Innovate faster with enterprise-ready Generative AI

In an era where artificial intelligence is revolutionizing industries, Google Cloud is at the forefront with its cutting-edge Vertex AI. Launched in 2021, Vertex AI has been instrumental in streamlining ML model development and deployment. From feature engineering to model training and low-latency inference, it encompasses all aspects under the vigilant eye of enterprise governance and monitoring. With an impressive clientele including Wayfair, Vodafone, Twitter, and CNA, Vertex AI has been evolving at a rapid pace. The latest update is a game-changer - introducing Generative AI support in Vertex AI, a one-stop solution for teams to exploit an array of generative models. Now, the full spectrum of generative AI is at your fingertips, seamlessly integrated into an end-to-end machine learning platform.

GenAI Workshop

  • Assisting businesses in defining their generative AI strategy by identifying relevant use cases, understanding business objectives, and formulating a roadmap for implementation.

  • Establishing processes and tools for monitoring the performance of generative AI models, addressing potential issues, and providing ongoing maintenance and support.

Related blogs

  • Assessing and implementing robust security measures to protect generative AI models and the data they process, ensuring compliance with privacy regulations.

Introduction to GenAI and VertexAI

GenAI, or Generative AI, is a new type of artificial intelligence that can generate new content, such as text, code, and images, from scratch. VertexAI is a managed machine learning platform from Google Cloud that provides a unified experience for building, training, and deploying ML models.

A review of the ML model garden

The ML model garden is a collection of pre-trained ML models that developers can use to build their own AI applications. The model garden includes models for a variety of tasks, such as image classification, natural language processing, and speech recognition.

How GenAI is being leveraged

GenAI is being leveraged in a variety of ways, including:

  • Creating new content: GenAI can be used to create new text, code, and images from scratch. This can be used to generate new marketing materials, product ideas, and even scientific discoveries.

  • Improving existing content: GenAI can be used to improve existing content, such as by filling in missing information, correcting errors, and making it more engaging.

  • Automating tasks: GenAI can be used to automate tasks that are difficult or time-consuming to do manually, such as writing reports, translating languages, and creating marketing campaigns.

Experimentation on GenAI platforms such as:

  • Develop a conversational AI model: You can use GenAI to develop a conversational AI model that can interact with users in a natural way. This can be used to create chatbots, virtual assistants, and other AI-powered applications that can communicate with humans.

  • Build a speech recognition model: You can use GenAI to build a speech recognition model that can transcribe audio to text. This can be used to create applications such as dictation software, voice search, and closed captioning.

  • Virtual technical discovery, architecture planning and design workshop sessions facilitated by Evonence: Evonence can provide virtual technical discovery, architecture planning, and design workshop sessions to help you get started with GenAI on VertexAI.

  • Deploy code for a sample App Engine application: Evonence can provide you with a sample App Engine application that you can deploy to VertexAI. This application can be used to experiment with GenAI models and serve them to users.

  • Cloning some notebooks into your project for internal experimentation: You can clone notebooks from the Evonence documentation into your own VertexAI project for internal experimentation. This allows you to explore GenAI models and tutorials without having to deploy them to production.

  • Deploying a simple Vertex Search/Conversation app onto the project: You can deploy a simple Vertex Search/Conversation app to your VertexAI project. This app can be used to experiment with GenAI models and serve them to users in a conversational interface.

Our Generative AI Consulting Services

  • Assisting in the development and training of generative AI models using Google's AI tools and frameworks, ensuring optimal performance and accuracy.

  • Evaluating an organization's readiness for generative AI adoption by assessing existing infrastructure, data availability, and organizational capabilities.

  • Supporting the seamless integration of generative AI models into existing systems, applications, or platforms, and facilitating their deployment for real-time use.

  • Providing guidance on data collection, labeling, and preprocessing strategies to ensure the availability of high-quality data for training generative AI models.

  • Analyzing and fine-tuning generative AI models to improve performance, reduce inference time, and optimize resource utilization.

  • Conducting workshops and training sessions to upskill teams on generative AI concepts, tools, and best practices, enabling organizations to leverage the technology effectively.

Work that defines us.

  • Recommending appropriate generative AI models and designing the architecture that best suits the business requirements, considering factors such as performance, scalability, and resource constraints.

  • Providing guidance on ethical considerations and strategies for identifying and mitigating biases in generative AI models, ensuring fairness and inclusivity.

  • Conducting thorough evaluations of generative AI models' performance, identifying areas for improvement, and implementing optimization techniques to enhance their capabilities.