Changing Perspectives:
Traditional computing education often misses the essence of real computing, which involves non-linear complexities of design. Embracing dissatisfaction is crucial for progress in computing, as it drives innovation and challenges complacency.

Design Challenges:
Design is inherently difficult due to our limited brain capacity and tendency to tinker incrementally. External constraints, such as those encountered in architecture, can be valuable in guiding design.

Nature of Computing:
Computing is a “bullshit field” where fads and design theories proliferate due to the lack of natural constraints. The underlying strength of computer materials masks the inadequacies of poor designs.

Historical Context:
In the early days of computing, most researchers had rigorous undergraduate degrees in challenging fields, which aided their thinking about computing.

Dissatisfaction as a Driver:
Effective designers find ways to maintain dissatisfaction without becoming paralyzed by it. The half-life of good ideas is shorter than the lifespan of bits, leading to outdated ideas dominating computing.

Complacency and Education:
Complacency with outdated ideas and practices is a major problem in computing. Students who have adapted to a significant amount of “bullshit” may lack the necessary level of dissatisfaction to drive innovation.

Design Evolution:
Design evolution can be slow, with significant gaps between improvements. An example from prehistoric stone axe design illustrates this slow pace of change.

The Invention of Tools:
Alex proposes that the blunt-end tool was likely reinvented multiple times throughout history. Inventing this tool violated the existing cultural norms and beliefs about the “correct” way of doing things. Attacking a culture’s beliefs and norms can be seen as an attack on the culture itself.

The Psychology of Programmers:
Alex suggests that many people who go into computing are uncomfortable with human interactions and prefer the control and predictability of the mechanical world. This may explain why many computer people struggle to design user-friendly interfaces. Programmers often prioritize efficiency and control over user experience, leading to a backlash against higher-level programming languages. Alex highlights the importance of understanding human psychology and behavior when designing user interfaces.

Human Limitations:
Alex emphasizes that humans have limited resources and are poor at multitasking. We can only hold a few things in our minds at a time and are more resource-limited than we think. Much of our behavior is older than humanity and language, sharing similarities with primates and mammals. We are more theatrical and have less control over our behavior than we realize.

The Reality Kit Experiment:
Alex distributes a reality kit to the audience and asks them to cover one eye and focus on a dot while moving their head back and forth. Many people experience the illusion of the dot disappearing, highlighting the limitations of human perception. This experiment demonstrates how our brains can deceive us and how our perception of reality is not always accurate.

The Blind Spot:
Squids and octopi have blood vessels that supply the eye on the outside of the eye, while mammalian eyes have them coming through and lying on top of the light-sensitive cells. This creates a blind spot where the blood vessels come in and the optic nerve goes out. The blind spot is about the size of a word when looking at something at normal reading distance.

Non-Linear Vision:
Vision is non-linear, meaning that the brain fills in the gaps and constructs a complete image. The brain subtracts out the blood vessels and the blank spot, so we don’t see them.

The Constructed Image:
What we see is not what is actually on our retina, but rather what our brain puts together. This is evident when we move our head and the blind spot winks out, but we continue to see the image.

Our Beliefs Shape Our Perception:
Our brains compare incoming visual information with our beliefs, resulting in a perceived reality that may differ from the actual world. This is evident in the example of two coins held at different distances, where our beliefs cause us to perceive the further coin as 80% the size of the closer coin, even though geometry dictates it should appear half the size.

The Waking Dream of Consciousness:
Consciousness can be seen as a waking dream, a continuous hallucination based on our beliefs and experiences. This is demonstrated by the ability to ignore objects in plain sight, such as the blind spot in our vision, due to our beliefs about the world.

The World of Beliefs vs. the Actual World:
We do not live in a world that accurately reflects the external reality. Instead, we inhabit a world shaped by our beliefs, which can lead to misperceptions and misunderstandings.

The Importance of Accepting Blindness:
To truly understand reality, we must first acknowledge our own blindness and limitations in perception. This requires admitting that our senses and beliefs may not provide an accurate representation of the world.

The Role of Experiments and Science:
Science was invented as a method to overcome our blindness and gain a deeper understanding of the world. By conducting experiments and questioning our assumptions, we can gradually uncover the true nature of reality.

The Contrast between Engineering and Science:
Engineering can be practiced without a deep understanding of the underlying principles, relying on cookbooks and heuristics. Science, on the other hand, requires a willingness to question and explore, leading to a more profound understanding of the world.

The Need to Destroy Reality to See It Clearly:
Microscopes, telescopes, and other instruments are tools that help us see beyond our limited perception. By breaking down reality into its components, we gain insights that would otherwise be inaccessible.

Bias in Human Perception:
Human nervous systems are innately biased, leading to faulty reasoning and conclusions. Biases include: Perfect reasoning from flawed premises, leading to errors like the Holocaust. Abandoning real problems for solvable ones, prioritizing convenience over importance. Scaling issues due to the limitations of Moore’s Law and the inability to adapt to the rapid growth of technology.

Francis Bacon’s Four Idols:
Francis Bacon identified four idols that hinder human understanding: Idols of the Tribe: Innate biases in human perception. Idols of the Cave: Personal biases and beliefs. Idols of the Marketplace: Biases due to language and communication. Idols of the Theater: Biases due to unquestioned traditions and beliefs.

Bacon’s Solution: Science:
Bacon proposed science as a solution to overcome these biases. Science is a collection of heuristics to work around human cognitive limitations. Science is also a process of experimentation, observation, and hypothesis testing to uncover truths about the world.

Conclusion:
Education should focus on teaching students how to see the invisible, not just memorize facts. Computing needs a balance of engineering, science, and an understanding of human biases to progress. Science is a crucial tool for overcoming biases and limitations in human perception and reasoning.

Built-in Human Universals:
Humans are not naturally born with the ability to think; we learn how to think through cultural education and rote memory. Anthropologists have identified human universals, traits that are present in every known culture, such as language, social kinship, culture, and fantasy. These universals are likely genetic and provide a starting point for learning and understanding the world around us.

Learning and Adapting:
Babies are born with a natural interest in learning and seeking out patterns in their environment. We develop high-resolution versions of low-res patterns, such as learning to recognize faces and objects. Our learning process takes time and is influenced by our surroundings and experiences.

Cultural Differences and Similarities:
Anthropologists initially believed that cultural differences were biological but later discovered that cultures share common categories and universals. The fundamental theory of anthropology is that a baby can be taken from any culture and raised in another and still become a full-fledged member of that community.

Progress and New Ideas:
Progress and new ideas are not innate; they are inventions that have emerged over time. Traditional cultures are incredibly stable and resist change, leading to the idea of the status quo. The idea of progress and constitutional conventions every 50 years was a new concept in the 18th century.

Competition, Cooperation, and Equality:
Our nervous system is wired to prefer differences over similarities, making it easier to identify contrasts and make quick reactions. Vendetta and revenge are universal concepts found in every traditional culture, and the legal system aims to prevent feuds and vendetta. Competition, cooperation, and the idea of equal rights are concepts we must learn and understand.

Understanding New Ideas:
We are naturally inclined to prefer familiar and easy-to-understand concepts, often leading us to overlook new and complex ideas. News and media tend to focus on familiar and easy-to-digest information rather than complex and challenging concepts. We need to be aware of our biases and actively seek out new and unfamiliar ideas to expand our understanding.

Unexpected Events and Emotional Responses:
When something unpredictable occurs, it can trigger excitement and a sense of wonder, as it opens up new possibilities and perspectives. Conversely, when something unexpected happens that doesn’t make sense, it can lead to feelings of frustration and upset.

Art’s Purpose:
Art serves as a reminder that there’s more to the world than what we currently perceive. It helps us transcend our limited perspectives and connect with something greater.

Art’s Varied Reactions:
Art can elicit different reactions, such as laughter, surprise, and excitement. Jokes are a form of art that unexpectedly takes us down a certain path and then surprises us with a punchline. Scientific discoveries can also be seen as a form of art, as they reveal new and unexpected aspects of the universe.

Computing and Art:
Computing can be seen as both a problem and an opportunity for art. The loaded nature of computing, with its vast amount of information and potential connections, can be overwhelming. However, computing also offers new possibilities for artistic expression and exploration.

Measuring Progress in Art:
True progress in art is often measured by its ability to help us understand and connect with the deeper, more meaningful aspects of life.

Art and Memory:
Art has the power to remind us of important things that we have forgotten or overlooked. It can transport us into familiar yet forgotten realms, evoking memories and emotions that may have been buried deep within us.

Examples of Aesthetic Experiences:
Feynman’s perspective highlights that science and mathematics can also be considered art forms due to their aesthetic and transformational qualities. People’s reactions to various situations, such as laughing at jokes or feeling awe at natural wonders, provide insights into the nature of aesthetics.

What is the MacReady Sweet Spot?:
The MacReady sweet spot is a concept in engineering that emphasizes the importance of spending sufficient time to identify the optimal solution to a problem. It is named after Kelly Johnson, also known as MacReady, a renowned aeronautical engineer who won the Mechanical Engineer of the Century Award.

Importance of Identifying the MacReady Sweet Spot:
It allows engineers to find a solution that makes the actual problem easier to solve. This approach can lead to significant breakthroughs and innovations. It involves spending an arbitrary amount of time to find the optimal solution rather than focusing on incremental improvements.

Examples of MacReady’s Success:
He was able to achieve manned flight in less than six months, while others had tried for 45 years. He won the first solar-powered race in Australia by more than 24 hours. He was one of the main inventors of all-electric cars.

Common Mistakes in Engineering:
Focusing on solving the actual problem instead of identifying the underlying principles that make the problem easier to solve. Being seduced by incremental improvements (the “better” trap) or aiming for perfection (the “perfect” trap), both of which can prevent finding the true solution. Not spending enough time to thoroughly understand the problem and identify the MacReady sweet spot.

Conclusion:
Engineers should strive to identify the MacReady sweet spot in their work to find innovative and effective solutions to engineering problems. This approach involves spending sufficient time to understand the underlying principles of the problem and identifying the optimal solution, rather than focusing on incremental improvements or aiming for perfection.

Inspiration and Motivation:
McCready was motivated by a personal financial crisis to pursue man-powered flight. He realized the potential of the Kramer Prize for man-powered flight to solve his brother-in-law’s debt.

Identifying the Problem:
McCready observed that previous attempts at man-powered flight failed due to insufficient crashes and inadequate airframe testing.

Innovative Methodology:
McCready prioritized creating an airframe that could withstand multiple crashes daily, allowing for rapid experimentation and learning. He focused on developing a lightweight and durable airframe with an enormous wing, enabling more flight attempts.

Initial Success:
Within six to eight weeks, McCready’s team achieved more flights than all previous attempts combined. They successfully tackled the control system challenges of flying a large, low-speed aircraft with significant rotation and inertia.

Scaling Up:
After achieving initial success, McCready’s team aimed for the larger prize of crossing the English Channel. They abandoned the traditional airplane approach and instead focused on developing a unique craft tailored to the specific requirements of man-powered flight.

The Key to Success:
McCready attributed their success to their focus on the entire flight rather than just building an airplane. They recognized that scaling up required new aerodynamic solutions and innovations.

Slow Thinking and Iterative Approach:
McCready’s approach involved slow thinking and a willingness to deviate from conventional wisdom. He emphasized the importance of gathering sufficient knowledge and experimentation to develop a viable solution.

Moore’s Law and Long-Term Technological Projections:
Alex’s experience in 1968 led him to recognize the potential of technology for education, especially for children. Moore’s Law, which predicts exponential growth in transistor count and computing power, provided a basis for long-term technological projections.

Envisioning Future Technologies:
Alex emphasizes the importance of looking far into the future and envisioning technologies that may seem impossible with current limitations. He suggests taking Gordon Moore’s 30-year projection and exploring what could be achieved with the anticipated technological advancements.

Challenging Assumptions and Pushing Boundaries:
Alex encourages questioning the status quo and asking bold questions about future technologies, rather than being limited by current engineering capabilities. He believes that aiming for distant goals can inspire innovation and drive progress.

Moore’s Law and Access to Supercomputers:
Moore’s Law enables access to supercomputer-level computing power for consumers in the future. This opens up possibilities for simulating complex problems and exploring new frontiers in technology.

Computing on Outdated Technology:
Alex criticizes the use of outdated computers and software in education, arguing that it hinders progress and prevents students from engaging with the future. He emphasizes the need for students to have access to cutting-edge technology to prepare them for the challenges of the future.

Complexity of Future Computing:
Alex highlights the increasing complexity of computing tasks in the future, requiring extensive optimization beyond the capabilities of individual students or small groups. He compares this to the complexity of chemical rocketry, suggesting that current educational practices are inadequate for preparing students for future computing challenges.

Impact of Commodity Devices on Computer Science Research:
Alex points out the negative impact of commodity devices on computer science research, arguing that they have hindered innovation and set back research progress. He believes that the widespread availability of consumer-grade devices has led to complacency and a lack of motivation to push the boundaries of technology.

Perception of Innovation Difficulty:
Alex responds to a question about the perceived difficulty of innovation today compared to 30 years ago. He clarifies that he is not suggesting that innovation was easier in the past, but rather that it may be perceived as more difficult today due to the high expectations and widespread satisfaction with existing technologies.

Abundant Resources and Limited Utilization:
Alex expresses his amazement at the current abundance of storage resources, contrasting it with the engineering challenges faced in the past due to limited storage.

The Allure of Computer Building in Earlier Times:
Back when building a computer was a complex task, major universities engaged their students in designing and creating both hardware and software for their own systems.

The Difficulty of Convincing People in Modern Times:
Alex finds it harder to convince people to undertake challenging projects in the present compared to the past, possibly due to the increased availability of resources.

The Xerox PARC Alto:
In 1973, Xerox PARC developed the Alto, a groundbreaking computer system that was conceptually similar to the Macintosh introduced in 1989.

The Cost and Impact of the Alto:
The Alto, costing approximately $125,000 in today’s currency, enabled experimentation and user interface innovations without optimization constraints.

Dan Eagles and Software Development:
Dan Eagles utilized Alex’s ideas to develop innovative software for the Alto, which later influenced Steve Jobs’ vision for the Macintosh.

The Legacy of the Alto:
Steve Jobs’ visit to Xerox PARC in 1979 exposed him to the Alto, leading to the development of the Macintosh in 1984, showcasing the Alto’s enduring impact on the computing industry.

The Importance of Flight Simulators in Software Development:
Flight simulators allow for extensive experimentation and optimization without the need for real-world resources. This approach enables the creation of innovative software solutions that push the boundaries of what is possible.

Microsoft Word as an Example:
Microsoft Word, initially developed in 1974, took a decade to become a commercial product in 1984. This highlights the lengthy development process required for groundbreaking software.

The Problem with Cyclical Software Development:
Traditional software development cycles limit progress to small, incremental changes. To achieve significant advancements, developers need to adopt a longer-term perspective and invest in substantial development efforts.

The Heuristic Approach to Innovation:
Innovation involves generating an initial concept, testing its feasibility, securing funding, and building a flight simulator. This approach facilitates real progress in computing by enabling the exploration of new ideas and technologies.

Imagination and Resource Constraints:
While imagination is limitless, the availability of resources can hinder the realization of innovative ideas. However, the primary obstacle to innovation often lies within individuals’ self-imposed limitations rather than external factors.

The Difficulty of Identifying Truly New Innovations:
Determining the novelty of an idea can be challenging, requiring exploration and experimentation. The transition from design to optimization can hinder the ability to reassume the design mindset, leading to missed opportunities for innovation.

Evidence Supporting the Flight Simulator Approach:
Empirical evidence supports the effectiveness of the flight simulator approach in driving software innovation.

Goal Conservatism vs. Knowledge Curiosity:
Most humans (95%) are goal conservative, meaning they evaluate new tools or ideas based on their contribution to their current goals. A small percentage (5%) are more interested in the merits of new things and may abandon old goals for new opportunities.

Interdirected vs. Outer-directed:
About 85% of people are outer-directed, meaning they are influenced by social norms and expectations. About 15% are interdirected, meaning they are less influenced by social norms and more focused on their own thoughts and values.

Conflict between Ideas New and Interdirected vs. Goal Conservative and Outer-directed:
There is a significant conflict between those who value new ideas and are interdirected, and those who are goal conservative and outer-directed. This conflict drives many of the dynamics seen over the past few thousand years.

Time for Social Acceptance of New Trends:
It takes a long time, often around 30 years, for new trends or ideas to become socially acceptable. This is because it takes a generation to become accustomed to the new thing.

Historical Examples of Slow Adoption of New Ideas:
It took about 30 years for baseball caps worn backward to become socially acceptable. It took about 30 years for girls to show their belly buttons after it became popular among outliers.

Typewriter Keyboard Design:
The QWERTY keyboard layout was invented to intentionally slow down typists, especially women, who were faster and more accurate than men. The Blickensderfer typewriter of 1904 had an optimized keyboard layout, but it was eventually changed to QWERTY due to resistance to change.

QWERTY as an Example of Stubbornness to Change:
QWERTY remains the standard keyboard layout despite its inefficiencies. Identifying the “QWERTYs” in programming languages can reveal inefficient or outdated elements that hinder progress.

English Language’s Focus on Things:
The English language is heavily focused on things rather than abstract concepts or relationships.

Ideas as Matter vs. Light:
Treating ideas as matter implies they don’t interpenetrate, like physical objects. Alternatively, treating ideas as light introduces the concept of superposition, allowing for multiple perspectives to coexist without immediate resolution.

Design as Postponing Decisions:
The design process often involves holding seemingly incompatible ideas simultaneously to gain a comprehensive understanding.

Reaching Goals Indirectly:
Sometimes, the path to a goal involves taking a detour or exploring alternative approaches.

The Superhighway of Powerful Ideas:
Identifying and leveraging powerful ideas can serve as a metaphorical superhighway, accelerating progress towards a desired outcome.

Eliminating Terrain Problems:
Addressing underlying issues and obstacles can lead to more efficient and effective problem-solving.

Solving Large Problems vs. Small Problems:
Real-world problem-solving often involves tackling large, complex issues that require different approaches compared to smaller, algorithmic problems.

Graduate School Focus on Large Problems:
Graduate-level education typically emphasizes addressing large problems, as these reflect the challenges encountered in real-world scenarios.

Discipline in Design:
Design involves two distinct worlds: engineering and problem-solving. Military engagement and policing require different types of discipline. Baseball analogy: striking out is not an error; it’s an overhead of attempting something difficult.

Applying Discipline to Computing:
Technical skills are important but should not hinder creative thinking. Compartmentalize different aspects of design, including science and engineering. Avoid munging variables to make state changes, as it leads to debugging difficulties.

Munging Variables:
Munging variables is conceptually satisfying but can lead to debugging problems. It’s equivalent to sending messages to multiple recipients without their knowledge.

Lucid Programming Language:
Lucid is an attempt to simplify functional programming and make it more intuitive. The swirls mechanism in Lucid helps conceptualize how worlds operate.

Atomic Transactions:
Atomic transactions are essential in databases, especially for bank records and other sensitive data. Companies are legally responsible for maintaining the integrity of their databases.

Programming Language Design:
Alex emphasizes the importance of 20 driving examples when designing a programming language, as they help define the language’s core features and functionalities. Critically evaluating each example and creating a small illustration of how it should function are essential steps in the design process.

Atomic Transactions:
Alex highlights the lack of atomic transactions in programming languages, leading to data inconsistencies. The concept of atomic transactions was controversial in the late 60s and early 70s, but Jim Gray made significant contributions to its practical implementation in IBM System R.

Whirls and File Versioning:
Whirls offers a mechanism for fine-grained undo operations, allowing developers to revert to specific states before changes were made. File versioning represents the coarsest grain of undo in checkpointing, while Whirls enables real-time undo for humans.

Backups and Alternative Pathways:
Whirls allows backups to a previous state, ensuring data integrity. Rethinking the concept of TRY without side effects is necessary to handle alternative pathways in programming. Possible worlds reasoning from AI may provide insights for handling such scenarios.

Complex Programs and Uncertain Pathways:
Whirls enables the creation of programs where every pathway is not guaranteed, but the state of each pathway is fully understood. This opens up possibilities for developing programs that address complex goals beyond simple algorithms.

Unexpected Innovation:
In response to a claim that it’s impossible to go downwind faster than the wind, a group of engineers in Silicon Valley took on the challenge and proved otherwise. Their invention involved a device that harnesses the power of the wind to achieve speeds faster than the wind itself.

Sailing Expertise:
Alex, a former sailor, brings up the example of sailboats that can sail faster than the wind by utilizing Bernoulli’s principle and the keel’s stabilizing effect. Sailboats can achieve speeds up to almost twice the speed of the wind in favorable conditions.

Inspiration from Sailboats:
The engineers drew inspiration from the sailing principle of using the sail as a wing to generate lift and propel the boat forward. By incorporating propellers into their design, they were able to mimic this effect and achieve speeds faster than the wind.

Saul Griffin’s Involvement:
Saul Griffin, a renowned mechanical engineer, is mentioned as a possible contributor to this innovative device. His expertise in mechanical engineering and innovative thinking aligns with the approach taken by the engineers in Silicon Valley.

Marketing Considerations:
The discussion shifts to marketing perspectives, suggesting that marketers seek solutions that challenge conventional wisdom and offer unique benefits.

Marketing vs. Education:
Marketing aims to identify and fulfill human desires, often amplifying innate genetic predispositions with technological advancements. Education, in contrast, focuses on teaching individuals what they need, which may conflict with their natural inclinations.

The Unnatural Nature of Education:
Education often trains individuals to control impulses and adopt behaviors that go against their natural genetic tendencies. This is why writing, deductive mathematics, science, democracy, and equal rights had to be invented, as they are not innate human inclinations.

Computing’s Need for Better Tools:
Computing lags behind other engineering fields in terms of user-friendly tools. CAD systems in mechanical, electrical, biological, and structural engineering are far more advanced than those used in computing, allowing for automated simulations and direct fabrication.

The Irony of Computer Programmers:
Computer programmers, who create the CAD systems used in other fields, often refuse to use reasonable tools and programming requirements for their own work.

The Future of Computing:
The future of computing lies in embracing the “cab-syn-fab” cycle, which involves designing, simulating, and fabricating systems using advanced tools.

Conclusion:
Alex emphasizes the need for educators and computing professionals to recognize the difference between what people want and what they need, and to use technology to promote positive behaviors and advance human progress.

Alex’s Disappointment in Brain Bar Submissions:
Alex expressed disappointment in the lack of participation and quality in the brain bar submissions. He believes that students have interesting and enlightening things to say about each other but were not motivated to do so. Alex emphasizes that the brain bar is anonymous and not graded, so the primary purpose is to encourage free expression of thoughts.

Alex’s Perspective on Writing Assignments:
Alex believes writing is a crucial tool for organizing and expressing thoughts. He disapproves of teachers assigning writing tasks without actively participating in the writing process themselves. Alex encourages students to view writing as a beneficial exercise rather than a burdensome chore.

Anonymous Brain Bars vs. One-Pagers:
Alex prefers anonymous brain bars as they encourage open and honest feedback among classmates. One-pagers, on the other hand, should not be anonymous as they serve as a foundation for peer feedback and iterative improvement.

Importance of Class Participation:
Alex emphasizes the importance of completing both brain bars and one-pagers, considering it unprofessional not to do so. Students who are not interested in participating in these assignments are encouraged to drop the class. Timely submission of assignments is crucial, with one-pagers due by Saturday night for peer feedback and iteration by Tuesday.