In 2024 artificial intelligence turned into an arms race. Almost every tech behemoth, a host of startups and firms across regions, from Europe to China, rushed to roll out their own AI products in an effort to chip away at OpenAI\u2019s lead.<\/p>\n
Here is a look at the notable launches and the most consequential events in the sector over the past 12 months.<\/p>\n
AI breakthroughs set the tone and drove US equities. Companies leaning hard into AI took turns at the top of the market-cap league table.\u00a0<\/p>\n
In January Microsoft overtook<\/a> Apple as the world\u2019s most valuable firm, hitting a $2.9 trillion valuation. Its shares had surged over the prior year as investors rewarded its AI advances.<\/p>\n In June Nvidia for the first time became<\/a> the most valuable company, powered by demand for its chips among large-language-model developers.<\/p>\n Nvidia, the dominant supplier of AI processors, tightened its grip by unveiling<\/a> the next generation of AI chips, Blackwell.\u00a0<\/p>\n The new parts deliver a hefty performance jump for neural-network workloads\u201420 petaflops versus 4 petaflops on the H100. CEO Jensen Huang said the added compute would let customers train larger, more complex models.<\/p>\n Two months later Nvidia announced<\/a> a new training-processor architecture dubbed Rubin.<\/p>\n Demand for Nvidia\u2019s processors remained intense. In January Meta said<\/a> it would buy 350,000 Nvidia chips to expand its AI capacity, citing a \u201chuge compute infrastructure\u201d need on its AI roadmap.<\/p>\n In September xAI launched<\/a> Colossus, billed as the world\u2019s largest AI-training cluster, using 100,000 Nvidia H100 GPUs, according to Elon Musk.\u00a0<\/p>\n Rivals pushed their own hardware to claw market share from Nvidia. In April Intel introduced<\/a> its next-gen AI chip, Gaudi 3, claiming over twice the energy efficiency of its predecessor and multiple configurations.\u00a0<\/p>\n In June Samsung outlined<\/a> upcoming manufacturing improvements aimed at wooing AI-chip designers. Media also reported<\/a> that OpenAI was working on its own solution.<\/p>\n OpenAI\u2019s in-house chips are meant to train and run both legacy and freshly minted models, including those debuting in 2024.<\/p>\n The splashiest launch was Sora, a video generator. The product was announced<\/a> in February, but the broader public gained<\/a> access only in December. Users can create videos from text prompts, \u201canimate\u201d images, extend existing clips and fill in missing frames.\u00a0<\/p>\n It was a packed year for OpenAI. Beyond Sora, the company:<\/p>\n The firm also closed a $6.6 billion funding round at a $157 billion valuation, one of the largest<\/a> venture deals on record.<\/p>\n Venture money did not flow only to OpenAI. Other multibillion-dollar deals included:<\/p>\n Healthcare emerged as one of AI\u2019s most promising use-cases in 2024. AI already helps researchers to:<\/p>\n AI also found military uses. In January OpenAI quietly removed<\/a> language from its use policy that banned \u201cmilitary\u201d applications of ChatGPT. Later Meta<\/a> and Anthropic<\/a> took similar steps, opening AI technology to US government agencies and defence contractors and their allies.<\/p>\n Meanwhile, 200 staff at Google\u2019s AI arm DeepMind voiced<\/a> discontent over the firm\u2019s military engagements, urging it to end contracts with defence and intelligence bodies. They fear the lab\u2019s technologies are being sold to militaries involved in active conflicts.<\/p>\n China is also deploying<\/a> AI for military purposes. A lab at the National University of Defense Technology\u2019s College of Joint Operations in Shijiazhuang, Hebei province, began testing an AI \u201ccommander\u201d. The country is running simulations of potential conflicts in the South China Sea, especially near Taiwan.<\/p>\n China worked to keep pace with America by building its own AI stack. The country far outstrips<\/a> others in generative-AI patent filings, and its AI user base has reached<\/a> 230 million.\u00a0<\/p>\n In June Alibaba announced<\/a> its new model, Qwen2. It later began work<\/a> on Tora, a Sora-like video generator, and also introduced<\/a> the reasoning-focused QwQ-32B-Preview.\u00a0<\/p>\n Kuaishou moved to rival OpenAI in video generation by releasing<\/a> the Kling model. Another startup, Zhipu, presented<\/a> its own alternative, Ying.<\/p>\n In America, the AI pipeline was even richer, OpenAI aside. The headline act was Apple\u2019s entrance.<\/p>\n Throughout the first half, rumours swirled<\/a> about a coming release. In June Apple finally unveiled its sweeping initiative, Apple Intelligence<\/a>. It includes:<\/p>\n Billionaire Elon Musk threatened<\/a> to ban Apple devices at his companies if ChatGPT from OpenAI is integrated into iOS, iPadOS and macOS.<\/p>\n Musk has a long-running feud with the startup he co-founded with Sam Altman. In February he sued<\/a> OpenAI, accusing it of abandoning openness after releasing a closed-source AI product.<\/p>\n He argues that Sam Altman and OpenAI violated an agreement \u201cto develop the technology for the benefit of humanity rather than for profit\u201d dating back to the startup\u2019s founding.<\/p>\n Musk later withdrew<\/a> the suit but soon filed<\/a> a new one with additional details.\u00a0<\/p>\n The entrepreneur also faced<\/a> a lawsuit from Tesla shareholders over xAI. They say the startup competes with Tesla in AI, \u201csiphoning the automaker\u2019s talent and resources\u201d. At least 11 Tesla employees moved to xAI, and Tesla provided the startup access to AI-related data, the filing claims.<\/p>\n Other tech giants kept up a brisk cadence of AI releases. Standouts included:<\/p>\n In Europe, Mistral remained the standard-bearer. In July it released<\/a> its flagship Large 2 model, and in September debuted<\/a> its first multimodal network, able to process images and text.\u00a0<\/p>\n 2024 was a breakthrough year for the fusion of cryptocurrencies and AI. Some venture capitalists voiced<\/a> scepticism, while others highlighted the benefits.\u00a0<\/p>\n In January Ethereum co-founder Vitalik Buterin outlined<\/a> four promising overlaps: countering AI centralisation, ensuring transparency, and improving data storage and security.<\/p>\n He later considered<\/a> using AI for formal code verification and bug-finding.<\/p>\n Meanwhile Binance said<\/a> it used AI to thwart fraud. The exchange prevented more than $2.4 billion in user-fund thefts in 2024, thanks to the technology. In August Binance Labs investment chief Max Konilio explained<\/a> the firm\u2019s AI push, calling AI and blockchain \u201ca powerful combination\u201d. AI, he argued, improves blockchain user experience and decentralised ecosystems, while blockchains provide authenticity, foster open-source collaboration and support AI compute needs.<\/p>\n In November former Binance CEO Changpeng Zhao (CZ) urged<\/a> building AI products with blockchain. In his view, the two are well suited to work together.<\/p>\n Coinbase also dove into AI\u2014over the summer it built and deployed a machine-learning model to predict traffic spikes and auto-scale databases to reduce downtime and improve performance. Later the exchange introduced<\/a> a service for building AI agents for crypto wallets, while Tether rolled out a tool for privacy-focused applications.<\/p>\n In June Bitwise senior crypto research analyst Juan Leon predicted<\/a> that by 2030 AI and digital assets would add $20 trillion to global GDP. He flagged partnerships between miners and AI firms as one possible avenue of collaboration.\u00a0\u00a0\u00a0<\/p>\n Rapid progress in AI, memecoins and crypto\u2014and the prospect of merging them\u2014spawned a new class of digital assets: AI tokens.\u00a0<\/p>\n The first boom came in the year\u2019s first half amid a wider crypto rally. In February the AI-token segment surged<\/a>, pushing aggregate market cap above $15 billion, likely on excitement over OpenAI\u2019s Sora video model. Prices jumped<\/a> again after Nvidia\u2019s earnings.<\/p>\n The market then corrected, and eye-catching headlines returned in autumn. In October a new memecoin, Goatseus Maximus (GOAT), soared<\/a> nearly 2,000% in two days on rumours of support from the AI bot Truth Terminal. The project ai16z<\/a> also drew attention, later reaching<\/a> a $100 million market cap.<\/p>\n A nascent narrative is AI agents\u2014systems that can act online without human input, such as booking flights or hotels. Some may issue their own tokens, a trend likely to catch on in crypto circles.<\/p>\n Recent launches include:<\/p>\n Microsoft has also signalled<\/a> plans to launch AI agents.\u00a0<\/p>\n As AI raced ahead, regulators worked up legal frameworks.<\/p>\n In March the European Parliament approved<\/a> the world\u2019s first comprehensive AI rulebook. It took effect on August 1 and drew<\/a> a wave of criticism.\u00a0<\/p>\n In America, California\u2019s SB 1047\u2014aimed at regulating AI\u2014was debated. It won support<\/a> from Elon Musk and Vitalik Buterin but never became law after the governor declined to sign it.\u00a0<\/p>\nHardware<\/strong><\/h2>\n
OpenAI updates<\/strong><\/h2>\n
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Investment<\/strong><\/h2>\n
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Medicine<\/strong><\/h2>\n
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Not only benign aims<\/strong><\/h2>\n
China<\/strong><\/h2>\n
Apple<\/strong><\/h2>\n
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AI products from others<\/strong><\/h2>\n
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The crypto\u2013AI symbiosis<\/strong><\/h2>\n
The AI-token boom<\/strong><\/h2>\n
AI agents<\/strong><\/h2>\n
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Regulation<\/strong><\/h2>\n