Title: The Emergence of Localized Generative AI: Challenges and Opportunities
Generative AI, an advanced form of artificial intelligence that can create content and solve problems without human interference, is rapidly evolving. However, it is largely optimized for English, limiting its application in non-English-speaking countries. To overcome this challenge, local tech groups are developing their own GAI models that are tailored to their languages and cultures. In this article, we explore the challenges and opportunities of localized generative AI and its potential impact on the tech industry and society.
Introduction: The Rise of Generative AI
Generative AI is a machine-learning technique that enables AI systems to generate unique content such as images, music, and text. GAI is a powerful tool for solving complex problems, creating unique products, and optimizing processes. The applications of GAI are limitless, from content creation to personalized customer service, chatbots, and medical diagnosis. GAI can learn from large datasets, identify patterns, and make predictions with high accuracy. However, GAI’s full potential is yet to be realized due to language and cultural barriers.
The Challenge of Non-English Speaking Countries
English enjoys a dominant position in the technology industry, with most tech products and services optimized for English-speaking users. However, this leaves behind millions of non-English-speaking users worldwide, limiting their access to advanced technology. For example, most of the widely used chatbots such as ChatGPT and Google chatbot Bard are optimized for English, making it challenging to use them in non-English-speaking countries. Even in regions where English is spoken as a second language, the models may not be accurate in generating the desired output that’s expected from a language familiar to the user.
Localized Alternatives: Opportunities and Challenges
The development of localized GAI models offers a solution to the language barrier problem that non-English-speaking countries face. Local companies can develop GAI models that are customized to their language, culture, and preferences, making it easier to use GAI for solving local problems. For example, Google’s chatbot Bard experimented with Korean, and the users report that it is the most fluent Korean conversationalist. Furthermore, customized models could reduce the fear of superpower surveillance that nations experience when relying on global giants to provide these services.
However, developing GAI models that are localized comes with its share of challenges. For instance, developing GAI models that reflect the cultural nuances of a specific community can be quite challenging. GAI’s ability to learn and pick up cultural traits raises ethical concerns, such as bias and discrimination. Additionally, creating localized GAI models requires an immense amount of data and computing power, which may not be available to smaller tech groups. For example, developing language models for the Arabic language presents unique technical challenges due to the language’s complexity.
Localized GAI: The Advantages over Global Giants
The emergence of localized generative AI will offer several advantages to local tech groups over global giants such as Google and Microsoft. Some of these benefits include:
1. Meeting the specific needs of the local users: localized GAI models can be designed to meet the unique needs and preferences of the local users, which global giants often overlook.
2. More effective user engagement: localized GAI models are more likely to engage the users more effectively than the global versions as it can respond better due to its familiarity in the language and culture.
3. Enhanced Privacy and Security features: Due to the fear of superpower surveillance, using localized GAI models will reduce privacy concerns and allow more secure implementation of the application.
4. Monetization opportunities: Localized GAI models can be monetized by selling or licensing to other businesses that value language customization in their product offerings.
Business Opportunities of Localized GAI
Localized GAI offers vast business opportunities for local tech groups. For example, Naver, South Korea’s largest online company, is set to launch its chatbots in July and have a considerable advantage compared to other players in the market. Furthermore, with several regions worldwide, with the Middle-East being a prime example, having political complexities, demand for localized GAI models will be high. The revenue generated in these regions can provide stability to a company and can lead to partnerships elsewhere.
Moreover, as more companies start to adopt localized GAI models, there will be an increased demand for professionals specializing in developing these models. This shift in user demand and technological developments presents opportunities for international companies to invest in local tech groups to develop customized GAI models.
Ethical Concerns of Localized GAI
There are several ethical concerns associated with the development of localized GAI models. One of the significant issues is bias and discrimination in GAI, which can lead to exclusion and propagation of stereotypes. For instance, in language models, the type of data used to train the model, the biases it contains, and the demographics of the available data can lead to biased generated output negatively impacting end-users. Another challenge is developing localized GAI models without compromising user privacy and data security. Therefore, new guidelines and regulations are necessary to ensure that GAI models are ethically developed and tested before implementation.
Conclusion: The Future of Localized GAI
The rise of localized GAI models presents businesses and tech groups with numerous opportunities to develop and implement customized AI solutions. However, developing GAI models that accurately reflect the unique needs and preferences of local users requires a lot of investment, research, data collection and analysis, infrastructure, and partnerships. Nonetheless, developing localized GAI models will lead to reduced privacy concerns and a cheaper, secure, and accurately generated output. Therefore, developing localized GAI models and ensuring they are properly tested and regulated to reflect ethical standards is key to scaling AI innovation and making it accessible to all worldwide.
Summary:
Localized GAI models offer a solution to language barriers for non-English speaking countries. Developing these models allows for more accurate and effective user engagement, privacy, security, and monetization opportunities. This presents several business opportunities such as launching Chatbots, customized templates, and onshore servers. However, developing localized models presents ethical concerns such as bias and discrimination, which may hinder effective user engagement. Regardless of the challenges, adopting localized GAI models that reflect the unique needs and preferences of local users will enable countries to take advantage of the economic and social benefits of advanced AI technologies.
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Generative AI has an English-speaking twist. It is believed that English accounts for about 97% of data learning by ChatGPT, the advertised chatbot supported by Microsoft. GAI options are currently limited in countries where English is not spoken. Local alternatives are needed.
Chat GPT and Google chatbot Bard experimented with Korean. Users report that Bard is the most fluent. But local tech groups could come out ahead.
Google has chosen Korean and Japanese for the extension Bardbecause it sees South Korea and Japan as safe environments for researching large language patterns. Furthermore, both countries’ mobile sectors are ahead of Western alternatives.
This also means that there is plenty of local competition. Naver, South Korea’s largest online company, will launch its own chatbots in July. Peer Kakao will follow suit in the coming months.
The couple plans to offer artificial intelligence highly customized templates to meet local preferences. These will contrast with the more universal models developed by Microsoft and Google.
Custom models and onshore servers are more likely to pass the scrutiny of users and governments who fear superpower surveillance. Tech companies based in the US or China may be at a disadvantage here.
Demand for localized JHA will be strong in the Middle East given the political complexities of the region. Naver hit a deal with Saudi Arabia earlier this year to develop a range of digital services, including artificial intelligence tools. This should produce years of stable revenue and a stepping stone to partnerships elsewhere.
Naver shares are up 14% this year and are trading at 30 times forward earnings. This puts them on a small discount on Microsoft stock. Won31tn’s Naver market cap ($24 billion) is larger than that of LG Electronics, a much more international company.
Naver is well positioned to tap into more overseas sales. If successful, the stock should rise accordingly. Compound growth is good news, whatever language you express it in.
Lex’s team is interested in hearing more from readers. Please tell us what you think about the local GAI in the comments section below.
https://www.ft.com/content/ccbf06d1-9383-4180-9fd6-81537da8fa21
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