Market update
A recent 3% inflation reading suggests that inflation is now more entrenched, signaling that higher prices may linger more than anticipated. Also, The US added 143,000 jobs in January, with
unemployment at 4% and wages up 4.1% year-over-year. Trump’s new 25% tariffs on steel and aluminum, along with trade tensions, add further uncertainty to inflation. Despite new Trump tariff threats,
strong corporate earnings propelled U.S. stocks near record highs, overshadowing lingering inflation worries. Meanwhile, Elon Musk and the Department of Government Efficiency (DOGE) face a
lawsuit over unauthorized access to government records, raising data privacy concerns.
Additionally, Apple is reportedly exploring humanoid robots, projecting 2028 for mass production. Lastly, on Sunday, the Super Bowl attracted a record 127.7 million viewers, partly due to a boost
from free streaming.

What’s in Store for the AI Market in 2025?
Moving on to one of the most dynamic and disruptive topics in tech—the AI market. As we step into 2025, artificial intelligence is not just an emerging technology; it is a foundational pillar reshaping industries and economic structures. With a projected market size of $1.8 trillion by 2030, AI is set to be one of the most influential drivers of global growth. From
healthcare and finance to transportation and automation, AI-powered solutions are improving efficiency, reducing costs, and revolutionizing how businesses operate.

In the U.S., AI adoption is accelerating at an unprecedented rate. Over 35% of businesses already integrate AI into their operations, and that number is expected to rise sharply as technology
becomes more affordable, scalable, and efficient. The potential economic impact is staggering— AI could boost global GDP by approximately $15.7 trillion by 2030, making it one of the most
significant value-generating innovations of the 21st century.

The AI Boom Meets a Reality Check

While AI’s potential continues to excite investors, the landscape is also witnessing a major shake-up. The recent debut of DeepSeek, a Chinese AI startup, has triggered industry-wide debates
on cost-efficiency, technological leadership, and market dominance. DeepSeek’s low-cost AI model, released in January 2025, has upended conventional beliefs about AI development and
its financial sustainability. Unlike traditional large-scale AI models requiring massive capital investments, DeepSeek’s model delivers comparable performance at a fraction of the cost. This
breakthrough has had immediate ripple effects:
• Tech stocks faced turbulence, with U.S. AI giants like Nvidia losing $590 billion in market value as investors reconsidered the economic efficiency of AI model training.
• AI infrastructure spending was questioned, as DeepSeek demonstrated that high- performance AI could be trained on less advanced chips at a significantly lower cost.
• The U.S.’s perceived lead in AI technology faced scrutiny, as DeepSeek proved that innovation can thrive beyond Silicon Valley. This disruption marks a pivotal moment for AI investments—shifting the focus from scaling up at all costs to delivering tangible, cost-efficient
results.
This disruption marks a pivotal moment for AI investments—shifting the focus from scaling up at all costs to delivering tangible, cost-efficient results. Despite the initial turbulence, U.S. tech giants remain steadfast in their AI investments. Companies like Microsoft, Amazon, Alphabet, and Meta have reaffirmed their commitment, with a combined $320 billion in planned AI-related capital expenditures for 2025. However, their investment strategies are adapting in response to DeepSeek’s disruption:
• Shift Toward AI Efficiency: Instead of endlessly scaling training models, hyperscalers are
focusing on AI inference—deploying models efficiently rather than continuously increasing computing
power.
• Diversification of AI Hardware Suppliers: As reliance on Nvidia GPUs becomes a strategic risk, tech firms are increasingly exploring alternative AI accelerators, including tensor processing
units (TPUs), field-programmable gate arrays (FPGAs), and next- generation photonic chips. This shift is driven by the need for greater cost efficiency, energy optimization, and supply chain resilience in AI model training and deployment.
• Data Center Expansion with Focused Spending: While hyperscalers were previously expected to increase AI-related power demand by 26% CAGR, DeepSeek’s efficiency suggests a more restrained
trajectory, leading firms to optimize spending on data centers. The market is moving from a “tell me” phase—where companies justified sky-high valuations based on
AI potential—into a “show me” era, where investors and shareholders demand tangible returns on AI spending. As we move deeper into 2025, AI is expected to enter a new phase—one that prioritizes
practicality, affordability, and sustainable innovation.

Top 5 Recent AI Highlights
With AI shifting toward efficiency and real-world impact, here are the top five highlights shaping the industry in this month.
[1] OpenAI plans to unify the “o” series into GPT-5 while outlining the roadmap, integrating all tools across tasks, and eliminating the standalone o-series models. CEO Sam Altman predicts that
the cost of using AI will decrease tenfold each year. He compares this trend to Moore’s Law but at a much faster rate, citing how the token cost from GPT-4 to GPT-4o dropped 150 times. Altman also
argues that AI intelligence grows in direct proportion to investment and that there is no reason for exponential spending to slow down. Additionally, Open AI devs released some “best practices”
for using the o-series. Read more from BI and X.

[2] Elon Musk’s consortium has offered a staggering $97.4 billion to buy out OpenAI’s nonprofit arm, escalating tensions with OpenAI CEO Sam Altman. Rumors suggest the nonprofit unit could be
only worth $40 billion. In a court filing, Musk pledged to withdraw his bid if the board halts OpenAI’s for-profit transition, complicating the value of OpenAI buying out the non-profit arm.
Meanwhile, OpenAI is fast-tracking its own AI chip production to reduce reliance on Nvidia by 2026. On that topic, Perplexity’s latest Sonar is using Cerebra’s chips to reduce reliance on Nvidia chips. OpenAI also ran a $14 million

Super Bowl ad, describing AI as the next major technological breakthrough. More from Reuters, YF, and TC.

[3] French President Emmanuel Macron announced a €109 billion AI investment to position France as a global leader, with funding from international and domestic sources. The investment will
primarily support AI-focused data centers, aligning with the U.S. Stargate initiative. Macron highlighted Europe’s AI competitiveness, citing startups like Mistral and LightOn. France also aims to leverage its nuclear electricity surplus to attract AI investments. Read more from TC.

[4] Vice President JD Vance, speaking in Paris, urged Europe to dismantle AI regulations. He emphasized an America First strategy, ensuring top A.I. systems use American-designed chips. Criticizing the EU’s Digital Services Act and other policies, he argued they stifle innovation and urged prioritizing growth over excessive oversight. His speech reinforced the Trump administration’s push for deregulation, aiming to solidify U.S. A.I. leadership while pressuring allies to adopt an innovation-friendly approach. Notably, the U.S. and U.K. declined to sign a universal AI declaration. More from WSJ.

[5] Former OpenAI chief scientist Ilya Sutskever’s AI startup, Safe Superintelligence (SSI), is in talks to raise funding at a $20 billion valuation, a fourfold jump since September. Unlike OpenAI,
SSI emphasizes AI safety over rapid commercialization. Founded in June with ex-Apple AI lead Daniel Gross and former OpenAI researcher Daniel Levy, SSI remains secretive about its technology.
However, Sutskever’s reputation and novel AI approach have fueled investor interest, highlighting the ongoing demand for safe, advanced AI development. More from YF.

Source:
Carter, Tom. “OpenAI Is Taking a Page Out of Big Tech’s Playbook by Reportedly Building Its Own Chips.” Business Insider, 31 Oct. 2024, www.businessinsider.com/openai-chip-design-
tsmc-broadcom-big-tech-nvidia-2024-10?utm_source=chatgpt.com.
Morgan, J. P. DeepSeek’s Latest AI Model Prompts Market Frenzy, but Investors Should Remember to Stay the Course | J.P. Morgan. www.jpmorgan.com/insights/markets/top-market-
takeaways/tmt-deepseeks-latest-ai-model-prompts-market-frenzy-but-investors-should-remember-to-stay-the-course.
PricewaterhouseCoopers. “PwC’s Global Artificial Intelligence Study: Sizing The Prize.” PwC, www.pwc.com/gx/en/issues/artificial-intelligence/publications/artificial-intelligence-study.html.
Subin, Samantha. “Tech Megacaps Plan to Spend More Than $300 Billion in 2025 as AI Race Intensifies.” CNBC, 8 Feb. 2025, www.cnbc.com/2025/02/08/tech-megacaps-to-spend-more-
than-300-billion-in-2025-to-win-in-ai.html#:~:text=Meta%2C%20Amazon%2C%20Alphabet%20and%20Microsoft,them%20ahead%20of%20the%20competition.