Imagine your business is an ocean. Under the surface, a rich ecosystem of processes, people, and technology needs to work together to create a healthy environment. Above the surface, constant waves can make or break your business, either propelling you to new opportunities or sinking you under pressure.
ChatGPT has taken the world by storm. Apps powered by large language models (LLMs) have suddenly taken center stage, with OpenAI, Google, Baidu, and Microsoft getting into the act. A spurt of startups and use cases has emerged on the scene. Suddenly, Generative AI, a branch to which these LLMs belong, seems to dominate every conversation, not just in the technology industry but among professionals the world over.
Artificial intelligence (AI) promises outsized gains in business efficiency. And since organizations live or die by their processes, integrating AI into the picture through AI process optimization can help boost ROI with end-to-end process automation and enhancements. This blog will explore five ways AI can be used to improve and optimize process efficiency. But first, let’s explain what AI process optimization means.
We recently rolled out our very own GPU autoscaler in Collaboration with Genesis Cloud and it has been quite a success. Also recently, YOLOv8 by Ultralytics was unveiled, the new king of object detection, segmentation and classification. In this blogpost we’ll see that you can train a computer vision model using the ClearML/Genesis Cloud autoscaler at a fraction of the cost of competing cloud services like AWS or GCP. And it even runs 100% off of green energy! 😎
The insurance industry has always been one of the most data-intensive industries. With a large amount of customer data, claims data, and other information, insurers have been adopting artificial intelligence (AI) to streamline their processes and provide better customer experiences. AI-powered technologies have enabled insurers to automate claims processing, fraud detection, and underwriting, among other things. Here are six top use cases of AI for insurance.
Artificial intelligence (AI) has become increasingly important as organizations use it to drive innovation, enhance efficiency, improve decision making, and boost digital transformation efforts. But ensuring success requires significant, ongoing efforts. Consider setting up an AI center of excellence (CoE) to boost the success of your AI initiatives.
ChatGPT has taken the world by storm. A simple interface is now being used by everyone and for everything. If you are in IT, I am sure not just your colleagues, but folks from your family that do not belong to the IT world are also talking about it. ChatGPT registered 13 million users per day in January. In comparison, it took Instagram and TikTok 2.5 years and 9 months, respectively, to reach 100 million users on their respective platforms.
As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics. ChatGPT is an excellent resource for gaining high-level insights and building awareness of any technology. However, caution is necessary when delving deeper into a particular technology.
“Software is eating the world” and “APIs are eating software” have become familiar proclamations across the modern-day software industry. Given the resounding hype, interest, and substantial monetary investments happening in Artificial Intelligence (AI), a likely follow-on statement is, “AI is eating APIs, software, and everything else!”
Open AI developed Chat GPT, an auto-generative technology for AI chatbots to use in providing online customer support. It employs Natural Language Processing (NLP) and has been trained to generate conversational responses. Textbooks, webpages, and other materials serve as its data source, from which it models its own language for reacting to human contact. When it comes to the IT sector, software testing is one area where Chat GPT is predicted to thrive.
2023 is looking likely to be a breakout year for artificial intelligence (AI) and machine learning (ML). Some industry-watchers predict that recent breakthroughs in AI might lead to a new revolution in society akin to the industrial revolution, the invention of the internet, or the advent of the smartphone. Yet, 2023 doesn’t mark the invention of AI—just the year it went viral thanks to OpenAI’s ChatGPT technology.
Unlike traditional debugging tools, which can be complex and require specific knowledge of the programming language, ChatGPT is accessible to programmers of all levels and works in any language. Simply ask ChatGPT specific questions about error messages or unexpected behavior and you’ll get a reply with relevant information that can help you identify and fix the issue.
Jasper is an automated content generation platform that uses AI technology to produce unique, human-like content for your website or social media campaigns. It’s one of the most popular tools for writing copies. Hundreds of people have used this tool and are pretty happy with it. The primary purpose of this software is to make your content better.
Today we’re excited to announce ThoughtSpot Sage, our new search experience that combines the power of GPT’s natural language processing and generative AI capabilities with the accuracy and security of our patented self-service analytics platform. With this new integration, data teams will be able to exponentially increase their impact across an organization as business users self-serve personalized, actionable, and trustworthy insights like never before.
Elements of the Google Data Cloud including BigQuery, DataFlow, and Vertex AI are behind Glean’s personalized enterprise search platform.
Artificial intelligence (AI) and machine learning (ML) bring significant efficiency gains to organizations and should play critical roles in any digital transformation efforts. One major use case for these technologies is AI document processing, also known as intelligent document processing (IDP). Organizations amass a large number of business documents—from invoices in billing departments to medical coding documents at hospitals.
