Chances are you think of text and image creation when you think of a foundation model. The models are being taken in a different direction by numbers station. The startup, which is announcing a $17.5 million Series A round today, is using these models to build an intelligent data stack automation platform. The funding round was led by Madrona, with participation from Norwest Venture Partners, Factory and a number of angels. Chris Aberger (CEO), Ines Chami (chief scientist) and Sen Wu (associate professor) founded Numbers Station with the goal of bringing the power of GPT-style foundation models to enterprise use cases. The company uses foundation models to translate queries into commands. When I asked Aberger about the origins of the company, he said that they all got PhDs on a mix of data and artificial intelligence. At the time, we saw that most of the talent was focused on applications that were sexy. Marketing content generation is one of the things you see in the news. The dirty data plumbing, data munging, data wrangling, and data preparation operations were not the focus of most of the artificial intelligence talent. It's not as sexy as saying that we're going to change the dates in your database, but that's still a huge enterprise problem. The numbers station has an image. Aberger noted that when the team looked at how different data-centric teams work together, a lot of different capabilities were locked up in different teams, all while these teams spent a lot of their time on the routine data transformation work that's needed to enable more complex use He thinks that Numbers Station and the foundation models that power it will be able to make it easier to access. "Our goal is to accelerate those teams and accelerate the data analyst teams so that they can spend more time giving insights and less time on mundane data operations," Aberger said. The numbers station has an image. The service currently has three different capabilities. One of the first things users can do is specify what they want in a natural language. The company calls it the ability to prototype intelligent data transformations powered by artificial intelligence. The record matching feature of Numbers Station allows users to combine the records in their sales and customer relationship management systems into a single database. The numbers station has an image. Ines Chami told me that the team isn't just taking a foundation model and applying it to all of the use cases. She said it was important to adapt the model to the organization. Fine tuning techniques and feedback are used to generate answers that are specific to the organization. She noted that the company starts users on a general purpose pre-trained model but then, as users give the model feedback, it creates smaller, organization specific models for these users. In order to adapt the model to the organizational knowledge, it is very much human-in- the-loop. It is important to go beyond the general-purpose model. Foundation models from the likes of Openai will become commoditized according to Aberger. He said that "what really matters is where you apply AI expertise on top of these models to make them perform better for specific organizations and a specific organization's tasks." The numbers station has an image. Numbers Station looks at the first three features as its entry point into the data stack. The larger vision here is to build a data intelligence platform that not only helps businesses transform their data, but also analyses it. Businesses need to clean up their records in order to do that. "Foundation models, specifically how the Numbers Station team is applying them, provide a truly zero to one opportunity to address the massive challenge of dealing with messy data," said Tim Porter, who will join the Numbers Station board. Data prep is just the beginning of the team's ambitious vision. One of the main advantages of the Numbers Station approach is the ability to immediately connect intelligent transforms into automated workflows. As they build out the platform we believe all enterprises will see as a crucial element in their modern data stack, we are thrilled to back this world class customer driven team. Over the past three years, founder Ren Zhengfei said, the company has replaced more than 13,000 components in its range of products with local replacements. According to a transcript of his speech, Ren said the production of circuit boards has "stabilised" after the Chinese telecom giant developed replacement parts from domestic sources. Despite being added to a US trade blacklist, a Chinese chip designer is attempting to develop its own general-purpose graphics processing unit. According to a response from the company this week, it is evaluating the advanced 7-nanometer process from a number of foundries to manufacture its future chips. 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The rise of artificial general intelligence -- now seen as inevitable in Silicon Valley -- will bring change that is "orders of magnitude" greater than anything the world has yet seen, observers say.This is the first time we're able to create intelligence itself and increase its amount in the universe," he told AFP.
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Numbers Station raises $17.5M to bring AI to your data stack
