As the contract lifecycle management company Ironclad is today releasing its AI redlining tool AI Assist out of beta, is has revealed that the tool is powered by OpenAI's GPT-4, making it what Ironclad says is the first contract redlining application powered by the latest version of Open AI's generative AI. "The results with AI Assist have been beyond what we could even have imagined," said Ironclad CEO and co-founder, Jason Boehmig. "An initial pass at contract redlining usually takes about 40 minutes. Already, some large enterprises are using Ironclad AI to review over 50% of their incoming contracts, so the compounding business impact there is unprecedented." Although Ironclad says that this is the first redlining tool to use GPT-4, Casetext's CoCounsel, which is built on GPT-4, has capabilities for checking contract policy compliance and suggesting redlines to bring contracts into compliance. It should also be noted that there are other contract redlining tools on the market that use AI, but not GPT-4.

Google and it's very own version of Chatbot Bard is soon to be released to the public. Recently Google AI engineers stated that it's opening up access to Bard, the Google's very own AI-powered chatbot that's a rival to services released by competitor Microsoft and it's OpenAI. Google is starting with users in the US and UK, who can go to the Bard site to sign up for the waiting list. "We've learned a lot so far by testing Bard, and the next critical step in improving it is to get feedback from more people," stated Google's Sissie Hsiao and Eli Collins. Google has announced Bard and the company went into "code red" following the release of the OpenAI's ChatGPT late last year to garner it's own AI Chat.

The AI field took a turn with the release of powerful Generative Artifical Intelligence (AI) models, and as a result, the world is seeing the automation of some skills around creativity and imagination sooner than many expected. For some organizations, Generative AI holds valuable potential for higher order opportunities, like new services and business models. Deloitte offers a method for selecting Generative AI use cases, as well as some next steps for business leaders in the Age of With . Generative AI has captured attention in global media and the public square, prompting questions and discussions around this transformative technology. Businesses, research organizations, and even lay users are experimenting with Generative AI, and given the excitement and interest, it is important to look more closely at the potential capabilities and implications for business.

HIMSS 2023 kicked off Monday in Chicago. Follow our live blog for the latest updates and happenings from the conference. Epic Systems is working with Microsoft to integrate generative AI technology into its electronic health record software for the first time, the companies said Monday. The announcement was made in conjunction with the first day of the HIMSS conference, which is being held in Chicago this week. Health systems using Epic's EHR system will be able to run generative AI solutions through Microsoft's OpenAI Azure Service.

Elon Musk Creates new AI Company to rival OpenAI as Elon Musk announced his plans to enter in the Artificial Intelligence (AI) market of worth more than US$ 125 billion, globally. Since, the global AI market is expected to hit US$ 1,591 billion by 2030 with a registered CAGR of 38.1% from 2022 to 2030, Elon Musk has planned to enter this arena. The boss of world's leading companies like Twitter, Telsa, StarLink, and SpaceX has announced a new venture and as he has registered a company called'X.AI'. It is reveled that the new subsidiary will be the home of efforts to build new AI based tools similar to ChatGPT that is currently owned by OpenAI. To accelerate with X.AI, Musk is reported that he is assembling a team of AI experts and researchers as he is discussing with with investors of SpaceX and Tesla about putting money into this new venture.

DALL-E 2 is an advanced artificial intelligence (AI) model developed by OpenAI that can generate high-quality images from textual descriptions. The model builds upon the success of the original DALL-E, which was first introduced in January 2021. DALL-E 2 is a significant improvement over its predecessor, with the ability to generate images that are larger, more complex, and more realistic than before. In this article, we will explore the technology behind DALL-E 2, its potential applications, and its impact on the field of AI and computer vision. DALL-E 2 is a generative model based on the GPT-3 architecture, which is a state-of-the-art language model developed by OpenAI.

OpenAI CEO confirms ChatGPT not training GPT-5, addresses safety concerns raised by open letter from tech community, Italy establishes task force on ChatGPT. OpenAI, a leading AI research organisation, has developed the ChatGPT programme, which has become immensely popular for its ability to provide quick and comprehensive answers to a wide range of queries. However, its fast expansion has sparked worries regarding its potential effects on employment, privacy, and safety. Recently, an open letter signed by tech giants Elon Musk, Steve Wozniak, and others urged companies to pause the development of AI systems that are more powerful than GPT-4, which was released by OpenAI. The open letter signed by Elon Musk and other researchers called for a halt in the development of AI systems that are more powerful than GPT-4, citing concerns about potential impacts on safety, privacy, and employment.

Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest model developed by OpenAI, GPT-4, was trained using an unprecedented scale of compute and data. In this paper, we report on our investigation of an early version of GPT-4, when it was still in active development by OpenAI. We contend that (this early version of) GPT-4 is part of a new cohort of LLMs (along with ChatGPT and Google's PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models.

Less than a month after debuting its new suite of Firefly generative AI editing tools, Adobe announced Monday that it is already working on a host of upgrades to further empower its users through Creative Cloud video and audio applications. The additions should be coming to Firefly's beta program later this year. Built from the company's long-running AI program, Sensei, Firefly is a suite of generative AI models that can both create and transform audio, video, illustrations and 3D models using text prompts in the same way that Dall-E and ChatGPT do. Firefly's features are already available across Adobe's ecosystem including Premiere Pro, Illustrator, After Effects and Photoshop, though they're currently only accessible through the closed beta program. The new features announced Monday are designed to help professional editors cut down on their drudge work, boosting color levels, inserting placeholder images, adding effects, autonomously recommending b-roll for a given project -- simply by typing their ideas into Firefly's AI text prompt and letting the algorithm do its thing.

Sustainability and generative AI are two topics that are currently taking the world by storm. While they may seem unrelated, there is a significant intersection between the two. A recent study called "Making AI Less Thirsty" reveals just how much water is consumed when training large AI models like OpenAI's ChatGPT and Google's Bard. The study was conducted by researchers from the University of Colorado Riverside and the University of Texas Arlington. It compares and measures the environmental impact of AI training that requires massive amounts of constant electricity and water. The water is used to cool data centers that are essential to keep them running.