Goodfire, an ambitious AI startup launched by seasoned entrepreneur Eric Ho, DeepMind alumnus Thomas McGrath, and Daniel Balsam, a founding engineer at RippleMatch, just raised a $50 million Series A round led by Menlo Ventures, with participation from Anthropic, Lightspeed Venture Partners, B Capital, Work-Bench, Wing, and South Park Commons.
The company is building Ember, an interpretability platform designed to expose and reprogram the internal logic of advanced AI models. Rather than relying on input/output behavior or prompt engineering, Ember gives developers direct, programmable access to what's actually happening inside the model's neural networks, according to Goodfire.
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Goodfire Is Breaking Open the Black Box
AI models are often referred to as “black boxes” due to their complex and opaque decision-making processes. Goodfire aims to change that narrative by developing tools that allow developers to peer inside these models, understand their reasoning, and guide their behavior toward safer and more reliable outcomes.
Founded in 2024 and based in San Francisco, Goodfire is positioning itself as a foundational player in mechanistic interpretability, a rapidly growing field aimed at making AI less of a black box and more of a controllable system, writes Tech Startups.
Goodfire’s team comprises some of the most respected names in AI research. According to Fast Company, Lee Sharkey is known for his work on sparse autoencoders in language models, while Nick Cammarata, another team member, started the interpretability team at OpenAI alongside Chris Olah, who later co-founded Anthropic.
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According to Tech Startups, Anthropic, the AI safety-focused startup behind the Claude chatbot, made its first-ever startup investment by contributing $1 million to Goodfire’s Series A round. This investment signals growing industry consensus that tools enabling transparency and control are critical infrastructure for the next generation of AI.
Goodfire’s Vision
Eric Ho, co-founder and CEO of Goodfire, emphasized the significance of their work in the startup’s funding announcement: “Nobody understands the mechanisms by which AI models fail, so no one knows how to fix them. Our vision is to build tools to make neural networks easy to understand, design, and fix from the inside out. This technology is critical for building the next frontier of safe and powerful foundation models.”
According to Fast Company, Goodfire has started receiving interest from Fortune 500 companies looking to understand and influence how their AI models “think” since many still treat these systems like traditional software, expecting reprogrammable logic where none exists, explained Eric Ho. Language models respond with probability, not precision, and reshaping their behavior means diving deep into how they reason. Goodfire's tools offer companies a first step toward that kind of control, even if the science is still in its early stages.
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Goodfire’s Ember platform is already being utilized by organizations like the Arc Institute to extract novel biological concepts from their DNA foundation model, Evo 2. This collaboration has enabled scientists to uncover insights that were previously hidden within the model’s complex structure.
The Road Ahead
With the new funding, Goodfire plans to expand its research initiatives and enhance the Ember platform. The goal is to make AI systems more transparent, controllable, and aligned with human values.
As AI continues to permeate various aspects of society, tools like Ember will be instrumental in ensuring that these systems operate safely and effectively.
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