March 4, 2024

Generative AI — AI that can write papers, create artwork and music, among other things — continues to attract a lot of attention from investors.Generative AI startups raised $1.7 billion in the first quarter of 2023, with another $10.68 billion worth of deals, according to a source Announce In this quarter but not yet completed.

Competition is fierce, including established players such as OpenAI and Anthropic. But despite this, VCs haven’t shy away from untested players and up-and-comers.

for example, Together, a startup developing open-source generative artificial intelligence, announced today that it raised $20 million — in a seed round — led by Lux Capital, with Factory, SV Angel, First Round Capital, Long Journey Ventures, Robot Ventures , Definition followed Capital, Susa Ventures, Cadenza Ventures and SCB 10x. Several high-profile angel investors also participated, including PayPal co-founder Scott Banister and Cloudera founding employee Jeff Hammerbacher.

“By providing an open ecosystem across compute and best-in-class foundational models, Together is leading AI’s ‘Linux moment,'” Brandon Reeves of Lux Capital told TechCrunch via email.The Together team is committed to creating a vibrant and open ecosystem where anyone from individuals to businesses can participate. “

Launched in June 2022, Together is the brainchild of Vipul Ved Prakash, Ce Zhang, Chris Re and Percy Liang. Prakash previously founded social media search platform Topsy, which was acquired by Apple in 2013, and he later became a senior director at the company. Zhang, an associate professor of computer science at ETH Zurich, is currently on sabbatical and leading research into “decentralized” artificial intelligence. As for Re, he co-founded several startups, including SambaNova, which builds hardware and integrated systems for AI. Liang, a professor of computer science at Stanford, leads the university’s Center for Research on Fundamental Models (CRFM).

Through Together, Prakash, Zhang, Re, and Liang are seeking to create open-source generative AI models and services that, in their words, “help organizations incorporate AI into their production applications.” To that end, Together is building a A cloud platform for running, training, and fine-tuning open-source models that the co-founders claim will provide scalable computing at “significantly lower” prices than major providers (e.g., Google Cloud, AWS, Azure).

“We believe that generative models are a socially impactful technology, and that open and decentralized alternatives to closed systems are critical to achieving the best outcomes for AI and society,” Prakash told TechCrunch in an email interview. When defining their generative AI strategy, they were looking for privacy, transparency, customization, and ease of deployment. Current cloud offerings with closed-source models and data do not meet their requirements.”

He has a point — at least if the incumbent feels the internal memo Give way Statements earlier this month suggested that the search giant and its rivals could not compete with open-source AI initiatives in the long run. Meanwhile, OpenAI is reportedly preparing to publicly demonstrate its first open-source text-generating AI model amid a proliferation of open-source alternatives.

One of Together’s first projects, red pajamas, which aims to foster a suite of open-source generative models, including a “chat” model similar to OpenAI’s ChatGPT. Together, a collaborative effort between groups including MILA’s Quebec Institute for Artificial Intelligence, CRFM, and ETH’s data science lab DS3Lab, RedPajama, is the first to release a dataset that enables organizations to pre-train licensed Model.

Together’s other efforts to date include GPT-JT, a fork of the open-source text generation model GPT-J-6B (published by research group EleutherAI), and OpenChatKit, an attempt at a ChatGPT equivalent.

“Today, training, fine-tuning, or productizing open-source generative models is extremely challenging,” Prakash said. “Current solutions require you to have deep expertise in AI while being able to manage the large-scale infrastructure required. The Together platform addresses both challenges out-of-the-box with an easy-to-use and accessible solution.”

It remains to be seen how seamless Together will be, though — the platform hasn’t launched in GA yet. And, one could argue, its efforts are a bit of a duplication in the broader field of artificial intelligence.Number of open source models from community groups and large labs growing day by day, actually. While not all software is licensed for commercial use, some, such as Databricks’ Dolly 2.0, are licensed for commercial use.

In terms of AI hardware infrastructure, in addition to the large public cloud providers, startups like CoreWeave claim to offer massive computing power at below-market prices. There have even been attempts to build community-supported free services to run AI text generation models. (Together intends to follow in the footsteps of these community groups by building a platform, tentatively called the Together Decentralized Cloud, that will pool hardware resources, including GPUs from Internet volunteers.)

So what does Together bring? Greater transparency, control and privacy, Prakash believes. The pitch is not dissimilar to that of the startup Stability AI, which pours computation and money into open-source research while commercializing various finished products and selling services on top of them.

“Regulated enterprises will be big customers of open source, as open source models pre-trained on open datasets enable organizations to fully inspect, understand and customize models to suit their own applications,” he said. “We believe that the challenges of artificial intelligence can only be overcome through the joint efforts of the global community. Therefore, our mission is to build and manage a self-sustaining open ecosystem to produce the best artificial intelligence systems for mankind.”

To be sure, this is a lofty goal. It’s still early days for Together, and it won’t say whether it currently has any customers — let alone revenue. But the company is forging ahead, planning to grow its team size from 24 employees to around 40 by the end of the year, and spend the rest of the seed money on R&D, infrastructure and product development.

“The Together solution, based on an open-source generative model, is built on understanding the needs of large organizations and addressing each of them, and is designed to provide the core platform for an enterprise’s generative AI strategy,” said Prakash. Huge interest in greater transparency, control and privacy.”