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Artificial Intelligence

Feedback loops shape our destiny.

inspiration to intent to action to insight
Question

Isn't there a chance intelligence has used humans as a vehicle to evolve itself?

Subject​

Principles​

What is critical for making meaningful progress with AI as a companion in realizing potential.

The three fundamental pillars of AI are data, algorithms, and computing power.

Algorithms​

Algorithms function as the engine of AI, providing the intelligence and decision-making capabilities1. They determine how the system learns from data and solves problems. Through algorithmic efficiency, AI systems can process information and generate outputs with increasing sophistication and accuracy2.

Computing Power​

Computing power acts as the accelerator of AI, providing the necessary processing capabilities to handle complex calculations1. This includes specialized hardware like GPUs and TPUs that enable AI systems to process massive amounts of data efficiently2. The advancement in computing power has been crucial for training larger models and handling more complex AI tasks.

Data​

Data serves as the fuel for AI systems, providing the foundation for learning and pattern recognition1. The quality, quantity, and diversity of data directly impact the accuracy and reliability of AI models. Without sufficient high-quality data, AI systems cannot effectively learn or make accurate predictions.

tip

Data is the differentiator

Potential​

Large Language Models (LLMs) have fundamentally transformed software's ability to comprehend and respond to human intent. This breakthrough enables natural interaction between humans and machines at an unprecedented scale, opening new possibilities for automation and augmentation of human capabilities.

Blockchain Innovation​

The fusion of LLM capabilities with blockchain's composable infrastructure creates a powerful new paradigm:

  • Decentralized Intelligence: Combining AI's pattern recognition with blockchain's trustless execution
  • Autonomous Systems: Self-organizing swarms and agent networks operating on-chain
  • Knowledge Systems: Advanced data pipelines and insight generation at scale

Development Opportunities:

  • Intelligent agents executing complex tasks on-chain
  • Pattern recognition systems operating at network scale
  • Advanced knowledge discovery and synthesis tools
  • Creative data processing and insight generation systems

See exploration of potential for more.

Questions​

Evolve protocols and practices to explore new opportunities to leverage AI to achieve more.

  1. What repetitive tasks am I doing that could be automated?
  2. Which customer pain points am I not addressing yet?
  3. How can I leverage my existing products or services to create new offerings?
  4. What emerging trends in my industry could I capitalize on?
  5. Are there any underserved niches within my target market?
  6. How can I use AI to improve my current products or services?
  7. What data am I collecting that could be monetized or used to create new value?
  8. Are there any successful business models from other industries I could adapt?

See addtional questions intended to evolve understanding

Adhoc Use Cases​

Using interfaces that abstract interaction with LLMs.

Finding Answers​

Replace google search with AI answers.

Evolve Understanding​

The evolution feedback loop.

Professional Services​

Business Development​

See masterlist of lists

Everyday Tasks​

AI is particularly useful for summarizing and extracting key information from large amounts of text, rather than generating content from scratch. practical day-to-day productivity gains with AI include:

Accelerating learning and skill acquisition

  • Teaching how to use new frameworks and technologies
  • Replacing web searches for setting up/configuring new packages and projects
  • Assisting with debugging error messages

Enhancing productivity

  • Automating boring/repetitive tasks to allow focus on higher-level problems
  • Replacing time-consuming web searches with direct AI assistance

Research assistance

  • Generating ideas for experiments
  • Analyzing and visualizing results (e.g. creating histograms)

Task automation

  • Automating data processing and analysis workflows
  • Creating scripts to automate repetitive tasks

Education​

Best channels for learning how to leverage AI.

Resources

YouTube Channels