Way to data scientist

Over the past few decades, the internet has profoundly transformed human lifestyles and created immense value by connecting people, information, and commerce. For instance, WeChat connects people, Taobao links users with goods, and Meituan bridges consumers with services—connection emerged as the most critical keyword of the internet era.

​The “Intelligence” Emphasized by AI​
AI’s intelligence is reflected in computer systems’ ability to understand, reason, and create like humans. Key aspects include:

• ​Understanding & Perception: Through computer vision, NLP, and other technologies, AI interprets unstructured data (images, speech, text) and extracts meaning from environments.
  Example: In cashier-less stores, AI vision systems use high-precision cameras and ML algorithms to track and analyze customer behavior in real time.
• ​Reasoning & Decision-Making: AI performs reasoning and predictions under uncertainty to optimize decisions. Applications span medical diagnosis and financial risk control.
  Example: DeepMind’s AlphaFold employs deep learning to predict protein folding structures, solving a decades-old scientific challenge by modeling over 200 million 3D protein configurations.
• ​Creation & Generation: Beyond preset rules, AI now autonomously generates content—text, images, music, even scientific solutions.
  Example: GPT models produce creative articles/code; DALL·E renders images from text. In drug discovery, generative AI designed the novel molecule ISM001-055, now in clinical trials—showcasing cross-domain innovation potential.

These capabilities enable AI systems to go beyond traditional internet applications: not just linking information but comprehending it to drive valuable creation and decisions. AI’s intelligence can be categorized into dimensions:

​From Data Interconnection to Intelligent Collaboration​
The shift from the internet to the AI era represents an evolution from data interconnection to intelligent collaboration. While the internet built bridges for information flow, AI empowers systems with autonomous analysis and coordination, driving transformative changes:

• ​Smart Cities: IoT sensors and AI algorithms enable adaptive infrastructure.
  Example: Beijing’s AI-optimized traffic lights dynamically adjust timings using real-time flow data, creating “green wave” corridors to reduce congestion.
• ​Personalized Medicine: AI analyzes genomic/clinical data to tailor treatments.
  Example: AI identifies patient-specific genetic drivers of disease, shifting medicine from one-size-fits-all to data-driven precision care.
• ​Industrial IoT: Predictive maintenance via sensors and AI minimizes downtime.
  Example: Equipment anomalies are detected pre-failure, boosting production continuity and safety versus traditional reactive maintenance.

In the AI era, industries are forming human-machine-object collaborative networks: data transforms from passive sharing to active decision-making fuel. This leap from connection to collaboration redefines value creation.

​Conclusion​
In essence, the internet era centered on connecting information, while the AI era focuses on understanding information to create value. Connections enable dissemination; intelligence generates insights. This core shift is reshaping business models and work paradigms—mastering AI’s capabilities will be key to seizing future opportunities.