On January 18, Meta CEO Mark Zuckerberg announced strategic changes to the company's artificial intelligence (AI) endeavors, emphasizing the integration of its business-focused generative AI research team with its fundamental AI research (FAIR) team. This move is intended to foster closer collaboration and enhance efforts to bring generative AI technology to market-ready products. Zuckerberg highlighted the company's commitment to significant investments in specialized computer chips, aiming to develop and deliver new generative AI models and products.
In a Thread video, Zuckerberg disclosed that Meta has initiated the training of its next-generation language models, known as Llama 3 (LLM). He emphasized the importance of building comprehensive general intelligence for the next generation of services, particularly in areas such as AI assistants for creators and enterprises. Meta's vision involves advancing various facets of AI, encompassing reasoning, planning, encoding, memory, and other cognitive abilities. The company aims to expand its technology infrastructure to accommodate the integration of generative AI into its product offerings.
To support these ambitions, Meta plans to procure approximately 350,000 H100 graphics processing units (GPUs) from chip designer Nvidia by the end of the year. This investment reflects Meta's commitment to fortifying its technological capabilities and staying at the forefront of AI development. The strategic alignment of its two advanced AI research units mirrors a similar move by Alphabet in 2023, where it integrated Google Brain and DeepMind to enhance its AI research efforts.
Meta has a robust history of AI research, spanning diverse areas such as unsupervised learning, strategy games like Diplomacy, machine translation, and computer vision algorithms. The company's GenAI team has notably developed Llama 2, an influential open-source language model. While Llama 2 may not be as advanced as competitors like OpenAI's GPT-4 or Google's Gemini models, developers favor it for its cost-effectiveness and customizability, particularly in building chatbots. Meta's concerted efforts underscore its commitment to advancing AI technologies and integrating them into practical, real-world applications.
