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What is Zochi?

Zochi distinguishes itself as the pioneering autonomous AI system that can navigate the complete scientific research process, from hypothesis generation to obtaining peer-reviewed publication, while producing innovative results. Unlike earlier systems that were limited to narrow, predefined tasks, Zochi excels in tackling research issues at the forefront of artificial intelligence. Its efficacy is underscored by a series of peer-reviewed publications accepted at the ICLR 2025 workshops, showcasing Zochi's ability to deliver creative and rigorously validated contributions to the field. Additionally, Zochi identified a critical challenge within AI: the phenomenon of cross-skill interference during parameter-efficient fine-tuning, where adapting models for multiple tasks may enhance one capability at the cost of others. To address this issue, Zochi proposed an innovative strategy known as CS-ReFT (Compositional Subspace Representation Fine-tuning), which focuses on modifying representations rather than changing weights. This transformative method could significantly alter the landscape of how AI systems are fine-tuned for various applications, promising to enhance their versatility and performance in real-world scenarios. The implications of Zochi's advancements may extend far beyond academia, influencing practical implementations across numerous sectors.

What is ESMC?

ESMC marks the latest innovation in the ESM series of protein language models, advancing the understanding of representation learning in protein biology. By training on an enormous dataset of billions of evolutionary sequences, it effectively captures representations that provide insights into the mechanistic aspects of protein structure and function. Utilizing a transformer architecture, the model prioritizes sequences as its main input and is trained on a dataset that includes up to 6 billion proteins. ESMC is designed for a range of applications within protein science, including structure prediction, functional annotation, protein design, and the investigation of evolutionary relationships among proteins. Furthermore, it has the ability to generate new proteins from partial sequences, structures, or specific functional requirements, which allows researchers to explore novel possibilities in protein design and biological research. The model is readily accessible through the Biohub Platform, enabling users to interact with it via an API and the ESM Python package, which offers quickstart resources for installation, API key generation, and connection to the platform, thus ensuring a user-friendly experience. This ease of access not only promotes wider participation in protein research but also fosters collaborative efforts across the scientific community, ultimately driving further advancements in the field. With its capabilities, ESMC opens new doors for innovation and discovery in protein science.

Media

Media

Integrations Supported

Integrations Supported

Biohub
Python

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Intology

Date Founded

2025

Company Location

United States

Company Website

www.intology.ai/blog/zochi-tech-report

Company Facts

Organization Name

Biohub

Date Founded

2016

Company Location

United States

Company Website

biohub.ai/models/esmc

Categories and Features

AI Research Tools

Not specified

AI Science

Not specified

Categories and Features

AI Models

Not specified

AI Science

Not specified

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