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Description
Wave is an advanced AI agent crafted to tackle intricate tasks with a level of understanding and reasoning similar to that of humans. Our goal is to streamline your workflow and boost your efficiency. Equipped with cutting-edge language models and tailored tools, Wave excels in conducting research, generating content, and supporting a broad spectrum of activities. As a robust modular AI agent system, Wave brings your tasks to fruition with remarkable effectiveness. Users have reported that by utilizing Wave's self-sufficient research features, they can cut their research time by as much as 87%. With access to an extensive network of more than 30 specialized AI agents collaborating to resolve challenging issues, Wave offers answers and practical insights up to five times quicker than conventional research techniques. The specialized modules within Wave integrate flawlessly to address complex tasks that would typically challenge a singular model approach. Furthermore, Wave keeps track of your preferences and past interactions, ensuring a tailored experience that continuously improves over time, making it an indispensable tool for enhancing productivity. As you engage more with Wave, you'll discover even greater efficiencies and insights that can transform the way you work.
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
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
wave
Country
United States
Website
thatswave.com/login
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)