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Description

Osmosis AI serves as an interactive study companion seamlessly integrated into the Osmosis learning platform, aimed at assisting medical and health professional students in grasping, reviewing, and solidifying intricate subjects through a mix of AI-driven explanations and reputable educational resources. It combines Elsevier's vast collection of peer-reviewed medical textbooks and materials with the Osmosis visual learning approach, providing responses that are evidence-based, properly cited, and linked to pertinent videos, diagrams, and study aids. This innovative tool allows students to inquire in real time without disrupting their study routine, offering straightforward explanations in accessible language along with direct citations to the original sources for validation. Unlike many platforms that depend on open web data, Osmosis AI functions within a defined "walled garden" of carefully selected medical content, minimizing the occurrence of inaccuracies and ensuring alignment with the educational standards for teaching and assessment in the medical field. As a result, students can engage in a more focused and reliable learning experience that enhances their understanding of complex topics.

Description

Zochi stands out as the first autonomous AI system capable of completing the entire scientific research cycle, ranging from formulating hypotheses to achieving peer-reviewed publication, while generating cutting-edge outcomes. In contrast to previous systems that were confined to specific, well-defined tasks, Zochi thrives in confronting research challenges that are at the cutting edge of artificial intelligence. The system's effectiveness is demonstrated through a series of peer-reviewed papers accepted at the ICLR 2025 workshops, highlighting Zochi's capacity to produce innovative and academically sound contributions. Furthermore, Zochi recognized a significant obstacle within the AI field: the issue of cross-skill interference during parameter-efficient fine-tuning. This problem arises when models are adapted for multiple tasks at once, leading to enhancements in one skill that may negatively impact others. To combat this challenge, Zochi introduced a novel approach called CS-ReFT (Compositional Subspace Representation Fine-tuning), which emphasizes the editing of representations instead of altering weights. This groundbreaking method has the potential to revolutionize how AI systems are fine-tuned for diverse applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Elsevier

Founded

1880

Country

The Netherlands

Website

www.elsevier.com/products/osmosis/osmosis-ai

Vendor Details

Company Name

Intology

Founded

2025

Country

United States

Website

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

Product Features

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Alternatives

Alternatives

LeapSpace Reviews

LeapSpace

Elsevier
LeapSpace Reviews

LeapSpace

Elsevier