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If it wasn’t clear earlier than, it’s positively very clear now: Open supply actually does matter for AI. The success of DeepSeek-R1 has substantively confirmed there’s a want and demand for open-source AI.
However what precisely is open-source AI? For Meta and its Llama fashions, it means free entry to make use of the mannequin, with some circumstances. DeepSeek is out there underneath a permissive open-source license with the mannequin code open and obtainable for anybody to make use of. What neither strategy permits, nevertheless, is full unconditional entry to all of the mannequin code, together with weights in addition to coaching information. With out all that info, builders can nonetheless work with the open mannequin however they don’t have all the required instruments and insights to grasp the way it actually works and extra importantly the best way to construct a wholly new mannequin. That’s a problem {that a} new startup led by former Google and Apple AI veterans goals to resolve.
Launching right now, Oumi is backed by an alliance of 13 main analysis universities together with Princeton, Stanford, MIT, UC Berkeley, College of Oxford, College of Cambridge, College of Waterloo and Carnegie Mellon. Oumi’s founders raised $10 million, a modest seed spherical they are saying meets their wants. Whereas main gamers like OpenAI ponder $500 billion investments in huge information facilities by way of initiatives like Stargate, Oumi is taking a radically totally different strategy. The platform offers researchers and builders with an entire toolkit for constructing, evaluating and deploying basis fashions.
“Even the biggest companies can’t do this on their own,” Oussama Elachqar, cofounder of Oumi and beforehand a machine studying engineer at Apple, instructed VentureBeat. “We were effectively working in silos within Apple, and there are many other silos happening across the industry. There has to be a better way to develop these models collaboratively.”
What open-source fashions like DeepSeek and Llama are lacking
Oumi CEO and former Google Cloud AI senior engineering supervisor Manos Koukoumidis instructed VentureBeat that researchers constantly inform him AI experimentation has grow to be extraordinarily complicated.
Whereas right now’s open fashions are a step ahead, it’s not sufficient. Koukoumidis defined that with present “open” AI fashions like DeepSeek-R1 and Llama, a corporation can use the mannequin and deploy it on their very own. What’s lacking is that anybody else who desires to construct on the mannequin doesn’t know precisely the way it was constructed.
The Oumi founders consider this lack of transparency is a significant hindrance to collaborative AI analysis and improvement. Even a challenge like Llama requires a major quantity of effort from researchers to determine the best way to reproduce and construct upon the work.
How Oumi works to open AI for enterprise customers, researchers and everybody else
The Oumi platform works by offering an all-in-one atmosphere that streamlines the complicated workflows concerned in constructing AI fashions.
Koukoumidis defined that to construct a basis mannequin, there are usually 10 or extra steps that must be accomplished, usually in parallel. Oumi integrates all vital instruments and workflows right into a unified atmosphere, eliminating the necessity for researchers to piece collectively and configure numerous open-source elements.
Key technical options embrace:
- Help for fashions starting from 10M to 405B parameters
- Implementation of superior coaching methods together with SFT, LoRA, QLoRA and DPO
- Compatibility with each textual content and multimodal fashions
- Constructed-in instruments for coaching information synthesis and curation utilizing LLM judges
- Deployment choices by way of trendy inference engines like vLLM and SGLang
- Complete mannequin analysis throughout normal {industry} benchmarks
“We don’t have to deal with the open-source development hell of figuring out what you can combine and what works well,” Koukoumidis defined.
The platform permits customers to start out small, utilizing their very own laptops for preliminary experiments and mannequin coaching. As customers progress, they will then scale as much as bigger compute assets, akin to college clusters or cloud suppliers, all throughout the identical Oumi atmosphere.
You don’t want huge coaching infrastructure to construct an open mannequin
One of many huge surprises with DeepSeek-R1 is the truth that it was apparently constructed with a fraction of the assets that Meta or OpenAI use to construct their fashions.
As OpenAI and others make investments billions in centralized infrastructure, Oumi is betting on a distributed strategy that might dramatically cut back prices.
“The idea that you need hundreds of billions [of dollars] for AI infrastructure is fundamentally flawed,” Koukoumidis mentioned. “With distributed computing across universities and research institutions, we can achieve similar or better results at a fraction of the cost.”
The preliminary focus for Oumi is to construct out the open-source ecosystem of customers and improvement. However that’s not all the corporate has deliberate. Oumi plans to develop enterprise choices to assist companies deploy these fashions in manufacturing environments.
