Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The software is developed and maintained by a team of highly skilled and seasoned programmers who possess extensive experience in the shipping industry. This module is specifically crafted to efficiently calculate and estimate voyages in a quick and user-friendly manner, accommodating all forms of voyage estimation. It utilizes either the FIFO or Average method to compute the costs associated with fuel supply. Moreover, it generates reports that analyze voyages and juxtapose estimated figures against actual calculations. Another vital component, the Crew module, focuses on the adaptable management of onboard human resources. It actively tracks certificates and their validity for vessels, sending timely reminders before expiration dates. Additionally, it updates the Crew List for every ship, monitoring the status of crew members—indicating who is proposed or rejected and when individuals are ready for their next embarkation. We consistently employ best practices and, when necessary, re-engineer existing workflows to guarantee that our solutions provide a competitive edge while facilitating effective cost management. This approach not only enhances operational efficiency but also contributes to a more streamlined decision-making process.
Description
Voyage AI has unveiled voyage-code-3, an advanced embedding model specifically designed to enhance code retrieval capabilities. This innovative model achieves superior performance, surpassing OpenAI-v3-large and CodeSage-large by averages of 13.80% and 16.81% across a diverse selection of 32 code retrieval datasets. It accommodates embeddings of various dimensions, including 2048, 1024, 512, and 256, and provides an array of embedding quantization options such as float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With a context length of 32 K tokens, voyage-code-3 exceeds the limitations of OpenAI's 8K and CodeSage Large's 1K context lengths, offering users greater flexibility. Utilizing an innovative approach known as Matryoshka learning, it generates embeddings that feature a layered structure of varying lengths within a single vector. This unique capability enables users to transform documents into a 2048-dimensional vector and subsequently access shorter dimensional representations (such as 256, 512, or 1024 dimensions) without the need to re-run the embedding model, thus enhancing efficiency in code retrieval tasks. Additionally, voyage-code-3 positions itself as a robust solution for developers seeking to improve their coding workflow.
API Access
Has API
No
API Access
Has API
No
Integrations
Elasticsearch
No
Milvus
No
Qdrant
No
Vespa
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Action Pc
Founded
2006
Country
Greece
Website
www.actionseas.gr
Vendor Details
Company Name
MongoDB
Founded
2007
Country
United States
Website
blog.voyageai.com/2024/12/04/voyage-code-3/
Product Features
Shipping
Air Shipping
No
Bills of Lading
No
Container Shipping
Yes
Freight Shipping
Yes
Ground Shipping
No
Import / Export
Yes
Ocean Shipping
Yes
Parcel Shipping
No
Quotes / Estimates
No
Shipment Tracking
No
Warehouse Management
Yes