The goal of Jasper’s creators was not to build a wise LLM generalist. Rather, they wanted to create a machine to generate very specific content in a targeted manner.
That’s why Jasper doesn’t offer a ChatGPT-style interface, but instead provides various templates for various tasks – such as real estate offers or product descriptions. The paid versions of this LLM are specifically aimed at companies that value consistent marketing texts.
Claude
With Claude, Anthropic has created a helpful AI assistant that can take on various text-based tasks in the corporate environment – from research to customer service. Anthropic deliberately allows long prompts to encourage more complex instructions and give users more control over the outputs.
Brains
When specialized hardware and general LLM are developed together, a fast and efficient solution can emerge – like Cerebras.
This Large Language Model is available on Hugging Face in a variety of sizes for those who want to run the model locally. However, most users will be interested in the cloud services that run on Cerebras’ integrated wafer-scale processors. They are optimized to sift through large amounts of training data.
Falcon
The Falcon LLM was created at the Technology Innovation Institute in the United Arab Emirates. The large language model was trained using a huge set of general examples from RefinedWeb – with the focus on optimizing inference.
The model was then released with Apache 2.0. Since then, thanks to its open source nature and low restrictions, it has been considered one of the best large language models for experimenting.
ImageBind
Meta is not only a social media giant, but also a force in the field of open source software development. As the AI boom continues, it is no surprise that the company is now sharing many of its in-house innovations with the public. ImageBind is one such project. The Large Language Model aims to prove that AI can also create many different types of data at once – in this case text, audio and video.
Gorilla
You have probably already read one or two articles on the subject of programming with Generative AI. The results are often impressive on the surface – only upon closer inspection does it become apparent how flawed they are: the syntax may be correct, but the API calls are not or refer to a function that does not even exist. Gorilla is a large language model designed to better handle programming interfaces.
The language model is also based on Metas Llama – but was subsequently optimized with a focus on more in-depth programming work. In addition, the team behind the Gorilla LLM also offers a number of its own API-centric benchmarks for testing purposes.
AgentGPT
Another LLM tool that supports developers in their creation is AgentGPT. It was designed to set up agents, which in turn can be used for tasks such as vacation planning or coding.
The source code of the Large Language Model is available (in large parts) under the GPL 3.0 license. AgentGPT is also available as a service.
FrugalGPT
The research team behind FrugalGPT has recognized that the largest and most expensive language models are not always necessary to answer certain questions. Therefore, the tool’s algorithm cascades through an entire list of LLMs until it finds a satisfactory output.
The researchers’ experiments suggest that this cautious approach can save nearly 98 percent of the cost of Large Language Models. (fm)
This article originally appeared at our sister publication Infoworld.com.
