Prediction is about foretelling the future outcome based on result form past execution.
Anticipation is about foretelling the future outcome based on factors considered and factors ignored or overlooked.
Statistical Analysis is about prediction. Logical Analysis is about anticipation. Proper use of anticipative strategy over prediction can achieve out-sized reward with limited risk.
There are plenty of reasons for businesses to use anticipation as a strategy. Absence of anticipative strategy leads to regretful execution, as in cases of some mega mergers, consolidation, and inorganic growth plans:
- Goldman Sachs acquisition of GreenSky - investing without anticipative strategy results in dumping money-losing fintech at a significant loss after paying more than $2 billion to buy the home improvement lender
- Companies relying on artificial intelligence technology that has yet to yield solutions
- Government making policy without anticipative strategy results in execution with after-thought - England delaying its ban on fossil fuel car and trucks.
An example of anticipative strategy: Finding option trade opportunity on target that is using Generative AI.
The following discussion is not about investment advice; rather, it is all about using the right tool for the right strategy.
Using statistical or ML based AI tool does not improve Anticipative Strategy; such tool is about learning previous instances of success or failure.
Anticipative Strategy is identifying certain trend or hype that is incorrectly pursued by the financial market while overlooked by the majority where a reversal is imminent. Without mapping such narrative into knowledge graph together with abstraction, such effort would be like finding a needle in hay stack.
Generative AI is not a solid technology ready for prime time and is vulnerable to unforgiving errors and exceptions. Yet, there is a lot of hype enjoyed by hardware exclusively used in Generative AI. By drilling down on the challenges as identified by ELAINE's Semantic Relevance and Logical Analysis, it enables one to focus on the risk in Generative AI adoption, and hence exposing a huge opportunity for those who wanted to rip the benefit from its decline.
Nvidia (NVDA) manufacturers GPU for Generative AI. Its share price has dropped over $80 in less than four weeks after earnings release. What are the challenge supporting factors based on NVDA's earnings conference call?
(enterprise,nvidia_ai,pre-trained)
(enterprise,software,nvidia_ai,pre-trained)(enterprise,software,pre-trained)(software,models,pre-trained)(software,nvidia_ai,pre-trained)(enterprise,software,nvidia_ai,on-prem)(enterprise,software,on-prem)(software,models,on-prem)(software,nvidia_ai,on-prem)(enterprise,gpu,nodes)(enterprise,nvidia_ai,gpu,nodes)(enterprise,software,nodes)(enterprise,software,nvidia_ai,nodes)(software,gpu,nodes)(software,nvidia_ai,nodes)
Turning narrative into knowledge graph and propositions helps to identify unnoticeable opportunities in investments.