CRM

Speech recognition has been successfully depolyed on various smart devices, and is changing the way we interact with them. Traditional phonetic-based recognition approaches require training of separate components such as pronouciation, acoustic and language model. Since the models are all trained separately with different training objectives, improving one of the components does not necessarily lead […]

Learning to answer open-ended questions about images, a task known as visual question answering (VQA), has received much attention over the last several years. VQA has been put forth as a benchmark for complete scene understanding and flexible reasoning, two fundamental goals of AI. But, apart from accurate answers, what would these milestones look like

When humans generate novel neural architectures, they go through a surprisingly large amount of trial and error. This holds true almost regardless of how much experience in deep learning that person might have! In an optimal world, the neural networks themselves would explore potential architectures and improve themselves over time. Without human intuition and insights

Published: April 2, 2018 This is part two of a two-part series about how to build ethics into AI. Part I focused on cultivating an ethical culture in your company and team, as well as being transparent within your company and externally. In this article, I will focus on mechanisms for removing exclusion from your

Published: March 27, 2018 This is part one of a two-part series about how to build ethics into AI. Part one focuses on cultivating an ethical culture in your company and team, as well as being transparent within your company and externally. Part two focuses on mechanisms for removing exclusion from your data and algorithms.

Introduction Deep learning has significantly improved state-of-the-art performance for natural language processing tasks like machine translation, summarization, question answering, and text classification. Each of these tasks is typically studied with a specific metric, and performance is often measured on a set of standard benchmark datasets. This has led to the development of architectures designed specifically

Having a consistent sales pipeline can be a headache for small businesses. Fortunately, artificial intelligence (AI) is your golden ticket because wherever there’s a will, there’s AI. Surveys show that 80% of salespeople using generative AI reports improved email efficiency and 70% are analyzing AI-powered market data to target potential customers effectively. Welcome to the

Delivering an exceptional customer experience hinges on unifying interactions across every touchpoint. Yet, many brands struggle with fragmented data spread across systems, channels, and clouds. Salesforce Data Cloud solves this challenge by ensuring a consistent customer data sync across all platforms. This allows brands to deliver personalized experiences in real time, no matter how or

Are disconnected tools and scattered data making it hard to close deals, maintain a clear view of your customers, and effectively leverage AI? The solution is tech consolidation. By focusing on an integrated, AI-powered CRM, your company can unlock powerful insights, reduce redundancies, and increase productivity.  Here’s how to get started: Build a solid foundation