Natures Technology

If anyone wishes to observe the works of nature, he should put his trust not in books of anatomy but in his own eyes...... Galen(Greek Physician, AD 129-199)

Nature’s technology, often referred to as biomimicry or bioinspiration, involves looking to nature for innovative solutions to human challenges.

Numerous studies have shown clear evidence of the mental and physical benefits of spending time in natural environments. During the pandemic, when indoor gatherings were restricted, access to green spaces was crucial for community health and resilience. A robust network of healthy ecosystems is essential for physical protection and resilience and for maintaining urban biodiversity.

Here are some ideas that draw on natural principles:

Self-Healing Materials: Inspired by how some organisms, like certain reptiles and amphibians, can regenerate lost limbs or heal wounds, researchers are developing materials that can repair themselves when damaged.

Water Filtration Systems: Studying natural filtration systems, such as how wetlands purify water, could lead to new, efficient water treatment technologies.

Animal-Inspired Robotics: Designing robots that mimic the movement and agility of animals, like birds or insects, could improve efficiency in tasks like search and rescue or surveillance.

Natural Cooling Systems: Inspired by termite mounds, which maintain a stable internal temperature, architects are developing buildings that naturally regulate temperature without relying heavily on air- conditioning.

Pollination Drones: Learning from bees and other pollinators, engineers are creating drones that can help with pollination in areas where bee populations are declining.

Biodegradable Packaging: Using materials inspired by natural processes, such as chitin from crustaceans, to create packaging that breaks down naturally without harming the environment.

Wind and Water Energy: Designing turbines and water wheels that mimic fish fins or bird wings for improved efficiency in harnessing renewable energy.

These concepts showcase how observing and understanding natural systems can lead to innovative and sustainable technological advancements.

San Francisco 1t.org pledges commitment to a future where nature and urban life harmoniously coexist. By enhancing biodiversity, fostering equitable access to natural spaces and bolstering community engagement, San Francisco sets a transformative example for urban sustainability.

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Intelligent Age

“Creativity is not predictable, linear, or programmable....People who creatively think about financial challenges are as creative as the people who get paid with the word ‘creative’ in their job title."-----JKR’s Rolston

Gig Economy and rise of gig work can lead to income instability.

The Intelligent Age is fundamentally altering how we communicate — both with one another and with the world around us. AI is taking instantaneous and global communication to the next level, enabling real-time translation across languages and content generation that caters to individual preferences.

The term "intelligent age" can refer to several concepts, often related to advancements in technology, artificial intelligence, and the evolving role of intelligence in society. It might denote:

Technological Advancement- The period where AI and machine learning play a crucial role in various sectors, enhancing decision-making and efficiency.

Information Age- A continuation of the digital revolution where access to information and the ability to process it effectively define success and progress.

Human-AI Collaboration- An era where human intelligence complements artificial intelligence, leading to new innovations and solutions.

Societal Impacts- The implications of these technologies on employment, ethics, education, and daily life.

let's look at the Social Impact

1- Digital Divide: Access to AI technology can exacerbate inequalities, leaving marginalized communities further behind.

2- Wealth Disparity: Companies leveraging AI effectively may accumulate wealth faster, widening the gap between tech-savvy and less tech-savvy populations.

3- Social Interaction: Increased reliance on digital communication can impact interpersonal relationships, potentially leading to loneliness or anxiety.

4- Mental Health: AI tools offer support for mental health through chatbots and apps, but they also raise questions about efficacy and human connection.

5- Informed Citizenship: Access to AI-driven data analytics can enhance public awareness and engagement in civic matters.

6- Misinformation: The spread of AI-generated misinformation poses challenges for democratic processes and informed decision-making.

The intelligent age offers opportunities and challenges that require thoughtful engagement from individuals, communities, and policymakers. Balancing technological progress with ethical considerations and social equity will be crucial in shaping a future that benefits everyone.

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A Genius and A Fool

Those who know how to win are much more numerous than those who know how to make proper use of their victories ------- (Polybius, Greek historian, c.200-c.118 BC)

The dichotomy between a genius and a fool is a fascinating one. A genius is often characterized by exceptional intellectual or creative ability, possessing insight or skills that are far beyond the norm. In contrast, a fool is typically seen as someone lacking in wisdom or common sense, often making decisions or behaving in ways that seem irrational or naive.

However, this contrast isn’t always so clear-cut. Sometimes, what appears as foolishness can be a sign of unconventional thinking that leads to groundbreaking ideas. Similarly, what seems like genius can sometimes be based on eccentric or unorthodox views that others might initially perceive as foolish.

We want our technological infrastructure to mimic nature in the way things fail. That will give us deep complexity rather than just surface complexity, and resilience rather than brittleness.

Elon Musk’s most significant businesses have started with a mission, not a business. Rather than finding a gap in the market to exploit or a tempting arbitrage opportunity, the process begins with him discovering what he considers a species-scale problem.

Musk created SpaceX after realizing that at some point in the future, Earth would die, and humanity would perish with it if it had not populated other planets. His solution was a commercial rocket company capable of delivering humans to Mars.

Just like Musk, China’s innovation ecosystem uniquely combines top-down government–industry coordination with the bottom-up drive of Chinese entrepreneurs. Startups that align with government-picked growth industries of the future can prosper through favorable policies, regulations, and centralized investment in scientific research.

A “whole-of-nation” approach to innovation marshals almost unlimited state resources. From 1995 to 2021, China’s total R&D outlay soared from $18.2 billion to $620.1 billion — a 3,299% increase compared to America’s 277%, according to the Netherlands’ Rathenau Institute. 

China has become a leading global hub for advanced scientific research. According to The Economist, Chinese scientists now lead the world in producing high-impact papers and contributing to famous scientific publications selected after rigorous peer review.

No segment better illustrates China’s technological prowess than clean tech. China now accounts for over 80% of global production capacity in 11 essential technologies, including solar wafers and lithium-ion battery components Just as Chinese companies once benefited from decades of Western investments in traditional industries like autos and chemicals, U.S. and European companies should now cash in on China’s colossal expenditures on clean tech.

China excels at tailoring affordable, innovative solutions to local needs. For instance, Chinese smartphone companies, led by Transsion Holdings, Xiaomi, and Huawei, captured 76% of the smartphone market in India and more than 60% of the African market by 2021. Similarly, Chinese EV manufacturers dominate Latin America, holding an impressive 86% market share. 

China’s markets — often described as a “Gladiators Arena” — often emerge as global champions. Think of CATL (batteries), BYD (batteries and electric vehicles), Tongwei (solar), Goldwind (wind), or Huawei (information and communications technology).

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Algorithms and Monopoly

“When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong” ............Arthur C. Clarke

With digital natives. digital is just not an accessory; it is the fabric of everyday life, and a “computer” is where life pulsate. The internet a playground, the smartphone a trusted friend and social media the town square. The unique understanding of these preferences becomes a dynamic entrepreneurial insight for emerging technology.

Funny memes, shocking news, and images all provide social platforms with unprecedented access to society. The platform influences and determines who sees what when and where. 

Chinese-owned companies are often in service to the Chinese Communist Party, while US-owned companies are in service to business goals. They both have unchecked surveillance power; they are both reshaping societies extracting data to serve content and develop products.

Key Considerations and Challenges

Algorithmic Opacity: The complexity and proprietary nature of algorithms can make it challenging for regulators to understand how decisions are made, assess their fairness, and ensure compliance with regulations.

Accountability: Ensuring that companies are held accountable for the outcomes of algorithmic decisions, particularly when these decisions affect competition and consumer welfare.

Bias and Discrimination: Algorithms can inadvertently perpetuate biases present in training data, leading to unfair treatment of certain groups of consumers.

Consumer Privacy: The extensive use of data by algorithms raises concerns about consumer privacy and the potential for misuse of personal information.

Rapid Innovation: The fast pace of technological innovation can outstrip the ability of regulatory frameworks to keep up, making it challenging to effectively oversee and regulate the use of algorithms.

Global Considerations: The global nature of many dominant firms, especially in technology, complicates the enforcement of antitrust laws, as different jurisdictions may have varying regulations and enforcement capabilities.

 A good question to ask now is when do I accept big data and algorithms to make decisions? 

 - To automatically control my thermostat 

 - To drive my car 

 - To optimize the traffic lights in the city. 

OR

 - To set tax rates, 

 - To set corporate regulations 

 - To set foreign policy. 

OR  

 - To declare war -- right now. 

Every individual, company and government can define their own limits. 

For now I prefer algorithms under my control that works on my behalf and not controlled by a large corporate monopoly. 

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Wellbeing Algorithm

 “If you can’t measure it, you can’t manage it”...... W.E. Deming (business theorist)

The health care industry produces an astonishing amount of data: nearly one-third of the world’s data volume. The amount of data health care providers generate can seem overwhelming—and it can overwhelm your ability to find valuable insights that can help physicians and its patients.

Algorithms analyze genetic data to tailor treatments to individual patients, improving efficacy and reducing side effects. It is about identifying areas where computational intelligence exceeds our capacity to do a given thing. 

We see this already in navigation, algorithms fly planes safer than humans can.

To list AI’s core competences. 

1- AI is really good as a summarizer. 

2- AI is good at explaining things, teaching with infinite patience.  

3- AI is fundamentally a prediction technology. Predictions about whether turning left or right will get you to your destination faster. Predictions about whether a tumor is cancerous might improve medical diagnoses. 

4- AI can assess. Assessing requires outside context and criteria.  

5- AI can decide. A decision is a prediction plus an assessment. We are already using AI to make all sorts of decisions.

At some point everyone will have an algorithm that will maintain their health and wellness.

Health machine learning algorithms analyze medical data (e.g., imaging, lab results) to assist in diagnosing diseases and recommending treatments. Examples include detecting cancers in medical images and predicting the onset of diseases like diabetes.

The Major Attributes:

Data Collection- Gathers data from wearable devices, user inputs (e.g., age, weight, fitness goals), and external sources (e.g., weather, location).

Activity Tracking- Monitors physical activity, heart rate, sleep patterns, and calorie expenditure.

Personalized Recommendations- Uses machine learning to analyze data and suggest tailored workout plans, nutrition advice, and wellness tips.

Progress Monitoring- Tracks progress over time, providing feedback and adjusting recommendations as needed.

Customization- Offers personalized plans that are more effective than generic advice.

Motivation- Provides regular feedback and goals to keep users motivated.

Health Improvement- Helps users achieve better health outcomes through consistent, data-driven advice.

 As a business you should regularly update algorithms based on new research and user feedback to maintain accuracy. As a client using an intuitive user interface, ensure your data is encrypted and only accessible to authorized personnel. 

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Build or Invest

I like reading all day. I can read all day, every day. If you’re the kind of person who wants to read all day every day, that’s probably a good signal you want to invest, not build. --------- Kyle Samani (2024, Venture Capitalist)

It takes over a decade for a successful startup to develop into a thriving public company. As an investor, you won’t receive positive feedback for over 10 years. You will receive plenty of negative feedback while many of your companies shut down. Maintaining belief in your abilities and processes takes a degree of productive delusion and strong self-confidence. 

Due Diligence and Analytical Skills

Evaluation Process: Employs a data-driven approach, with a dedicated team for market research and financial analysis.

Risk Management: Focuses on startups with strong management teams and scalable business models to mitigate risks.

Personal Traits and Skills

Visionary Thinking: Known for identifying disruptive technologies early.

Decisiveness: Quick to make investment decisions, often outpacing competitors.

Resilience: Has experienced failures but learned and adapted from them.

A successful investor combines industry expertise, a strong network, and a keen eye for innovative startups, which together drive their continued success in the venture capital ecosystem.

As a builder Elon Musk said, “boil things down to their fundamental truths and reason up from there as opposed to reasoning by analogy.”

This involves a three-step process: 

(1) challenging conventional thinking, 

(2) breaking problems into their fundamental principles (i.e., their most basic elements or truths) 

(3) creating new solutions from scratch. 

Musk famously used this process to come up with Space X’s affordable and reusable rockets. 

His original plan was to buy secondhand rockets in Russia, but they were too expensive. 

Starting with first principles thinking,

(step 1) he wondered why rockets are so expensive. 

(step 2) After breaking them down into their components, he noticed that the cost of materials 

was only two percent of the total price. 

(step 3) Therefore, he decided to buy materials (such as aluminum alloys, titanium and carbon fiber) on the commodity market and build his own rockets.

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Robot Population

"Robots are the expression of our highest aspirations as human beings: to make life easier, to explore the universe, to extend our reach beyond the limits of our bodies and our minds." - Daniel H. Wilson

The term "robot population" typically refers to the number of robots in existence within a particular context, such as a country, industry, or specific application. Robot population can vary significantly depending on factors such as technological advancements, economic conditions, regulatory frameworks, and societal acceptance of automation.

If Big Tech’s trajectory is any signal, AI tools will increasingly be involved in how we learn and how we express our thoughts. But these tools will also influence how we schedule our daily activities including laundry, how we design products, how we write laws, and even how we diagnose diseases. 

The expansive role of these technologies in our daily lives gives corporations opportunities to exert control over more aspects of society.

• AI-powered ads, industry leaders say, will be much better. 
• Google assures you that AI can tweak your ad copy in response to what users search for, and that its AI algorithms will configure your campaigns to maximize success. 
• IBM is confident its Watson AI will make your ads better.
• Amazon wants you to use its image generation AI to make your toaster product pages look cooler.

Different experts mean different things when they talk about “AI”, but they also hold widely different views on how good it is and where it’s going. 

• Elon Musk thinks we’ll have AI smarter than humans by 2025. 
• Dario Amodei predicts that by2025 “AI models could be able to replicate and survive in the wild”. 
• Yann LeCun of Meta says today’s systems are stupider than a house cat.
• Gary Marcus reckons it’s nothing more than a magic trick. 

Demis Hassabis says Google will spend $100 billion developing AI. And every week, a new AI model appears to supposedly rival GPT-4, but never quite manages it; and each week brings yet another example of the weaknesses of these models. 

Chinese company SenseTime has released SenseNova 5.0, which is reportedly better than GPT-4 in a range of scenarios.  Sam Altman said: “We can say right now, with a high degree of scientific certainty, GPT-5 is going to be a lot smarter than GPT-4 and GPT-6 will be a lot smarter than GPT-5, we are not near the top of this curve.”

However, the impending robot “population boom” is the result of technological breakthroughs, intense investor appetite, labor cost arbitrage, and long-standing demographic trends. 

But buying a robot outright is expensive. 

• Will large corporations choose to buy machines outright? 
• Will they lease them similar to a car? 
• Will they simply “hire” them, as you would any other worker? 

Or should robotics companies give them away for free, receiving a portion of the efficiency gains as royalty? 

In addition to industrial robots, there are various other types of robots, including service robots (such as those used in healthcare, hospitality, and domestic settings), agricultural robots, autonomous vehicles, and drones. The population of these robots varies depending on their respective applications and adoption rates.

The next decade will reveal which model best meets commercial realities.

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