Stocks sold off sharply on Friday 28th March 2025, pressured by growing uncertainty on U.S. trade policy as well as a grim outlook on inflation
The Dow Jones Industrial Average closed down 715 points at 41,583. The S&P 500 lost 1.97% to close 5,580 ending the week down for the fifth time in the last six weeks. The Nasdaq Composite plunged 2.7% to 17,322.
Shares of several technology giants also fell putting pressure on the broader market. Google-parent Alphabet lost 4.9%, while Meta and Amazon each shed 4.3%.
This week, the S&P 500 lost 1.53%, while the 30-stock Dow shed 0.96%. The Nasdaq declined by 2.59%. With this latest losing week, Nasdaq is now on pace for a more than 8% monthly decline, which would be its worst monthly performance since December 2022.
Dow Jones one-day chart (28th March 2025)
Dow Jones one-day chart (28th March 2025)
Stocks took a leg lower on Friday after the University of Michigan’s final read on consumer sentiment for March 2025 reflected the highest long-term inflation expectation since 1993.
Friday’s core personal consumption expenditures price index also came in hotter-than-expected, rising 2.8% in February and reflecting a 0.4% increase for the month, stoking concerns about persistent inflation.
Economists had reportedly been looking for respective numbers of 2.7% and 0.3%. Consumer spending accelerated 0.4% for the month, below the 0.5% forecast, according to fresh data from the Bureau of Economic Analysis.
The market is getting squeezed by both sides. There is uncertainty about reciprocal tariffs hitting the major exporting sectors like tech alongside concerns about a weakening consumer facing higher prices
Trump’s tariffs push will hit the U.S. harder than Europe in the short term, it has been reported.
Japan’s Nikkei enters correction as Trump’s tariff assault drives sell-off in Asia markets
U.S. tech giants are making bold strides in the development of humanoid robots, signalling a transformative shift in the robotics industry
Companies like Tesla, Google, Microsoft, and Nvidia are investing heavily in this cutting-edge technology, aiming to create machines that mimic human movement and behaviour.
These humanoid robots are envisioned to revolutionise industries ranging from manufacturing to healthcare, offering solutions to labor shortages and enhancing productivity.
Tesla’s Optimus project is a prime example of this ambition. CEO Elon Musk has announced plans to produce thousands of these robots, designed to perform repetitive and physically demanding tasks.
Optimus robots are expected to integrate seamlessly into factory settings, reducing the need for human intervention in hazardous environments.
Similarly, Boston Dynamics, known for its agile robots, continues to push the boundaries of what humanoid machines can achieve, focusing on tasks that require precision and adaptability.
The integration of artificial intelligence (AI) is a driving force behind these advancements. AI enables robots to learn from their environments, adapt to new tasks, and interact with humans in more intuitive ways.
Companies like Nvidia are leveraging their expertise in AI and machine learning are helping to develop robots capable of complex decision-making and problem-solving.
However, challenges remain. High production costs, limited battery life, and safety concerns are significant hurdles that need to be addressed before humanoid robots can achieve widespread adoption.
Despite these obstacles, the potential benefits are immense. From assisting the elderly to performing intricate surgeries, humanoid robots could redefine the boundaries of human capability.
As U.S. tech giants continue to innovate, the race to dominate the humanoid robotics market intensifies.
Tesla Optimus Gen 2
With China and other nations also making significant investments, the competition is fierce. Analysts warn that U.S. firms could lose out to China, which aims to replicate its success with electric vehicles in the robotics space race.
The future of humanoid robots promises to be a fascinating blend of technology, creativity, and global collaboration
U.S. companies that may benefit from this AI humanoid tech advancement
Tesla: Known for its Optimus humanoid robot project, Tesla is pushing boundaries in robotics and AI.
Google (Alphabet): A leader in AI and robotics research, with projects aimed at enhancing humanoid capabilities.
Microsoft: Investing in AI technologies that support robotics and automation.
Nvidia: Provides advanced AI chips and systems crucial for humanoid robot development.
Boston Dynamics: Famous for its agile robots like Atlas, focusing on precision and adaptability.
Agility Robotics: Creator of Digit, a humanoid robot designed for logistics and manufacturing.
Meta (Facebook): Exploring humanoid robots for social and interactive applications.
Apple: Investing in robotics and AI for potential humanoid advancements.
Amazon: Developing robots like Astro for home monitoring and other tasks.
Figure AI: Innovating humanoid robots like Figure 02 for various industries.
Bill Gates on AI
Bill Gates has shared some fascinating insights about AI recently. He reportedly believes that within the next decade, AI will transform many industries, making specialised knowledge widely accessible.
For example, he predicts that AI could provide high-quality medical advice and tutoring, addressing global shortages of doctors and educators.
Gates has also described this shift as the ‘age of free intelligence,’ where AI becomes a commonplace tool integrated into everyday life. While he acknowledges the immense potential of AI to solve global challenges – like developing breakthrough treatments for diseases and innovative solutions for climate change – he also recognises the disruptive impact it could have on jobs and the workforce.
Despite these concerns, Gates remains optimistic about AI’s ability to drive innovation and improve lives.
He has emphasised that certain human activities, like playing sports or hosting talk shows, will likely remain uniquely human.
However, despite all these predictions from powerful tech leaders – it does beg the question, do these ultra rich CEOs predict the future, or simply make it?
What if Quantum Physics coincides and collides with the ‘full’ arrival of AI and humanoid robots
Quantum computing could enhance the capabilities of AI-powered robots by solving complex optimisation problems, improving machine learning algorithms, and enabling real-time decision-making.
For instance, robots equipped with quantum sensors could navigate intricate environments, detect subtle changes in their surroundings, and interact with humans in more intuitive ways.
This fusion could revolutionise industries such as healthcare, manufacturing, and space exploration. Imagine humanoid robots performing intricate surgeries with precision, managing large-scale logistics, or exploring distant planets with advanced problem-solving abilities.
However, this convergence also raises ethical and societal questions. The potential for such powerful technologies to disrupt industries, impact employment, and challenge privacy norms must be carefully managed.
Collaboration between scientists, policymakers, and ethicists will be crucial to ensure these advancements benefit humanity as a whole.
The intersection of quantum physics, AI, and humanoid robotics is not just a technological milestone – it’s a glimpse into a future where the boundaries of human capability and machine intelligence blur.
It’s an exciting, albeit complex future humans are creating.
But will AI surpass human intelligence – and if it does what then for the human civilisation?
Artificial General Intelligence (AGI), a form of AI capable of matching or surpassing human intelligence across all tasks, is expected to emerge within the next five to ten years, according to Demis Hassabis, CEO of Google DeepMind.
Speaking recently, Hassabis highlighted the advancements in AI systems that are paving the way for AGI.
While current AI excels in specific domains, such as playing complex games like chess or Go – it still lacks the ability to generalise knowledge and adapt to real-world challenges.
But the advancements made in AI chatbots such as ChatGPT from OpenAI and DeepSeek have showcased remarkable development, and at speed too. Applying AI to work environments, science and domestic tasks is forever expanding.
Hassabis emphasised that significant research is still required to achieve AGI. The focus lies on improving AI’s understanding of context and its ability to plan and reason in dynamic environments.
Multi-agent systems, where AI entities collaborate or compete, are seen as a promising avenue for development.
These systems aim to replicate the intricate decision-making processes humans exhibit in complex scenarios.
The implications of AGI are profound, with potential applications spanning healthcare, education, and beyond.
However, its development also raises ethical and societal questions, including concerns about control, safety, and equitable access.
While the timeline remains speculative, Hassabis’s insights underscore the accelerating pace of AI innovation, bringing humanity closer to a future where machines and humans collaborate in unprecedented ways.
The escalating AI competition between the U.S. and China has taken a new turn with the emergence of DeepSeek, a Chinese AI startup that has introduced a low-cost AI model capable of rivaling the performance of OpenAI’s models.
This development has significant implications for data centres and the broader technology sector.
The rise of DeepSeek
DeepSeek’s recent breakthrough involves the development of two AI models, V3 and R1, which have been created at a fraction of the cost compared to their Western counterparts.
The total training cost for these models is estimated at around $6 million, significantly lower than the billions spent by major U.S. tech firms. This has challenged the prevailing assumption that developing large AI models requires massive financial investments and access to cutting-edge hardware.
Impact on data centres
The introduction of cost-effective AI models like those developed by DeepSeek could lead to a shift in how data centers operate.
Traditional AI models require substantial computational power and energy, leading to high operational costs for data centers. DeepSeek’s models, which are less energy-intensive, could reduce these costs and make AI technology more accessible to a wider range of businesses and organizations.
Technological advancements
DeepSeek’s success also highlights the potential for innovation in AI without relying on the most advanced hardware.
This could encourage other companies to explore alternative approaches to AI development, fostering a more diverse and competitive landscape. Additionally, the open-source nature of DeepSeek’s models promotes collaborative innovation, allowing developers worldwide to customise and improve upon these models2.
Competitive dynamics
The competition between DeepSeek and OpenAI underscores the broader U.S.-China rivalry in the AI space. While DeepSeek’s models pose a limited immediate threat to well-funded U.S. AI labs, they demonstrate China’s growing capabilities in AI innovation.
This competition could drive both countries to invest more in AI research and development, leading to faster technological advancements and more robust AI applications.
Broader implications
The rise of DeepSeek and similar Chinese and other AI startups could have far-reaching implications for the global technology sector.
As AI becomes increasingly integrated into various industries, the ability to develop and deploy AI models efficiently will be crucial.
Data centres will need to adapt to these changes, potentially investing in more energy-efficient infrastructure and exploring new ways to support AI workloads.
Where from here?
DeepSeek’s emergence as a significant player in the AI race highlights the dynamic nature of technological competition between the U.S. and China.
While the immediate impact on data centres and technology may be limited, the long-term implications could be profound.
As AI continues to evolve, the ability to innovate cost-effectively and collaborate across borders will be key to driving progress and maintaining competitiveness in the global technology landscape.
DeepSeek’s impact probably isn’t yet fully reflected in U.S. stocks
The ramifications of the Chinese startup DeepSeek, with its promise of delivering cheaper and more energy-efficient alternatives to harness artificial intelligence (AI), have yet to be fully reflected in U.S. equities.
If DeepSeek ends up delivering a less costly way forward – it will make it much easier and cheaper for smaller more typical companies to create AI ‘agents’ or AI opportunities for their businesses.
Under this scenario there will be ‘useful’ and meaningful benefits from DeepSeek that could bring huge earnings potential for a broader mix of companies beyond the current AI heavyweights through greater efficiencies and productivity from less-expensive AI solutions.
It also put huge sums being pledged for AI infrastructure by U.S. mega cap tech companies under a microscope. Rather than back down, the U.S. spending race has intensified.
Meta’s Chief Executive Mark Zuckerberg spoke a week ago of spending ‘hundreds of billions of dollars’ on AI infrastructure in the coming years, after pledging $60 billion to $65 billion on AI this year.
Alphabet announced AI investment for 2025, a bigger figure than Wall Street was anticipating.
Google forecast $75 billion in capital expenditures in 2025, a bigger figure than Wall Street was anticipating.
Microsoft reported its cloud and AI spending grew 95% in its fiscal second quarter to $22.6 billion.
Amazon has reported big AI investment too.
The spending frenzy on anything AI sends the market into a spin. How much more has to be spent before we see capital expenditures reduced or decrease is anyone’s guess right now – but current levels of AI expenditure are high, and returns will be expected.
“When is enough, enough?”
Or more to the point you might ask – when is ‘enough’ too much?
Fresh AI-spending commitments helped lift shares of Nvidia on while we saw a slump for Tesla shares in the week.
China this week saw the U.S. slap new 10% tariffs, while Canada and Mexico saw Trump threaten but delay 25% tariffs by 30 days. China retaliated in kind.
Catching up with the ‘Magnificent Seven’
Despite the high scrutiny on AI stocks, there is also much renewed focus from investors on other areas of the market.
There has been a bit of a rotation – while tech has been under pressure, defensive and rate-sensitive parts of the market have been gaining. This seems to be an emerging pattern.
But there should be reason for caution. For one thing, the growth rate of ‘Magnificent Seven’ earnings has been tailing off in recent quarters, especially since the group reached a 61% yearly rate in the fourth quarter of 2023 – the spend on AI investment has yet to fully appreciate the full return.
Forward analysts’ expectations have this percentage reportedly closer to 16% to 18% for the end of this year.
But that also would move the group closer to the roughly 12% to 13% yearly growth rate expected for the rest of the companies in the S&P 500 index, potentially making the high valuations of the ‘Magnificent Seven’ tougher to justify.
One of the most surprising things of the past couple of weeks, given the news around DeepSeek and shocks on the trade front, is the fact that stocks were still close to their all-time highs.
The market is pretty resilient right now, but tech stocks are sitting at a very high valuation – a pullback is due, even a correction (in my opinion).
The arrival of DeepSeek creates an alternative ‘cheaper’ AI option and that will unravel the status quo.
China Launches Probes into Google and Apple Over Antitrust Concerns
China has recently initiated investigations into both Google and Apple, raising concerns over potential antitrust violations.
The State Administration for Market Regulation (SAMR) is considering whether to formally investigate Apple’s App Store practices, particularly focusing on the fees Apple charges and its policies that block third-party payment providers. This move has already caused Apple’s shares to fall.
In addition to the probe into Apple, China has also opened a separate investigation into Google, although details about the focus of this investigation have not been disclosed. These probes come at a time when trade tensions between the U.S. and China are escalating under President Donald Trump’s administration.
Apple’s app store under scrutiny
Apple’s App Store has been under scrutiny globally, with regulators in Europe recently forcing the company to open up its App Store under the Digital Markets Act, allowing non-Apple companies to offer app stores and app developers to use third-party payment systems.
If the China probe goes ahead, it would pose further challenges for Apple in one of its largest markets, where it is already facing stiff competition from local companies such as Huawei.
Google
Google, on the other hand, has not yet commented on the specifics of the investigation, but the move highlights the increasing regulatory pressures faced by U.S. tech giants in China.
Both companies will need to navigate these investigations carefully as they continue to operate in a highly competitive and regulated environment.
The outcome of these probes could have significant implications for the tech industry, potentially leading to changes in how these companies operate in China and other markets.
As the investigations unfold, the world will be watching closely to see how Google and Apple respond to these regulatory challenges.
U.S. technology stocks plunged as Chinese startup DeepSeek sparked concerns over competitiveness in AI and America’s lead in the sector, triggering a global sell-off
DeepSeek launched a free, open-source large-language model in late December 2024, claiming it was developed in just two months at a cost of under $6 million.
The developments have stoked concerns about the large amounts of money big tech companies have been investing in AI models and data centres.
DeepSeek is a Chinese artificial intelligence startup that has recently gained significant attention in the AI world. Founded in 2023 by Liang Wenfeng, DeepSeek develops open-source large language models. The company is funded by High-Flyer, a hedge fund also founded by Wenfeng.
The AI models from DeepSeek have demonstrated impressive performance, rivaling some of the best chatbots in the world at a fraction of the cost. This has caused quite a stir in the tech industry, leading to significant drops in the stock prices of major AI-related firms.
The company’s latest model, DeepSeek-V3, is known for its efficiency and high performance across various benchmarks.
DeepSeek’s emergence challenges the notion that massive capital expenditure is necessary to achieve top-tier AI performance.
The company’s success has led to a re-evaluation of the AI market and has put pressure on other tech giants to innovate and reduce costs.
President Donald Trump announced a joint venture with OpenAI, Oracle and Softbank to invest billions of dollars in artificial intelligence infrastructure in the U.S.
The project, dubbed Stargate, was unveiled at the White House by Trump, Softbank CEO Masayoshi Son, OpenAI CEO Sam Altman and Oracle co-founder Larry Ellison.
The executives committed to invest an initial $100 billion and up to $500 billion over the next four years in the project, which will be set up as a separate company.
Softbank’s Son had reportedly already promised a four-year, $100-billion investment when he recently visited then-President-elect Trump at his Mar-a-Lago resort.
And this new AI investment is over and above the investments from the likes of Microsoft, Google, Apple, Anthropic and many others already in progress.
The UK is charting its own course when it comes to regulating artificial intelligence, signaling a potential divergence from the approaches taken by the United States and the European Union. This move is part of a broader strategy to establish the UK as a global leader in AI technology.
UK AI framework
Britain’s minister for AI and digital government, Feryal Clark, emphasised the importance of the UK developing its own regulatory framework for AI.
She highlighted the government’s strong relationships with AI companies like OpenAI and Google DeepMind, which have voluntarily opened their models for safety testing. Prime Minister Keir Starmer echoed these sentiments, stating that the UK now has the freedom to regulate AI in a way that best suits its national interests following Brexit.
Unlike the EU, which has introduced comprehensive, pan-European legislation aimed at harmonising
AI rules across the bloc, the UK has so far refrained from enacting formal laws to regulate AI.
Instead, it has deferred to individual regulatory bodies to enforce existing rules on businesses developing and using AI. This approach contrasts with the EU’s risk-based regulation and the U.S.’s patchwork of state and local frameworks.
Labour Party Plan
During the Labour Party’s election campaign, there was a commitment to introducing regulations focusing on ‘frontier’ AI models, such as large language models like OpenAI’s GPT. However, the UK government has yet to confirm the details of proposed AI safety legislation, opting instead to consult with the industry before formalising any rules.
The UK’s AI Opportunities Action Plan, endorsed by tech entrepreneur Matt Clifford, outlines a comprehensive strategy to harness AI for economic growth.
The plan includes recommendations for scaling up AI capabilities, establishing AI growth zones, and creating a National Data Library to support AI research and innovation. The government has committed to implementing these recommendations, aiming to build a robust AI infrastructure and foster a pro-innovation regulatory environment.
Despite the ambitious plans, some industry leaders have expressed concerns about the lack of clear rules. Sachin Dev Duggal, CEO of AI startup Builder.ai, reportedly warned that proceeding without clear regulations could be ‘borderline reckless’.
He reportedly highlighted the need for the UK to leverage its data to build sovereign AI capabilities and create British success stories.
The UK’s decision to ‘do its own thing’ on AI regulation reflects its desire to tailor its approach to national interests and foster innovation.
While this strategy offers flexibility, it also presents challenges in terms of providing clear guidance and ensuring regulatory certainty for businesses. As the UK continues to develop its AI regulatory framework, it will be crucial to balance innovation with safety and public trust
The advent of quantum computing presents both opportunities and challenges for the field of cryptography, especially in relation to cryptocurrencies.
Quantum computers, leveraging the principles of quantum mechanics, have the potential to revolutionise computing by solving certain problems significantly faster than classical computers.
One of the primary concerns is the impact of quantum computing on cryptographic algorithms that underpin the security of cryptocurrencies like Bitcoin and Ethereum.
Traditional public-key cryptography, which relies on the difficulty of factoring large prime numbers or solving discrete logarithms, could be broken by a sufficiently powerful quantum computer. Algorithms such as RSA, ECC (Elliptic Curve Cryptography), and DSA (Digital Signature Algorithm) could become vulnerable, as quantum algorithms like Shor’s algorithm are capable of efficiently solving these problems.
This potential vulnerability poses a significant threat to the security and integrity of cryptocurrency transactions. If quantum computers can crack these cryptographic codes, they could potentially access private keys, allowing malicious actors to steal funds or forge transactions. As a result, the trust that underpins the entire cryptocurrency ecosystem could be eroded.
However, the quantum threat is not without its solutions. The field of post-quantum cryptography is actively developing new cryptographic algorithms that are resistant to quantum attacks.
These algorithms leverage mathematical problems believed to be hard even for quantum computers, such as lattice-based cryptography, hash-based cryptography, and multivariate polynomial cryptography.
Transitioning to post-quantum cryptographic algorithms is crucial for ensuring the long-term security of cryptocurrencies in a quantum computing era.
In conclusion, while quantum computing poses a formidable challenge to current cryptographic systems, proactive measures and the development of quantum-resistant algorithms can mitigate these risks.
The cryptocurrency industry must stay ahead of the curve, adopting new technologies and strategies to safeguard against potential quantum threats and ensure the continued security and trust in digital currencies.
It has been estimated that the arrival of quantum computer is at least 10 years away. But is that allowing for the use of AI in its creation?
What is Willow and Quantum Computing?
Willow is the start of a new era of ultra-powerful ‘quantum’ microchips designed by Google. Willow’s speed is almost incomprehensible – according to Google, it is able to perform a computation in under five minutes that would take one of today’s fastest supercomputers 10 septillion years to solve.
This new chip design will inevitably lead to new quantum innovations and computer design over the coming years.
If you don’t understand (not many people do) what makes up quantum computing – there is a very simplified way simplified way of thinking about the breakthrough.
Imagine a maze and how a classical computer would try to find its way through the maze from start to finish. It would try one potential path at a time. A quantum computer would be able to try each path at the same time.
The quantum computer is coming. The only delay will be in design restrictions and the power needed to run the system.
Google released the first version of its Gemini 2.0 family of artificial intelligence models in December 2024
Gemini 2.0 Flash, as the model is named is available in a chat version for users worldwide, while experimental multimodal version of the model, with text-to-speech image generation capabilities, available to developers.
‘If Gemini 1.0 was about organising and understanding information, Gemini 2.0 is about making it much more useful,’ Google CEO Sundar Pichai reportedly said in a statement.
Google’s latest large language model surpasses its predecessors in most user request areas, including code generation and the ability to provide factually accurate responses. However, it falls short compared to Gemini1.5 Pro when it comes evaluating longer contexts.
To access the chat-optimized version of the experimental Flash 2.0, Gemini users can select from the drop-down menu on both desktop and mobile web platforms. According to the company it will soon be available on the Gemini mobile app.
The multimodal version of Gemini Flash .0 will be accessible through Google’s AI Studio and Vertex AI developer platforms.
The general availability of Gemini 2.0 Flash’s multimodal version is scheduled for January, along with additional Gemini 2.0 model sizes, Google announced. The company also plans to expand Gemini 20 to more Google products in early 2025.
Gemini 2.0 signifies Google’s latest efforts in the increasingly competitive AI industry. Google is competing with major tech rivals such as Microsoft and Meta, as well as startups like OpenAI, the creator of ChatGPT, Perplexity, and Anthropic, which developed Claude.
In addition to new Flash, other research prototypes are aimed at developing more ‘agentic’ AI models and experiences. According to the company, agentic models ‘can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision’.
Google has unveiled a new chip which it claims takes five minutes to solve a problem that would currently take the world’s fastest super computers ten septillion or 10,000,000,000,000,000,000,000,000 years to complete.
Google’s Quantum Leap: The Willow chip
In a groundbreaking achievement, Google has unveiled its latest quantum computing chip, named Willow. This new chip marks a significant milestone in the journey toward realising the full potential of quantum computing, a technology that promises to revolutionise numerous fields through its unparalleled processing power.
Unprecedented speed and efficiency
At the core of Willow’s innovation is its remarkable ability to perform computations at speeds previously deemed impossible. To put this into perspective, Willow can solve a complex problem in just five minutes – a task that would take the world’s most advanced supercomputers an astounding 10 septillion years to complete. This leap in speed and efficiency showcases the potential of quantum computing to tackle problems beyond the reach of classical computers.
This quantum power combined with artificial intelligence will become a formidable force in the world, potentially a foe!
Breakthrough in Quantum error correction
One of the most significant advancements with the Willow chip lies in its approach to quantum error correction. Traditionally, error rates in quantum computations have posed a substantial barrier to practical applications. Willow, however, exhibits an exponential reduction in errors as more qubits (quantum bits) are integrated into the system. This breakthrough in error correction brings the technology closer to practical, large-scale quantum computing, paving the way for more reliable and accurate results.
Potential applications and future prospects
While Willow represents a monumental step forward, experts caution that a fully functional, widely applicable quantum computer is still years away. Nonetheless, the potential applications of quantum computing are vast, ranging from breakthroughs in medicine and drug discovery to advancements in artificial intelligence and energy solutions. With continued investment and research, Willow could be the precursor to a new era of technological innovation, fundamentally altering how we approach complex problems.
Expert insights
Leading experts in the field commend Google’s achievement, highlighting Willow’s significance in the broader context of quantum computing development. While challenges remain, the unveiling of Willow underscores the rapid progress being made and the exciting possibilities that lie ahead. As we stand on the brink of a quantum revolution, Willow serves as a beacon of what the future may hold.
Conclusion
Google’s Willow chip is more than just a technological marvel; it represents the relentless pursuit of innovation and the profound impact that quantum computing can have on our world.
As research continues and technology evolves, Willow stands as a testament to the incredible possibilities that lie within the realm of quantum physics.
Quantum computers operate on a fundamentally different principle than the computer in your phone or laptop. They utilise quantum mechanics, which governs the peculiar behaviour of particles at the smallest scales, to solve problems much more quickly than conventional computers.
The hope is that quantum computers will one day accelerate complex tasks, like the development of new medications. However, there are concerns that this power could be misused, such as breaking certain forms of encryption that safeguard sensitive information.
Samsung, previously a powerhouse in the semiconductor industry, has encountered significant hurdles in the AI competition, leading to a notable decline in market value. The company’s faltering stance can be attributed to a variety of factors, such as strategic errors, fierce competition, and swift technological progress in the AI field.
Missteps
A key factor in Samsung’s downturn in the AI sector is its insufficient investment in high-bandwidth memory (HBM) technology, which is vital for AI applications due to its ability to expedite data processing and enhance performance.
Although Samsung was once at the forefront of memory technology, it did not leverage the increasing demand for HBM, thus ceding ground to competitors such as SK Hynix. SK Hynix made significant investments in HBM and forged a robust partnership with Nvidia, an influential entity in the AI domain.
Competition
The AI sector is fiercely competitive, featuring key companies such as Nvidia, Google, and Microsoft, which are making substantial advancements in AI technology. Nvidia has notably become a frontrunner with its GPUs, crucial for AI training. Samsung’s struggle to match these developments has resulted in a decline in both market share and revenue.
Rapid technological advancements
The swift advancement of technology in the AI sector has presented challenges for Samsung. The company’s emphasis on conventional memory technology did not fully prepare it for the transition to AI-centric applications. With the rise of AI applications such as OpenAI’s ChatGPT, the need for sophisticated memory solutions surged, highlighting Samsung’s insufficient investment in High-Bandwidth Memory (HBM) as a notable shortcoming.
Financial implications
Samsung’s difficulties in the AI sector have significantly affected its finances. The company has seen a reported loss of around $122 billion in market value since July 2024, marking the most substantial drop among global chipmakers. This decline is largely due to Samsung’s challenges in adapting to the evolving AI industry and competing with its rivals.
Prospects
Despite facing challenges, Samsung is actively striving to advance in the AI domain. The company has recently introduced its next-generation Bixby AI, which utilizes large language model technology, positioning it to better contend with competitors such as ChatGPT and Google Gemini.
Additionally, Samsung is cultivating its proprietary AI model, named Samsung Gauss, with the goal of augmenting device functionality and elevating the consumer experience.
Samsung’s lag in the AI sector is due to strategic errors, fierce competition, and swift technological progress. Despite considerable financial setbacks, the company is vigorously pursuing new AI initiatives and investments to recover its standing in the industry.
The path forward is fraught with challenges, yet Samsung’s commitment to innovation and adaptation could enable it to regain its status as a frontrunner in the AI domain.
Amazon Web Services (AWS) has announced the signing of an agreement with Dominion Energy, the utility company of Virginia U.S., to explore the development of a small modular nuclear reactor near Dominion’s existing North Anna nuclear power station.
As Amazon’s cloud computing subsidiary, AWS has an ever-growing demand for clean energy, particularly as it expands into generative AI. This agreement aligns with Amazon’s journey towards net-zero carbon emissions.
Amazon joins other major tech companies like Google and Microsoft in turning to nuclear power to meet the increasing energy needs of data centres.
AI systems, particularly generative AI, necessitate substantial computational power, leading to significant energy use. Conventional energy sources might not meet these growing demands.
Environmental Commitments
Numerous tech firms have pledged to lower their carbon emissions. Nuclear power, a low-emission energy source, supports these environmental commitments.
Dependability
Nuclear energy offers a consistent and uninterrupted power supply, essential for data centres that operate around the clock.
Technological Advancements
Progress in nuclear technologies, such as small modular reactors (SMRs), has enhanced the feasibility and appeal of nuclear power for extensive use.
For example, Google has entered into an agreement with Kairos Power for electricity from small modular reactors to bolster its AI operations. In a similar vein, Microsoft has collaborated with Constellation to refurbish an inactive reactor at the Three Mile Island nuclear facility.
These collaborations mark a notable transition in the energy strategies of the tech sector, as they pursue dependable, eco-friendly, and robust power solutions to support their AI initiatives.
Nvidia’s shares have reached a record peak as the company continues to benefit from the surging demand for its AI chips
Tech giants such as Microsoft, Meta, Google, and Amazon are acquiring Nvidia’s GPUs in large volumes to create extensive AI computing clusters.
Nvidia, with a market capitalisation of around $3.4 trillion, ranks as the second most valuable publicly traded company in the U.S., trailing behind Apple, which has a market cap of approximately $3.55 trillion.
Oh, the volatility of tech stocks, don’t you just love it?
The company’s stock rose by 2.4% to close at $138.07, exceeding the previous high of $135.58 set on 18th June 2023. The shares have increased by nearly 180% this year and have experienced a more than ninefold increase since early 2023.
Regarded as the leading supplier in the AI revolution, Nvidia has gained significantly from the generative AI surge initiated by OpenAI’s ChatGPT release in November 2022. Nvidia’s GPUs are instrumental in developing and running sophisticated AI models, including those that operate ChatGPT and related platforms.
You can’t go far wrong when big players such as Microsoft, Meta, Google and Amazon are buying your stuff.
Europe’s top court upheld a €2.4 billion ($2.65 billion) fine against Google on Tuesday 10th September 2024 for unfairly promoting its shopping comparison service, exploiting its market dominance.
The ruling stems from a 2017 antitrust investigation by the European Commission, the executive arm of the European Union.
The Commission reportedly found that Google had unfairly favoured its own shopping comparison service, to the detriment of rival services.
The U.S. government is targeting the heart of Google’s vast wealth – its highly profitable monopolising advertising technology business
A trial scheduled to begin on Monday 9th September 2024 will scrutinise the Department of Justice’s (DoJ) claims that Alphabet, the parent company of Google, is unlawfully sustaining a monopoly in the marketplace.
In the previous year, the firm amassed over $200 billion (£152 billion) through the placement and sale of online advertisements.
Alphabet attributes its success to the ‘effectiveness’ of its business. Conversely, prosecutors contend that the company has leveraged its market control to stifle competition.
The legal action, launched by the Department of Justice (DoJ) and several states in 2023, charges Google with dominating the digital advertising market and employing its influence to obstruct innovation and competition.
Google asserts that it is simply one of numerous companies that arrange digital advertisement placements for consumers.
The corporation argues that the digital advertising industry is increasingly competitive, citing the growing advertising revenues of entities like Apple, Amazon, and TikTok as proof, as mentioned in a blog post responding to the DoJ’s lawsuit in 2023.
The contentions will be laid out before the U.S. District Judge who is expected to deliver a verdict.
This trial comes on the heels of a notable decision in a separate antitrust lawsuit against Google by the Justice Department last month. Judge Amit Mehta ruled that Google had illegally stifled competition in its online search services.
Major technology corporations such as Microsoft, Alphabet, and Meta are channelling billions into data centre infrastructures to bolster generative AI, which is causing a spike in energy demand.
Sustainable Metal Cloud has announced that its immersion cooling technology is 28% less expensive to install compared to other liquid-based cooling methods and can cut energy use by up to 50%.
The surge in artificial intelligence has increased the need for more robust processors and the energy to cool data centres.
This presents an opportunity for Sustainable Metal Cloud, which runs ‘sustainable AI factories’ consisting of HyperCubes located in Singapore and Australia.
These HyperCubes house servers equipped with Nvidia processors immersed in a synthetic oil known as polyalphaolefin, which is more effective at dissipating heat than air. The company claims this technology can reduce energy consumption by as much as 50% when compared to the conventional air-cooling systems found in most data centres.
Additionally, the Singapore-based company states that its immersion cooling technology is more cost-effective to install by 28% than other liquid cooling options. The HyperCubes are modular and can be integrated into any data centre, utilising spaces that are currently unoccupied within existing facilities.
What is a Hypercube?
Structure: A hypercube topology connects nodes in a way that each node is connected to others in a manner similar to the geometric hypercube. For example, in a 3-dimensional hypercube (a cube), each node is connected to three other nodes.
Scalability: This structure allows for efficient scaling. As the number of dimensions increases, the number of nodes that can be connected grows exponentially.
Fault Tolerance: Hypercube networks are known for their robustness. If one connection fails, there are multiple alternative paths for data to travel, ensuring reliability.
Benefits in data centres
High Performance: The multiple pathways in a hypercube network reduce latency and increase data transfer speeds, which is crucial for big tech companies handling vast amounts of data.
Efficient Resource Utilisation: The topology allows for better load balancing and resource allocation, optimising the performance of data centres.
Flexibility: Hypercube networks can easily adapt to changes in the network, such as adding or removing nodes, without significant reconfiguration.
Big Tech Companies: Companies like Google, Amazon, and Microsoft likely use hypercube topologies in their data centres to ensure high performance and reliability.
High-Performance Computing (HPC): Hypercube networks are also used in supercomputers and other HPC environments where efficient data transfer is critical.
A U.S. judge has ruled that Google illegally maintained a monopoly in online searches and related advertising. The lawsuit, brought by the Department of Justice, charged Google with controlling around 90% of the online search market.
It was reportedly noted by the judge that Google’s billions of dollars in investments to become the default search engine on smartphones and browsers could be anticompetitive.
The decision, issued on Monday 5th August 2024, could potentially change how tech giants operate.
It was reported that in his extensive 277-page decision, Judge Mehta remarked, “Google has acted as a monopolist and engaged in anticompetitive practices to maintain its monopoly.”
This represents a significant victory for federal antitrust enforcers who have pursued similar cases against other leading technology companies for illegal monopolistic behaviours.
Companies like Meta Platforms, which operate Facebook and WhatsApp, as well as companies like Amazon and Apple., have also faced lawsuits from federal regulators.
The judgment comes after a 10-week trial where it was argued that Google’s substantial payments to remain the primary search engine have impeded the competition’s ability to challenge effectively.
This is a seismic shift in the way search engines and advertising may operate in the future. Already with the advent of AI, search engines look and feel different.
The seven most valuable U.S. tech companies experienced a combined loss of $1 trillion in market value at the start of Monday’s trading session – 5th August 2024
The Nasdaq declined over 3% following its sharpest three-week drop in two years.
Nvidia’s shares fell approximately 6%, while Apple’s dropped more than 4%.
On Monday, as the U.S. markets commenced trading, the market capitalization of the largest tech companies plummeted by about $1 trillion, exacerbating a decline that pushed the Nasdaq into correction territory the previous week.
Markets go up and markets go down
In early trade Nvidia’s market cap decreased by over $300 billion, but it swiftly regained about half of that loss. The chipmaker’s shares ultimately closed down 6.4%, equating to a $168 billion loss. Apple and Amazon saw their valuations fall by $224 billion and $109 billion at market open. Apple’s market cap finished 4.8% lower, a $162 billion decrease. Amazon’s valuation fell by 4.1% at closing, a $72 billion reduction.
Including significant drops in Meta, Microsoft, Alphabet, and Tesla, the top seven tech giants saw a $995 billion loss in market value in the initial moments of trading, although they did recover somewhat as the day went on.
Microsoft reported better-than-expected earnings and revenue for Q4
In extended trading on 30th July 2024, the stock experienced a quick decline as attention was drawn to the less-than-expected Azure revenue, despite management’s forecast for growth in the upcoming quarters.
The company’s total revenue saw a 15% increase compared to the previous year.
Despite surpassing earnings and revenue expectations, Microsoft’s shares dropped by up to 7% in extended trading on Tuesday, with investors concentrating on the underwhelming cloud revenue. However, executives offered a positive outlook, anticipating an acceleration in cloud growth during the first half of 2025.
Microsoft one day chart 30th July 2024
Microsoft one day chart 30th July 2024
Microsoft’s cloud division holds significant interest for investors, as it competes with Amazon Web Services (AWS) and Google in the artificial intelligence (AI) work arena. These three tech giants are pouring substantial resources into enhancing AI capabilities, aiming to attract both startups and established companies as generative AI technology swiftly progresses.
For Amazon, AWS has served as a vital profit centre for the past ten years.
OpenAI on Thursday 25th July 2024 announced a prototype of its search engine, called SearchGPT, which aims to give users “fast and timely answers with clear and relevant sources.”
The company has announced plans to eventually incorporate the tool, presently in testing with a select user group, into its ChatGPT chatbot.
The introduction of ChatGPT could have significant implications for Google’s search engine dominance. Since ChatGPT’s debut in November 2022, there has been growing concern among Alphabet’s investors that OpenAI may capture a portion of Google’s market share by offering consumers innovative methods to obtain information on the internet.
Alphabet three month share price as of 25th July 2024
Alphabet three month share price as of 25th July 2024
OpenAI’s ChatGPT was incorporated into Microsoft’s search engine Bing as Copilot and the companies have kept market dominance with this shrewd AI move. Google, on the other hand, has struggled to keep up in the AI race and may now be suffering the effects.
This announcement could have implications for Microsoft’s Copilot as well.
Stocks sold off Wednesday 24th July 2024, blighted by underwhelming reports from Tesla and Alphabet – leading the Nasdaq Composite and the S&P 500 to post their worst sessions since 2022.
The S&P 500 index dropped to closing at 5427, while the tech-heavy Nasdaq slid around 3.65% to end at 17342. The Dow Jones Industrial Average shed 504 points closing at 39853.
Nasdaq Comp one day chart 24th July 2024
Nasdaq Comp one day chart 24th July 2024
Shares of Google parent company Alphabet fell 5% for their biggest one-day drop since 31st January, when they dropped 7.5%. Although Alphabet reported good numbers, YouTube advertising revenue came in below the consensus estimate causing share to dip.
Alphabet one day chart 24th July 2024
Tesla shares declined around 12% – their worst day since 2020 – on weaker-than-expected results and a 7% year-on-year drop in auto revenue.
To put this figure into some perspective, the loss is comparable to the GDP output of a small country, such as Norway, Singapore, or the UAE, for example.
Global semiconductor stocks experienced volatility on Tuesday following a decline in Nvidia’s shares from the previous trading sessions.
Shares of chip firms in Europe and Asia fell in early trade as investors reacted to Nvidia losing more than $500 billion in market capitalization over three trading days. Some of the stocks recouped losses, however, as shares in the U.S. chipmaking giant recovered around 6 – 6.5% as of Tuesday 25th June 2024.
This follows a significant drop in Nvidia’s share value, which fell 13% over three consecutive sessions from the record highs achieved on Thursday 20th June 2024.
On Monday 24th June 2024, Nvidia’s stock closed down 6.7%, marking its second-largest decline of the year, yet the shares began to recover in early trading on Tuesday 25th June 2024.
Last week, the company surpassed Apple and Microsoft to become the most valuable U.S. company, achieving a market capitalization of over $3.4 trillion. However, by the end of Monday, Nvidia’s market value had declined by more than $540 billion from its intraday record on Thursday 20th June 2024.
Nvidia reported that the demand for its highly sought-after artificial intelligence graphics processing units (GPUs) continues to be strong.
Companies such as Microsoft, Google, Amazon, and Meta are investing billions of dollars in these chips to enhance their data centres and cloud services.
Nvidia, traditionally recognised within the gaming community for its graphics chips, has become the world’s most valuable publicly traded company.
On Tuesday 18th June 2024, Nvidia’s shares rose by 3.6%, increasing its market cap to $3.34 trillion and overtaking Microsoft, now valued at $3.32 trillion. Earlier in the month, Nvidia’s valuation reached $3 trillion for the first time, surpassing Apple.
Nvidia $3.34 trillion market cap
Nvidia $3.34 trillion market cap
So far this year, Nvidia’s shares have surged over 170% and saw further gains after announcing first-quarter earnings in May 2024. Since the close of 2022, the stock has increased more than ninefold, paralleling the rise of generative artificial intelligence.
Apple’s shares dropped by 1.1% on Tuesday, resulting in a market value of $3.29 trillion for the tech giant.
Nvidia commands roughly 80% of the market share for AI chips in data centres, a sector that has expanded rapidly as companies like OpenAI, Microsoft, Alphabet, Amazon, and Meta have competed to acquire the necessary processors for constructing AI models and managing growing workloads.
In the latest quarter, Nvidia’s data centre business saw a 427% increase in revenue from the previous year, reaching $22.6 billion and comprising approximately 86% of the company’s total sales.
Established in 1991, Nvidia initially focused on hardware, selling gaming chips for running 3D games. The company has also ventured into cryptocurrency mining chips and cloud gaming services.
However, in the last two years, Nvidia’s stock has soared as investors recognised its pivotal role in the AI boom, a trend that continues to accelerate. This surge has increased the net worth of co-founder and CEO Jensen Huang to an estimated $117 billion, ranking him as the 11th richest individual globally, according to Forbes.
But is the rise too fast and is it time for a share price valuation adjustment in its meteoric rise, to bring it back down to Earth?
