{"id":61453,"date":"2022-02-03T07:00:22","date_gmt":"2022-02-03T06:00:22","guid":{"rendered":"https:\/\/www.clickworker.com\/general\/grosse-unternehmen-kuenstliche-intelligenz\/"},"modified":"2022-12-09T13:04:42","modified_gmt":"2022-12-09T12:04:42","slug":"big-players-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.clickworker.com\/customer-blog\/big-players-artificial-intelligence\/","title":{"rendered":"How the Big Players Are Deploying AI"},"content":{"rendered":"

\"Big<\/p>\r\n\r\n

While the last couple of years has undoubtedly been difficult for all types of businesses, it didn’t slow down development within the artificial intelligence (AI)<\/a> and machine learning (ML)<\/a> space<\/p>\r\n

According to IDC<\/a>, as much as 65% of organizations have accelerated the use of digital technologies this year. In this case, technologies like AI will transform existing business processes to boost employee productivity, drive customer engagement, and enhance business resiliency.<\/p>\r\n\r\n\r\n\r\n

This is hardly unexpected because AI and its subset ML is a big deal. As such, companies continue to invest heavily in this technology. It comes as no surprise that the industry giants are leading the way.<\/p>\r\n

Data is the lifeblood of companies like Amazon, Facebook, and Google, which run their operation almost entirely online. So, they have the most data and can profit the most from it if they use their data and smart algorithms wisely.<\/p>\r\n

With these oceans of data, for example, they can come up with new products and services that we never imagined before, improve customer engagement, or optimize processes to boost efficiency. All this together gives tech giants a competitive advantage in the marketplace.<\/p>\r\n

They are at the frontlines as they deal with larger volumes of data and have the necessary resources to research and innovate. So, what exciting products and services are they building with AI? How will it transform their businesses and the industry as a whole?<\/p>\r\n

We all know about AI’s role in placing ads in Google Search and YouTube, translations<\/a>, and how Amazon uses smart algorithms to power product recommendations. How else are the big players using AI, ML, and deep learning (DL) <\/a> to transform their offerings? Let’s dive right in.<\/p>\r\n

Facebook’s Anticipative Video Transformer<\/h2>\r\n

Last October, Facebook (nka Meta)<\/a> announced the release of their new ML-process, anticipated video transformer or AVT. This cutting-edge technology can predict future actions purely based on visual interpretations.<\/p>\r\n

This is a progression of the company’s projects dedicated to smart algorithms that continuously train<\/a> using publicly available videos. As such, AVT follows an end-to-end attention-based model that is a new model driven by recent breakthroughs in transformer architectures.<\/p>\r\n

This is especially true in natural language processing (NLP) and image modeling for apps ranging from augmented reality (AR) to connected self-driving vehicles.<\/p>\r\n

It works by analyzing activity and predicting the possible result. As such, the company plans to leverage this technology to work across apps in its metaverse. It will also enable access to others through APIs that communicate with each other.<\/p>\r\n

Based on the vision transformer (VIT) architecture, AVT splits the frame into patches that don’t overlap. It then embeds them with a feedforward network and appends a classification token. This is then applied to various layers of multi-head self-attention.<\/p>\r\n

The head architecture can take pre-framed features and then apply another transformer architecture with casual attention. By doing so, this model can depend on only past features when generating a new representation of any of these individual frames.<\/p>\r\n

Going forward, expect to see AVT in AR tools, AI assistants, and more. We can also expect to see similar technologies follow suit.<\/p>\r\n\r\n

Tip:<\/strong><\/p>\r\n\r\n

AI projects are only as successful as the training datasets available to them. So, if you need an extensive dataset to train your ML and DL algorithms, look no further than clickworker. Whether it\u2019s audio, video, or photo and image datasets<\/a>, our Clickworkers are available to power your next project.\r\nGet more information about the clickworker solution service<\/b><\/p>Datasets for Machine Learning<\/a><\/blockquote>\r\n\r\n\r\n

Google’s Vertex AI, CCAI, and DocAI<\/h2>\r\n

Last May, Google<\/a> released Vertex AI, a comprehensive platform for all your favorite ML tools. It was a significant release as Vertex AI helps data teams quickly build, deploy, and maintain multiple ML models.<\/p>\r\n

What exactly is Vertex AI? At its most basic, Vertex AI uses AI-driven pipelines to build Auto-ML classification end-to-end workflows. This approach helps optimize reinforcement learning and more.<\/p>\r\n

Unlike older competing platforms that demand at least 80% fewer lines of code to train a model, Vertex AI enables machine learning operations (MLOps)<\/a>. It’s also an excellent solution for ML veterans and beginners alike.<\/p>\r\n

Google Cloud’s Contact Center AI (CCAI)<\/a> helps enterprises, especially call centers with limited AI capabilities, discover insights about their customer and partner from relationships and interactions. It also allows organizations to deploy virtual agents that behave and chat naturally.<\/p>\r\n

Document AI (DocAI)<\/a>, on the other hand, takes the guesswork and physical labour out of document processing. This means it helps teams better understand and capture data in documents to optimize and streamline workflows.<\/p>\r\n

Apple’s AI-Powered Apps<\/h2>\r\n

It’s safe to say that anyone who has owned an Apple device has come in direct contact with intelligent algorithms. Some of the standard AI-powered technologies<\/a> we have come across in iOS, macOS, watchOS, and iPadOS are the following:<\/p>\r\n