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Meet ChatGPU: Inference.ai Launches Generative AI-Powered Bot to Eliminate Guesswork in Buying GPU

Inference.ai, a leading provider of GPU’s (Graphics Processing Unit) for the AI revolution, announces the launch of ChatGPU, a new tool to help bring clarity around purchasing GPUs for AI training and inferencing. Inference.ai’s generative AI-powered chatbot asks users simple questions about their product concept to help identify the computing power needed, then suggests the perfect GPU setup to bring their AI vision to life. Inference.ai’s new bot offers a unique solution that adds transparency to the buying process, giving technical decision-makers confidence that they are investing in the correct infrastructure. ChatGPU is currently in beta testing and will be improved with more features as the user base grows.

In the current GPU market, the buying process offers little in the way of certainty – buyers don’t necessarily know exactly what they need or if the GPU will even be available to them. With an industry-wide shortage of chips, combined with the sheer variety of GPUs on the market, technical decision-makers have no way to test if their investment will meet or exceed their needs before they buy. As a result, they are left unsure of what chips they want, how many they need, or how long it’ll take to train their application on the chips they can get.

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“You would never buy a car without test-driving it, but that’s what’s happening with GPUs,” said John Yue, CEO and co-founder of Inference.ai. “People are buying two-year GPU commitments based on blind guesswork for how much processing power they need, and GPUs are much more expensive than a car. Our solution makes it clear exactly what GPU is needed before they spend anything.”

How ChatGPU Works

ChatGPU guides users through the end-to-end process of GPU sourcing – from discovery to purchase. The step-by-step process for users entails:

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  1. Users describe the AI product they want to create in plain English to ChatGPU.
  2. ChatGPU asks users questions about the project, such as if the AI product requires computing power for training from scratch, operates based on an existing model, or is set to inference.
  3. Based on the computational requirements, budget, scalability needs, software compatibility, and timeline, ChatGPU narrows the list of GPUs and provides a recommendation on which GPUs the company should invest in.
  4. Once the user and ChatGPU have fully detailed the product requirements, Inference.ai connects with the shopper to the sales team to handle payment and deployment.

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Experienced developers can be detailed, complex, and exact in describing their product idea and workflow with ChatGPU. For those less experienced with the technical side, Inference.ai’s bot lowers the barrier to entry: ChatGPU guides users through the selection process, offering suggestions to uncertainties and asking clarifying questions about the product goals.

For example, a user can tell ChatGPU that their company wants to create an AI software that uses LLMs to draw pictures for a comic book. ChatGPU asks for specific information about the training requirements for the model, such as the number of pages at which specific resolution or the total file size of information the AI will be trained on. Once answered, ChatGPU can then recommend the right GPU model and quantity.

“Our goal is to make it easy for anyone to create the AI products of their dreams, without having to worry about making mistakes with their infrastructure investments,” continued Yue. “Guesswork should never be the foundation of your company’s future.”

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[To share your insights with us as part of editorial or sponsored content, please write to sghosh@martechseries.com]

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