Overview

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Generative AI powered by Large Language Models (LLMs) is the next electricity or Internet (Jamie Dimon 2024; Jensen Huang, 2024). Now is the first inning of the AI industrial revolution. Businesses and government agencies cannot use public LLMs such as ChatGPT with private data because of privacy, security, and safety concerns. Athena AI solves the problems by providing private, secure, and safe enterprise LLMs to understand and reason enterprise unstructured big data like humans. Like ChatGPT, Athena AI can discover new knowledge, connect new and existing knowledge, and retrieve relevant knowledge stories. Athena AI pre-tunes and fine-tunes enterprise LLMs to understand enterprise documents and images. It can then use the enterprise local LLMs to solve the privacy, security, and safety challenges to LLMs enterprise adoption. Athena AI platform is designed as a base platform for customizations in enterprise AI, vision AI, mobile AI, AI safety and security. See Athena AI capabilities and use cases at https://ranty.net , e.g., Parquet Hub, Agents Studio, reading technical charts to predict and validate individual stock trends, chatting with Websites and book authors, Deepfake detection, etc.. See sizable use cases in DOJ, DOL, NIH, CDC. You can create local institutional LLMs: As opposed to sharing LLMs with the public using ChatGPT, Athena platform allows institutions to own local Athena base model files that are accessible in GGUF format (this is not available in cloud providers). The platform's Web UI supports simultaneous responses from multiple LLMs, enabling institutions to compare answers to mitigate potential hallucinations. You can create new local LLMs for institutions by extending Athena base models including DeepSeek-R1.
Highlights
- Create Project AI Assistant with private LLMs and RAG: Accelerate your enterprise projects with a project AI Assistant that delivers accurate insights from your knowledge base via RAG and private LLMs. Find example code at {~/awsrag}. With Athena Web UI for LLMs, you can also create RAG-based private project LLM with your project data for your project's AI assistant.
- Jump start secure GenAI applications on Athena LLM APIs: The platform supports fast local deployment of Athena Video AI Understanding (VAU) for drones and robotics, Athena AI Agents Studio for stock analysts, Athena AI Psychologist etc. The Gen AI application security can be automated to comply with standards such as NIST SP 800-53 rev5. Web: https://ranty.net. Email pnncapitalus@gmail.com.
- Meet AI safety, security and privacy requirements: Athena "test to stop" service (not included) for LLMs uses AI Risk Index (ARI) to quantify AI safety, monitor, test, stop and protect the private LLM services. Athena platform enables institutions to operate on private LLMs as opposed to exposing private (PII HIPPA) data to public LLMs. The platform uses private LLMs to understand data like humans (Big Data 2.0) with RAG (Retrieval-Augmented Generation).
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
RAG code example
Additional details
Usage instructions
- launch AMI - get public IP
- download a .pem file
- ssh -i {.pem file} ubuntu@{IP}
- annual users send email to demo@deepcybe.com for additional support
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Support
Vendor support
Athena Parquet Hub and Agents Studio: launch the Athena LLM Institutions Platform from AWS Marketplace, then send email to pnncapitalus@gmail.com to request the incremental services (https://ranty.net ).
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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