If your organization is like many, you have identified numerous generative AI (GenAI) use cases that can positively impact your business. And you’re continuing to discover more.
You’d like to conduct proofs of concept (PoC) for as many use cases as possible. At the same time, you have a limited number of AI-capable developers on your team.
One thing is certain: you don’t want your critical developer resources to be spending time on comparing technology stacks. Rather, their focus needs to be on getting business functionality out to users.
Now, as part of the Dell AI Factory, we’re making it easy to boost AI developer productivity in three easy steps. This approach combines retrieval augmented generation (RAG) on a powerful AI mobile workstation running developer workbench software, with new professional services to make it easy for you to take advantage of this innovative approach. In turn, you’ll deliver more solutions to your business users faster.
Step 1: Start with RAG to Easily Bring AI to Your Data
The first step is to use retrieval-augmented generation, or RAG, to “augment” the language model’s training knowledge by retrieving context-specific data from a vector database. The model combines the retrieved data with its training data to answer the prompt. As an example, a model has been trained on general customer support interactions, which is augmented with a vector database populated from past tickets and cases from a company’s own support history database.
The vector database used in a RAG model is easy to keep up to date with automated processes to regularly load new data, such as new pricing or technical improvements.
Developers have the skills to build RAG PoC projects, whereas data scientists must be added to the team to fine-tune a model. RAG also requires less GPU and CPU memory, storage and compute for inferencing than fine-tuned models.
An additional benefit is that a base model, such as one for a virtual professional assistant, can be applied to multiple use cases by using it with RAG and different vector databases.
Step 2: Add Precision AI-ready Workstations to Make AI Developers More Agile
IT leaders can equip developers with an environment that lets them work quickly with models, vector embedding and RAG. The environment needs to be fast, contain robust developer tools and protect corporate data from outside exposure.
Dell Precision AI-ready workstations have powerful, scalable CPUs and the latest professional NVIDIA RTX™ GPUs to meet the demands of GenAI development. They can simplify deployment and development of complex GenAI workloads out of the box, enabling developers and data scientists to customize and deploy LLMs.
When NVIDIA AI Workbench is added to a Precision workstation, developers get a rich set of tools for data science, machine learning and AI project development. AI Workbench streamlines access to popular repositories like Hugging Face and contains tools for RAG retrieval, model customization, inferencing, moving and scaling workloads, automating workflows and much more.
Step 3: Accelerate Your RAG Momentum with Dell Services
Using RAG with a compact language model and vector database simplifies generative AI development projects. Equipping developers with Dell Precision AI-ready workstations with NVIDIA AI Workbench further reduces complexity.
To accelerate your GenAI projects even more, Dell is introducing Accelerator Services for RAG on Precision AI-ready workstations. This service helps customers jumpstart their journey into GenAI. We provide a ready-to-use mobile lab as a convenient, cost-effective way for customers to explore use cases and improve skills in a low-risk environment. This mobile lab not only enables developers to experiment with and investigate GenAI, but also is an ultra-convenient way to demonstrate the effectiveness and outcomes of GenAI.
Expert consultants will set up a GenAI lab on a mobile Precision workstation and implement a RAG use case with your data. The service includes installation and configuration of NVIDIA AI Workbench. Dell transfers knowledge to your team throughout the process so that each developer is prepared to take on new projects.
Start Exploring Your Use Cases Today
According to IDC, two-thirds of businesses will leverage GenAI and RAG to power domain-specific, self-service knowledge discovery by 2025, improving decision efficiency by 50%.
Dell solution engineering and NVIDIA AI Workbench make it easy to develop GenAI solutions on Dell Precision workstations and then deploy them on a full range of Dell infrastructure—AI servers in the datacenter or at the edge, or in a private cloud.
Experiment with more of your backlog of use cases faster. You’ll deliver solutions to business users sooner, and your AI developers will swiftly ramp up their proficiency.
Source: dell.com
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