Latest news with #JevonsParadox
Forbes
24-03-2025
- Business
- Forbes
DeepSeek And ASI-1 Mini: A Closer Look At AI Computing Optimization
AI is advancing faster than ever—that much is clear. But what's often overlooked is the knock on effect on computing power, which is struggling to keep up with demand. With models like DeepSeek and ASI-Mini 1 introducing smarter architectures, it might seem like we're on the verge of a solution. Yet, this opens up a bigger question—are we solving the compute crisis, or are we actually accelerating it? The common denominator between DeepSeek and ASI-Mini 1 is their use of Mixture of Experts (MoE)—an architecture incorporating multiple expert sub-models. Rather than engaging the entire model for every request, MoE selectively activates specialised expert models, reducing computational strain while maintaining performance. This approach enhances compute efficiency, scalability, and specialisation, making AI systems more adaptable and resource-conscious. This breakthrough has highlighted the growing importance of MoE in AI development. While both models employ MoE, ASI-Mini 1, built by takes this even further by incorporating Mixture of Agents (MoA) or Mixture of Models (MoM). As an example, MoA allows multiple autonomous AI agents to collaborate, optimising resource use and making AI more adaptable. Not only excelling in expansion, but also becoming the world's first Web3 large language model. Optimised compute usage should, in theory, reduce overall computing demand. However, it's not that simple. Jevons Paradox suggests that efficiency gains often lead to greater adoption, ultimately driving demand even higher. DeepSeek's ability to deliver high-performance AI at lower costs is a prime example—by making AI more accessible, it fuels greater investment in AI projects, intensifying the need for infrastructure. As a result, the focus shifts toward ensuring solutions are not only cost-efficient, but also scalable and adaptable to sustain AI's rapid growth. Both LLMs and AI Agents are intensifying this demand, requiring substantial computing power for training, inference, and real-time decision-making. LLMs, particularly the latest iterations with billions of parameters are computationally expensive not just during training but also where they process massive datasets and in inference, where generating responses at scale remains resource-intensive. AI Agents, operating in dynamic environments, introduce continuous workloads, constantly analysing incoming data and making autonomous decisions in real time. This sustained computational demand places additional strain on infrastructure, requiring consistent access to high-performance compute resources. As highlighted in Aethir's analysis, GPUs remain the foundation of AI infrastructure, yet their high costs, supply chain constraints, and availability pose significant challenges for businesses scaling AI operations. This surge in AI adoption makes high-performance, cost-efficient, and scalable infrastructure an imperative, particularly as businesses seek flexible, transparent, and globally distributed compute solutions to maintain a competitive edge. The market isn't just seeing incremental advancements. What we're experiencing is an infrastructural shift, where companies must rethink how they build, deploy, and sustain AI systems. That's the new status quo. One of the biggest shifts is the broadening of AI applications which are no longer limited to research labs or enterprise automation, AI is embedding itself into consumer products, financial systems, and real-time decision-making engines. AI agents, once a niche concept, are now being deployed in autonomous trading, customer interactions, creative fields, and decentralised networks, all of which require constant, real-time compute power. At the same time, we're witnessing an evolution in how AI infrastructure is funded and scaled. SingularityNET's $53M investment in AI infrastructure reflects a broader trend: businesses aren't just developing better models—they're strategising around compute access itself. The scarcity of GPUs, the need for decentralised compute solutions, and the rising costs of cloud AI infrastructure are becoming as critical as AI model improvements themselves. But, how will companies sustain this level of growth? Even with MoE and its extensions reducing computational inefficiencies, the demand isn't shrinking—it's accelerating. Companies that once focused solely on AI capabilities now must navigate compute economics just as carefully. Those who fail to plan for infrastructure growth risk being left behind.
Yahoo
24-03-2025
- Business
- Yahoo
Nvidia, AMD, Meta lead tech stock rally as tariff news, AI breakthroughs boost sector
Tech stocks were leading the US stock market rally on Monday, with headlines on more targeted tariff plans from President Donald Trump and a new AI breakthrough from Jack Ma's Ant Group helping boost the sector to start the week. Shares of Meta (META) and AMD (AMD) were each up better than 3% in early trade, while Nvidia (NVDA) stock rose as much as 2.3%. The tech-heavy Nasdaq Composite (^IXIC) was up 1.5% shortly after the market open. Monday's broad market rally followed reports late Sunday that Trump would narrow the number of US trading partners subject to reciprocal tariffs on April 2. The administration is also reportedly set to limit some industry-specific tariffs that were set to take effect, including those on cars and chips. In the tech world, news early Monday out of China that Ant Group, the Jack Ma-backed tech conglomerate, has trained cheaper AI models using Chinese-made chips and those from AMD was the latest sign the AI race continues to push new boundaries. Speaking last week at its GTC Conference, Nvidia CEO Jensen Huang said the introduction of lower-cost models — like those most notably put forth by China's DeepSeek — shows the computing needs for AI are actually higher than previously thought. Nvidia's chips are also subject to an export ban from the US in China. Earlier this year, Nvidia stock fell over 16% in a single day after DeepSeek's R1 model matched the performance of higher-cost AI models like those from OpenAI ( at a fraction of the cost. In the weeks since these developments, the industry has seen similar breakthroughs in the same vein as that vocalized by Huang: These reflect the larger-than-imagined potential of even deeper AI investments rather than exposing the limits of current plans. (See also: Jevons Paradox.) Also in tech news, a South Korean AI chip startup, FuriosaAI, reportedly rejected an $800 million offer from Meta. This both takes a potential headache away from Meta shareholders, who might have to price in regulatory overhangs and integration costs, and shows AI startups have plenty of confidence to explore the market independently. Tech-specific developments, though a boost for the AI trade on the margins, still take a backseat to trade news. And though AI may not be the clearest fundamental winner or loser due to Trump's tariffs, tech's central role in the stock market rally since late-2022 has seen these stocks retain their leadership position on the way up and way down. As Yahoo Finance's Josh Schafer noted over the weekend, last week's reaction to the Federal Reserve's latest announcement made clear tariffs are — and will be — the key catalyst for markets in the coming weeks. Fears about the health of the US economy, the outlook for corporate profits, and the direction of Fed policy have all taken a turn leading the daily market discussion during the S&P 500's swift 10% pullback from its Feb. 19 record close. But tariffs have become the clear catalyst in shaping investor sentiment and the market's daily direction. First, in their absence. And on Monday, as a positive presence. "We are watching headline to headline," Jay Woods, chief market strategist at Freedom Capital Markets, told Yahoo Finance last week. "And when didn't we have headlines? We didn't get any headlines out of Washington last Friday [March 14]. We didn't get any headlines out of Washington last Monday [March 17]. Guess what we did? We rallied." Click here for in-depth analysis of the latest stock market news and events moving stock prices Sign in to access your portfolio
New York Times
14-02-2025
- Business
- New York Times
DeepSeek Doesn't Scare OpenAI, Thanks to the ‘Jevons Paradox'
Economic jargon is usually confined to textbooks and business school seminars. But every once in a while, something happens in the world that drives the lingo out of obscurity and into popular discussions. One such emergence happened late last month when, following a weekend of alarm over the viability of A.I. investments, Microsoft's chief executive, Satya Nadella, told followers in a post on X: 'Jevons paradox strikes again! As A.I. gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can't get enough of.' The Jevons Paradox is named after the 19th-century economist and logician William Stanley Jevons. In his 1865 book, 'The Coal Question,' he noted that as engines improved and made coal more efficient — requiring less of the resource to produce the same amount of energy — demand for coal would actually increase, not decrease. In other words, he said, a drop in the cost of production often leads to greater production. Televised citations (and recitations) of Jevons took off on Monday Jan. 27, as the U.S. stock market was rattled. A Chinese artificial intelligence start-up, DeepSeek, became an overnight sensation when its app shot to the top of Apple's App Store following the release of its latest reasoning model. The Chinese company had created an A.I. tool with analytical capabilities rivaling those developed by Google and Microsoft's OpenAI. And, it appeared, the company had done it at a fraction of the cost. That sparked an 'oh, expletive' panic for U.S. investors who had been shoveling trillions of dollars into the megatech firms that were building and buying advanced U.S. chips for A.I. Nvidia — the center of the American A.I. universe, and the world's most valuable company — experienced a staggering one-day rout, losing hundreds of billions of dollars in market capitalization. But wait a second, pump the brakes, said a counter-chorus of analysts and executives, echoing Mr. Nadella. Even if DeepSeek was as cheap as its coders claimed, they said, it could actually be a pleasant surprise, boosting demand for U.S. chips and A.I. products in general. Was Mr. Nadella's invocation of the paradox self-serving thinking? Yes. But the argument also has a decent track record, beyond coal. (Even though Jevons himself failed to predict how resource substitutes, like petroleum, would complicate demand for coal.) Computers, for example, were once the size of living rooms and far too expensive for the average person. When they shrunk in size and cost, thanks to more-efficient processing chips, personal computers became a staple in every home. Later, smartphones settled into every palm. A lot of tech companies that were big in the '80s were trounced. But the industry blossomed. The paradox has a darker side. Greater coal use gave us an early taste of modern comforts we now can't imagine living without (thank you, electricity). It also contributed greatly to global warming. Smartphones have made us more connected and productive, but also hopelessly addicted to mindless scrolling (and in some ways, lonelier). If these past Jevons paradoxes are any guide, greater A.I. use is sure to give us a similar mix of unforeseen marvels, and miseries.
Yahoo
07-02-2025
- Business
- Yahoo
Buying This Top Artificial Intelligence (AI) Stock Looks Like a No-Brainer Right Now
The artificial intelligence (AI) ecosystem was rocked recently by news that Chinese start-up DeepSeek had developed a cost-effective and competent large language model on the cheap. That revelation called into question the tens of billions of dollars that are being poured into the buildout of AI infrastructure, but it looks like the robust spending environment in the tech sector is here to stay. Even after the DeepSeek news, the CEOs of both Meta Platforms and Microsoft asserted that heavy capital expenses would still be necessary to meet the computing power requirements for the forecast increase in demand for AI applications. Moreover, DeepSeek's ability to build an AI model with a significantly lower investment is expected to spur the demand for AI, based on an economic concept called Jevons Paradox. The management team at ASML Holding (NASDAQ: ASML) holds a similar view. In an interview with CNBC discussing the Dutch company's fourth-quarter results (which it released on Jan. 29), CEO Christophe Fouquet remarked that a low-cost AI model could drive demand for AI applications, which in turn would increase the need for processing power to support them. Fouquet added that he doesn't see a slowdown in chip demand following DeepSeek's breakthrough, and demand for its chipmaking equipment was solid in Q4. All this was enough to send shares of ASML up by more than 3% following its earnings report. Here's why this semiconductor sector bellwether seems worth buying right now. ASML sells lithography equipment that's used by chipmakers in their foundries. So, the health of the semiconductor industry and the state of chip demand tend to dictate ASML's financial performance. However, the stock has been underperforming over the past couple of years. ASML is up by just 9% in the last two years as compared to the 63% gains registered by the PHLX Semiconductor Sector index over the same period. That below-par performance can be attributed to weaknesses in certain pockets of the semiconductor market, which counterbalanced the sharp growth in demand for high-end AI chips. However, ASML's latest results suggest that a better year is in the cards in 2025. The company recorded new bookings worth 7.1 billion euros in Q4, an increase of almost 170% from the third quarter. Analysts were expecting just 3.5 billion euros worth of new bookings in Q4. ASML smashed that target thanks to the robust demand for its extreme ultraviolet lithography (EUV) machines. EUV machines are used to print the most advanced chips, such as the ones that are best suited to handle AI workloads. ASML received 3 billion euros worth of orders for these machines during the quarter, suggesting that demand for AI chips will remain healthy. As a result, ASML entered 2025 with a solid order backlog of 36 billion euros. Management is confident that it will be able to hit the higher end of its 2025 revenue forecast range of 30 billion euros to 35 billion euros if "AI demand continues to be strong and customers are successful in bringing on additional capacity online to support that demand." The higher end of the guidance range would equate to a jump of 24% in revenue. Additionally, the company expects its gross margin to land between 51% and 53% this year, which at the midpoint would be a slight improvement over its 2024 gross margin. This could set ASML up for better bottom-line performance in 2025 following a slight dip in its earnings per share last year. Analysts' consensus estimate is for a 24% increase in ASML's earnings in 2025 to 23.92 euros per share. That would translate into $24.50 at the current exchange rate. Assuming ASML indeed hits that mark and trades at 33.4 times earnings at that time (in line with the tech-laden Nasdaq-100 index's earnings multiple), its stock price would rise by 11% to $819 in the next 12 months. However, stronger gains cannot be ruled out if the company clocks stronger earnings growth and the market decides to reward the stock with an even higher multiple. Given that ASML is trading at 29 times forward earnings right now, investors can get a good deal on a semiconductor stock with the potential to deliver healthy gains. Before you buy stock in ASML, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and ASML wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $765,024!* Now, it's worth noting Stock Advisor's total average return is 921% — a market-crushing outperformance compared to 177% for the S&P 500. Don't miss out on the latest top 10 list. Learn more » *Stock Advisor returns as of February 3, 2025 Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends ASML, Meta Platforms, and Microsoft. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy. Buying This Top Artificial Intelligence (AI) Stock Looks Like a No-Brainer Right Now was originally published by The Motley Fool
Yahoo
07-02-2025
- Business
- Yahoo
Palantir (PLTR) Faces Sell Rating Despite AI Growth and Strong Earnings
We recently published a list of . In this article, we are going to take a look at where Palantir Technologies Inc. (NASDAQ:PLTR) stands against other top AI stocks trending on Wall Street. The tech world may be steering in a new direction with the emergence of DeepSeek and the cheaper and more efficient models it promises. In the latest news, bulls from Europe have deemed that the sector may have further to run, despite the emergence of these Chinese copies. This news emerged after January 27, when the tech world witnessed a broad market sell-off driven by DeepSeek's advancements, investors' concerns regarding West's huge investments in chipmakers and data centers, valuation risks, and increasing competition from alternative AI models. In short, DeepSeek sparked a rout in the tech world. READ ALSO: and With the emergence of these models, companies are readjusting their approaches, focusing more on efficiency rather than demand. Even big AI names such as OpenAI have been prompted to rethink their strategies. The AI startup is reportedly thinking of 'figuring out a different open-source strategy' after DeepSeek released a lower-cost open-source AI model, Seeking Alpha reported Saturday. Moreover, OpenAI Chief Product Officer Kevin Weil recently unveiled that the company was considering open-sourcing older AI models. This reflects a broader industry shift toward efficiency and accessibility. Nevertheless, since the sell-off, tech stocks have thankfully rebounded. European markets in particular are hitting new highs, Reuters reports. One economic theory, known as the 'Jevons Paradox' seems to be the answer. According to the paradox, when a resource becomes more efficient to use, demand may increase rather than the other way around. This is because the price of using the resource drops. 'I hadn't discussed it until Monday (last week), and then suddenly it's everywhere. This paradox highlights one of the uncertainties at the moment,' said Jewell, flagging that a key question for European stock-pickers is whether data centres and their suppliers will be less in demand.' For this article, we selected AI stocks by going through news articles, stock analysis, and press releases. These stocks are also popular among hedge funds. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter's strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (). A software engineer manipulating a vast network of code on virtual Technologies Inc. (NASDAQ:PLTR) is a leading provider of artificial intelligence systems. On February 3rd, William Blair analyst Louie DiPalma reiterated their bearish stance on the stock, giving a 'Sell rating'. The rating largely stems from Palantir (NASDAQ:PLTR)'s valuation and future growth prospects. According to the firm, recent revenue and operating income exceeded expectations, and its software products, Foundry and Gotham, are also gaining traction. CEO Alex Karp has attributed much of the company's growth to their use of artificial intelligence. Nevertheless, the firm stated that the stock is currently valued at a premium compared to peers with similar business fundamentals. Moreover, despite positive developments in AI, the risk of valuation multiple compression remains a risk. The potential market correction and the company's revised revenue guidance for 2025 which falls short of previous targets has in turn led the firm to maintain the Sell rating. Overall, PLTR ranks 7th on our list of top AI stocks trending on Wall Street. While we acknowledge the potential of PLTR as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and doing so within a shorter time frame. If you are looking for an AI stock that is more promising than PLTR but that trades at less than 5 times its earnings, check out our report about the . READ NEXT: 20 Best AI Stocks To Buy Now and Complete List of 59 AI Companies Under $2 Billion in Market Cap Disclosure: None. This article is originally published at Insider Monkey. Sign in to access your portfolio
