In the fast-paced world of technology investment, another critical earnings season is upon us, particularly focusing on major U.Stech companiesThis week, giants like Apple, Microsoft, Meta, and Tesla are poised to release their financial reports, with their stock prices lingering near all-time highs and valuations that have reached unprecedented levelsHowever, this earnings season is marked by a significant change; analysts predict that the growth in quarterly profits for the so-called "Magnificent Seven" tech giants will represent the slowest pace in nearly two yearsAs Wall Street analysts suggest, the bar for exceeding expectations has been significantly raised this time aroundSince the end of 2022, the Nasdaq 100 index, driven by these tech behemoths, has seen an astronomical market capitalization expansion of approximately $15 trillion, which now faces a formidable test.

In parallel with these market developments, a notable event is unfolding: the rise of DeepSeek and its groundbreaking "low-cost computing revolution." Investors are starting to question whether the enormous investments being made by U.S

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tech giants in artificial intelligence are justified or have become irrationalThe DeepSeek R1, a robust AI model developed by a team from China, has taken the American social media landscape by storm, ranking at the top of app download charts in the U.Sand Apple’s Chinese store, even surpassing ChatGPTThe advent of DeepSeek R1 signifies a remarkable reduction in the costs associated with AI training and reasoningWith investment costs falling below $6 million, this new AI model is poised to rival OpenAI’s offerings, despite being based on less performant chips.

The recent surge in DeepSeek's popularity traces back to January 20, when it officially introduced its reasoning model, DeepSeek-R1. This new model had been validated by numerous tech experts for its prowess in critical areas like mathematics, programming, and reasoning, reaching a performance level that could take on OpenAI’s O1 model, often touted as the “strongest reasoning model in history,” while boasting costs of API calls that are 90%-95% lower.

DeepSeek’s success stems from meticulous engineering and incremental optimization, executed at every phase of the AI model's training

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By deploying aggressive training and data compression strategies driven by a focus on minimizing unnecessary computational power, they have successfully maximized resource utilization during trainingTechniques such as Multi-Layer Attention (MLA), FP8 mixed precision, DualPipe parallel communication, and expert gate load balancing have contributed significantly to achieving efficiency without sacrificing performanceInnovative AI training methods like reinforcement learning, distillation, and optimized data processing have further bolstered DeepSeek's output.

In essence, DeepSeek's approach exemplifies how fine-tuned engineering, keen data optimization, and refined post-training techniques can slash the ineffective consumption of generic computational resourcesBy concentrating their efforts on elements that most significantly boost performance — critical operators, attention heads, and fine-tuning mechanisms — DeepSeek poses a serious challenge to the traditional high-cost, money-burning modus operandi that has long characterized research and development within the tech domain in the U.S.

Amidst this dynamic landscape, global investors are keenly watching whether the massive investments made by the four giants in AI can yield substantial revenues and profitability, which would ideally surpass market expectations

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Should these companies fail to deliver profits that reflect their substantial input in AI development, the interpretation would be that their spending could dangerously erode profits attributable to common shareholders, potentially triggering a wave of selling across the market.

This week, Apple's, Microsoft's, Meta's, and Tesla's performances are closely scrutinized as they symbolize hopes for U.Sstock performanceTheir results hold immense significance not only for U.Smarkets but for the global stock scene, as these companies command nearly 40% weighting within the S&P 500 and the Nasdaq Composite indicesTheir outcomes could potentially reshape investment sentiment surrounding AI's profitability and growth prospects; a dissatisfactory performance would likely lead to skepticism about the revenue-generating prospects tied to AI investments, possibly resulting in a downturn reminiscent of last summer's global tech stock plunge.

The term "Magnificent Seven," which includes Apple, Microsoft, Google, Tesla, Nvidia, Amazon, and Meta Platforms, defines the powerhouse driving the new peaks in the technology sector and beyond

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Their consistent engagement in AI has resulted in robust revenue streams and solid fundamentals, leading to a surge of investments drawn from numerous global sourcesAs companies like Google, Nvidia, and Amazon prepare to report their earnings soon, the world watches with bated breath.

This earnings season, which signals a potentially sobering realization for bullish investors on Wall Street, comes amidst a backdrop of rising market capitalizations driven by the tech sectorThe so-called "big seven" continue to report increasing earnings; however, forecasts indicate a noticeable slowdown in growth rates compared to prior quartersThe current capital requirements, together with a shifting baseline and lingering uncertainty regarding the expansive investment in AI, suggest that the performance of these technology giants is under increasing scrutiny.

Since late 2022, the optimistic outlook for tech giants concerning AI profitability fueled a phenomenal expansion of the Nasdaq 100 index's total market capitalization, estimated to be around $15 trillion

Yet, this trajectory has slowed significantly as the market grows concerned that expectations for AI profitability may diverge from reality — a situation that could obstruct growth potential and profits.

According to Dan Taylor, Chief Investment Officer at Man Numeric, the already elevated expectations for earnings have made exceeding them all the more challengingHe articulated, "This should be a fairly decent earnings season, but the benchmarks have risen, and they may struggle to meet the high expectations from the market." This sentiment indicates that the performance of these giants may not achieve the high bar set in past quarters, especially given that their valuations have significantly increased.

The profit growth of this "Magnificent Seven" faces a pivotal moment as their earnings will begin surfacing post-market hours on WednesdayCompanies like Microsoft, Meta, and Tesla are slated to unveil their results, while Apple will follow with its report on Thursday, and giants like Amazon and Google will round out the reporting cycle next week

Nvidia, a leader in AI chip manufacturing, is expected to disclose its performance on February 26.

As the long-standing bull market that began over two years ago has continued to thrive, substantial returns driven by exceptional earnings growth linked to AI have significantly contributed to this momentumDuring this period, approximately 70% of the increase in the S&P 500 index can be attributed to the performance of major tech companiesHowever, with fears of declining profits looming and skepticism about when AI investments will start yielding substantial returns now casting a cloud over market sentiment, growth has experienced a deceleration, with a brief market downturn witnessed last summer.

The findings aggregated by Bloomberg Intelligence indicate that analysts on Wall Street expect these seven tech leaders will see their profits increase by only 22% in the fourth quarter—marking the smallest growth rate since the first quarter of 2023. While this figure still significantly outpaces the expected 8% increase for the overall S&P 500 index, it falls drastically from the surefire 51% growth seen just a year prior, thus continuing the trend of decreasing profit growth.

Michael Kasper, an analyst from Bloomberg Intelligence, expressed justified concern

He noted that the tech sector in the S&P 500 has an approximate 10% higher weighting in terms of market capitalization compared to its share of total earningsAs such, expectations for earnings growth must either exceed the high bar already set, or the valuations must undergo some contraction to align more closely with profit realities.

With the emergence of DeepSeek and its low-cost computing paradigm, market participants are beginning to call into question whether the vast expenditures made by American tech giants in AI are rationalIf the output from these burgeoning AI investments remains unable to provide satisfactory revenue and profits, or if the anticipated earnings data fails to exceed market forecasts, tech stocks could face a monumental sell-off larger than that seen last summerKasper succinctly articulated the essence of investor sentiment: "We all know how investors will react if the actual results from these American tech behemoths fail to meet everyone’s expectations."

In terms of stock valuation relative to expected sales, American tech companies appear increasingly volatile