Found a total of 2248 related content
Omdia: Generative AI faces the same challenges as broader AI
Article Introduction:London, UK, March 14, 2023 – Omdia’s latest report “Generative AI Market Landscape 2023” shows that although ChatGPT, StableDiffusion and other generative AI (GenerativeAI) bring to the market The obvious excitement and potential opportunities are real, but generative AI will not solve any of the market challenges facing any type of AI, and generative AI is not a panacea. “Generative AI will not solve the fundamental challenges facing AI – bias, privacy, accountability, consistency and explainability”, Omdi
2023-04-19
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IBM launches basic model for generative artificial intelligence
Article Introduction:The IBM Granite family of foundational models applies generative artificial intelligence to natural language and coding tasks. In addition, Watsonx generative artificial intelligence capabilities will also come to Watsonx data lake. IBM released a generative artificial intelligence basic model and an enhanced version of Watsonx.ai's generative artificial intelligence, improving the capabilities of the Watsonx artificial intelligence and data platform. On September 7, it released the IBM Granite series of multi-size basic models using the "decoder" architecture to Generative AI is applied to language and coding tasks. Supports enterprise NLP (natural language processing) tasks such as summarization, content generation and insight extraction. IBM plans to provide a comprehensive list of data sources and instructions for generating Grani
2023-09-16
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How generative AI is reshaping retail
Article Introduction:Today, there is a strong global interest in generative artificial intelligence. And for good reason. Generative AI is already creating countless new opportunities for retailers and consumer brands. It represents a leap in capabilities because it is both extremely powerful and extremely flexible. It’s this ability to adapt that will help leaders reinvent the way they run their businesses, serve their customers and get their jobs done. Until recently, outside of cutting-edge AI, almost no one had heard of large-scale language models or generative AI. At the end of 2022, OpenAI released ChatCPG. A few months later, companies like Google, Microsoft, and Meta created their own large-scale language models. For retailers, generative AI opens up endless opportunities. For retailers and brands, ask
2023-06-07
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Can generative AI and data quality coexist?
Article Introduction:In this high-tech era, everyone must be familiar with generative artificial intelligence, or at least have heard of it. However, everyone always has concerns about the data generated by artificial intelligence, which has to involve data quality. In this modern era, everyone should be familiar with generative artificial intelligence, or at least have some understanding of it. However, there are still some concerns about the data generated by artificial intelligence, which has also led to discussions about data quality. What is generative artificial intelligence? Generative artificial intelligence is a type of artificial intelligence system whose main function is to generate new data, text, images, audio, etc., rather than just analyzing and processing existing data. Generative artificial intelligence systems learn from large amounts of data and patterns to generate new models with certain logic and semantics.
2024-02-20
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Explore the mutual benefits of generative AI and the cloud
Article Introduction:It’s no coincidence that interest in generative AI and cloud convergence has continued to grow in recent years. Generative artificial intelligence (AI) and cloud computing have revolutionized the IT industry, redefining industries and bringing unprecedented functionality to new technology tools. Let’s take a deeper look at the profound impact of generative AI on cloud computing, and how cloud computing empowers and enhances the capabilities of generative AI. The emergence of generative artificial intelligence has brought new opportunities and challenges to cloud computing. By combining generative artificial intelligence with cloud computing, enterprises can better utilize data resources, improve work efficiency, and accelerate innovation and development. Cloud computing provides efficient computing and storage resources for generative artificial intelligence, allowing it to handle complex tasks and large-scale tasks faster.
2024-02-28
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Seven challenges for learning generative AI
Article Introduction:Generative AI has become a transformative force, pushing the boundaries of what machines can achieve. From text and image generation to creating realistic simulations, generative AI has demonstrated its potential in a variety of fields. As the demand for professionals in the field of generative artificial intelligence continues to increase, the journey to mastering this technology becomes even more challenging. This requires a deep understanding of its complexity and challenges on multiple fronts, including complex model architectures, ethical considerations, and evolving technological competition. Learning generative AI requires overcoming difficulties, but it can also bring excitement and satisfaction. Learners need to constantly keep up with technological developments while responding to changing needs and challenges in order to achieve radical change in this field. 1. Technical complexity and understanding generative artificial intelligence
2024-02-19
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What is generative artificial intelligence, and how is it evolving?
Article Introduction:Generative AI is a general term for any automated process that uses algorithms to generate, manipulate, or synthesize data, often in the form of images or human-readable text. It’s called generative because AI creates something that didn’t exist before. This is how it differs from discriminative AI, which differentiates between different types of input. In other words, discriminative AI tries to answer questions like: “Is this picture a rabbit or a lion?” while generative AI responds “Picture me a picture of a lion and a rabbit sitting together. picture" prompt. Mainly introduces generative AI and its use with popular models such as ChatGPT and DALL-E. We'll also consider the limitations of this technology, including why "too many hands
2023-05-09
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How will generative AI impact the future of work?
Article Introduction:Generative artificial intelligence is Silicon Valley’s new favorite. But what exactly is it? And what does it mean for the future of work for you and me? Experts believe that generative AI will soon enter the workplace, predicting that by 2023, generative AI will be able to combine scientific papers with visual design models Combined, by 2030 it will be able to write, design and code better than human professionals in the field. Yet few of us have a clear idea of how this will play out. How will it all begin? That’s why it’s important to delve into what technology is and isn’t. In the case of the insurance industry, it is believed that generative AI will not knock every creative worker out of their job, but it will change how they do their jobs and where their time and energy will be focused.
2023-04-14
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Generative artificial intelligence is coming, how to protect minors? | Journal of Social Sciences
Article Introduction:The Development of Artificial Intelligence and the Protection of Minors In response to the rapid development of powerful generative artificial intelligence, UNESCO held its first global education ministers meeting on this topic on May 25 this year. Comprehensive and objective analysis of the unprecedented development opportunities and risks and challenges of generative artificial intelligence is an urgent proposition of the times to ensure the healthy growth of minors, and is also a key part of implementing the protection and development of minors. Original text: "Generative Artificial Intelligence is Coming, How to Protect Minors" Author | Beijing Normal University School of Journalism and Communication Fang Zengquan/Researcher Yuanying/Lecturer Qi Xuejing/Assistant Researcher Picture | The top ten scientific breakthroughs in 2022 published by the Internet in "Science" Among them, generative artificial intelligence (AIGC) is impressively listed. Generative AI exhibits
2023-06-12
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35 Generative AI Tools Businesses Should Use in 2023
Article Introduction:2022 is an important turning point in the development of generative artificial intelligence. In this year, more powerful, more accessible, and more applicable large-scale language models such as ChatGPT were launched. While OpenAI’s ChatGPT is just the beginning, cutting-edge generative AI tools have made it the fastest-growing part of the AI field. Businesses and individuals alike are leveraging generative AI to increase productivity and deliver better customer journeys. Generative AI, which primarily falls under the umbrella of machine learning, can be applied across industries to create exciting new content in different formats, including text, audio, code, images, and videos. In addition to generating content, generative AI can be used to create new products
2023-04-27
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How do you predict that generative AI will change the future of work?
Article Introduction:With the recent launch of ChatGPT and the rapid development of generative artificial intelligence, we are currently in the midst of a technological revolution. The resulting impact was earlier and more significant than the introduction of any other new technology. Where and How Work Has Changed As the descendant of cutting-edge large language models (LLMs) like OpenAI’s GPT-4, generative AI is transforming industries and the future of work in ways we couldn’t have imagined just a few years ago. Here are three areas where this is already happening: Creative Industries: The creative industries have long been considered the bastions of human ingenuity and imagination. However, generative AI now demonstrates the ability to be both a collaborator and a creator. AI-generated content, from copywriting and website design to video game music
2023-05-09
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The cost and sustainability of generative AI
Article Introduction:AI is resource intensive for any platform, including public cloud. Most artificial intelligence technologies require a large amount of inference calculations, which collectively require higher processor, network, and storage requirements, and will also result in higher electricity bills, infrastructure costs, and carbon footprints. The rise of generative artificial intelligence systems, taking ChatGPT as an example, has brought the above issues into focus again. Given the widespread adoption of this technology, and its likely large-scale adoption by companies, governments, and the general public, we can see the electricity consumption growth curve taking on a worrying arc. Artificial intelligence technology has been around since the 1970s. Since the work of a mature artificial intelligence system requires a large amount of resources, it did not initially produce much
2023-04-14
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How generative AI is redefining image search
Article Introduction:To rewrite the content without changing the original meaning, the language needs to be rewritten into Chinese, and the original sentence does not need to appear. Review | The content of Chonglou needs to be rewritten. In recent months, generative artificial intelligence has relied on its ability to create unique text, sounds, and The power of images has aroused great interest. However, the potential of generative AI is not limited to creating new data. The underlying technologies of generative AI, such as Transformers and diffusion models, can power many other applications, including the search and discovery of information. In particular, generative AI could revolutionize image search, enabling people to browse visual information in ways that were previously impossible. Here’s what people need to know about how generative AI can redefine the image search experience. images and text
2023-09-29
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The impact of data management on generative AI
Article Introduction:2023 will be the mainstream start of what we remember as the era of artificial intelligence, driven by the technology everyone is talking about: ChatGPT. Generative AI language models like ChatGPT have captured our imaginations as, for the first time, we are able to see AI converse with us like real people and generate prose, poetry, and other new content that we find creative . Generative AI solutions appear to be full of breakthrough potential, enabling faster and better innovation, productivity and time to value. However, their limitations are not yet widely understood, nor are their data privacy and data management best practices. Recently, due to a lack of understanding of the use of artificial intelligence technology and adequate regulatory guardrails, technology
2023-06-07
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How contextualization unlocks the potential of generative AI
Article Introduction:As generative artificial intelligence (GenAI) develops at a rapid pace, contextualization is critical for businesses looking to capitalize on its true value. In just a short period of time, generative AI has gone from science fiction to reality, leaving businesses scrambling to Keep up with its rapid development and identify its practical applications. According to a recent survey, 70% of organizations are exploring ways to leverage this technology, and nearly half (45%) have increased their investment in artificial intelligence (AI) due to the popularity of generative AI. Amid the trend, an important question is: How can companies ensure a strong return on investment and fully leverage the capabilities of generative AI? The answer lies in contextualization. Businesses must provide solutions with broad domain expertise
2023-10-31
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Generative AI: Types, skills, opportunities and challenges
Article Introduction:Generative AI refers to a class of machine learning techniques designed to generate new data that is similar, but not identical, to training data. In other words, generative AI models learn to create new data samples that have similar statistical properties to the training data, allowing them to create new content that has never been seen before, such as images, videos, audio, or text. There are several types of generative AI models, including: Variational Autoencoders (VAEs): VAEs are a generative model that learns to encode input data into a low-dimensional latent space and then decode the latent space back to an output space, to generate new data similar to the original input data, often used for image and video generation. Generative Adversarial Network (GAN): GAN is a generative model that works by making two neural networks (generator and
2023-04-11
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BYOK (Bring Your Own Key) has two sides in generative artificial intelligence
Article Introduction:Original author | Emmanuel Ajala Bring Your Own Key (BYOK) – a concept that promises customizability and controllability stands out in the ever-evolving world of artificial intelligence (AI). While BYOK is often discussed in the context of cloud computing and security, this article will delve deeper into its application in the field of generative artificial intelligence. Unlike traditional AI models where developers use algorithms, BYOK enables users to choose their preferred AI model, providing unprecedented flexibility and personalization capabilities. So let’s embark on this journey into BYOK at the heart of generative artificial intelligence, where personalization meets responsibility. What is BYOK in generative artificial intelligence? In the field of generative artificial intelligence, BringYo
2024-01-26
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Discover how generative AI is transforming the financial services industry
Article Introduction:Generative AI is an emerging field of artificial intelligence focused on creating new content by analyzing patterns in existing data. This cutting-edge technology can generate a wide range of data samples, including text, graphics, code and music. By leveraging large amounts of input data, generative AI algorithms can identify patterns and structures to generate new content that mimics human-like behavior. Its potential to improve accuracy and efficiency has made it increasingly popular in the banking industry. In short, generative AI is a powerful tool that has the potential to change the way we solve problems in various fields, including banking. Value of Artificial Intelligence for Banking The banking industry is witnessing the transformative impact of artificial intelligence as it enables personalized and efficient customer experience. via chatbots, virtual
2023-05-08
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Applying generative artificial intelligence technology to improve the agricultural industry
Article Introduction:The agriculture industry has huge potential to transform due to the potential value perspectives and productivity gains of generative artificial intelligence (AI). Generative AI has the potential to revolutionize many areas of agriculture through complex algorithms and the ability to analyze large amounts of information. The following are some application areas of generative artificial intelligence in agriculture: Crop optimization and prediction: Generative models can analyze large amounts of agricultural data, including soil, climate, crop growth conditions, etc., to predict the best planting time, fertilizer amount and Irrigation scheme. This helps maximize crop yields, reduce waste, and conserve resources. Pest and disease identification and management: Generative artificial intelligence can train identification models for different pests and diseases, and detect and predict potential disease risks in a timely manner by monitoring crop images. this
2023-08-10
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How to achieve accurate coding using generative artificial intelligence
Article Introduction:Generative artificial intelligence (GenAI) has had a major impact on the technology landscape, and its transformative potential is extending to software engineering. With the application of generative artificial intelligence, especially with the help of prompts, the concept of "coders" has become a reality. The technology offers a promising avenue for enhancing the software development process by leveraging its capabilities in natural language processing, intent recognition, and code generation. Generative AI’s ability to generate code that meets high-level requirements is a game-changer. Through extensive requirements analysis facilitated by natural language processing and intent recognition, developers can streamline the process of converting high-level requirements into functional code. Industry-specific training further enhances the capabilities of generative AI, enabling it to
2023-12-15
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