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Updated by Charles Bystock on 10/07/2023
GenAI

There’s little doubt left for enterprise companies — it’s time to get on board with generative artificial intelligence (GenAI). But even with doubt off the table, business leaders are still wrestling with the remaining question: how to get on board. It’s one thing to play with a few GenAI products; it’s another to integrate them into the fabric of your IT infrastructure. What would training look like? What are the unique and specific use cases teams need to be in the loop in on? How can managers know what’s working and adapt?

We have some answers.

As organizations look to capitalize on an emerging GenIT infrastructure, it’s important to have a clear understanding of current software tools and frameworks for implementing it. To get started, it helps to work with an IT partner capable of handling a full-scale rollout.

Software tools for deploying GenAI

The question of integrating GenAI into company operations often comes down to what needs to be done and which tools can do it. Before making any decisions, it’s important to broadly understand the variety of GenAI models and their capabilities.

  • Text-generation models produce text, including articles, code, and scripts. Examples of text-generation models include GPT-4, Bard, and LaMDA.
  • Image-generation models are appropriately named for their ability to generate visual renderings. Examples of image-generation models include DALL-E 2, Imagen, and Parti.
  • Audio-generation models can create music, speech, and sound effects. Examples of audio-generation models include Jukebox, MuseNet, and VQ-VAE.
  • Video-generation models produce realistic videos of people, places, and events. Examples of video-generation models include Imagen Video and Parti Video.

Too often, stakeholders see GenAI through the lens of existing apps and use cases rather than through the capabilities of the technology. A good vendor will have relatable examples and the ability to showcase the potential of GenAI as a tool.

GenAI implementation frameworks

GenAI implementation frameworks

You’ll also want a roadmap for deployment. Building a GenIT infrastructure is only possible through the successful integration of GenAI models. That means exploring key implementation frameworks and their compatibility within the existing IT infrastructure. Here are a few:

  • TensorFlow: This JavaScript library for training and deploying machine learning models can be used to implement generative AI models in the browser.
  • PyTorch Lightning: This Python library makes it easier to train and deploy machine learning models. It can be utilized to implement generative AI models in Python.
  • JAX: A high-performance numerical computation library for Python, JAX also can help implement GenAI models in Python.
  • Diffusers: This Python library simplifies the training and deployment of diffusion models. It can generate images, text, and other types of data.

Again, supportive vendors will offer a path to implementation, including a focus on meeting the organization’s needs with turnkey solutions designed with a future-focused architecture in mind.

The value of an IT service partner

Partnering with a proficient IT service provider offers immense value to any organization integrating advanced GenAI technologies into its operations. A GenIT-focused provider can save considerable time and resources compared to developing and deploying these technologies with an in-house team.

A good GenIT partner can also help assess a company’s needs and choose the right generative AI tools and frameworks for a specific implementation. Your partner’s experience and support can assist with implementation at scale, which is key for enterprise organizations with multifaceted integration considerations.

GenIT is a team effort

The shift to GenIT is a team effort

It’s important to note these tools and frameworks are still evolving and may not always produce perfect results. So it’s essential to have a reliable IT partner on your side. They’ll help with troubleshooting and modifying deployments so they meet the expectations of each unique use case.

As generative AI continues to develop, organizations can expect to see even more innovative tools and frameworks emerge in the future — along with new capabilities that will revolutionize the enterprise IT infrastructure. With that in mind, you can see it’s critical that your IT partners keep up with the latest tools and technology. After all, when they’re on top of their game, you can stay on top of yours and scale your business for the future.

Learn more about the importance of having a good IT partner for implementing GenAI at windzr.com.