Today, almost everyone is trying to get a piece of the action to generate artificial intelligence. While most attention is still focused on model vendors such as OpenAI, Anthropic, and Cohere, or large companies such as Microsoft, Meta, Google, and Amazon, there are actually many startups trying to solve the generative AI problem in various ways. The way.

Fireworks.ai is one such startup. While lacking the brand recognition of some other players, it has the largest open source model API with over 12,000 users per company. This open source appeal tends to attract the attention of investors, and the company has raised $25 million to date.

Fireworks co-founder and CEO Qiao Lin noted that her company does not train a base model from scratch, but rather helps fine-tune other models to meet the specific needs of the business. “It can be an off-the-shelf open source model, or it can be a model that we tune, or it can be a model that our customers can tune themselves. All three varieties can be served through our inference engine API,” Qiao told TechCrunch.

As an API, developers can plug it into their applications, train the model of their choice based on their data, and add generative AI features such as quick questions. Joe says it’s fast, efficient, and produces high-quality results.

Another advantage of the Firework approach is that it allows companies to try multiple models, which is important in a rapidly changing market. “The idea is that we want to give users the ability to iterate and experiment with multiple models and have effective tools to inject their data into multiple models and test them with the product,” she said.

Perhaps more importantly, they lowered costs by limiting the model size to between 7 billion and 13 billion tokens, compared to over 1 trillion tokens in ChatGPT4. While this limits the range of words that large language models can understand, it allows developers to focus on smaller, more focused datasets designed to address more limited business use cases.

Qiao is uniquely qualified to build such systems, having previously worked at Meta, leading the AI ​​platform development team, with the goal of building a fast, scalable development engine to provide artificial intelligence support for all Meta products and services. She was able to take this knowledge from working at Meta and create an API-based tool that would allow any company to use this functionality without having to have the level of engineering resources that a company the size of Meta would have.

The company raised $25 million in funding in 2022, led by Benchmark, with participation from Sequoia Capital and angel investors such as Databricks and Snowflake. The latter two are particularly interesting strategic investors because they are both data storage tools, and Fireworks will enable users to put this data to use.

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