{"id":94838,"date":"2023-03-25T13:54:20","date_gmt":"2023-03-25T06:54:20","guid":{"rendered":"http:\/\/www.thestorythailand.com\/?p=94838"},"modified":"2023-03-25T13:54:51","modified_gmt":"2023-03-25T06:54:51","slug":"beyond-chatgpt-the-future-of-generative-ai-for-enterprises","status":"publish","type":"post","link":"https:\/\/www.thestorythailand.com\/en\/beyond-chatgpt-the-future-of-generative-ai-for-enterprises\/","title":{"rendered":"Beyond ChatGPT: The Future of Generative AI for Enterprises"},"content":{"rendered":"\n

ChatGPT, while cool, is just the beginning; enterprise uses for generative AI are far more sophisticated.<\/p>\n\n\n\n

Venture capital firms have invested over US$1.7 billion in generative AI solutions over the last three years, with AI-enabled drug discovery and AI software coding receiving the most funding. <\/p>\n\n\n\n

Early foundation models like ChatGPT focus on the ability of generative AI to augment creative work, but we expect more than 30% of new drugs and materials to be systematically discovered using generative AI techniques by 2025 \u2013 up from zero today. And that is just one of numerous industry use cases.<\/p>\n\n\n\n

Uses cases for generative AI<\/h3>\n\n\n\n

Generative AI can explore many possible designs of an object to find the right or most suitable match. It not only augments and accelerates design in many fields, it also has the potential to \u201cinvent\u201d novel designs or objects that humans may have missed otherwise. <\/p>\n\n\n\n

Marketing and media are already\u00a0feeling the impacts of generative AI<\/a>. Gartner predicts that 30% of outbound marketing messages from large organizations will be synthetically generated by 2025, up from less than 2% in 2022. In addition, a major blockbuster film will be released by 2030 with 90% of the film generated by AI (from text to video).<\/p>\n\n\n\n

– NVIDIA GTC 2023 to feature latest advances in AI Computing Systems and industrial metaverse<\/a><\/p>\n\n\n\n

Still, AI innovations<\/a> are generally accelerating, creating numerous use cases for generative AI in various industries.<\/p>\n\n\n\n

1. Drug Design<\/strong><\/p>\n\n\n\n

Generative AI has already been used to design drugs for various uses within months, rather than years, offering pharma significant opportunities to reduce both the costs and timeline of drug discovery.<\/p>\n\n\n\n

2. Material Science<\/strong><\/p>\n\n\n\n

Generative AI is impacting the automotive, aerospace, defense, medical, electronics and energy industries by composing entirely new materials targeting specific physical properties.<\/p>\n\n\n\n

The process, called inverse design, defines the required properties and discovers materials likely to have those properties rather than relying on serendipity to find a material that possesses them. The result is to find, for example, materials that are more conductive or greater magnetic attraction than those currently used in energy and transportation \u2014 or for use cases where materials need to be resistant to corrosion.<\/p>\n\n\n\n

3. Chip Design<\/strong><\/p>\n\n\n\n

Generative AI can use reinforcement learning (a machine learning technique) to optimize component placement in semiconductor chip design (floorplanning), reducing product-development life cycle time from weeks with human experts to hours with generative AI.<\/p>\n\n\n\n

4. Synthetic data<\/strong><\/p>\n\n\n\n

Generative AI is one way of creating synthetic data<\/a>, a class of data that is generated rather than obtained from direct observations of the real world. This ensures the privacy of the original sources of the data that was used to train the model. For example, healthcare data can be artificially generated for research and analysis without revealing the identity of patients whose medical records were used to ensure privacy.<\/p>\n\n\n\n

5. Parts design<\/strong><\/p>\n\n\n\n

Generative AI enables industries, including manufacturing, automotive, aerospace and defense, to design parts that are optimized to meet specific goals and constraints, such as performance, materials and manufacturing methods. Automakers, for example, can use generative design to innovate lighter designs \u2014 contributing to their goals of making cars more fuel efficient.<\/p>\n\n\n\n

Embedding the right technologies<\/h3>\n\n\n\n

Most AI systems today are classifiers, meaning they can be trained to distinguish between images of dogs and cats. Generative AI systems can be trained to generate an image of a dog or a cat that doesn’t exist in the real world. The ability for technology to be creative is a game changer.<\/p>\n\n\n\n

Generative AI enables systems to create high-value artifacts, such as video, narrative, training data and even designs and schematics.\u00a0<\/p>\n\n\n\n

– Amity launches new product with ChatGPT\u2019s technology to empower Thai businesses<\/a><\/p>\n\n\n\n

Generative Pre-trained Transformer (GPT), for example, is the large-scale natural language technology that uses deep learning to produce human-like text. The third generation (GPT-3), which predicts the most likely next word in a sentence based on its absorbed accumulated training, can write stories, songs and poetry, and even computer code \u2014 and enables ChatGPT to do your teenager\u2019s homework in seconds.<\/p>\n\n\n\n

Beyond text, digital-image generators, such as DALL\u00b7E 2, Stable Diffusion and Midjourney, can generate images from text. <\/p>\n\n\n\n

Don\u2019t forget the risks<\/h3>\n\n\n\n

Before you forge full-speed ahead, remember that generative AI doesn\u2019t just present opportunities for business, the threats are real too<\/a>. Some examples include the potential for deepfakes, copyright issues and other malicious uses of generative AI technology to target your organization.<\/p>\n\n\n\n

Work with security and risk management leaders to proactively mitigate the reputational, counterfeit, fraud and political risks that malicious uses of generative AI present to individuals, organizations and governments.<\/p>\n\n\n\n

Also consider implementing guidance on the\u00a0responsible use of generative AI<\/a>\u00a0through a curated list of approved vendors and services, prioritizing those that strive to provide transparency on training datasets and appropriate model usage, and\/or offer their models in open source.<\/p>\n\n\n\n

Article by Brian Burke, Research VP for Technology Innovation at Gartner<\/em><\/p>\n\n\n\n

mu Space and OneWeb partner to distribute OneWeb capacity in mainland Southeast Asia<\/a><\/p>\n\n\n\n

REDPAPER reveals three real estate megatrends for Thailand<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

ChatGPT, while cool, is just the beginning; enterprise uses for generative AI are far more sophisticated.<\/p>\n","protected":false},"author":8,"featured_media":94828,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[118,122,667],"tags":[16761,17969,6603],"class_list":["post-94838","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-the-story-special","category-technology-en","category-columnist-en","tag-chatgpt-2","tag-generative-ai-2","tag-gartner-2"],"yoast_head":"\nBeyond ChatGPT: The Future of Generative AI for Enterprises - The Story Thailand<\/title>\n<meta name=\"description\" content=\"ChatGPT, while cool, is just the beginning; enterprise uses for generative AI are far more sophisticated.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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