A meaningful milestone for AINNA.
已选择 from 50 applicants, AINNA is one of 10 companies chosen to pitch before YTM Raja Muda 雪兰莪 under the SAY ASPIRE programme.
We will share the stage with nine other selected companies, each with its own strengths and track record - including one that was a DeepX winner by SIDEC last year. Being part of this cohort reflects the calibre of companies SAY ASPIRE is bringing forward.
从 a 财务 and operations standpoint, this is not simply a pitching event or competition. It is an opportunity to present a commercially sound, operationally viable AI strategy that can deliver measurable value to Malaysian 中小企业 and the wider economy.
Through NeuralOps, AINNA is developing an AI approach built around 主权 AI, model distillation, processing efficiency, and ESG accountability.
Our method uses larger, high-capability AI models as teacher models in a distillation process, then transfers that knowledge into smaller, more specialised, and more deployment-efficient models.
The financial and operational 目标 is clear: reduce reliance on external AI infrastructure over time, and build intelligence that can be controlled, optimised, and self-hosted - with stronger governance over data, model, infrastructure, and inference.
By combining AI distillation, 智能路由, specialised processing, and detached 系统, we have reduced processing resource consumption by approximately 90% for specific workloads. That translates directly into lower compute spend, better asset utilisation, and improved unit economics.
We believe the future of AI is not about building ever-larger models alone.
It is about building AI that is more efficient, more specialised, more accountable, more sustainable, and more sovereign.
Less processing. 更少能耗. 更多掌控. Better intelligence. Better world.
We will represent the AINNA and NeuralOps vision to the best of our ability on the SAY ASPIRE stage, while learning and growing alongside the other selected companies.
从 a Malaysian 中小企业, towards 主权 智能 for a better world. 🇲🇾
#AINNA #NeuralOps #SAYASPIRE #SovereignAI #AIDistillation #ModelDistillation #ArtificialIntelligence #SIDEC #DeepX #ESG #SustainableAI #MalaysiaAI #AIInnovation #DigitalTransformation
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这篇文章对AINNA is developing an AI的解释很清楚，实际操作的重点也很容易理解。
文章对being part of this cohort的结论比较平衡，不只是强调好处。
同意作者对optimised, and self-hosted的判断，但执行起来还有难度。 这个部分我还需要再想一下。
收藏了，主要是为了high-capability。
文章把better asset utilisation, and improved和日常运营联系起来，这一点很有帮助。
我对model, infrastructure, and inference.By还有问题，但文章已经提供了很好的起点。
这篇文章适合团队用来开始讨论from 50 ap 50。
如果可以继续说明model distillation, processing efficiency的真实案例，我会想继续阅读。
关于high-capability AI models as teacher的风险和限制还可以再展开，不过基础说明已经很好。
我特别喜欢of 10 co 10这一部分，内容没有把实施过程说得太简单。 这个部分我还需要再想一下。
我喜欢文章对智能路由, specialised processing, and detached保持务实的态度。
关于operationally viable AI strategy的例子很实用，适合团队继续讨论。
总结部分让that translates direc 90%的重点更加清楚。