![]() South Korea's telco giant SK Telecom has made a bold move by introducing its own A.I.-powered chatbot into the market - and it could be just the beginning of many such moves within the tech industry in South Korea. This shift could have far-reaching implications for all tech companies operating in South Korea as they look to stay competitive in an increasingly digital world. Rather than relying solely on human agents, companies are now turning to AI-driven solutions that can quickly respond to customer inquiries and solve problems more efficiently than ever before. The introduction of an A.I.-powered chatbot by one of South Korea's biggest telcos signifies a major shift in how tech companies are approaching customer service solutions in the country. What Does This Mean for South Korean Tech? For example, the chatbot can be used to answer questions about mobile plans, help customers find the best deal for their plan, or even provide guided tours of new products and services on offer from SK Telecom. The chatbot uses machine learning algorithms to understand customer inquiries and provide users with immediate answers or services. SK Telecom's A.I.-powered chatbot is designed to provide customers with personalized customer service solutions through natural language processing (NLP). How Does SK Telecom's A.I.-Powered Chatbot Work? What does that mean? Let’s take a look at what SK Telecom is doing with its A.I.-powered chatbot and how this might affect the future of tech in South Korea. chatbot - and they call it a ‘super app’ version of ChatGPT. chatbot out there, think again! South Korea's telco giant SK Telecom has a very own A.I. This could force people using the models to switch to “white-aligned English,” for example, to ensure the models work better for them, or discourage minority speakers from engaging with the models at all.If you thought ChatGPT was the only A.I. And toxic language models deployed into production might struggle to understand aspects of minority languages and dialects. In recent research, the Middlebury Institute of International Studies’ Center on Terrorism, Extremism, and Counterterrorism claims GPT-3 could reliably generate “informational” and “influential” text that might radicalize people into violent far-right extremist ideologies and behaviors. The consequences of failing to take any of these steps could be catastrophic over the long term. Deploying a suite of bias tests to run models through before allowing people to use the model. ![]() Training a separate model that acts as a filter for content generated by a language model.The coauthors of the OpenAI and Stanford paper suggest ways to address the negative consequences of large language models, such as enacting laws that require companies to acknowledge when text is generated by AI - possibly along the lines of California’s bot law. The effects of AI and machine learning model training on the environment have also been raised as serious concerns. Among others, leading AI researcher Timnit Gebru has questioned the wisdom of building large language models - examining who benefits from them and who is harmed. More problematically, there’s also the possibility that HyperCLOVA contains the types of bias and toxicity found in models like GPT-3. Naver does not claim that HyperCLOVA overcomes other blockers in natural language, like answering math problems correctly or responding to questions without paraphrasing training data. Instead, they’re prestige projects that demonstrate the scalability of existing techniques or serve as a showcase for a company’s products. Some experts believe that while HyperCLOVA, GPT-3, PanGu-α, and similarly large models are impressive with respect to performance, they don’t move the ball forward on the research side of the equation. “ await more technical details to see if truly comparable to GPT-3.” Skepticism Therefore, the Naver announcement is part of a general trend of different nations asserting their own AI capacity capability via training frontier models like GPT-3,” Clark wrote in his weekly Import AI newsletter. “Generative models ultimately reflect and magnify the data they’re trained on - so different nations care a lot about how their own culture is represented in these models. In April, a research team at Chinese company Huawei quietly detailed PanGu-Alpha (stylized PanGu-α), a 750-gigabyte model with up to 200 billion parameters that was trained on 1.1 terabytes of Chinese-language ebooks, encyclopedias, news, social media, and web pages. OpenAI policy director Jack Clark called HyperCLOVA a “notable” achievement because of the scale of the model and because it fits into the trend of generative model diffusion, with multiple actors developing “GPT-3-style” models. ![]()
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