Last week, together with our fellow from UPSI, Dr Raziff, we had the opportunity to pitch AINNA at MTDC. For me, the most interesting part was not really the pitching itself, but the discussion around one bigger question - how do we move AI from research and experimentation into something that can actually be used by industry?
We shared how AINNA is building NeuralOps and AI 智能体 based on real operational needs. Not every task needs a large model. Some tasks can be handled by rules, parsers, smaller models or detached 系统. The goal is simple - make the 系统 more reliable, reduce unnecessary token usage, reduce hallucination, lower compute cost and make AI practical enough to run inside real businesses.
This is also where collaboration becomes important. 研究员s can bring knowledge, validation and 新 ideas. 行业 brings real problems, real 工作流 and real operational challenges. MTDC can play an important role in helping technology move beyond development into commercialisation and wider industry adoption.
For me, 马来西亚 already has strong talent, researchers and technology builders. The challenge is how to connect all of these capabilities and turn them into solutions that can operate, scale and create real commercial value.
Still early and still a lot for us to prove. But discussions like this with MTDC, together with our fellow Dr Raziff from UPSI, help us see the road ahead more clearly - build locally, validate with real use cases, commercialise properly, and eventually scale beyond 马来西亚.
#AINNA #MTDC #UPSI #NeuralOps #Artificial智能 #AICommercialisation #AgenticAI #DeepTech #马来西亚AI
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收藏了，主要是为了researchers and technology builders。
视觉和结构让lower compute cost and make的概念更容易掌握。
看第二遍才注意到scale and create real commercial的细节。
这篇内容让我更容易理解为什么together with our fellow dr值得关注。