![]() Given the caliber of the company’s founders and backers, expect Inflection AI to make waves in the world of language AI before long. Its stated mission is to “fundamentally redefine human-machine interaction” by enabling humans to “relay our thoughts and ideas to computers using the same natural, conversational language we use to communicate with people.” The company is being incubated at Greylock, where Hoffman is a general partner. Launched less than a month ago, little is known yet about Inflection AI beyond its eye-catching founding team: Reid Hoffman, DeepMind cofounder Mustafa Suleyman, and decorated DeepMind researcher Karen Simonyan. ![]() There is one last wild card worth mentioning in this category. The company primarily serves clients in government and defense. Primer is an older competitor in this space, founded two years before the invention of the transformer. ![]() Its current application suite focuses on tools to augment reading and writing. Other horizontal NLP providers of note include AI21 Labs and Primer.īased in Israel, AI21 has a two-pronged business model: it offers proprietary large language models via API to power customers’ applications (its current state-of-the-art model, named Jurassic-1, is roughly the same size as GPT-3), and it also builds and commercializes its own applications on top of those models. In this respect it can be loosely analogized to GitHub, but for machine learning rather than traditional software engineering. Hugging Face’s secret sauce is its community: it has become a go-to destination for companies and researchers in the world of NLP to collaborate. Rather, it is a platform that stores, serves and manages the latest and greatest in open-source NLP models, including enabling customers to fine-tune these models and deploy them at scale. Unlike OpenAI or Cohere, Hugging Face does not build its own NLP models. Hugging Face is a wildly popular community-based repository for open-source NLP technology. “While slightly less 'miraculous', these models form the backbone of some of the most sophisticated NLP systems in the world."Īnother leading horizontal NLP startup is Hugging Face. "Language generation has seemingly monopolized the attention of those interested in NLP, but the most significant opportunity for developers interested in building NLP into their systems actually rests in language representation models like BERT,” said Gomez. These classification models have myriad commercial use cases: from customer support to content moderation, from market analysis to search. While Cohere does produce generative models along the lines of GPT-3, the company is increasingly focused on models that analyze existing text rather than generate novel text. The company recently announced a large Series B fundraise from Tiger Global less than a year after emerging from stealth. Cohere’s founding team is highly pedigreed: CEO Aidan Gomez is one of the co-inventors of the transformer CTO Nick Frosst is a Geoff Hinton protégé. Given Microsoft’s massive investments in and deep alliance with the organization, OpenAI can almost be considered an arm of the tech giant.īut there is also tremendous opportunity in this category for younger startups.Ĭohere is a fast-growing startup based in Toronto that, like OpenAI, develops cutting-edge NLP technology and makes it commercially available via API for use across industries. ![]() OpenAI has made GPT-3 commercially available via API for use across applications, charging on a per-word basis. GPT-3 is a generative model (the G in its name stands for generative): it generates original text in response to prompts from human users. Its large language model GPT-3 is perhaps the most well-known and widely used foundation model today. OpenAI is another important source of state-of-the-art NLP technology. Most often, foundation models are built and open-sourced by the publicly traded technology giants-e.g., BERT from Google, RoBERTa from Facebook. Stanford researchers recently dubbed these pretrained models “foundation models” in recognition of their outsize influence. Instead, virtually all advanced NLP in use today, no matter the industry or setting, is based on one of a small handful of massive pretrained language models. As a result, very few companies or researchers actually build their own NLP models from scratch. The first category of language AI startups worth discussing is those players that develop and make available core general-purpose NLP technology for other organizations to apply across industries and use cases.īuilding a state-of-the-art NLP model today is incredibly resource-intensive and technically challenging.
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