Leveraging Quality Engineering to Move the Enterprise Generative AI Needle Forward
Over the years, there has been a growing emphasis on enhancing both the quality of software and the processes used to[...]
Globally, enterprises are working to keep up with current generative AI trends and identify the benefits and practical use cases while addressing risk. They want to know how to avoid possible threats and, at the same time, move quickly toward generative AI technology adoption to remain competitive.
Everest Group is helping business leaders find the needed answers to their questions, so they can uncover the right opportunities determine the best price, and ensure safety.
Enterprises can identify use cases and opportunities to move quickly on generative AI adoption. Everest Group is helping enterprises frame the speed of adoption and effort put in by addressing questions such as:
Business leaders need to consider the risks surrounding generative AI, including data security and privacy, bias and ethics, ownership and responsibility, and explainability. The risk questions we’re currently helping enterprises address include:
Take our Generative AI Risk Assessment to gauge the level of risk associated with adoption.
Utilizing generative AI technology across a wide range of applications can come with a substantial cost. Enterprises have the option to carefully choose specific use cases to ensure a return on investment (RoI). We are helping enterprises with their pricing questions, including:
Service providers can play a significant role in making generative AI adoption more feasible. We’re helping business leaders select the best provider for their needs, answering questions like:
Everest Group is also helping providers investigate questions as they position their services to meet enterprises’ generative AI needs and stay competitive in the market, including:
Over the years, there has been a growing emphasis on enhancing both the quality of software and the processes used to[...]
With the emergence of generative AI models, enterprises are increasingly investing in this technology. Organizat[...]
Since the introduction of ChatGPT, organizations have shown a keen interest in exploring the applications of generative AI across various busines[...]
Large Language Models (LLMs) have revolutionized the field of Artificial Intelligence (AI), driving remarkable achievements across diverse language-related tasks. However, the market is flooded with LLMs, ranging from proprietary off-the-shelf to open-source options. What’s missing is a single, consolidated source of detailed information on these models and a fair and practical framework to assess them.
To address this challenge, we have assessed the most popular LLMs available today so organizations can identify the best one for their needs. For this assessment, we have analyzed 13 popular proprietary and open-source LLMs to help enterprises and service providers across all industries and geographies compare and assess key LLM providers’ offerings.
Our assessment framework evaluates LLMs and rates them according to their ease of adoption and capabilities.
Please select the LLMs you would like to compare.
Capability
Measures the basic ability of an LLM to generate effective outputs; measured through four subdimensions.
Ease of adoption
This variable evaluates the factors that are crucial for enterprise adoption of an LLM through three subdimensions.
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