The fascination around generative AI, artificial intelligence technology capable of creating essays, artwork, music and more, continues to draw significant investor interest. A recent report suggests generative AI startups amassed $1.7 billion in Q1 2023, with a further $10.68 billion in deals declared in the same quarter but yet to be finalized.
Despite the fierce competition with established players such as OpenAI and Anthropic, venture capitalists are not hesitating to invest in emerging and unproven startups in the sector.
A shining example is Together, a young company focused on developing open-source generative AI, which has just announced a substantial seed funding round of $20 million. The round was led by Lux Capital and included other investors such as Factory, SV Angel, First Round Capital, Long Journey Ventures, Robot Ventures, Definition Capital, Susa Ventures, Cadenza Ventures, and SCB 10x. High-profile individual investors also participated, including PayPal co-founder Scott Banister and Cloudera founding member Jeff Hammerbacher.
Brandon Reeves of Lux Capital praises Together for leading what he terms the “Linux moment” of AI, providing an open ecosystem spanning compute and top-tier foundation models. He lauds the company’s commitment to fostering a dynamic open ecosystem that allows participation from individuals to enterprises.
Launched in June 2022, Together is the creation of Vipul Ved Prakash, Ce Zhang, Chris Re, and Percy Liang. Together is focused on creating open-source generative AI models and services aimed at aiding organizations in integrating AI into their production applications. To achieve this, the startup is developing a cloud platform for running, training, and fine-tuning open-source models, aiming to provide scalable compute at significantly lower prices than leading vendors, such as Google Cloud, AWS, and Azure.
Prakash expresses the belief in the societal importance of generative models and the critical need for open and decentralized alternatives to closed systems to ensure the best outcomes for AI and society. He emphasizes the growing demand from enterprises for privacy, transparency, customization, and ease of deployment, areas where current cloud offerings with closed-source models and data fall short.
