
Asteromorph
Foundation model for autonomous scientific research, emulating human intuition to generate hypotheses and run experiments in silico and in vitro.
Date | Investors | Amount | Round |
---|---|---|---|
* | KRW5.0b | Seed | |
Total Funding | 000k |
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Asteromorph is positioned at the nexus of artificial intelligence and fundamental scientific research, with the objective of developing 'superintelligence'. The company's stated goal is to construct an AI that can significantly accelerate knowledge expansion by automating scientific discovery.
The firm was established by a team that includes Evgeny Putin and Petr Panteleev. Evgeny Putin brings to the venture a substantial background in applied artificial intelligence, notably his tenure as the Deep Learning Lead at Insilico Medicine. At Insilico, he was instrumental in developing and applying deep learning models for complex challenges in drug discovery and aging research. This prior experience in leveraging sophisticated AI for tangible scientific outcomes forms a direct lineage to Asteromorph's more expansive vision of creating a generalized AI for science.
The core of Asteromorph's strategy is the development of a proprietary foundation model. This is not a general-purpose language model, but rather a specialized AI architected to emulate the intuitive and reasoning processes of a scientist. Its function is to autonomously generate novel hypotheses and subsequently validate them through self-directed experiments. The company literature suggests a dual-pronged approach to this validation, encompassing both computational simulations ('in silicon') and interactions with the physical world, which implies a potential future integration with robotic or automated laboratory systems.
The business operates in the high-stakes market of AI-driven research and development. Its primary clients are expected to be pharmaceutical corporations, biotechnology firms, materials science researchers, and academic or governmental laboratories engaged in pioneering research. The business model, while not publicly detailed, will likely revolve around providing access to its powerful AI platform. This could manifest as a subscription-based service (SaaS), tailored research partnerships for specific discovery projects, or licensing agreements for the foundation model. The ultimate aim is to create a new paradigm in R&D, shifting from human-led experimentation to AI-augmented, and eventually AI-driven, discovery cycles. Keywords: superintelligence, foundation models, AI for science, scientific discovery, autonomous scientist, AI research, Evgeny Putin, Petr Panteleev, computational science, automated experiments, hypothesis generation, AI drug discovery, deep learning, machine learning, R&D automation, biotech AI, materials science AI, artificial intelligence research, generative AI, scientific reasoning