arms race among tech giants

The year 2024 in the artificial intelligence (AI) sector was marked by an “arms race,” with nearly all leading tech giants, numerous startups, and companies from various countries including European and Chinese firms striving to develop and showcase their own AI products to challenge OpenAI’s dominance.

Arms Race Among Tech Giants: How 2024 Went in the AI Sector and its Impact on Stock Market Dynamics

Innovations in AI set trends and became a driving force in the U.S. stock market. The AI boom has led to significant investments by major tech companies, influencing market capitalization. In January, Microsoft overtook Apple to become the world’s most valuable company with a market cap of $2.9 trillion, buoyed by investor confidence in its AI advancements. Nvidia also achieved a milestone in June, becoming the most valuable company due to its AI chips, which are highly sought after by developers of large language models.

The Impact of Artificial Intelligence on the Stock Market

The AI arms race is reshaping the stock market landscape, with tech companies pouring tens of billions into AI systems to secure a competitive edge. Artificial intelligence is revolutionizing how data is analyzed, patterns are identified, and market trends are predicted. This technological leap has given rise to AI-powered trading platforms capable of executing trades at lightning-fast speeds and with unparalleled accuracy, far surpassing human capabilities. As a result, the stock market is becoming increasingly reliant on AI, with some experts forecasting that AI will soon dominate the majority of trading activities. This shift underscores the profound impact of AI on market dynamics and the strategic moves of tech companies in this high-stakes arms race.

How AI Is Changing the Way Stocks Are Traded

AI systems are fundamentally transforming the mechanics of stock trading. By analyzing vast amounts of data from financial statements and news articles to social media posts — AI can identify trends and make highly accurate predictions about future market movements. This capability allows traders to make more informed decisions and respond swiftly to market changes. Moreover, AI-powered trading platforms can execute trades at speeds unattainable by human traders, leading to faster and more efficient trading processes. This technological advancement is not only enhancing the precision of trading strategies but also reshaping the entire trading landscape.

Hardware Developments

Nvidia solidified its leading position in AI processor development by introducing the advanced Blackwell generation of chips, providing significant performance boosts for neural network operations — 20 petaflops compared to 4 petaflops of its predecessor, H100. The expansion of data centers is crucial to support the increasing computational demands of these AI processors. CEO Jensen Huang noted that this additional computational power would enable training of larger and more complex models. Two months later, Nvidia announced a new architecture called Rubin for training AI models. In January, Meta revealed plans to purchase 350,000 Nvidia chips for AI development, citing the need for substantial computational infrastructure. By September, Elon Musk’s xAI launched the world’s largest AI training cluster, Colossus, utilizing 100,000 Nvidia H100 GPUs.Other hardware developers also sought to capture market share from Nvidia. Intel introduced its next-generation Gaudi 3 AI chip in April, which is over twice as energy-efficient as its predecessor and comes in various configurations. Samsung announced upcoming manufacturing technology enhancements aimed at attracting AI chip creators.

OpenAI’s Generative AI Innovations

OpenAI required proprietary chips for training and maintaining both old and new neural networks introduced in 2024. OpenAI’s significant AI investments are aimed at enhancing efficiency and driving innovation. Notable products included Sora — a video generator announced in February but made publicly available only in December allowing users to create videos from text prompts and enhance existing footage. Throughout 2024, OpenAI also launched:

• GPT-4o: A more human-like version of ChatGPT capable of processing visual data.

• GPT-4o mini: The most powerful and cost-effective small model available.

• o1: A large language model trained via reinforcement learning for complex reasoning.

• An expanded voice mode for ChatGPT.

• A new search tool within ChatGPT that provides timely answers with links to relevant sources.

Additionally, OpenAI closed a funding round of $6.6 billion at a valuation of $157 billion, marking one of the largest deals in venture capital history.

AI Investments Landscape

Venture capital interest extended beyond OpenAI, with numerous other billion-dollar deals. These investments are expected to add substantial value to the global economy:

• Microsoft partnered with French firm Mistral AI for $2.1 billion.

• Amazon invested $2.75 billion into AI startup Anthropic, totaling $4 billion.

• Musk’s xAI secured $12 billion across two funding rounds.

• Scale AI raised $1 billion at a valuation of $13.8 billion.

• Canadian company Cohere attracted $500 million at a valuation of $5.5 billion.

• Safe Superintelligence, founded by former OpenAI scientist Ilya Sutskever, raised $1 billion.

Medical Applications

AI found effective applications in medicine during 2024, aiding researchers in:

• Early detection of Alzheimer’s disease.

• Identifying heart conditions.

• Interpreting ambiguous medical imaging results.

• Diagnosing 13 types of cancer with 98.2% accuracy.

• Monitoring Parkinson’s disease progression through patient hand movements.

• Detecting tuberculosis.

Military Applications in the AI Arms Race

The military domain also saw increased AI utilization. In January, OpenAI quietly removed restrictions on using ChatGPT for military purposes. Following suit were Meta and Anthropic, which opened their technologies to U.S. government agencies and defense contractors. Meanwhile, 200 employees from Google’s DeepMind expressed concerns over the company’s military contracts.China is also applying AI for military purposes; tests began on an AI commander at the National Defense University’s joint operations college in Hebei province.

China’s Advances

China made significant strides in developing its own AI technologies and surpassed other nations in generative AI patents. By June, Alibaba announced the release of its new AI model Qwen2 and began working on Tora — a video generation tool inspired by Sora. The company also launched QwQ-32B-Preview — a reasoning-oriented AI model.Kuaishou aimed to compete with OpenAI’s video generation capabilities through its model Kling, while Zhipu introduced a similar solution named Ying.

Apple’s Entry

Apple made headlines with its entry into the AI space during the first half of the year amid speculation about a major announcement. In June, it unveiled Apple Intelligence — a comprehensive initiative that includes:

• Integrating ChatGPT into Siri and system-wide tools like Writers Tools.

• Enhanced photo search and clip creation capabilities.

• Email transcription features.

• Focus mode for displaying only important notifications.

• Writing assistance tools and image generation technologies.

Elon Musk threatened to ban Apple devices from his companies if ChatGPT was integrated into Apple’s operating systems due to his long-standing rivalry with OpenAI co-founder Sam Altman.

Other Tech Giants’ Innovations

Tech titans like Google, Meta, and Microsoft continued to unveil new AI products throughout the year:

• Google integrated generative AI across its services including search and Gmail while releasing Gemini 2.0 — its most powerful model yet.

• Meta launched Movie Gen — an AI video generator and introduced new Llama models while adding AI characters to Instagram and Meta AI assistants across platforms.

• xAI showcased Grok chatbots throughout the year with image generation capabilities.

• Microsoft updated its Copilot assistant with voice recognition features.

In Europe, Mistral led the way by releasing its flagship model Large 2 and a multimodal neural network capable of processing both images and text.

The Intersection of Cryptocurrency and AI

2024 marked a breakthrough year for the intersection of cryptocurrency and AI technologies. Despite skepticism from some experts about this union, others highlighted potential benefits such as countering centralization in AI and ensuring data transparency.Binance reported using AI to combat fraud successfully preventing over $2.4 billion in user fund thefts during the year. The company’s investment director emphasized that combining these sectors enhances user experience within blockchain ecosystems.Coinbase also ventured into AI by developing machine learning models to predict traffic spikes while launching services for creating privacy-focused applications using Tether technology.Analysts predicted that by 2030, global GDP could increase by $20 trillion due to digital assets and AI industries collaborating effectively.

The Emergence of AI Tokens

The rapid growth of both the AI sector and cryptocurrency led to the emergence of a new category: AI tokens during early 2024 amidst an overall market surge. In February alone, activity within this segment surged significantly following excitement around OpenAI’s Sora video generation announcement.However, after initial growth came market corrections until October when new meme coins like Goatseus Maximus saw dramatic price increases due to rumors surrounding support from an AI bot.

The Rise of Autonomous Agents

A notable trend emerging was that of autonomous agents neural networks capable of performing tasks online without user intervention (e.g., booking flights). These tools may develop their own tokens appealing to cryptocurrency communities.Recent developments included:

• Anthropic releasing Claude 3.5 Sonnet — an agent capable of interacting with computers like a human.

• OpenAI preparing to launch an agent dubbed “Operator” for executing tasks such as coding or travel bookings autonomously.

• Google introducing its first autonomous agent capable of independent online actions.

Microsoft also expressed interest in launching similar agents.

The Risks and Challenges of AI-Powered Trading

While AI-powered trading holds immense potential, it also introduces significant risks and challenges. One major concern is the possibility of AI systems making errors or being manipulated by malicious actors. Additionally, the rise of AI in trading raises the specter of job displacement, as human traders may find themselves replaced by machines. The increasing dependence on AI also brings the risk of market instability, necessitating robust regulatory frameworks to mitigate potential disruptions. These challenges highlight the need for a balanced approach to integrating AI into trading, ensuring that the benefits are maximized while the risks are carefully managed.

Regulatory Developments

As rapid advancements occurred within the field of artificial intelligence, the tech industry was significantly involved in the global governance of AI, influencing regulatory developments. Regulators were not idle; they prepared legislative frameworks for oversight. In March, the European Parliament approved foundational regulations governing AI activities which took effect on August 1st amid critisism. In the U.S., discussions around California’s SB 1047 bill aimed at regulating artificial intelligence gained traction but ultimately did not pass due to gubernatorial vetoes. In December, newly elected President Donald Trump nominated David Sachs as “czar” overseeing both digital assets and artificial intelligence—viewing these sectors as pivotal within his administration’s agenda.

The Evolution of the Stock Market in the Age of AI

The stock market is undergoing a rapid transformation in the age of AI, driven by substantial investments from tech giants and AI companies in AI infrastructure and development. The prevalence of AI in trading is set to increase, with future innovations likely to include generative AI for creating new investment products and large language models for analyzing financial data. However, this evolution also brings safety concerns and regulatory challenges that must be addressed. As the AI landscape continues to evolve, it is crucial to strike a balance between fostering innovation and ensuring the stability and integrity of the stock market.

Conclusion

The past year demonstrated a clear consensus: everyone from startups to tech giants, venture investors to governments is betting on artificial intelligence as a revolutionary technology akin to smartphones that is here to stay for the long haul.