Together, a startup that’s building a decentralized, open-source cloud for artificial intelligence development, announced Sunday it has raised $20 million in seed funding.
The round was led by Lux Capital and saw participation from a host of other investors, including Factory, SV Angel, First Round Capital, Long Journey Ventures, A Capital, Robot Ventures, Common Metal, Definition Capital, Susa Ventures, Cadenza Ventures. In addition, various angle investors, including PayPal Inc. co-founder Scott Banister, Cloudera Inc. co-founder Jeff Hammerbacher, Transformer architecture co-inventor Jakob Uszkoreit and many others participated in the round.
The funding will be used to support Together’s mission of creating a decentralized alternative to the closed AI systems winning all the plaudits today, such as OpenAI LP’s ChatGPT. Together intends to democratize AI so everyone can participate together in one of the hottest trends in technology.
As part of this mission, Together aims to establish open source as the default way to design and build AI. One of its aims is to create open models that outperform their closed-source brethren. To do this, Together is collaborating with various open-source groups, academic and corporate research labs, while assembling an impressive team of committed AI researchers, engineers and practitioners.
“It’s an honor to reach this milestone with the support of incredible investors who believe in our mission: to empower innovation and creativity by providing leading open-source generative AI models and a cloud platform that makes AI accessible to anyone, anywhere,” Together founder and Chief Executive Vipul Ved Prakash wrote in a blog post announcing the round.
Together argues that closed-source AI models create risks around liability and visibility into how they work, since the users have no insight into how they work or what they were trained on. With open-source AI models, these risks can be eliminated, while increasing accessibility, the company says.
Even before this funding round, Together has made a number of achievements, creating several generative AI projects such as GPT-JT, OpenChatKit and its flagship project RedPajama, which is said to be supported by hundreds of thousands of AI developers. According to Prakash, the company is working to lay the groundwork for open-source AI by releasing various datasets, models and research created in collaboration with its partners.
RedPajama is an effort to produce reproducible, fully open large language model in collaboration with partners such as Ontocord.AI, Eidgenössische Technische Hochschule Zürich’s DS3 Lab and the Stanford Center for Research on Foundation Models. The project has three components, including pretraining data, base models trained on that data, and instruction tuning-data and models that are used to improve the base model to make it useful and safe.
RedPajama has already shown considerable promise, but is only one aspect of Together’s efforts. In addition, the company is partnering with various decentralized infrastructure providers to make the computational resources needed for training and operating LLMs more accessible. It’s creating a cloud platform that’s designed to do a more efficient job of scaling up training and inference for large models through distributed optimization.
Together Senior Vice President of Product Jamie de Guerre told VentureBeat that in one of the company’s projects, it was able to reduce networking traffic by 200 times during model training and fine-tuning. It’s also building technologies to improve AI inference, thereby creating a more scalable infrastructure that will be accessible to smaller companies and individual developers.
The company will use the funds it has raised to improve its cloud platform and expand its team and research efforts.
“In the coming months we plan to open up access to this platform, enabling rapid customization and coupling of foundation models with production tasks,” Prakash said. “Open models will give developers and organizations greater ability to understand, inspect and utilize AI, without vendor lock-in and with strong privacy protections.”
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