Solid Green Fire 木熒

Wisdom-based Data editor (Chinese and English). Generalist, Empath, Flâneur. Creating training dataset with Dark data.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 1:
Shut the fxck up and do True listening.

[Solid Green Fire 木熒 @solidgreenfire]

@cat88tw 所以我下會推出處理Cognitive debt的服務。因為產生問題的根源不是在AI的技術

[Solid Green Fire 木熒 @solidgreenfire]

https://t.co/zPIB0Libpc

[Solid Green Fire 木熒 @solidgreenfire]

https://t.co/TJdER15anN

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 364:
Should a person bravely overcome default modes, or evade the risks that must be borne? It would be better to first understand what risk truly is.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 363:
Some people discover that default modes can conceal dangers, silently harming both body and mind. Within those cracks filled with contradictions, complexities, and subtleties lie simple and clear answers.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 362:
Many people misunderstand the true nature of risk, believing that uncertainty is the source from which it arises, while forgetting that certainty can also serve as its raw material.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 361:
Real judgement is never limited to text and digitized data. Such data must exist. And they can’t capture the holistic reality.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 360:
Eyes (vision), ears (hearing), nose (smell), body (touch), and mind (cognition) form the foundation of the judgement spectrum. It help us differentiate between knowledge, intellect, and wisdom.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 359:
“Live life as humanly as possibly can, and bring that love and energy back to whatever it is you decide to do in the future.”

[Solid Green Fire 木熒 @solidgreenfire]

https://t.co/pTjsnsZGGx

[Solid Green Fire 木熒 @solidgreenfire]

https://t.co/ZncfEdjxNx

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 358:
Cognitive gaps create inequality, and information not based on facts is as dangerous as cancer cells.

[Palantir @PalantirTech]

In Japan, billions are spent on elder care, but over a third is lost to inefficiencies — affecting care quality.

SOMPO and #Palantir's platform integrates 100s of datasets to power smart care decisions. Plans that once took 30 min can be made in seconds: https://t.co/s4Gf7lUiEr

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 357:
In the era of AI, people who lack judgment and have insufficient knowledge are extremely easy to deceive, just like obsessed believers who blindly worship cult leaders.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 356:
Absurdity mean a statement or belief manifestly inconsistent with one’s own opinion. Do AI have own cognition to write a statement or belief from creation?

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 355:
Ontology:
what the AI?

Causality:
why the AI?

Epistemology:
how the why the AI?

Phenomenology:
the AI.

[Solid Green Fire 木熒 @solidgreenfire]

How we create training dataset with Dark data?

Day 354:
Data often cloaks itself in the guise of “science” and “objectivity.” It make many people unconsciously surrender their right to judgment.