Magic, an AI startup that creates models that generate code and automate a variety of software development tasks, has raised a significant amount of funding from investors including former Google CEO Eric Schmidt.
Magic announced in a blog post Thursday that it had closed a $320 million funding round, with contributions from Schmidt, Alphabet’s CapitalG, Atlassian, Elad Gill, Jane Street, Nat Friedman & Daniel Gross, Sequoia and others. The funding brings the company’s total funding to nearly $500 million ($465 million), and puts it in the company’s league of well-funded AI coding startups that includes Codeium, Cognition, Poolside, Anysphere and Augment. (Interestingly, Schmidt also backed Augment.)
Reuters reported in July that Magic was looking to raise more than $200 million at a valuation of $1.5 billion. The round apparently exceeded expectations, but the startup’s current valuation could not be confirmed. Magic was valued at $500 million in February.
Magic today announced a partnership with Google Cloud to build two “supercomputers” on Google Cloud Platform: the first, Magic-G4, will be powered by Nvidia H100 GPUs, while the other, Magic G5, will be built with Nvidia’s next-generation Blackwell chips (GPUs are often used to train and serve generative AI models because they can perform many calculations in parallel).
Magic said it aims to scale the latter cluster to “tens of thousands” of GPUs in the future.
“We’re excited to partner with Google and Nvidia to build a next-generation AI supercomputer on Google Cloud,” Magic co-founder and CEO Eric Steinberger said in a statement. “Nvidia’s [Blackwell] This system enables much more efficient model inference and training. Google Cloud also offers the fastest scaling timelines and a rich ecosystem of cloud services.”
Steinberger and Sebastian de Lo co-founded Magic in 2022. In a previous interview, Steinberger told TechCrunch that he was inspired by the potential of AI at a young age, and that as a high school student, he and some friends wired up their school’s computers to train machine learning algorithms.
The experience led Steinberger to complete a computer science degree at Cambridge (he dropped out after one year) and then work as an AI researcher at Meta. De Lo comes from German business process management company FireStart, where he rose to become CTO. Steinberger and De Lo met at ClimateScience.org, an environmental volunteer organization Steinberger co-founded.
Magic is developing an AI-driven tool (not yet available for sale) designed to help software engineers write, review, debug, and plan code changes. The tool works like an automated pair programmer, understanding the context of different coding projects and trying to continuously learn.
Many platforms do the same, and GitHub Copilot is no exception. But one of Magic’s innovations is in the ultra-long context window of its model. The architecture of this model is called a “long-term memory network,” or “LTM” for short.
A model’s context, or context window, refers to the input data (e.g., code) that the model considers before generating an output (e.g., additional code). A simple question like “Who won the 2020 US Presidential election?” can act as context, as can a movie script, show, or audio clip.
The larger the context window, the larger the size of the document (or possibly the codebase) that fits within it. Longer context helps prevent the model from “forgetting” the content of recent documents or data, and from going off topic and making erroneous inferences.
Magic claims that its latest model, the LTM-2-mini, has a context window of 100 million tokens. (Tokens are bits of raw data, like the syllables “fan,” “tas,” and “tic” in the word “fantastic.”) 100 million tokens is the equivalent of about 10 million lines of code, or 750 novels. This is by far the largest context window of any commercially available model. The next largest is Google’s Gemini flagship model, with 2 million tokens.
Magic says that thanks to its long context, the LTM-2-mini was able to implement a password strength meter for an open source project and create a calculator almost autonomously using a custom UI framework.
The company is now training a larger version of that model.
The Magic’s team is small — about two dozen people — and its revenues aren’t huge, but Polaris Research estimates that the Magic could be worth $27.17 billion by 2032, and investors see it as a worthwhile (and likely quite lucrative) endeavor.
Despite security, copyright and reliability concerns surrounding AI-powered coding assistance tools, developers have expressed enthusiasm for them, with a majority of respondents in GitHub’s latest survey saying they have adopted some form of AI tool. Microsoft reported in April that Copilot has more than 1.3 million paying users and more than 50,000 enterprise customers.
And Magic’s ambitions are grander than automating mundane software development tasks: The company’s website talks about its path to AGI, an AI that can solve problems more reliably than humans could ever do on their own.
Toward that end, San Francisco-based Magic recently hired Ben Chess, former head of OpenAI’s supercomputing team, and plans to expand its cybersecurity, engineering, research and systems engineering teams.
