### Analysis of AI technology's loss of value and potential to increase its value 100 times in the future
#### 1. **The phenomenon of AI losing its value**
- **Hype decline**: AI has recently gone through a “hype loss” phase as investors and businesses have begun to doubt the technology’s profitability. The stock prices of leading tech companies like Nvidia, Microsoft, and Apple have fallen about 10% since their 2024 peaks, reflecting market caution.
- **ROI challenges**: Many businesses are questioning the return on investment (ROI) from AI. Only 5.1% of US companies use AI to produce goods and services, down from 5.4% at the beginning of 2024. This indicates a slowdown in the adoption of AI in practice.
- **Overhyped expectations**: Some AI projects have not achieved the expected results, leading to a sense that the "AI bubble" is bursting. This is a natural phenomenon in the technology development cycle, similar to the early stages of the Internet.
#### 2. **Causes of devaluation**
- **High costs and unclear efficiency**: Companies have invested billions of USD in AI but have not seen corresponding profits. For instance, the cost of optimizing AI technology to handle simple tasks can be up to 6 times higher than traditional methods.
- **Lack of breakthrough applications**: Currently, AI is mainly used to improve work efficiency (such as coding and translation) but has not yet created world-changing applications.
- **Ethical and safety risks**: Issues such as deepfakes, algorithmic bias, and privacy are undermining user and business trust in AI.
#### 3. **Potential to increase value 100 times in the future**
- **Multimodal AI and AI agents**: By 2025, multimodal AI (combining text, images, and sound) will become the standard, improving customer experience and optimizing workflows. AI agents will automate complex tasks, thereby increasing productivity and efficiency.
- **Optimizing AI infrastructure**: Companies will focus on optimizing performance and reducing operational costs of AI. For example, LG AI Research has reduced operational costs by 72% and processing time by 50% by using multimodal models.
- **Applications in key areas**: AI will revolutionize industries such as healthcare, education, and energy. For example, AI can help predict molecular structures for developing new drugs or optimize renewable energy systems.
- **Creating new jobs**: Although AI may replace some jobs, it will also create millions of new jobs in areas such as research, development, and AI management. It is expected that by 2030, AI will create between 20 to 50 million new jobs globally.
- **Addressing global challenges**: AI has the potential to solve major issues such as climate change, poverty, and pandemics through data analysis and accurate predictions.
#### 4. **Conclusion**
- **Natural adjustment phase**: The current devaluation of AI is part of the technology development cycle. After this phase, AI will mature and provide much greater value.
- **Enormous potential**: With the development of multimodal AI, AI agents, and applications in key areas, the value of AI could increase 100 times compared to the current state. This requires serious investment in research, development, and risk management to ensure AI serves the interests of humanity.
The currencies $BTC will have linked value!
this analysis.
