AI Landscape in Malaysia
Big names such as OpenAI’s GPT models (including the well-known ChatGPT) and, to a lesser extent, Meta’s LLaMa and Google’s PaLM have made their mark on the large language model (LLM) field, but this doesn’t fully depict the artificial intelligence (AI) landscape in Malaysia.
Since the AI boom of last year, the world has found itself in what appears to be an arms race to develop progressively sophisticated models, and Malaysia is no exception. For instance, there’s Mesolitica, a local startup specialising in the creation of narrow AIs (machine learning focused on a single, specific task) and the training of LLMs, having already released a number of them as open-source projects.
The startup’s co-founder and chief technical officer, Husein Zolkepli, says that the goal was to make a model capable of interacting entirely in Bahasa Malaysia. “We want an AI model to capture the context of Malaysians; a lot of those existing models do not crawl enough data for local context.”
“When it comes to current events or other topics that they were not trained on, ChatGPT Plus and Bing Chat rely on indexed search engine results, which they will rephrase before providing a response. These are not embedded within the models by default,” he says, adding that Mesolitica’s AI models are focused on including contextual details, with data from local forums, news portals, and social media posts that were used in the training process
According to the Mesolitica Github page, the database has accumulated a total of 240GB of text as of Nov 21. Khalil (left) and Husein formed Mesolitica to create generative AI capable of interacting entirely in local languages. — YAP CHEE HONG/The Star The current release of the model has the capacity to understand local nuances, such as slang, bahasa pasar and Manglish, along with Mandarin and Tamil.”Another thing is about privacy. When you make a request to ChatGPT or Bing Chat,everything goes to their servers.”
“But with open-source models like ours, any user can host their own on a local machine, with their own set of intended goals, ideas, rules and practices.“It’s all about keeping things decentralised instead of having to rely on a specific company like OpenAI to keep things running,” Husein says. Khalil Nooh, the CEO and co-founder of Mesolitica, has observed a rising demand for this sort of LLM in the local commercial space.
“From the business perspective, companies will say that they want their own AI, that they want to jump on the bandwagon with their own private datasets and train their own LLMs.”Moving forward, they may explore other possibilities with LLMs that involve text-based tasks that can be built on top of the base model. “We’ve already done a few rounds of training on our models to incorporate Malaysian context. Everything is available as open source. On my end, I can confidently say that we have a 100% alternative to GPT.”
However, those actively involved in AI training, like Husein, hope for little to no regulation, as they fear that any form of control could impede their ability to take the technology further. “Technologists like me want to push things as much as possible. I just want the technology to be there.“I just hope that it remains open as it currently is, with minimal regulation despite the concerns,” he says, arguing that training LLM using content available online is akin to how Google’s search bots crawl the Internet to index search results.
Another potential issue is that major tech companies set rules – known as AI alignment – for the AI models they host, but users running open-source models can choose to set no conditions at all.
