Tools & Platforms
It shocked the US market but has China’s DeepSeek changed AI?
ShutterstockUS President Donald Trump had been in office scarcely a week when a new Chinese artificial intelligence (AI) app called DeepSeek jolted Silicon Valley.
Overnight, DeepSeek-R1 shot to the top of the Apple charts as the most downloaded free app in the US.
The firm said at the time its new chatbot rivalled ChatGPT. Not only that. They asserted it had cost a mere fraction to develop.
Those claims – and the app’s sudden surge in popularity – wiped $600bn (£446bn) or 17% off the market value of chip giant Nvidia, marking the largest one-day loss for a single stock in the history of the US stock market.
Several other tech stocks with exposure to AI were caught in the downdraft, too.
DeepSeek also cast doubt on American AI dominance. Up until then, China had been seen as having fallen behind the US. Now, it seemed as though China had catapulted to the forefront.
Venture capitalist Marc Andreessen referred to the arrival of DeepSeek-R1 as “AI’s Sputnik moment,” a reference to the Soviet satellite that had kicked off the space race between the US and the USSR more than a half century earlier.
Bloomberg via Getty ImagesStill relevant
It has now been six months since DeepSeek stunned the world.
Today, China’s breakthrough app has largely dropped out of the headlines. It’s no longer the hot topic at happy hour here in San Francisco. But DeepSeek hasn’t disappeared.
DeepSeek challenged certain key assumptions about AI that had been championed by American executives like Sam Altman, CEO of ChatGPT-maker OpenAI.
“We were on a path where bigger was considered better,” according to Sid Sheth, CEO of AI chip startup d-Matrix.
Perhaps maxing out on data centres, servers, chips, and the electricity to run it all wasn’t the way forward after all.
Despite DeepSeek ostensibly not having access to the most powerful tech available at the time, Sheth told the BBC that it showed that “with smarter engineering, you actually can build a capable model”.
The surge of interest in DeepSeek took hold over a weekend in late January, before corporate IT personnel could move to stop employees from flocking to it.
When organisations caught on the following Monday, many scrambled to ban workers from using the app as worries set in about whether user data was potentially being shared with the People’s Republic of China, where DeepSeek is based.
But while exact numbers aren’t available, plenty of Americans still use DeepSeek today.
Certain Silicon Valley start-ups have opted to stick with DeepSeek in lieu of more expensive AI models from US firms in a bid to cut down on costs.
One investor told me for cash-strapped firms, funds saved by continuing to use DeepSeek are helping to pay for critical needs such as additional headcount.
They are, however, being careful.
In online forums, users explain how to run DeepSeek-R1 on their own devices rather than online using DeepSeek’s servers in China – a workaround they believe can protect their data from being shared surreptitiously.
“It’s a good way to use the model without being concerned about what it’s exfiltrating” to China, said Christopher Caen, CEO of Mill Pond Research.
US-China rivalry
CFOTO/Future Publishing via Getty ImagesDeepSeek’s arrival also marked a turning point in the US-China AI rivalry, some experts say.
“China was seen as playing catch-up in large language models until this point, with competitive models but always trailing the best western ones,” policy analyst Wendy Chang of the Mercator Institute for China Studies told the BBC.
A large language model (LLM) is a reasoning system trained to predict the next word in a given sentence or phrase.
DeepSeek changed perceptions when it claimed to have achieved a leading model for a fraction of the computational resources and costs common among its American counterparts.
OpenAI had spent $5bn (£3.7bn) in 2024 alone. By contrast, DeepSeek researchers said they had developed DeepSeek-R1 – which came out on top of OpenAI’s o1 model across multiple benchmarks – for just $5.6m (£4.2m).
“DeepSeek revealed the competitiveness of China’s AI landscape to the world,” Chang said.
American AI developers have managed to capitalize on this shift.
AI-related deals and other announcements trumpeted by the Trump administration and major American tech companies are often framed as critical to staying ahead of China.
Trump’s AI czar David Sacks noted the technology would have “profound ramifications for both the economy and national security” when the administration unveiled its AI Action Plan last month.
“It’s just very important that America continues to be the dominant power in AI,” Sacks said.
DeepSeek has never managed to quell concerns over the security implications of its Chinese origins.
The US government has been assessing the company’s links to Beijing, as first reported by Reuters in June.
A senior US State Department official told the BBC they understood “DeepSeek has willingly provided, and will likely continue to provide, support to China’s military and intelligence operations”.
DeepSeek did not respond to the BBC’s request for comment but the company’s privacy policy states that its servers are located in the People’s Republic of China.
“When you access our services, your Personal Data may be processed and stored in our servers in the People’s Republic of China,” the policy says. “This may be a direct provision of your Personal Data to us or a transfer that we or a third-party make.”
Feature China/Future Publishing via Getty ImagesA new approach?
Earlier this week, OpenAI reignited talk about DeepSeek after releasing a pair of AI models.
These were the first free and open versions – meaning they can be downloaded and modified – released by the American AI giant in five years, well before ChatGPT ushered in the consumer AI era.
“You can draw a straight line from DeepSeek to what OpenAI announced this week,” said d-Matrix’s Sheth.
“DeepSeek proved that smaller, more efficient models could still deliver impressive performance—and that changed the industry’s mindset,” Sheth told the BBC. “What we’re seeing now is the next wave of that thinking: a shift toward right-sized models that are faster, cheaper, and ready to deploy at scale.”
But to others, for the major American players in AI, the old approach appears to be alive and well.
Just days after releasing the free models, OpenAI unveiled GPT-5. In the run-up, the company said it significantly ramped up its computing capacity and AI infrastructure.
A slew of announcements about new data centre clusters needed for AI has come as American tech companies have been competing for top-tier AI talent.
Meta CEO Mark Zuckerberg has ploughed billions of dollars to fulfil his AI ambitions, and tried to lure staff from rivals with $100m pay packages.
The fortunes of the tech giants seemed more tethered than ever to their commitment to AI spending, as evidenced by the series of blowout results revealed this past tech earnings season.
Meanwhile, shares of Nvidia, which plunged just after DeepSeek’s arrival, have rebounded – touching new highs that have made it the world’s most valuable company in history.
“The initial narrative has proven a bit of a red herring,” said Mill Pond Research’s Caen.
We are back to a future in which AI will ostensibly depend on more data centres, more chips, and more power.
In other words, DeepSeek’s shake-up of the status quo hasn’t lasted.
And what about DeepSeek itself?
“DeepSeek now faces challenges sustaining its momentum,” said Marina Zhang, an associate professor at the University of Technology Sydney.
That’s due in part to operational setbacks but also to intense competition from companies in the US and China, she said.
Zhang notes that the company’s next product, DeepSeek-R2, has reportedly been delayed. One reason? A shortage of high-end chips.
Tools & Platforms
Speaking to the dead? Spanish lessons? How A.I. is changing N.J. classrooms. – NJ.com
Artificial intelligence has sparked widespread concern surrounding not only its impact on jobs, but also its voracious appetite for electricity and ultimately its own environmental toll.
Industry leaders speaking at Gastech 2025 in Milan during a panel session titled ‘From investment to impact: Unlocking the potential of low consumption AI technologies to accelerate energy transition goals’ agreed that developing and deploying low-energy, high-impact AI solutions is essential to capitalise on this transformative technology while making the best use of its potential to aid in decarbonisation.
“AI is energy-hungry and it needs to be fueled heavily, and so there’s this growing demand for energy to fuel that,” said Uwa Airhiavbere, Chief Commercial Officer for Worldwide Energy & Resources at Microsoft.
Ultimately, by prioritising innovation that minimises energy consumption without compromising impact, stakeholders can ensure artificial intelligence delivers on its decarbonisation promise.
Airhiavbere stated that the true test of AI’s potential will not be just its intelligence, but its efficiency, also in terms of power consumption. Microsoft is tech provider as well as a significant energy consumer – he explained- and as such it is aiming to run all data centers in 24 countries on 100% renewable energy by year-end. It has also signed partnerships for nuclear energy and fusion energy to contain its impact on the environment. Forecast models are also part of the strategy.
“AI is energy-hungry and it needs to be fueled heavily, and so there’s this growing demand for energy to fuel that.”
– Uwa Airhiavbere, CCO – World Wide Energy & Resources, Microsoft
“We also have an inclusive, 24/7 carbon free matching, where we leverage our AI tools to match renewable energy hour by hour, to make sure that we’re not waiting to offset that energy use at the end of the year,” Airhiavbere said.
While artificial intelligence is poised to revolutionise industries and could add an estimated $13 trillion to the global economy by 2030 according to McKinsey, realising that promise depends entirely on sustainably meeting the substantial power demands of its data centers. This puts immense pressure on global energy providers who are already navigating a complex transition.
Long-term sustainable
From the perspective of energy management, the integration of AI is a delicate balancing act, explained Henri Domenach, Global Head of Energy Management at ENGIE.
“Ai is a great opportunity; we need to turn it in a long-term sustainable technology” with a more efficient management of the power needs. Domenach stressed that the integration of AI will itself help optimise the production and reduce carbon footprints. He cited improvements in renewable energy forecasting, crucial for grid stabilisation and value improvement, and a recent commissioning of a 100 MWh battery in Belgium.
Parisa Bardouni, Senior Vice President and Chief Technology Officer at Aker Solutions, said, “There is a lot to gain from collaborations and alliances among technological and energy companies as well as with customers and consumers” to find the best ways to address the AI’s power hunger.
Convergence strategy
“You need to have gas, you need to have nuclear, you need to have renewable — you cannot rely on one specific feedstock because you need to have a resilient grid to power the AI,” said Manoj Narender Madnani, Managing Director for International at MARA.
The convergence of AI and energy management, therefore, presents a clear opportunity to activate transformative solutions. These advancements could serve as a powerful catalyst for a cleaner, more streamlined energy future, driven by innovation in both hardware and software.
Increasingly, “there is a fine line between top tech companies and top energy companies,” Madanani added, saying that he would not be surprised to see some of the former become also energy businesses to better manage the artificial intelligence’s power needs.
Tools & Platforms
Unisound AI Technology (SEHK:9678): Does the Current Valuation Reflect Future Growth Potential?
Unisound AI Technology (SEHK:9678) caught the attention of investors this week with a move in its share price, prompting debate about what might be driving momentum, or if it signals fresh risks or opportunity for the company. While there hasn’t been a clear event or announcement to point to, these kinds of movements often act as a spark for investors to take a closer look at what’s happening under the hood, especially when it comes to future prospects versus the current price tag.
Stepping back, Unisound AI Technology’s performance over the year has painted a mixed picture. After gaining nearly 99% year-to-date, the stock has seen a more subdued run lately, with a modest uptick over the past day but declines across the month and week. For a company with ambitions in AI technology, such swings are a reminder that investors are constantly fine-tuning their expectations, whether that’s in response to sector enthusiasm, competitive concerns, or changes in risk appetite.
So is the recent slip a sign that the shares are set up for a rebound, or are markets wisely factoring in the next chapter of growth already? Let’s dig into the valuation to see what the numbers tell us.
Price-to-Sales of 22.3x: Is it justified?
Unisound AI Technology currently trades at a price-to-sales (P/S) ratio of 22.3, making it appear significantly more expensive than both the Hong Kong Software industry average (2.8x) and its closest peers (6.3x).
The price-to-sales ratio compares a company’s market value to its revenue, serving as a key measure for businesses that are not yet profitable. For technology and software firms, investors often use P/S when earnings are negative or volatile, as it provides a way to assess how much the market is willing to pay for each unit of sales.
A P/S ratio this elevated suggests investors are pricing in substantial growth or market dominance in the future. However, such a premium also signals heightened expectations. Unisound must deliver meaningful revenue acceleration to justify this multiple, especially given its current unprofitability.
Result: Fair Value of $589.00 (OVERVALUED)
See our latest analysis for Unisound AI Technology.
However, weak revenue growth and sustained losses remain key risks. These factors could undermine the high valuation and dampen near-term investor confidence.
Find out about the key risks to this Unisound AI Technology narrative.
Another View: What Does Our DCF Model Say?
Taking a different approach, our SWS DCF model also sizes up Unisound AI Technology but finds no reason to challenge the lofty price. It flags the stock as overvalued based on future cash flows. Could this reinforce market caution, or is there still something the market sees that is missed in the numbers?
Look into how the SWS DCF model arrives at its fair value.
Stay updated when valuation signals shift by adding Unisound AI Technology to your watchlist or portfolio. Alternatively, explore our screener to discover other companies that fit your criteria.
Build Your Own Unisound AI Technology Narrative
If you have a different perspective or want to dig into the numbers yourself, you can easily craft your own assessment in just a few minutes. Do it your way.
A great starting point for your Unisound AI Technology research is our analysis highlighting 1 key reward and 2 important warning signs that could impact your investment decision.
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This article by Simply Wall St is general in nature. We provide commentary based on historical data
and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your
financial situation. We aim to bring you long-term focused analysis driven by fundamental data.
Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material.
Simply Wall St has no position in any stocks mentioned.
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