Ingest

Leverage data and artificial intelligence (AI) as a competitive advantage.

[Ingest @ingestai_io]

1. Introduction

Artificial Intelligence (AI) is expected to contribute approximately $15.7 trillion to the global economy by 2030, according to a recent study by PwC. As AI continues to play a crucial role in various domains, Generative AI and Large Language Models (LLM) have emerged as a powerful building block in creating AI-powered applications capable of generating enormous business value and generative AI is the key element in these kinds of applications.

[Ingest @ingestai_io]

2. Problem

Although assessment metrics are clearly defined and intrinsic metrics are normally assessed almost instantly when an LLM model is released, there’s no available tools (open-source or proprietary) that enable developers to seamlessly make task-specific (intrinsic) assessments on their unique data. The only solution close to it is the LangChain LangSmith, which is still in closed beta and is not mature enough to provide comprehensive extrinsic metrics that are essential for adoption.

[Ingest @ingestai_io]

3. Solution

To address this challenge of reliability, we (IngestAI Labs) have developed Deepmark AI - a benchmarking tool that enables assessment of large language models (LLM) on various extrinsic (task-specific) metrics on your own data. It has pre-built integration with leading Generative AI APIs such as GPT-4, Anthropic, GPT-3.5 Turbo, Cohere, AI21, and others.

[Ingest @ingestai_io]

2. Problem

Although assessment metrics are clearly defined and intrinsic metrics are normally assessed almost instantly when an LLM model is released, there’s no available tools (open-source or proprietary) that enable developers to seamlessly make task-specific (intrinsic) assessments on their unique data. The only solution close to it is the LangChain LangSmith, which is still in closed beta and is not mature enough to provide comprehensive extrinsic metrics that are essential for adoption.

[Ingest @ingestai_io]

1. Introduction

Artificial Intelligence (AI) is expected to contribute approximately $15.7 trillion to the global economy by 2030, according to a recent study by PwC. As AI continues to play a crucial role in various domains, Generative AI and Large Language Models (LLM) have emerged as a powerful building block in creating AI-powered applications capable of generating enormous business value and generative AI is the key element in these kinds of applications.