Colorado, United States, 5th Jun 2024 – Recently, Nvidia released its first-quarter financial report, with strong results exceeding market expectations, showcasing significant growth in both revenue and net profit. Nvidia’s stock surged nearly 7%, breaking the $1,000 mark for the first time, with market value skyrocketing by $1.35 trillion overnight, bringing the total to $2.8 trillion. This surge in Nvidia’s stock price pushed most tech stocks higher, leading the Nasdaq to break the 17,000-point threshold for the first time in history.
The rapid development of AI has driven a strong demand for high-performance computing, particularly in the data center sector, which has been a major growth driver for Nvidia. The financial report shows that Nvidia achieved $26 billion in revenue in the first quarter, with data center business driving the core growth, contributing $22.26 billion, marking a 427% year-over-year increase.
Currently, Nvidia is the third-largest company by market value globally and the most sought-after AI chip manufacturer. With global tech companies and government agencies increasing their investments in AI technology, the demand for Nvidia’s high-performance GPUs has grown accordingly.
Nvidia’s Market Surge Highlights AI’s Future and the Rise of AI Investment Trends
The story begins with OpenAI, which paved the way for generative AI by developing advanced models like the GPT series and DALL-E. Since then, large language models have developed rapidly. Companies like Google, Microsoft, Meta, Amazon, and OpenAI have invested billions in Nvidia GPUs to develop and deploy AI applications. For instance, Meta’s latest large language model, Lama 3, used 24,000 H100 GPUs. Nvidia’s leading technology in GPUs and other AI chips has given it a monopolistic position globally.
Nvidia’s soaring market value underscores the immense potential of AI technology as a future growth engine. As AI technology continues to penetrate various industries, investment and attention in the AI field are increasing. Jensen Huang stated that there are approximately 15,000 to 20,000 generative AI startups across various fields. Nvidia’s better-than-expected financial report has driven a surge in AI-related stocks, indicating investor confidence in AI’s transformative potential and long-term returns.
Market research firm PitchBook recently released its latest Q1 2024 global AI and machine learning investment data report, showing that 1,779 financing transactions were completed in the AI field globally in the first quarter, raising a total of $21.6 billion. Recently, Musk’s xAI secured $6 billion in funding, with a valuation of $24 billion. Against this backdrop, the decentralized AI platform WorldBrain has also seized development opportunities, offering innovative business models and technical solutions to facilitate the widespread application of AI technology.
WorldBrain: Opportunities for Decentralized AI
WorldBrain, an innovative project initiated by OpenAI’s Worldbrains Foundation, aims to create an unprecedented distributed intelligent neural network system based on the WorldModel. Combining WorldModel and Web3 technologies to empower AI, WorldBrain represents cutting-edge development in the AI field, promoting higher intelligence and autonomy while achieving decentralization.
Massive Computing Demands and Energy Consumption of AI Foster Distributed Computing Solutions
AI models, especially large neural networks, require immense computing power and energy to train and operate, leading to high power consumption and environmental impact, raising sustainability concerns. Research firm CB Insights recently released a report on generative AI industry predictions for 2024:
On one hand, generative AI infrastructure consumes a tremendous amount of energy. With the advancement of AI technology, the energy demand for high-performance GPUs is steadily increasing. By 2024, the energy consumption of Nvidia’s high-end H100 chips is expected to match that of a small country. Traditional data centers will face the pressure to upgrade to meet AI’s high-power and high-heat demands.
On the other hand, chip shortages are causing computational resource constraints. Amid the GPU shortage, the price of Nvidia’s high-end H100 chips has soared. The high cost of high-performance chips presents challenges for small companies, limiting their competitiveness and development speed in the large model research field.
In response, WorldBrain proposes a distributed computing solution. Distributed computing doesn’t rely on powerful computing resources; it requires minimal device specifications, allowing anyone on Earth to participate using small devices like smartphones. Utilizing distributed computing technology and DePIN networks, any physical device globally can freely access the decentralized WorldBrain network. WorldBrain also features low energy consumption; the energy consumed by the intelligent operations in the brain is comparable to a light bulb, with a single APP neuron consuming only 1/20 of the total power of a smartphone, making the computing cost extremely low.
Democratizing AI Technology: Co-creating a Fair Future
Einstein once said, “Technology has exceeded humanity.” Currently, global AI technology is controlled and managed by a few tech monopolies. We have seen the monopolistic ambitions of tech giants, with algorithms, traffic, and big data disrupting fundamental societal rules. Algorithms monopolize news, shopping, travel, and social interactions, infringing on privacy and negating individual value. They exploit authors’ creativity to make money through big data and algorithms. The democratization of AI technology concerns everyone’s privacy and interests.
Challenging Silicon Valley’s monopolistic power and countering digital utopias, the development of decentralized AI helps break the monopoly of computing resources by a few enterprises, promoting the democratization and popularization of AI technology. In the WorldBrain ecosystem, users achieve self-management through smart contracts and DAOs. Using distributed storage and blockchain technology, data and computing tasks are distributed across multiple nodes, with no single control center, better protecting user privacy and allowing all participants to verify and access information more transparently.
WorldBrain leverages distributed computing technology to deploy hardware devices globally via the DePIN network and applies token-based incentive mechanisms, making every user a creator and owner of the WorldBrain system. The wealth created by WorldBrain, sufficient for human prosperity, is effectively distributed to every participant. This ensures that the benefits of general AI represented by WorldBrain reach ordinary people.
Empowering AI with Web3: The Explosive Potential of DePIN and Decentralized AI
WorldBrain empowers AI with Web3 technology, achieving true decentralization. By innovating with DePIN and AI technology, it utilizes idle computing power and physical devices worldwide to provide efficient and affordable computing resources for the AI industry.
The WorldBrain project is the first to launch an AI system using decentralized technology. By integrating cutting-edge AI development with blockchain technology, WorldBrain offers innovative decentralized AI solutions, gaining significant favor from capital markets, including Morgan Stanley and Goldman Sachs. Currently, the WorldBrain neural network incentive system has amassed substantial user data, with 2,669,017 registered users and 81,921 on-chain wallet addresses. This dual support of capital and user traffic indicates WorldBrain’s immense potential in future technological development.
As WorldBrain continues to advance and improve, we have reason to believe it can build a decentralized, open, and transparent environment where everyone can participate equally and share the benefits of AI technology. Whether it’s acquiring knowledge, sharing creativity, or creating value, WorldBrain will provide a fair, secure, and efficient platform, enabling everyone to find their place in this intelligent era and allowing global users to participate in and benefit from AI development.
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