AI Investment: Bridging Gaps, Global Trends

● **Recession Looming**

Key to Model Development, Bridging Existing Gaps, and Shifting Investment Strategies

This article systematically organizes the following four aspects:
– Why AI model developers continuously improve their models.
– How the resulting ‘investment gap’ is disappearing.
– What AI investment strategies we should prepare for in the changing model market.
– Global technology trends and economic impact.

After reading this article, you will clearly understand how AI model development is changing the investment landscape and what optimal strategies investors and companies should adopt in the future.

1. The Principle of How Rapid AI Model Development Eliminates Market Gaps

Why AI Investment Has Changed Drastically in Just a Few Years
AI technologies such as deep learning and generative AI are developing at an incredible rate.
Even competitive models are quickly narrowing the ‘gap’ as developers continuously update their performance.
For example, initially, a specific model might produce significantly better results, making it a valuable investment, but this gap almost disappears when the latest version is released.
In the past, the competition was about ‘who can create a better model,’ but now, it is rapidly shifting to ‘who can apply and strategically utilize it faster than others.’

2. ‘How to Utilize’ Models is the Core of Innovation, Not the Models Themselves

Changes in AI Investment Focus
It is becoming increasingly difficult to gain a long-term advantage with model technology alone.
The pace of improvement is so fast that competitors quickly catch up to similar levels.
Recently, the focus is shifting from the performance of the model itself to how it is incorporated into the business and what utilization strategies are established.
Examples:
– Competition in model performance → Competition in model ‘utilization strategies’
– Incorporating AI into products/services, innovating internal operations, and rapidly interpreting the market environment with AI, etc.

3. AI Investment: Using Existing Methods Could Lead to ‘Wrong Choices’

Past Investment Cases and Practical Points
In the past, ‘investing in good models’ was the answer, but now, investment decisions are more complex due to the short competitive advantage of models.
There have been many cases where investing in ‘companies with excellent models’ resulted in the existing gap disappearing as the developer’s entire model was upgraded.
Now, the proportion of investment is increasing in infrastructure such as GPUs and datasets, as well as platforms and derivative services that can be quickly and appropriately incorporated into the actual market.

4. Global AI Market Trends and Our Strategy

Why the Entire Market is Shifting to a Focus on ‘Strategic Innovation’
Major global AI companies (e.g., OpenAI, Google, Microsoft, etc.) are all increasingly refining their models to bridge existing gaps.
In this process, corporate investment is also focused on:
– Not ‘core models’ but
– Applying models to practical use quickly or creating specialized services.
Both developers and investors need to develop strategies to benefit from ‘model development.’
– Along with continuous model upgrades,
– The competitiveness of the data itself,
– User-customized AI applications,
– And the speed of rapidly adopting derivative models/services specialized for industrial practice will be the points of advantage in the future.

5. New Directions for AI Investment Through Key Keywords

– Artificial Intelligence, Digital Innovation, Data, Investment Strategy, Global Economic Outlook
The acceleration of digital innovation is establishing itself as the essence of AI competitive advantage.
From the investor’s perspective, ‘which companies apply AI to the actual market quickly, differentially, and continuously’ will become more important than ‘which AI model is leading the way.’
In line with the ever-changing global technology and economic outlook, viewing AI models not as assets but as ‘utilization capabilities’ is becoming an essential investment strategy in both B2B and B2C.

< Summary >
AI model development quickly eliminates competitive gaps.
The investment focus should now be on application strategies and actual service innovation, not model performance.
The future of AI investment lies in utilization capabilities, speed, and continuous derivative innovation.

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*YouTube Source: [조코딩 JoCoding]

– 거인의 어깨에 올라타야한다 #shorts

● **”Recognition Deficit, Pragmatism.”**

2024 Branding: From Products to Solidarity, a Comprehensive Summary of Successful Strategies

This article deeply and accessibly explores brand identity, practical branding success stories (Pokémon Bread, Fish Cake Tea, Homeplus Pedometer Cart, etc.), changing consumer needs, the convergence of performance marketing and branding, AI utilization, and the types of relationships and UX (experience) brands need to create to thrive in the current market, all from the latest economic trends perspective.
It covers attitudes, strategies, real business concerns, and brand philosophy, presenting practical insights that haven't been compiled anywhere else.

1. The Core of Strengthening Brand Identity: Projecting It onto Products

– “Companies speak through their products.” Like Pokémon Bread, the brand’s identity and differentiation must be genuinely integrated into the actual products and services.
– As seen in the Homeplus Pedometer Cart example, branding isn’t just about slapping a logo on promotional activities.
– The brand’s message should naturally flow from the product itself and the experience itself, so consumers can feel it.

2. Branding and Success Story Report

Pokémon Bread: Reborn by nostalgia of the 90s elementary school generation + digital campaign pre-boosting strategy. SNS bragging contests, Ttibu Seal videos, rarity, etc., brand-product-emotion are connected at once.
Homeplus Pedometer Cart: Actualized the brand slogan of health into the consumer experience in the store. Naturally increased sales.
Jos Tteokbokki ‘Fish Cake Tea’: Maximized topicality by quickly commercializing ideas within the organization + exclusive launch on a commerce platform + leveraging in-store synergy.

3. Branding Message: The One Brand-One Message Rule

– Only one core message per brand.
– Maintaining consistency in message/design/product/symbol is impactful and budget-efficient.

4. BI·CI Rebranding: Familiarity and Shock, and Public Opinion

– People generally react negatively to changing something familiar.
– Examples: Korean Air, Innisfree, LG, Samsung, etc., face criticism whenever logos/names/colors are changed, but transition to sophistication in the long term.
– Revealing the change process in advance alleviates shock (Cyworld case).
– It must be based on strategy (judgment of the company’s long-term direction).

5. Consumers and Market Environment: Approval Deprivation, Overwhelming Importance of Solidarity

– Today’s consumers have a ‘desire to be recognized’ rather than monetary deprivation.
– Brands can play a role in filling this emptiness and building community.
– Trust and loyalty start from brand communities, positive user experience sharing, and two-way feedback with customers.

6. Practical Concerns of Branding in the IT/Mobility·Service Sector

– In the case of service-type products (SoCar, etc.), the experience is intangible and satisfaction is low → designing the experience journey well is necessary to leave a real impression.
– Performance marketing (special offers, targeted benefits, time-based events, etc.) should also be combined with branding.
– Segment products according to customer usage patterns → expand the portfolio to include Want-satisfying products.

7. The Collapse of the Boundaries Between Branding and Performance Marketing

– The formula of large-scale branding campaigns = increased sales, as in the past, is not working well.
– A society where practicality and cost-effectiveness (real benefits) are prioritized.
– Performance advertising can also be an excellent branding tool (cross-measurement and effect management are possible).

8. Branding·Marketing Cases in the AI Era

– Explosive use of AI tools such as target customer classification, A/B testing, and copy/design drafts.
– Faster and more complete, but human observation and relationship building are differentiating factors.
– In the future, AI can also use branding power, but the human value of ‘solidarity and naturalness’ is irreplaceable.

9. The Future of Human-Centered Branding: Solidarity + Naturalness

– The true brand differentiation point in the AI era = building “relationships” & a brand attitude of “trying to improve even if not perfect”.
– Building trust with both light users and heavy users through feedback reflection, revealing the change process, and forming communities.
– Ultimately, brand loyalty is created as ‘shared stories’ accumulate between the brand and users.

The 2024 branding success formula is a combination of ‘product-centric messages’ immediately felt from the product, the brand’s unique identity, thorough market and consumer insights, and practicality-focused performance marketing.
Execute quickly and precisely with AI, but the authenticity of the brand survives in the relationships, solidarity, and attitude of natural growth that only humans can provide.
From now on, we are in an era where ‘solidarity’ and ‘experience’ create powerful brands.

2024 Branding Trends and Success Strategies: Product-Centric Identity, Solidarity, Practicality, AI Marketing, Performance Branding

Based on economic outlook keywords such as 2024 brand strategy, branding success stories, product branding, AI marketing innovation, and performance marketing, we deeply explore the essence and future of branding.
It can be used as a comprehensive summary of brand success methods that can implement sales growth, secure market competitiveness, brand loyalty, maximize customer experience, and digital innovation.

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*YouTube Source: [티타임즈TV]

– “인정에 대한 결핍, 그리고 실용” (조준형 쏘카 CMO)