I am sure you would agree readily that artificial intelligence (AI) and large language model (LLM) have led us into a promising and exciting future, at accelerating speed. This development has spawned fundamental repercussions across the chain of research analytics, machine learning and deep learning, which all boils down to data resources.

Data occurs, according to estimates on the Internet, at 402 million terabytes per day in 2024. To put that number in a perspective to which most of us could relate, those data would produce approximately 9.4 billion 200-page books, per second. Dig deeper, 90% of today’s data were generated in the last two years, and 90% of them are replicated data.

Unconsciously, the effect of the current trend of analytics pursuit resulted in an unsurpassed consumption and manufacturing of computer, network and storage devices, due to the existing mindset of gathering data before each and every analytics begins. Imagine the electricity consumption involved in downloading, storing and repetitive data preparation, besides the hardware manufacturing cycles. We must ask, is this paradigm environment friendly?

Software engendered process flow, again, plays a critical role going forward, not just on how well the algorithms or the analytical features perform, but also the fundamental impact on our collective natural and cultural environment. We are truly at a historic crossroad. Breakthrough or breakdown, the choice is in our hands.

It is my great pleasure to share with you the whitepaper on a sustainable data ecosystem that we envisioned and authored, called Aralia, please enjoy.

Sincerely,

Dr. Wenwey Hseush
Co-Founder and Chief Executive Officer