CRM

Use the LLM Open Connector to Build Generative AI Solutions Using Your Preferred Models and Platforms

LLMs are evolving rapidly, and within the enterprise space, organizations are iterating on their AI strategies by using different model providers and platforms to address their unique use cases. We launched BYO LLM earlier in 2024 to give customers the ability to connect their own models, hosted on OpenAI, Microsoft Azure, Google Vertex AI, or

Use the LLM Open Connector to Build Generative AI Solutions Using Your Preferred Models and Platforms Read More »

Agentforce for Nonprofits and Higher Education: What You Need to Know

When it comes to innovation, Cloud for Good has always been on the front lines. We’ve been a part of Salesforce’s Nonprofit and Education Cloud Design Partner group and are among the first to see the newest products, features, and enhancements in action. We’re consistently looking at how the latest and greatest innovations can be

Agentforce for Nonprofits and Higher Education: What You Need to Know Read More »

How Agents Can Take Smarter Actions With Prompt Builder

Agentforce is now generally available, empowering enterprises to build, customize, and deploy autonomous and assistive artificial intelligence (AI) agents. This technology helps you foster both customer and employee success. But where does Prompt Builder fit in? Does Agentforce replace Prompt Builder? Should you bypass prompt creation and dive straight into build agents? We’ll show you

How Agents Can Take Smarter Actions With Prompt Builder Read More »

Who Is an Agentblazer?

You’ve heard about AI agents that can take on tasks and innovate at companies in ways we never thought possible. But what can they do for you? How can they save your company money and make your operations more efficient? How will they shape the future? If you’re asking these questions, you’re an Agentblazer. And

Who Is an Agentblazer? Read More »

Dynamic Memory Networks for Visual and Textual Question Answering

Neural network architectures with memory and attention mechanisms exhibit certain reasoning capabilities required for question answering. One such architecture, the dynamic memory network (DMN), obtained high accuracy on a variety of language tasks. However, it was not shown whether the architecture achieves strong results for question answering when supporting facts are not marked during training

Dynamic Memory Networks for Visual and Textual Question Answering Read More »

MetaMind Neural Machine Translation System for WMT 2016

Neural Machine Translation (NMT) systems, introduced only in 2013, have achieved state of the art results in many MT tasks. MetaMind’s submissions to WMT ’16 seek to push the state of the art in one such task, English→German newsdomain translation. We integrate promising recent developments in NMT, including subword splitting and back-translation for monolingual data

MetaMind Neural Machine Translation System for WMT 2016 Read More »