AI Research Memo

A recent discussion on GIAI Square brought up concerns about networking opportunities in the SIAI 2.0 AI MBA program. While technical students focus on engineering and quantitative finance, business track students need a different kind of networking—one that connects them to venture capitalists, private equity firms, and AI-driven business leaders.

In a recent discussion on GIAI Square, a student raised concerns about networking opportunities in the SIAI 2.0 AI MBA program, particularly about the strength of the alumni network and its impact on career opportunities post-graduation. As a professor and industry professional, I provided my perspective based on both academic experience and real-world industry exposure.

Unlike typical AI bootcamps, SIAI offers in-depth AI education with a strong foundation in mathematics, statistics, and real-world business applications. The MSc AI/Data Science program at SIAI emphasizes rigorous scientific studies, ensuring students master the theoretical and practical aspects of AI. SIAI’s MBA AI programs incorporate extensive business case studies, with a new MBA AI/Finance track focusing on corporate finance and financial investments.

GIAI's primary research objective with the coming cycle's of MSc AI/Data Science is to build a graph-based Shapley Value for HR contribution analysis.

Mathematical ability differs across cultures, with Western academia emphasizing abstraction over procedural speed AI is automating routine calculations, making conceptual thinking more valuable than ever Future professionals must focus on logical reasoning and model formulation to stay relevant After years of teaching here at SIAI, we have witnessed a varying cultural differences in perception of experts in AI/Data Science in the western hemisphere and in Asia.

Many amateur data scientists have little respect to math/stat behind all computational modelsMath/stat contains the modelers' logic and intuition to real world data

AI talks turned the table and become more pessimisticIt is just another correction of exorbitant optimism and realisation of AI's current capabilitiesAI can only help us to replace jobs in low noise data

Boot camp is for software programming without mathematical trainingMSc is a track for PhD, with in-depth scientific research written in the language of math and stat

Top brains in AI/Data Science are driven to challenging jobs like modelingSeldom a 2nd-tier company, with countless malpractices, can meet the expectations

ChatGPT is to replace not jobs but tedious tasksFor newspapers, 'rewrite man' will soon be goneFor other jobs, the 'boring' parts will be replaced by AI,

Data Science can find correlation but not causalityIn stat, no causal but high correlation is called 'Spurious regression'Hallucinations in LLMs are repsentative examples of spurious correlation Imagine two twin kids living in the neighborhood. One prefers to play outside day and night, while the other mostly sticks to his video games. After a year later, doctors find that the gamer boy is much healthier, thus conclude that playing outside is bad for growing children's health.

STEM majors are known for high dropoutsStudents need to have more information before jumping into STEM

People following AI hype are mostly completely misinformedAI/Data Science is still limited to statistical methodsHype can only attract ignorance As a professor of AI/Data Science, I from time to time receive emails from a bunch of hyped followers claiming what they call 'recent AI' can solve things that I have been pessimistic. They usually think 'recent AI' is close to 'Artificial General Intelligence', which means the program learns by itself and it is beyond human intelligence level.

Math in AI/Data Science is not really math, but a shortened version of English paragraph.

Korean GDP growth was 6.4%/y for 50 years until 2022, but down to 2.1%/y in 2020s.Due to low birthrate down to 0.7, population is expected to 1/2 in 30 years.Policy fails due to nationwide preference to leftwing agenda.

Transition from column to matrix, matrix to tensor as a baseline of data feeding changed the scope of data science,

When an expectation for future is shared, market reflects it immediatelyUS Fed hints to lower interest rates in March, which is already reflected in prices

Web novel to Webtoon conversion is not only based on 'profitability'If the novel author is endowed with money or bargaining power, 'Webtoonization' may be nothing more than a marketting tool for the web novel.

Not the quality of teaching, but the way it operatesEasier admission and graduation bar applied to online degrees

Asian companies convert degrees into years of work experienceWithout adding extra values to AI degree, it doesn't help much in salary