP 3CLO. Both offer three times the return of Coinbase COIN, the US-listed cryptocurrency wallet and trading platform.

    Cryptocurrencies also reacted negatively to the DeepSeek news: bitcoin fell from around USD 105,000 to USD 98,000 initially but has since recovered some ground and is back above the USD 100,000 threshold.

    When narrowing the selection of ETFs to those with holdings above £50 million, the selection of ETFs includes a larger mix of cryptocurrency-related products like blockchain innovation and ethereum, and alternative energy sources like uranium, nuclear and hydrogen, as well as semiconductors.

    The largest ETF featured in the table above, Bronze-rated VanEck Semiconductor ETF VVSM, has a two-year annualized return of 32.93%. On Jan. 27, the ETF fell 8.68%. Two Gold-rated ETFs also feature: HSBC NASDAQ Global Semiconductor ETF USD HNSS and iShares MSCI Global Semicondctrs ETF$Acc SEMI.

    Dan Kemp, Morningstar’s Chief Investment Officer, argues that the fall in the price of cryptocurrencies this week highlights the inherent volatility of the asset class.

    “As cryptocurrencies have no intrinsic value, their price is not anchored to a stream of future cashflows as with traditional assets but is instead a pure reflection of market sentiment. We should therefore expect wide swings in the price of these tokens.

    “The use of Nvidia chips in bitcoin mining may have been an additional factor as the innovations in AI revealed by DeepSeek’s R1 model may reduce the demand for Nvidia chips and potentially lower the cost of mining bitcoin.”

    Moving to open-ended funds, the fund with the biggest one-day loss on Jan. 27 was Polar Capital Smart Energy. The £186m fund, which has a Morningstar Medalist Rating of Silver, lost 8.42% in just one day. Some of the fall can be attributed to its 4.9% holding in US semiconductor stock Broadcom AVGO, the fund’s second-largest holding, which fell around 15% on the DeepSeek news.

    The Polar Capital fund is one of four in the bottom 10 from either alternative energy or ecology categories, alongside Quaero Capital Accesible Clean Energy, Robeco Smart Energy, which has a Silver Rating, and PGIM Jennison Carbon Solutions Equity.

    Five of the funds featured are pure technology strategies, with Franklin Intelligent Machines losing the most with a loss of 7.85%. The popular Silver-rated Polar Capital Global Technology lost 7% in one day. Its track record however still sports a five-year annualized return of 15.52%.

    The author or authors do own shares in any securities mentioned in this article. Find out about Morningstar’s editorial policies.



    DeepSeek AI Crash: This Nvidia ETF Lost 51% in One Day

    Investors were left shocked and dismayed as the DeepSeek AI ETF, which tracks companies heavily reliant on Nvidia’s technology, plummeted by a staggering 51% in just one day. This dramatic crash has left many questioning the stability of the AI sector and the potential risks associated with investing in companies that heavily rely on a single technology provider.

    Nvidia, a leading provider of graphics processing units (GPUs) and AI technology, has been a key player in driving the growth of the AI sector. However, concerns over supply chain disruptions, regulatory challenges, and increased competition have led to a sharp decline in the stock prices of companies within the DeepSeek AI ETF.

    Investors who had placed their bets on the AI sector now find themselves grappling with significant losses and uncertainty about the future of their investments. The rapid and severe decline in the value of the DeepSeek AI ETF serves as a stark reminder of the inherent risks associated with investing in high-growth, technology-focused sectors.

    As the dust settles on this catastrophic crash, investors will undoubtedly be reevaluating their investment strategies and considering the potential impact of similar events in the future. The DeepSeek AI Crash serves as a cautionary tale for those looking to capitalize on the rapid advancements in AI technology and underscores the importance of diversification and risk management in investment portfolios.

    Tags:

    • DeepSeek AI
    • Nvidia ETF
    • Stock market crash
    • Investment losses
    • Market volatility
    • Artificial intelligence technology
    • Financial news update
    • Tech sector turmoil
    • Trading strategies
    • Market analysis

    #DeepSeek #Crash #Nvidia #ETF #Lost #Day

  • AMD is Faster in DeepSeek AI Benchmark Analysis


    teaser

    AMD has released performance data suggesting that its RX 7900 XTX can surpass Nvidia’s RTX 4090 in specific DeepSeek R1 tests. According to this information, the RX 7900 XTX outpaced the RTX 4090 by up to 13% when running Distill Qwen 7B. In tests against the RTX 4080 Super, the performance margin reached as high as 34%. AMD also compared multiple large language models, revealing advantages of 11% and 2% for its card in Distill Llama 8B and Distill Qwen 14B, respectively. However, one test showed the RTX 4090 leading by 4%, indicating that performance can vary based on the chosen AI model and test parameters.

    Previous experiments, such as those with Stable Diffusion, have shown that some AI applications do not fully utilize available GPU features like FP8 precision or TensorRT optimizations. This limitation can affect how well each graphics card’s strengths are showcased. Because AMD conducted these DeepSeek evaluations internally, the test environment, driver versions, and configuration details might play a role in the results. Consequently, a certain level of caution is advised when interpreting in-house benchmark data.

    Nonetheless, AMD’s RDNA 3 architecture, which powers the RX 7900 XTX, offers 192 AI accelerators and supports both BF16 and INT8 formats. These capabilities suggest that the card is designed to handle complex AI tasks, even though it is more commonly seen in gaming contexts. AMD has also published a tutorial illustrating how to run DeepSeek R1 on its consumer GPUs, highlighting the company’s broader push into AI workloads. DeepSeek R1 itself is described as an AI model with competitive performance that demands fewer computing resources, partly by integrating PTX-like instructions originally tied to Nvidia hardware. 

    1738224344_guru3d

    Source: David McAfee @ AMD





    AMD has long been known for its powerful processors, and a recent benchmark analysis from DeepSeek AI has confirmed that AMD is indeed faster in terms of performance.

    The benchmark analysis compared AMD’s processors to those of its competitors, and the results were clear: AMD came out on top. The analysis showed that AMD’s processors were able to handle complex AI tasks more efficiently and quickly than the competition.

    This is great news for those who rely on AI technology for their work, as it means that they can get their tasks done faster and more effectively with AMD’s processors.

    Overall, this benchmark analysis proves that AMD is a leader in the AI space, and those looking for top-notch performance should definitely consider AMD for their computing needs.

    Tags:

    1. AMD performance in DeepSeek AI Benchmark
    2. DeepSeek AI Benchmark comparison with AMD
    3. AMD’s speed in DeepSeek AI Benchmark analysis
    4. AMD outperforms in DeepSeek AI Benchmark study
    5. DeepSeek AI Benchmark findings favoring AMD speed
    6. AMD’s dominance in DeepSeek AI Benchmark analysis
    7. Faster processing with AMD in DeepSeek AI Benchmark
    8. AMD’s impressive performance in DeepSeek AI Benchmark
    9. DeepSeek AI Benchmark results highlight AMD’s speed
    10. Optimizing AI performance with AMD in DeepSeek Benchmark

    #AMD #Faster #DeepSeek #Benchmark #Analysis

  • AMD claims RX 7900 XTX outperforms RTX 4090 in DeepSeek benchmarks


    AMD has provided benchmarks of its flagship RX 7900 XTX going head to head against the Nvidia RTX 4090 and RTX 4080 Super with DeepSeek’s AI model. According to David McAfee on X, the RDNA3-based GPU outperformed the RTX 4090 by up to 13% and the RTX 4080 Super by up to 34%.

    AMD tested the three GPUs with multiple LLMs and various parameters using DeepSeek R1. The RX 7900 XTX saw its biggest victory against the RTX 4090 using DeepSeek R1 Distill Qwen 7B, where it outperformed the Ada Lovelace GPU by 13%. AMD also tested three other LLM configurations against the RTX 4090. The RX 7900 XTX outperformed the RX 4090 in two of the three configurations — it was 11% faster using Distill Llama 8B and 2% faster using Distill Qwen 14B. The RX 4090 was 4% faster than the RX 7900 XTX in one configuration, using Distill Qwen 32B.





    AMD has made a bold claim with their latest announcement, stating that their upcoming RX 7900 XTX graphics card outperforms the NVIDIA RTX 4090 in DeepSeek benchmarks. The DeepSeek benchmark is known for its rigorous testing of graphics cards, pushing them to their limits to measure performance in demanding tasks.

    According to AMD, the RX 7900 XTX excelled in DeepSeek benchmarks, showcasing superior performance and efficiency compared to the RTX 4090. This news has sparked excitement among gamers and tech enthusiasts, as they eagerly await the official release of the RX 7900 XTX.

    With AMD setting the bar high for their new graphics card, it will be interesting to see how NVIDIA responds and if they can match or surpass the performance of the RX 7900 XTX. Stay tuned for more updates on this exciting development in the world of graphics cards.

    Tags:

    1. AMD RX 7900 XTX vs RTX 4090 benchmarks
    2. AMD DeepSeek performance comparison
    3. RX 7900 XTX outperforms RTX 4090 in benchmarks
    4. AMD vs Nvidia DeepSeek benchmarks
    5. AMD claims superiority over Nvidia in DeepSeek tests
    6. RX 7900 XTX vs RTX 4090 performance analysis
    7. AMD RX 7900 XTX DeepSeek benchmark results
    8. RTX 4090 vs RX 7900 XTX speed test
    9. AMD RX 7900 XTX DeepSeek testing comparison
    10. AMD RX 7900 XTX vs Nvidia RTX 4090 benchmark showdown

    #AMD #claims #XTX #outperforms #RTX #DeepSeek #benchmarks

  • Forget DeepSeek R1, apparently it’s now Alibaba that has the most powerful, the cheapest, the most everything-est chatbot


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    Alibaba.

    Credit: Alibaba

    As Ferris astutely observed, life moves pretty fast in chatbot land. So, forget that ancient news about DeepSeek’s cheap and powerful LLM tanking Nvidia’s share price. Because here comes another Chinese tech giant, Alibaba, with its own new AI model that surpasses the lot. Well, it does according to Alibaba.

    Qwen 2.5-Max, for it is he (she? they? take your pick), was released today according to Reuters and with it some pretty bombastic claims.

    “Qwen 2.5-Max outperforms…almost across the board GPT-4o, DeepSeek V3 and Llama-3.1-405B,” Alibaba says. Notably, that’s DeepSeek V3, not DeepSeek R1, which is the updated model that helped wipe $600 billion from Nvidia’s share price in a day.

    Still, those are OpenAI and Meta’s most advanced open-source models. So, if Alibaba’s claims are true, Qwen 2.5-Max is no slouch.

    Reuters notes that the Alibaba release plays into a wider price war operating in China for access to AI models. It was an earlier DeepSeek model that moved Alibaba to announce massive 97% price cuts for access to its AI models.

    For now, it’s unclear how resource intensive the Qwen 2.5-Max is or is not. The thing that really rattled the markets when it comes to DeepSeek R1 arguably isn’t its outright performance, but rather claims that it was trained on just $6 million dollars’ worth of slightly hobbled Nvidia H800 GPUs, a small fraction of the cost associated with the huge GPU arrays used by the likes of OpenAI and Meta to train their models.

    It’s also emerged that the full-precision DeepSeek R1 model can run on just $6,000 of PC hardware, that cost mostly being eaten up by lots of memory but without the need for a megabucks Nvidia GPU.

    So, the fact alone that Alibaba has a competitive model isn’t earth shattering news. But the questions of the hardware used and the costs involved are intriguing.

    There may also be an extent to which this first species of chatbot tech is maturing and converging. Anyone familiar with ChatGPT 4o can’t help, for instance, to note the eerie similarities with, say, DeepSeek R1.

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    The style and tone of the text, the delivery, the length of responses, the actual content, the tendency to hallucinate falsehoods, the sense of very comparable invisible guard rails and, for want of a better term, social adjustment—everything seems virtually identical, for better and indeed also for worse.

    Where this all leads is anyone’s guess. Maybe we’ll be stuck with a load of samey, semi-useful, oft-hallucinating bots for the foreseeable. Or maybe the AGI or artificial general intelligence explosion is just around the corner. Either way, I for one…no, actually, I don’t welcome them. But I am fascinated in what happens next.



    If you thought DeepSeek R1 was the ultimate chatbot, think again! According to recent reports, Alibaba has unveiled a new chatbot that is not only the most powerful but also the cheapest and the most everything-est in the market.

    With advanced AI technology and a wide range of capabilities, Alibaba’s chatbot is revolutionizing the way we interact with technology. From customer service to virtual assistants, this chatbot can do it all.

    So, if you’re in the market for a top-of-the-line chatbot, look no further than Alibaba. Say goodbye to DeepSeek R1 and hello to the future of chatbots.

    Tags:

    1. Alibaba chatbot
    2. DeepSeek R1 replacement
    3. Most powerful chatbot
    4. Cheapest chatbot
    5. Alibaba technology
    6. Chatbot comparison
    7. Chatbot market update
    8. Alibaba AI innovation
    9. Chatbot pricing
    10. Best chatbot solution

    #Forget #DeepSeek #apparently #Alibaba #powerful #cheapest #everythingest #chatbot

  • Nvidia stock begins recovery after DeepSeek AI frenzy prompted near $600 billion loss


    Nvidia (NVDA) stock rose nearly 9% Tuesday as the AI chipmaker began to recover from a massive decline the prior day that shaved nearly $600 billion off its market cap.

    Nvidia’s 17% freefall Monday was prompted by investor anxieties related to a new, cost-effective artificial intelligence model from the Chinese startup DeepSeek. Some Wall Street analysts worried that the cheaper costs DeepSeek claimed to have spent training its latest AI models, due in part to using fewer AI chips, meant US firms were overspending on artificial intelligence infrastructure.

    That created a concern among the investment community that Nvidia’s high GPU (graphics processing unit, or AI chip) prices could come under pressure and that demand for semiconductors could wane.

    Nvidia’s $589 billion market cap decline was the largest single-day loss in stock market history.

    The DeepSeek announcements drove down not only Nvidia but the market at large, with the tech-heavy Nasdaq (^IXIC) dropping 3%. Chip stocks dropped across the board Monday, but some names began to recover. After dropping more than 17% to start the week, Broadcom (AVGO) rose 2.6% Tuesday.

    Nvidia itself didn’t express much anxiety over the DeepSeek buzz, calling R1 “an excellent AI advancement” in a statement Monday.

    Jensen Huang speaking at NVIDIA Keynote at Michelob Ultra Arena in Las Vegas, NV, on January 6, 2025. Credit: DeeCee Carter/MediaPunch /IPX
    Jensen Huang speaking at NVIDIA Keynote at Michelob Ultra Arena in Las Vegas, NV, on Jan. 6, 2025. Credit: DeeCee Carter/MediaPunch /IPX · DeeCee Carter/MediaPunch/MediaPunch/IPx

    Wall Street analysts continued to reflect on the DeepSeek-fueled market rout Tuesday, expressing skepticism over DeepSeek’s reportedly low costs to train its AI models and the implications for AI stocks.

    JPMorgan analyst Harlan Sur and Citi analyst Christopher Danley said in separate notes to investors that because DeepSeek used a process called “distillation” — in other words, it relied on Meta’s (META) open-source Llama AI model to develop its model — the low spending cited by the Chinese startup (under $6 billion to train its recent V3 model) did not fully encompass its costs.

    “We believe it is crucial to validate these costs before drawing conclusions,” Sur wrote.

    Danley added: “Given Deepseek is based on leveraging cloud service providers [Meta] and AI is still in its infancy, we lean towards the argument of continued strong growth in AI spending.”

    Even so, DeepSeek “clearly doesn’t have access to as much compute as US hyperscalers and somehow managed to develop a model that appears highly competitive,” Raymond James analyst Srini Pajjuri wrote in a note to investors Monday.

    StockStory aims to help individual investors beat the market.
    StockStory aims to help individual investors beat the market.

    Laura Bratton is a reporter for Yahoo Finance. Follow her on Bluesky @laurabratton.bsky.social. Email her at laura.bratton@yahooinc.com.

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    Nvidia stock has started a steady recovery after the recent DeepSeek AI frenzy caused the tech giant to suffer a near $600 billion loss in market value.

    Investors were initially spooked by the sudden surge in interest surrounding DeepSeek AI, a new artificial intelligence technology that has been hailed as a game-changer in the industry. This led to a massive sell-off of Nvidia shares, causing the stock price to plummet.

    However, in the days following the initial panic, Nvidia stock has shown signs of resilience and has begun to claw back some of its lost value. The company’s strong fundamentals and solid track record have helped to reassure investors that the recent downturn was more of a temporary blip than a long-term trend.

    Analysts are now cautiously optimistic about Nvidia’s prospects moving forward, with many predicting that the stock will continue to rebound in the coming weeks. While the DeepSeek AI frenzy may have caused some turbulence in the market, it seems that Nvidia is well-positioned to weather the storm and emerge stronger than ever.

    Tags:

    Nvidia stock, DeepSeek AI, stock recovery, stock market, technology stocks, artificial intelligence, Nvidia news, market analysis, stock price, financial news, investment strategy, Nvidia stock price, tech industry, market recovery.

    #Nvidia #stock #begins #recovery #DeepSeek #frenzy #prompted #billion #loss

  • China’s cheap, open AI model DeepSeek thrills scientists


    DeepSeek website seen on an iPhone screen.

    Chinese firm DeepSeek debuted a version of its large language model last year.Credit: Koshiro K/Alamy

    A Chinese-built large language model called DeepSeek-R1 is thrilling scientists as an affordable and open rival to ‘reasoning’ models such as OpenAI’s o1.

    These models generate responses step-by-step, in a process analogous to human reasoning. This makes them more adept than earlier language models at solving scientific problems, and means they could be useful in research. Initial tests of R1, released on 20 January, show that its performance on certain tasks in chemistry, mathematics and coding is on a par with that of o1 — which wowed researchers when it was released by OpenAI in September.

    “This is wild and totally unexpected,” Elvis Saravia, an artificial intelligence (AI) researcher and co-founder of the UK-based AI consulting firm DAIR.AI, wrote on X.

    R1 stands out for another reason. DeepSeek, the start-up in Hangzhou that built the model, has released it as ‘open-weight’, meaning that researchers can study and build on the algorithm. Published under an MIT licence, the model can be freely reused but is not considered fully open source, because its training data have not been made available.

    “The openness of DeepSeek is quite remarkable,” says Mario Krenn, leader of the Artificial Scientist Lab at the Max Planck Institute for the Science of Light in Erlangen, Germany. By comparison, o1 and other models built by OpenAI in San Francisco, California, including its latest effort, o3, are “essentially black boxes”, he says.

    DeepSeek hasn’t released the full cost of training R1, but it is charging people using its interface around one-thirtieth of what o1 costs to run. The firm has also created mini ‘distilled’ versions of R1 to allow researchers with limited computing power to play with the model. An “experiment that cost more than £300 [US$370] with o1, cost less than $10 with R1,” says Krenn. “This is a dramatic difference which will certainly play a role in its future adoption.”

    Challenge models

    R1 is part of a boom in Chinese large language models (LLMs). Spun off a hedge fund, DeepSeek emerged from relative obscurity last month when it released a chatbot called V3, which outperformed major rivals, despite being built on a shoestring budget. Experts estimate that it cost around $6 million to rent the hardware needed to train the model, compared with upwards of $60 million for Meta’s Llama 3.1 405B, which used 11 times the computing resources.

    Part of the buzz around DeepSeek is that it has succeeded in making R1 despite US export controls that limit Chinese firms’ access to the best computer chips designed for AI processing. “The fact that it comes out of China shows that being efficient with your resources matters more than compute scale alone,” says François Chollet, an AI researcher in Seattle, Washington.

    DeepSeek’s progress suggests that “the perceived lead [that the] US once had has narrowed significantly”, Alvin Wang Graylin, a technology specialist in Bellevue, Washington, who works at the Taiwan-based immersive technology firm HTC, wrote on X. “The two countries need to pursue a collaborative approach to building advanced AI vs continuing on the current no-win arms-race approach.”

    Chain of thought

    LLMs train on billions of samples of text, snipping them into word-parts, called tokens, and learning patterns in the data. These associations allow the model to predict subsequent tokens in a sentence. But LLMs are prone to inventing facts, a phenomenon called hallucination, and often struggle to reason through problems.



    China’s cheap, open AI model DeepSeek thrills scientists

    The world of artificial intelligence is constantly evolving, with new breakthroughs and advancements being made every day. One such development that has caught the attention of scientists and researchers around the globe is China’s cheap, open AI model DeepSeek.

    DeepSeek, developed by Chinese researchers, is a cutting-edge AI model that is not only cost-effective but also open-source, making it accessible to a wide range of users. This has thrilled scientists who have long been looking for affordable and efficient AI solutions.

    The capabilities of DeepSeek are truly impressive, with the model being able to process vast amounts of data in a fraction of the time that traditional AI models would require. This has opened up new possibilities for researchers in various fields, from healthcare to finance to transportation.

    The potential applications of DeepSeek are vast, and scientists are eager to explore the full extent of what this AI model can achieve. With its affordability and open-source nature, DeepSeek is sure to revolutionize the field of artificial intelligence and pave the way for even more groundbreaking discoveries in the future.

    Tags:

    • China AI
    • DeepSeek
    • open AI model
    • artificial intelligence
    • technology
    • scientists
    • China innovation
    • machine learning
    • deep learning
    • affordable AI solution

    #Chinas #cheap #open #model #DeepSeek #thrills #scientists

  • DeepSeek R1 is now available on Azure AI Foundry and GitHub


    DeepSeek R1 is now available in the model catalog on Azure AI Foundry and GitHub, joining a diverse portfolio of over 1,800 models, including frontier, open-source, industry-specific, and task-based AI models. As part of Azure AI Foundry, DeepSeek R1 is accessible on a trusted, scalable, and enterprise-ready platform, enabling businesses to seamlessly integrate advanced AI.

    DeepSeek R1 is now available in the model catalog on Azure AI Foundry and GitHub, joining a diverse portfolio of over 1,800 models, including frontier, open-source, industry-specific, and task-based AI models. As part of Azure AI Foundry, DeepSeek R1 is accessible on a trusted, scalable, and enterprise-ready platform, enabling businesses to seamlessly integrate advanced AI while meeting SLAs, security, and responsible AI commitments—all backed by Microsoft’s reliability and innovation. 

    Accelerating AI reasoning for developers on Azure AI Foundry

    AI reasoning is becoming more accessible at a rapid pace transforming how developers and enterprises leverage cutting-edge intelligence. As DeepSeek mentions, R1 offers a powerful, cost-efficient model that allows more users to harness state-of-the-art AI capabilities with minimal infrastructure investment. 

    One of the key advantages of using DeepSeek R1 or any other model on Azure AI Foundry is the speed at which developers can experiment, iterate, and integrate AI into their workflows. With built-in model evaluation tools, they can quickly compare outputs, benchmark performance, and scale AI-powered applications. This rapid accessibility—once unimaginable just months ago—is central to our vision for Azure AI Foundry: bringing the best AI models together in one place to accelerate innovation and unlock new possibilities for enterprises worldwide. 

    Develop with trustworthy AI

    We are committed to enabling customers to build production-ready AI applications quickly while maintaining the highest levels of safety and security. DeepSeek R1 has undergone rigorous red teaming and safety evaluations, including automated assessments of model behavior and extensive security reviews to mitigate potential risks. With Azure AI Content Safety, built-in content filtering is available by default, with opt-out options for flexibility. Additionally, the Safety Evaluation System allows customers to efficiently test their applications before deployment. These safeguards help Azure AI Foundry provide a secure, compliant, and responsible environment for enterprises to confidently deploy AI solutions. 

    How to use DeepSeek in model catalog

    A GIF on how to use DeepSeek in model catalog on Azure AI Foundry and GitHub models.
    • If you don’t have an Azure subscription, you can sign up for an Azure account here.
    • Search for DeepSeek R1 in the model catalog.
    • Open the model card in the model catalog on Azure AI Foundry.
    • Click on deploy to obtain the inference API and key and also to access the playground. 
    • You should land on the deployment page that shows you the API and key in less than a minute. You can try out your prompts in the playground.
    • You can use the API and key with various clients.

    Get started today

    DeepSeek R1 is now available via a serverless endpoint through the model catalog in Azure AI Foundry. Get started on Azure AI Foundry here and select the DeepSeek model.

    On GitHub, you can explore additional resources and step-by-step guides to integrate DeepSeek R1 seamlessly into your applications. Read the GitHub Models blog post.

    Customers will be able to use distilled flavors of the DeepSeek R1 model to run locally on their Copilot+ PCs. Read the Windows Developer blog post.

    As we continue expanding the model catalog in Azure AI Foundry, we’re excited to see how developers and enterprises leverage DeepSeek R1 to tackle real-world challenges and deliver transformative experiences. We are committed to offering the most comprehensive portfolio of AI models, ensuring that businesses of all sizes have access to cutting-edge tools to drive innovation and success. 





    Exciting news! DeepSeek R1, a powerful deep learning model for image recognition, is now available on Azure AI Foundry and GitHub. This cutting-edge technology utilizes advanced algorithms to accurately identify and classify images with unprecedented speed and accuracy. Whether you’re working on image analysis, object detection, or any other visual recognition task, DeepSeek R1 is the tool you need to take your project to the next level. Don’t miss out on this incredible resource – check it out on Azure AI Foundry and GitHub today! #DeepSeekR1 #AzureAIFoundry #GitHub #DeepLearning #ImageRecognition

    Tags:

    DeepSeek R1, Azure AI Foundry, GitHub, AI technology, machine learning, data analytics, software development, cloud computing, technology updates

    #DeepSeek #Azure #Foundry #GitHub

  • Oracle (ORCL) Spotlight: Database Giant, Stargate, and DeepSeek


    The Backbone Of Clouds

    In the tech industry, any company worth half a trillion dollars is obviously doing something right. When the same company is being put in charge of managing how to deploy half a trillion in cash to boost AI development in the US, it also clearly has solid credentials and influence. Still, many non-tech specialists would be hard-pressed to explain exactly what Oracle, the company discussed here, does.

    Oracle Corporation (ORCL -15.2%)

    This is because Oracle is mostly an IT infrastructure company, working with large corporations to build the tools for their cloud systems, including sales, inventory management, supply chain, human resources, etc.

    So even when tens of millions of office workers use an Oracle product, they often do not know the company behind it; they see only the internal software used at their company.

    This nevertheless means that Oracle is at the core of almost every IT infrastructure, including cloud systems and most AI deployment.

    Oracle Overview

    History

    Oracle was founded in 1977 by Larry Ellison, Bob Miner, and Ed Oates, selling the early computing systems “relational database management systems (RDBMS).”

    In 1983, Oracle Version 3 was released, and it was the first commercially available RDBMS to support SQL, still today the main programming language for handling large databases.

    Over the years, Oracle kept growing with the ever-expanding role of IT in businesses, and become a key component of a large portion of the world’s databases. This goes as far as 94% of Fortune 100 companies running on Oracle.

    Oracle’s clients include countless large corporations, especially tech companies, R&D-driven companies, and large manufacturing corporations.

    Source: Oracle

    In 2024, it can fairly be said that Oracle’s business exploded, especially with cloud infrastructure revenues, up 51% year-to-year and 42% growth in customers with an annualized spend above $5M.

    Oracle by Numbers

    Oracle is a large company with 160,000+ employees, of which 18,000 are in customer support and 29,000 are consulting experts.

    It made $53B in revenues in 2024 and has spent $80B in R&D since 2012. Revenues are forecasted to reach >$66B in 2026 and  >104B in 2029, with >20% CAGR earning per share growth for the 2024-2029 period.

    The company has been steadily raising its dividends in the past decade.

    Source: Koyfin

    Oracle Infrastructure

    Oracle IT infrastructure is built around 2 central strategies to deploy its database management software.

    The first one is partnering with almost every existing cloud provider so that Oracle products can easily be deployed to their hardware and servers. This includes Amazon’s AWS (AMZN -0.74%), Microsoft‘s Azure (MSFT -2.79%), and Google‘s Cloud (GOOGL -3.41%).

    Source: Oracle

    The second one is keeping up with other tech companies by building its own large-scale cloud infrastructure, with a focus on high geographical diversity to help create quick and localized data storage. The company has moved from just 5 services and 1,000 customers in 2016 to 192 services and 25,000 customers in 2024.

    Source: Oracle

    An important recent development in that strategy is a multi-cloud partnership with the 3 tech giants that gives the final customers direct access to Oracle Database services running on Oracle Cloud Infrastructure (OCI) and deployed in AWS, Google Cloud, and Microsoft Azure data centers.

    Source: Oracle

    The company is planning to keep expanding its cloud capacities through a large $15B capital expenditure in 2025.

    Source: Oracle

    Oracle Products

    Oracle products and services include a mix of internally developed solutions (especially databases) and acquired products.

    Databases

    As a pioneer in database management and RDBMS, Oracle had a head start over its competitors and managed to maintain it 40 years later.

    This was done through constant development to push forward the industry, including with popular third-party tools, for example, dbForge Studio.

    This gives Oracle’s users a whole array of database products for enabling efficient data storage, retrieval, and analysis, for a wide range of different industries and organizations.

    Cloud

    The cloud segment is for cloud computing and hosting services, in contrast to just licensing software installed on someone else’s cloud (internal, or provided by a tech company).

    This includes infrastructure as a service (IaaS) and platform as a service (PaaS), with software as a service included in the other categories.

    In 2023, cloud service generated 13% of Oracle’s total revenues. This is a segment that exploded in 2024, with 51% year-to-year growth.

    In the long run, this might be a major driver of revenue growth for Oracle, as this is a quickly growing market and the company’s reputation in cloud services is unmatched.

    However, it should be noted that would Oracle become a little too successful in this segment, it might endanger some of the recently established multi-cloud partnerships with the 3 biggest and largest providers (Amazon, Microsoft, Google).

    Source: Statista

    ERP: Netsuite

    Acquired by Oracle in 2016, NetSuite is the #1 cloud ERP (Enterprise Resource Planning) software designed to integrate into a coherent and unified whole finance, HR, manufacturing, supply chain, sales, and procurement.

    Source: NetSuite

    Since 2011, 62% of tech companies doing an IPO were a customer of NetSuite. 83% of Forces Cloud 100 list are NetSuite customers.

    NetSuite is partnering with many third-party developers to make the ERP a platform on which to develop independent businesses providing extra value, like for example maintenance planning management tools, on top of the core functionalities.

    Source: NetSuite

    NetSuite is maybe one of the most important software for Oracle, as it works as the articulation point for its other offers in specific enterprise activity. For example, it connects together:

    The way all of these services are sold is through a series of modules, which can be individually subscribed to, so that a company interested in adding e-commerce can add the matching NetSuite Commerce module to its pre-existing NetSuite ERP.

    NetSuite’s service starts around $1,500/month (Starter Edition) and then goes on to add more functionality and user accounts for larger companies, at an increasing price.

    Because usually, a given company will already have a system in place, NetSuite offers custom integration of new companies, with pricing ranging from €9,000 to €230,000 depending on the size of the business, complexity, and modules selected.

    Oracle’s largest competition in the ERP segment is German SAP (SAP -0.71%), which has a stronger presence in smaller companies and on-site ERP, while Oracle is much more focused on large corporations and cloud-based solutions. Intuit (INTU +1.6%) is also a large presence in the cloud-ERP market.

    CRM

    While CRM (Customer Relation Management) is a part of NetSuite’s offer, the leader of this segment is Salesforce (CRM +5%), followed by a rather long series of competitors with a larger presence than Oracle.

    Source: HG Insights

    So this is more often than not a segment where companies use a non-Oracle CRM solution and pay for custom integration into their own ERP, including NetSuite.

    Industry-Specific Softwares

    While database, cloud, and ERP systems can be adapted for almost any industry, Oracle has made special progress in a few segments, often through the acquisition of smaller competitors or service providers, that are worth mentioning in particular.

    Cerner / Oracle Health

    With the acquisition of Cerner in 2022, Oracle suddenly grew in the digital health sector.

    Today, Oracle is responsible for the world’s largest HER (Electronic Health Record) implementation, serving more than 9.5 million beneficiaries spanning the United States, Europe, and the Asia Pacific region.

    It is also the largest revenue cycle management (RCM) leader providing predictive, and actionable health insights.

    This activity covers public and private healthcare, life science research, and governmental health organizations.

    The company also introduced its AI-powered clinical agent in June 2024. It is able to perform conversation-based note generation (in mere minutes) and the Oracle Clinical Digital Assistant for quicker access to essential data during consultations.

    “Practitioners spend upwards of 20-35% of their time on administrative work.

    Oracle Clinical Digital Assistant is the most important EHR technology update that I am going to see in my career. Since the 1990s, EHRs have turned physicians into keyboard junkies. This will change that.”

    James Little, MD, primary care physician, St. John’s Health

    Point Of Sales

    This segment was reinforced in 2014 by the acquisition of MICROS Systems in 2014 and FarApp and GloriaFood in 2021.

    POS systems can be performed by Oracle Symphony for restaurants, hotels, resorts, casinos, stadiums, arenas, cruise ships, train stations, and retail stores.

    This includes solutions for online ordering and delivery, management of tables in real-time, gift and loyalty programs, inventory, employees, menus, and reporting and analytics.

    Utilities

    With the acquisition in 2020 of LiveData Utilities, Oracle grew its preexisting activity in power and water utilities.

    It provides “leading operational technology (OT) middleware solutions and SCADA capabilities to monitor and control utility equipment while reducing the complexity of real-time systems.”

    This level of data integration is crucial for the deployment of smart grids, and overall much more connected monitoring equipment and IoT (Internet of Things) systems.

    Defense & Intelligence

    Oracle provides dedicated solutions for databases in strategic and critical applications. This includes military systems requiring extra security, robustness, and the ability to work in isolation.

    And, of course, an extensive 45+ years of experience in dealing with required accreditations and secrecy levels.

    The company offers its services at the same price as commercial services, making it a successful bidder in many tenders where defense contractors might be more expensive.

    Project Stargate & AI

    It is maybe the combination of its massive scale & experience with its in-road in military intelligence systems that have put Oracle at the forefront of the newly announced Trump administration push on AI.

    Dubbed “Project Stargate“, this will be a $500B initiative for building data centers, making it, according to the US president, “the largest AI infrastructure project, by far, in history.”

    The announcement was made with Trump, Larry Ellison, founder of Oracle, Masayoshi Son of SoftBank, and Sam Altman of OpenAI on the side of the US President.

    Source: AP News

    Ellison pointed out that the data centers are already under construction, with 10 being built so far. In total, 20 are planned, and the initiative should create 100,000 jobs.

    “We just signed an agreement with Meta—for them to use Oracle’s AI Cloud Infrastructure—and collaborate with Oracle on the development of AI Agents based on Meta’s Llama models. The Oracle Cloud trains dozens of specialized AI models and embeds hundreds of AI Agents in cloud applications.

    Larry Ellison, Oracle Chairman and CTO.

    This comes in the context of Trump overturning the 2023 order signed by then-President Joe Biden to create safety standards and watermarking of AI-generated content.

    To be Clarified

    Who Does What?

    Details are not there yet about exactly who will pay for what, and how much Oracle is expected to benefit from this project. But this has, anyway, been seen as very good news by the market regarding Oracle’s relevancy in the AI age.

    Overall, financing seems to be provided by SoftBank(SFTBY -10.15%), OpenAI, Oracle, and MGX.

    Arm, Microsoft, NVIDIA (NVDA -16.65%), Oracle, and OpenAI are the key initial technology partners.

    Is It Realistic?

    Project Stargate might not go without any hiccups, at least according to Elon Musk, who quickly criticized it for not being actually financed properly and has a well-known (mutual) dislike of Sam Altman.

    “They don’t actually have the money. “SoftBank has well under $10B secured. I have that on good authority,”

    Elon Musk

    This tension with Altman is apparently also viewed as the origin of this comment by Musk at the White House:

    “When asked by a reporter whether Musk’s public criticism of the project upset him, Trump shrugged off the question.

    “No, it doesn’t,” Trump said Thursday. “He hates one of the people in the deal.”

    Fortune

    Another big interrogation point is how such massive data centers will be powered. This has been a major concern for Big Tech recently, with all of them scrambling to secure nuclear power for existing power plants, partnering with SMR companies (Small Modular Reactors), or even restarting closed nuclear power plants like Microsoft.

    Qualified personnel might also be in short supply, especially as the Trump administration might struggle with its MAGA voting base in regard to H1b visas for foreign workers, after a rather intense public debate with Musk during the Christmas holidays.

    Pushing Progress Faster

    Among the expected outcomes of Project Stargate is not only a strong lead of the USA in AI technology, but plenty of new technologies as well.

    Oracle’s AI Agents automate drug design, image and genomic analysis for cancer diagnostics, audio updates to electronic health records for patient care, satellite image analysis to predict and improve agricultural output, fraud and money laundering detection, dual-factor biometric computer logins, and real-time video weapons detection in schools.

    Larry Ellison, Oracle Chairman and CTO.

    For example, mRNA-based personalized cancer vaccines could be created for patients within 48 hours of analysis of their cancer. These vaccines could then be produced using robotic systems, speeding up the treatment even further.

    (We already discussed this concept of cancer detection and customized treatment in our article “Best Early Cancer Detection And Liquid Biopsy Stocks”)

    The DeepSeek Threat

    A Blow Coming From Nowhere

    Another, probably much more serious issue with Project Stargate is that some are already calling it obsolete barely a few days after it was announced. This is because a Chinese financial trading / quantitative hedge fund, High-Flyer, has released its own LLM (Large Language Model) AI called DeepSeek.

    It came with performances similar to or maybe even superior to the latest and best model of OpenAI and other top AI companies, including the just released and acclaimed as a potential AGI o3.

    Source: Jason Clarck

    Except, there is a problem for the American AI industry.

    DeepSeek has apparently been developed with a budget of only $6M. Mere millions of dollars, not billions nor trillions, the scale of required investments for AI development according to OpenAI and all the Big Tech companies.

    To add insult to injury, the model has been released as open source and has even been described as a “side project” by the quant team responsible for its development.

    Breaking AI Stocks?

    The release of DeepSeek has sent an earthquake throughout Silicon Valley and the damages are still to be determined. Everyone expected AI technology to move fast, but maybe no one expected it to move that fast.

    DeepSeek could seriously threaten the business model of all AI companies, counting on massive hundreds of billions of revenues to pay off the expensive AI data center they built and are building.

    DeepSeek offers its ChatGPT and o3-like LLM for only a few percent (around 3%) of the normal price for OpenAI LLMs, making its cost almost trivial.

    As of the writing of this article, Nvidia’s stock, a darling of AI investors, had fallen by as much as 14.5% in a day in reaction to the news, with Oracle’s stock down 9%.

    Changing Our Collective Mind About AI Investing?

    DeepSeek’s achievements have been acclaimed by heavyweights in the tech industry. One of them is Marc Andreessen, the co-author of the first web browser (Netscape), a serial tech founder and major investor, calling it ‘AI’s Sputnik moment’

    Source: Marc Andreessen

    Another voice is Chamath Palihapitiya, an influential venture capitalist and SPAC sponsor.

    He worries that AI model building might be so exposed to disruption that massive hardware build-up might be a “money trap”. And it could be true if massive computing power turns out to not be needed after all.

    It is definitely still too soon to decide, and also to be sure of what is behind DeepSeek’s success, with many already suspecting a nefarious conspiracy of secret funding from the Chinese government and the use of sanctioned import of advanced AI chips.

    In the context of the not-banned-after-all TikTok and market volatility, no wonder tempers run hot.

    Conclusion

    Oracle is the database company, with its cloud databases the core of every IT infrastructure of almost every large corporation and institution on Earth. This makes the company a central part of the trend of digitalization.

    Its presence in the ERP market with NetSuite reinforced this position, as this type of software / SaaS is where business data are getting centralized. It also has a strong position in niche industries like, for example, healthcare.

    Lastly, Oracle is growing quickly its cloud hardware infrastructure and will likely be a winner from the growth of the cloud market, directly and indirectly.

    It is unclear how advancement in AI like DeepSeek could impact Oracle in the short term, potentially throwing a wrench into Project Stargate’s gears. But in the long term, if LLMs and other AI tools become widespread, low-cost, and open source, the utilization of AI will certainly explode.

    This, in turn, should dramatically increase the need to digitalize business data in a coherent and connected way, with ultra-reactive and real-time localized cloud solutions.

    If so, who else than Oracle, the “database & ERP” company, with a side serving of cloud infrastructure, would benefit more from that trend in the long term?



    Oracle Corporation (ORCL) is a well-known database giant in the technology industry, providing a wide range of software and hardware products to businesses around the world. With a strong focus on innovation and cutting-edge technology, Oracle has continued to stay ahead of the curve in the ever-evolving world of data management.

    One of Oracle’s most exciting new projects is Stargate, a scalable and highly performant data gateway that aims to revolutionize how businesses access and interact with their data. With features like real-time analytics, built-in security, and seamless integration with other Oracle products, Stargate is set to become a game-changer in the world of data management.

    Another exciting development from Oracle is DeepSeek, an advanced search engine that leverages artificial intelligence and machine learning to provide users with more accurate and relevant search results. By analyzing user behavior and preferences, DeepSeek is able to deliver personalized search experiences that are tailored to each individual user.

    As Oracle continues to push the boundaries of what is possible in the world of data management, it is clear that this database giant is not resting on its laurels. With innovative projects like Stargate and DeepSeek, Oracle is poised to remain a key player in the tech industry for years to come.

    Tags:

    Oracle, ORCL, Database, Technology, Software, Stargate, DeepSeek, Data Management, Cloud Computing, Business Solutions, IT Services, Enterprise Software, Oracle Corporation, Big Data, Artificial Intelligence, Innovation.

    #Oracle #ORCL #Spotlight #DatabaseGiantStargate #DeepSeek

  • DeepSeek clouds AI picture just as Big Tech is set to report earnings


    Big Tech’s earnings roll call kicks off later this afternoon, with Microsoft (MSFT) and Meta (META) set to announce their results after the bell. If you’d asked anyone last week about the biggest thought on Wall Street’s mind heading into earnings, they likely would have given you a number of responses ranging from the impacts of the new Trump administration to capital expenditures.

    That all changed Monday when the market went into full meltdown over DeepSeek AI. The China-based company sent Wall Street into panic mode over claims that its latest AI model, DeepSeek-R1, matches the performance of models produced by Silicon Valley’s biggest tech names, including OpenAI and Meta, for just a fraction of the cost.

    Now the big question on investors’ minds is how Big Tech will respond to what could mark a titanic shift in the ever-changing AI space. It’s not only a question of how companies like Microsoft, Meta, Google (GOOG, GOOGL), and Amazon (AMZN) are spending the billions they’ve poured into developing AI models, but whether Nvidia (NVDA), the biggest winner of the AI explosion, is wildly overvalued.

    Wall Street already hammered Nvidia Monday, sending shares plummeting and wiping out nearly $600 billion from its market cap. But it’s not all doom and gloom for the AI trade. Some analysts see DeepSeek as a net positive for the AI industry.

    In a recent investor note, Bernstein analyst Stacy Rasgon said that if DeepSeek’s claims are correct and it’s managed to improve overall AI training efficiency, tech companies will likely see an increase in demand for AI technologies and that any computing power saved by DeepSeek’s approach will end up being used up to meet that new demand.

    Rasgon also points out that it’s highly unlikely that competing AI firms were unaware of the techniques DeepSeek used to develop its latest model. That’s not a stretch either. DeepSeek announced its DeepSeek-V3 model in December and R1 on Jan. 20.

    DeepSeek-V3 is the model the company said it spent just $5 million to train, compared to the estimated $100 million other companies have spent training their models. Despite knowing about both V3 and R1, Meta went ahead and announced its plans to spend upwards of $65 billion in 2025 on AI.

    Microsoft, for its part, said that it will spend $80 billion on its own AI buildout in the company’s fiscal 2025, though it made the announcement in early January.

    Other analysts still have questions about DeepSeek’s claims, with Truist Securities analyst William Stein saying it’s difficult to confirm the company’s statements as to the number and type of chips it used to train its models and how long training took.





    As Big Tech giants like Amazon, Apple, Google, and Facebook prepare to report their earnings, all eyes are on the future of AI technology. And one company that is making major waves in the industry is DeepSeek Clouds.

    DeepSeek Clouds is revolutionizing the way we interact with AI through their cutting-edge picture recognition technology. By leveraging advanced machine learning algorithms, DeepSeek Clouds is able to analyze images with unprecedented accuracy and speed.

    As the tech giants gear up to reveal their financial performance, the spotlight is on the potential impact of AI on their bottom line. Will DeepSeek Clouds’ innovative AI picture recognition technology disrupt the market and change the game for Big Tech? Only time will tell.

    Stay tuned for more updates on DeepSeek Clouds and the future of AI in the tech industry. This is one company to watch as we enter a new era of innovation and growth. #DeepSeekClouds #AI #BigTechEarnings.

    Tags:

    1. DeepSeek clouds AI picture
    2. Big Tech earnings report
    3. AI technology in cloud computing
    4. Tech industry earnings forecast
    5. SEO for DeepSeek cloud AI
    6. Big Tech financial performance
    7. Artificial intelligence in tech earnings
    8. Cloud computing trends in Big Tech
    9. DeepSeek AI picture analysis
    10. Tech giants earnings report.

    #DeepSeek #clouds #picture #Big #Tech #set #report #earnings

  • Why DeepSeek could mark a turning point for Silicon Valley on AI



    New York
    CNN
     — 

    Silicon Valley is coming to grips this week with the realization that creating an advanced artificial intelligence model may no longer be as specialized a task as was once believed.

    The wakeup call came in the form of DeepSeek, a year-old Chinese start-up whose free, open-source AI model, R1, is more or less on par with advanced models from American tech giants — and it was built for a fraction of the cost, apparently with less advanced chips and it demands far less data center power to run.

    Until now, the widely accepted wisdom in the US tech world was that American tech giants could stay ahead by spending billions of dollars, amassing advanced chips and building out huge data centers (despite the environmental cost). Essentially, because they’re among the richest companies in the world, they believed they could throw more resources at the problem than anyone else and come out on top.

    Now, all of that has been called into question. And tech giants are facing tough questions from Wall Street.

    The name of the AI game may no longer be winning with the most expensive, ever-more powerful models.

    “The paradigm is shifting,” said Zack Kass, an AI consultant and former OpenAI go-to-market lead.

    “It’s so hard to own a scientific breakthrough” such as an AI model advancement, Kass said, and prevent competitors from catching up. Instead, tech companies may now find themselves competing to lower costs and build more helpful applications for consumers and corporate customers — and also to suck up less power and natural resources in the process.

    At least one American tech leader has already promised to respond to DeepSeek by speeding up the release of more powerful models.

    OpenAI CEO Sam Altman called DeepSeek’s R1 model “impressive” in an X post Monday, adding that “we will pull up some releases” of new models in response. OpenAI Chief Product Officer Kevin Weil also said the company’s upcoming o3 model, set to launch in the coming weeks, would “be another major step up.”

    “It’s a super competitive industry, right? And this is showing that it’s competitive globally, not just within the US,” Weil said on a call with reporters about OpenAI’s new ChatGPT offering for government agencies, in response to a question from CNN. “We’re committed to moving really quickly here. We want to stay ahead.”

    But analysts also expect the Big Tech companies to scale back their data center spending plans and potentially rethink how much they’re charging consumers. DeepSeek has proved it’s possible to provide the technology at a lesser cost, although some industry experts have raised eyebrows at the startup’s claims about spending just under $6 million to build its model.

    OpenAI’s largest investor, Microsoft, is investigating whether DeepSeek trained its model off of stolen OpenAI data, Bloomberg reported. Even if the company achieved its efficiency revolution with some malfeasance, DeepSeek’s achievements have lit a fire under Silicon Valley’s AI industry.

    “All those other frontier model labs — OpenAI, Anthropic, Google — are going to build far more efficient models based on what they’re learning from DeepSeek,” said Gil Luria, head of technology research at investment firm D.A. Davidson. “And you’ll be able to use those at a fraction of the price that you can now, because it’s going to be a fraction of the cost to run those models.”

    To be sure, the industry was almost certainly going to eventually shift its focus to “efficiency” — working to add AI capabilities using a set amount of computing power versus adding more servers to juice the technology. There are only so many computers you can build and only so much electricity available to service them. And an AI tool can only get so proficient at, say, writing emails or planning trips, before making it marginally more powerful is no longer worthwhile.

    But DeepSeek appears to have sped up that timeline. And in Silicon Valley, unwinding spending on data centers could be tricky.

    Just last week, OpenAI, Oracle and SoftBank visited the White House to announce the creation of a new company and a $500 million investment in US AI infrastructure; Microsoft CEO Sundar Pichai affirmed he was “good for” his company’s planned $80 billion investment in AI development and infrastructure this year; and Meta CEO Mark Zuckerberg said his company’s AI spending could reach as much as $65 billion this year.

    “That crazy AI data center build-out that we’ve been talking about for the last couple of years? They don’t need to do that anymore. They can build a lot less because they can provide a lot more services at a much lower price,” Luria said. He added that investors will likely expect to hear about those plans in the American tech companies’ earnings calls over the next two weeks.

    Of course, if the tech giants cut data center costs for training AI models — and therefore charge customers less — their tools will get used more, putting more inference (or people asking questions) strain on the data centers, Bloomberg Intelligence analysts wrote Tuesday. So just how dramatic that pullback on data center spending might be remains to be seen.

    Some tech leaders say they’re looking at DeepSeek as validation — rather than a threat.

    Proponents of open-source AI — where the model’s underlying architecture is made publicly available, rather than charged for — say the Chinese model is proof that American companies should be sharing their innovations rather than gatekeeping them. That way, the whole US field could advance more quickly and remain the technology standard around the world.

    “The United States already has the best closed models in the world. To remain competitive, we must also support the development of a vibrant open-source ecosystem,” former Google CEO Eric Schmidt wrote in a Washington Post op-ed Tuesday.

    Meta, which has pushed open-source AI with its Llama model, also said such models are “driving a significant shift in the industry, and that’s going to bring the benefits of AI to everyone faster.”

    And even if DeepSeek forces a short-term rethinking of the business model Silicon Valley had envisioned for AI, people who believe the technology will change the world should be glad for the advancement, Kass said.

    “We are freaked out fairly, I suppose, because we thought we had global AI supremacy, when, in fact, we should be celebrating,” Kass said. “Because this is one more piece of evidence that the AI revolution is going to democratize technology and it’s going to be fairly distributed.”



    DeepSeek, the latest AI technology developed in Silicon Valley, has the potential to mark a turning point for the tech industry. With its advanced capabilities in deep learning and natural language processing, DeepSeek has the power to revolutionize how we interact with technology.

    One of the key features of DeepSeek is its ability to understand and respond to human language in a more natural and intuitive way. This opens up a whole new world of possibilities for AI applications, from virtual assistants to customer service bots. By enabling more human-like interactions, DeepSeek has the potential to greatly enhance user experience and make technology more accessible to a wider audience.

    Furthermore, DeepSeek’s deep learning capabilities allow it to continuously improve and adapt to new information, making it more efficient and accurate over time. This means that as more data is fed into the system, DeepSeek will only get smarter and more effective at its tasks.

    With the potential for such groundbreaking advancements, DeepSeek could be the catalyst for a new era of AI innovation in Silicon Valley. By pushing the boundaries of what is possible with artificial intelligence, DeepSeek could inspire other tech companies to invest in similar technologies and drive the industry forward.

    Overall, the emergence of DeepSeek signals a significant milestone for Silicon Valley and the tech industry as a whole. By harnessing the power of AI in new and innovative ways, DeepSeek has the potential to reshape the future of technology and usher in a new era of possibilities.

    Tags:

    1. DeepSeek AI technology
    2. Silicon Valley innovation
    3. Artificial intelligence breakthrough
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    10. DeepSeek’s potential in shaping Silicon Valley’s future

    #DeepSeek #mark #turning #point #Silicon #Valley

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