“Be careful who you praise and admire. Be careful who you look down upon and wish to avoid becoming.”
Morgan Housel
Reality has a surprising amount of detail (johnsalvatier.org)
In his blog post "Reality has a surprising amount of detail," John Salvatier explores the intricate complexities of everyday tasks and the broader implications for intellectual endeavors. Drawing from personal experiences, such as building stairs with his father, Salvatier demonstrates how seemingly simple activities are fraught with nuanced challenges and unexpected details. He extends this observation to various fields, arguing that this complexity is a fundamental property of reality, not just human-centric activities. Salvatier warns that failing to recognize these details can lead to intellectual stagnation, even for experts. He emphasizes the importance of seeking out and paying attention to these details to avoid getting intellectually stuck and to improve one's understanding and problem-solving abilities.
Key Points
Complexity in Everyday Tasks
Salvatier's detailed recounting of his experience building basement stairs is a microcosm for understanding complexity in the broader world. Each step in the process, from cutting boards to aligning brackets, reveals hidden layers of difficulty that are not immediately apparent. This resonates with anyone undertaking a DIY project, only to find it far more challenging than anticipated.
Universality of Detail
The post emphasizes that this complexity is not isolated to specific tasks like carpentry but is a universal reality feature. Whether it’s programming, where new tasks constantly introduce new "fiddly" details, or scientific phenomena like boiling water, the hidden intricacies are ever-present. This universality suggests that a careful, detail-oriented approach is valuable in virtually any endeavor.
Key Concepts
Invisible vs. Transparent Details
Salvatier introduces a critical distinction between "invisible" and "transparent" details. Invisible details are those we haven't yet noticed and, therefore, cannot act on. Once we become aware of them, they become transparent, seamlessly integrating into our understanding to the point where we might forget they were a challenge. This concept is crucial for learning and skill development, highlighting why beginners often struggle with tasks that experts find straightforward.
Intellectual Stagnation
The idea of intellectual stagnation is a powerful warning. Salvatier suggests that even experts can become stuck if they fail to recognize critical details. This can lead to frustration and the mistaken belief that a problem is insurmountable or that one's approach is fundamentally flawed. Recognizing and incorporating new details can be the key to breaking through these intellectual barriers.
Practical Implications
Problem-Solving and Innovation
An awareness of hidden details can significantly enhance problem-solving abilities. By acknowledging that unseen complexities exist, we can adopt a more thorough and investigative approach, leading to more innovative solutions. This mindset is particularly important in fields requiring constant innovation, such as technology and science.
Learning and Skill Acquisition
For learners and educators, understanding the role of invisible details can shape how new skills are taught and acquired. It emphasizes the need for patience and persistence, as initial difficulties are often due to unnoticed complexities rather than a lack of ability.
Teamwork and Collaboration
Recognizing that different people notice different details can improve teamwork and communication. When team members appreciate the unique perspectives and insights each brings, conflict can be reduced, and collaborative problem-solving enhanced. This is especially relevant in interdisciplinary teams, where diverse expertise can uncover more details.
Broader Significance
Real-World Examples
Salvatier's insights apply to numerous real-world scenarios. For instance, in software development, the "fiddliness" of programming means that new developers often struggle with tasks that seasoned programmers find routine. Similarly, in scientific research, the path to discovery is often littered with unexpected challenges that require meticulous attention to detail.
Personal Growth
On a personal level, embracing reality's complexity can lead to greater resilience and adaptability. By expecting and preparing for hidden details, individuals can better navigate life's challenges, from career development to personal projects.
Conclusion
John Salvatier's blog post underscores a fundamental truth about reality: it is rife with unexpected details that can complicate even the simplest tasks. Recognizing and embracing this complexity is crucial for effective problem-solving, continuous learning, and successful collaboration. By doing so, we can avoid intellectual stagnation and cultivate a mindset that is both detail-oriented and adaptable, better preparing us for the challenges we encounter in both professional and personal contexts.
Key Quotes
"If there’s one thing I’ve learned from all this building, it’s that reality has a surprising amount of detail."
"You might think that the fiddliness of programming is a special feature of programming, but really it’s that everything is fiddly, but you only notice the fiddliness when you’re new."
"Surprising detail is a near universal property of getting up close and personal with reality."
"The more difficult your mission, the more details there will be that are critical to understand for success."
"Before you’ve noticed important details they are, of course, basically invisible."
"If you’re trying to do impossible things, this effect should chill you to your bones. It means you could be intellectually stuck right at this very moment, with the evidence right in front of your face and you just can’t see it."
Why It Matters
Salvatier's insights are crucial for several reasons:
Enhanced Problem-Solving: Recognizing the inherent complexity in tasks can improve problem-solving skills by encouraging a more thorough and detailed approach.
Avoiding Intellectual Stagnation: Understanding that details matter helps prevent intellectual stagnation, allowing individuals and teams to innovate and overcome challenges more effectively.
Broad Applicability: The concept of hidden complexity is applicable across various fields, from programming to physics, making it a universal principle that can enhance understanding and performance in diverse areas.
Improved Communication: By appreciating the details others find important, we can improve communication and collaboration, reducing conflicts and enhancing teamwork.
Mindfulness and Observation: Salvatier's advice to seek out and notice details encourages mindfulness and a more observant approach to life, leading to deeper insights and a better appreciation of the world around us.
Why reliable AI requires a paradigm shift (substack.com)
In the article "Why reliable AI requires a paradigm shift," Alejandro Piad Morffis discusses the critical issue of hallucinations in AI systems, particularly large language models (LLMs). Hallucinations refer to instances where AI generates outputs that appear coherent and plausible but are factually incorrect or nonsensical. These hallucinations pose significant challenges to the reliability and trustworthiness of AI, especially in high-stakes applications like healthcare, finance, and public safety. Morffis argues that the root cause of hallucinations lies in the fundamental assumptions of current language modeling paradigms, which rely on statistical patterns in training data rather than explicit factual knowledge. He suggests that addressing hallucinations will require a paradigm shift in machine-learning approaches.
Key Points
Definition of Hallucinations:
Hallucinations in AI are outputs that seem plausible and coherent but do not reflect reality or the intended purpose.
They differ from out-of-distribution errors and biased outputs, as hallucinations occur within the input distribution and lack obvious telltales for detection.
Impact of Hallucinations:
Hallucinations can lead to erroneous decision-making and harmful outcomes in critical applications like healthcare and finance.
They undermine user trust and pose barriers to the widespread adoption of AI.
Causes of Hallucinations:
Current language models generate outputs based on statistical correlations rather than explicit factual knowledge.
The training data, often sourced from the internet, contains inaccuracies and fabricated information, contributing to hallucinations.
The smooth, lossy compression of training data in models leads to plausible but potentially false outputs.
Challenges in Eliminating Hallucinations:
Hallucinations are an inherent feature of the statistical nature of generative models.
Even with high-quality data, the probabilistic nature of these models means hallucinations can never be eliminated.
Recent research suggests that any sentence that can be generated has a prompt that can trigger it, making it impossible to guarantee a hallucination-free system.
Mitigation Strategies:
Incorporating external knowledge bases and fact-checking systems.
Developing more robust model architectures and training paradigms.
Enhancing transparency and interpretability of AI models.
Establishing standardized benchmarks and test sets for hallucination assessment.
Fostering interdisciplinary collaboration to improve understanding and mitigation of hallucinations.
Need for a Paradigm Shift:
Current generative AI models, by design, will always produce some hallucinations.
A new machine learning paradigm beyond current statistical models is needed to address the issue fundamentally.
Key Quotes
"Hallucinations are the fundamental barrier for the widespread use of AI, and they won't be solved anytime soon."
"Hallucinations can lead to erroneous decision-making, false conclusions, and potentially harmful outcomes, especially in critical applications such as healthcare, finance, and public safety."
"The statistical language modeling paradigm, at its core, is a hallucination machine."
"There are absolutely zero generative AI systems today that can guarantee they don't hallucinate."
Why It Matters
Addressing the issue of hallucinations is crucial for the reliable and trustworthy deployment of AI systems. As AI becomes more integrated into critical areas such as healthcare, finance, and public safety, the consequences of hallucinated outputs can be severe. Understanding and mitigating hallucinations will help develop more robust and reliable AI systems, ensuring they can be trusted for decision-making in high-stakes environments. Moreover, the call for a paradigm shift in AI modeling emphasizes the need for innovative approaches beyond current limitations, potentially leading to more advanced and reliable AI technologies.
Ode to software - by Rohit Krishnan - Strange Loop Canon
In "Ode to Software," Rohit Krishnan explores software development's intricate, often ephemeral nature and its profound impact on modern society. Krishnan argues that software, unlike tangible structures such as the pyramids or the Colosseum, is a continuous and complex process that reflects management decisions and problem-solving steps. He compares the creation and maintenance of software to the development and upkeep of vast empires or intricate cultures, emphasizing that software's value lies not in its static existence but in its dynamic evolution and iterative improvement.
Krishnan also highlights the immense scale of human effort invested in creating software, comparing it to the construction of historical monuments and the running of large organizations. He underscores that software development is a never-ending cycle of refactoring and adaptation, driven by the need to stay relevant in a rapidly changing technological landscape. The article touches on technical debt, the importance of open-source contributions, and the necessity of craftsmanship in software development.
Key Points
Software as a Kludge: Krishnan describes the software as a "clumsy, inelegant, and jerry-built contraption" that, despite its imperfections, functions to some degree.
The scale of Effort: The article compares the man-hours involved in software development to the construction of historical monuments, revealing that modern software projects like Facebook and Uber have required hundreds of millions of man-hours, rivaling the efforts behind monumental constructions.
Continuous Evolution: Software is not a static product but a process that requires constant updates and improvements. It evolves through iterative development, like cultures and organizations.
Technical Debt: Krishnan redefines technical debt as the commit history of past decisions, suggesting that a pristine codebase is an unrealistic ideal.
Complexity and Dependencies: The dependency graphs for machine learning frameworks like TensorFlow and PyTorch illustrate the intricate web of dependencies that characterize modern software.
Historical Comparisons: The article draws parallels between software development and empire maintenance, emphasizing the ongoing effort required to keep both running smoothly.
Open Source and Collaboration: Contributions to open source projects are likened to building blocks others can reuse, pushing the collective expertise forward.
Ephemerality and Craftsmanship: Unlike physical monuments or classic works of art, the code itself is transient and often undervalued. The true value lies in the ability to create and innovate continuously.
Key Quotes
"Software, like all technologies, is a kludge. It's a clumsy, inelegant, and jerry-built contraption that sort of works, some of the time."
"Creating software is some of the most work we’ve put into building almost anything, far beyond the wonders in Rome or Luxor."
"Technical debt isn’t debt, it’s the commit history of the decisions made in the past."
"Software is ephemeral because what we want is ephemeral. We find new ways of doing things, and it changes."
"You don’t win by creating the Pyramid, you win by creating something as splendorous as the pyramids, faster. And then again!"
Why It Matters
Krishnan's insights underscore software's transformative role in contemporary society. Understanding software as a dynamic and iterative process rather than a static product helps us appreciate the continuous innovation and effort required to maintain and improve technological systems. This perspective is crucial for software developers, managers, and anyone involved in the tech industry, as it highlights the importance of adaptability, ongoing learning, and collaboration.
Moreover, recognizing the ephemeral nature of software shifts the focus from the end product to the craftsmanship and problem-solving skills involved in its creation. This viewpoint can inspire a greater appreciation for the work that goes into developing and maintaining the digital tools and platforms that underpin modern life. By comparing software development to historical and cultural processes, Krishnan provides a broader context for understanding the challenges and rewards of this critical field.
There's Plastic in My Plaque! - by Eric Topol (substack.com)
In "There's Plastic in My Plaque!" Eric Topol discusses the groundbreaking discovery of microplastics and nanoplastics (MNPs) in atherosclerotic plaques and their association with adverse cardiovascular outcomes. Published in the New England Journal of Medicine, the study reveals that MNPs are present in the plaques of patients undergoing carotid endarterectomy and that their presence correlates with a significant increase in the risk of death, heart attack, and stroke. The article emphasizes the pervasive nature of plastics, their toxicological impacts, and the urgent need for strategies to mitigate exposure.
Key Points
Breakthrough Discovery: Detection of MNPs in atherosclerotic plaque tissue for the first time.
Study Background: Conducted in Italy, the study involved 257 patients, 58% of whom had MNPs in their plaques, linked to a 4.5-fold increase in adverse cardiovascular events.
Health Risks of Plastics: Plastics, produced in massive quantities, contain additives that are carcinogenic, neurotoxic, and endocrine-disrupting. MNPs have been linked to numerous health issues, including asthma, cancer, cognitive impairment, and more.
Study Findings: The study identified various plastic polymers in plaques, with polyethylene being the most common. Patients with MNPs showed increased inflammatory markers and lower collagen content in their plaques.
Pro-Inflammatory Impact: MNPs in plaques were associated with elevated levels of inflammatory cytokines and markers, suggesting a link to plaque instability and cardiovascular risk.
Implications for Public Health: The pervasive presence of MNPs in the environment and their potential health impacts call for urgent action to reduce plastic use, especially single-use plastics.
Policy Recommendations: The article advocates for major efforts to address plastic pollution, including banning single-use plastics and implementing strategies to reduce toxic exposure.
Key Quotes
"The finding of microplastics and nanoplastics in [atherosclerotic] plaque tissue is itself a breakthrough discovery that raises a series of urgent questions." — Philip Landrigan
"It’s a deeply concerning report that will (of course) require independent replication."
"The massive, unchecked buildup of plastics with overwhelming evidence of our ingestion and inhalation, with systemic distribution within our bodies through blood circulation, should provoke major efforts to get ahead of this plastic-demic."
"The new study takes the worry about micronanoplastics to a new level—getting into our arteries and exacerbating the process of atherosclerosis, the leading global killer—and demands urgent attention."
Why It Matters
This study is significant because it highlights a previously unknown risk factor for cardiovascular disease, the leading cause of death worldwide. The discovery that MNPs are present in atherosclerotic plaques and linked to worse clinical outcomes adds a new dimension to our understanding of cardiovascular risk and the broader implications of plastic pollution. It underscores the urgent need for public health interventions to reduce plastic exposure and calls for further research to confirm and expand on these findings. This information is crucial for policymakers, healthcare providers, and the public as it emphasizes the importance of addressing plastic pollution's environmental and health impacts.
Jevons paradox is not surprising | Seth's Blog (seths.blog)
In Seth Godin's blog post "Jevons Paradox is Not Surprising," he discusses the concept of the Jevons Paradox, which states that increased efficiency in resource use often leads to higher overall consumption. Godin gives several examples to illustrate this phenomenon, such as improved fuel efficiency in cars leading to more driving and advancements in AI increasing the demand for programmers. He argues that this paradox is a natural outcome of human behavior and innovation, where making something easier or more efficient makes it more attractive and thus more widely used. Godin also expresses optimism about the future of AI, suggesting it will create more opportunities than it eliminates.
Key Points
Jevons Paradox Explained: The paradox suggests that as a resource becomes more efficient, its overall consumption increases rather than decreases.
Examples of Jevons Paradox:
Fuel Efficiency: Better gas mileage leads to more driving and fuel consumption.
AI and Programming: As AI improves at writing code, the demand for programmers rises because more efficient code is more appealing and needed in larger quantities.
Household Appliances: Time-saving appliances lead to higher standards of cleanliness and more frequent use because they make the task easier.
Human Behavior and Innovation: Godin emphasizes that humans tend to create more jobs and opportunities as they innovate, pointing out that billions of jobs have been created during his lifetime.
Optimism about AI: Despite common fears, Godin is optimistic that AI will generate more opportunities than it will destroy.
Key Quotes
"When a resource can be used more efficiently, we end up using more of the thing, not less."
"When cars get better gas mileage, people drive more, and consumption can actually go up."
"When AI learns to write computer code, the demand for programmers goes up, because more efficient code is more attractive, and we want more of it."
"Household appliances that are designed to save time and trouble end up being used for more than simply maintaining the previous level of tidiness."
"My hunch is that AI is going to produce far more opportunities than it destroys."
Why It Matters
Understanding Jevons Paradox is crucial for policymakers, businesses, and individuals as it challenges the assumption that efficiency improvements alone will lead to reduced resource consumption. This insight is pivotal in designing sustainable policies and technologies. Godin's perspective also underscores the importance of anticipating human behavior in response to technological advances. His optimism about AI creating opportunities rather than destroying jobs can help guide more balanced and forward-thinking approaches to integrating AI into various sectors. This article serves as a reminder that efficiency should be paired with conscious efforts to responsibly manage consumption and leverage new opportunities.
Against the nerds | Locklin on science (wordpress.com)
In the blog post "Against the Nerds" by Scott Locklin, the author argues that the current societal belief in the necessity of a "nerd clerisy" to manage and advance civilization is misguided. Locklin traces the rise of this clerisy back to the 1930s under FDR, criticizing its effectiveness and asserting that true progress and victories, such as those in World War II, were achieved not by nerds but by pragmatic leaders like Leslie Groves, who managed and directed these intellectuals. He argues that nerd proliferation post-WWII resulted from prosperity rather than a driver of it and that nerds should remain in their laboratories under the strict supervision of more practical, hands-on leaders. The author contrasts the failures of nerd-led societies with the successes of those led by more physically and practically oriented individuals, proposing that nerds lack objectivity and are often too dogmatic, making them unsuitable for leadership roles.
Key Points
Historical Context and Critique of Nerd Clerisy:
Locklin attributes the rise of the nerd clerisy to the policies of FDR in the 1930s.
Critiques the effectiveness of this clerisy, suggesting it contributed to the Great Depression rather than alleviating it.
Argues that true wartime success was due to pragmatic leaders like Leslie Groves, who managed the nerds effectively.
Post-War Nerd Proliferation:
The post-WWII proliferation of nerds is seen as a result of American prosperity, not its cause.
It suggests that the current system overemphasizes the need for extensive formal education (Ph.D.s), which delays practical productivity.
Failures of Nerd-Led Societies:
It cites examples of nerd-led societies like Weimar Germany and the Soviet Union during peak Gosplan and certain periods of Chinese history, labeling them failures.
Contrasts these with successful, non-nerd-led entities like the British East India Company.
Critique of Nerds in Modern Leadership:
Argues that successful tech leaders are not true nerds but have practical, hands-on experience (e.g., Elon Musk, Larry Ellison).
Criticizes the dogmatic nature of nerds, who often cling to ideas even when proven wrong.
Nerds and Objectivity:
Asserts that nerds are good at absorbing and regurgitating dogma but cannot critically analyze and discard incorrect ideas.
Suggests that nerds' identity is tied to their intellectualism, making them resistant to change.
Management of Nerds:
Proposes that nerds should be managed by practical, hands-on leaders who can hold them accountable.
Emphasizes the need for a balance between intellectual input and practical execution.
Key Quotes
On the Rise of Nerd Clerisy:
“One of the delusions of modern times is that we need a nerd clerisy to help us run things.”
On American Victory in WWII:
“Groves is the type of man leaders have relied on for all of human history, and quite a few centuries before.”
On Post-War Nerd Proliferation:
“The proliferation of nerds and nerd institutions was a result of prosperity; not a driver of it.”
On Nerd Leadership:
“Nerd leadership isn’t good. Nerds belong in the laboratory. If they’re not in the laboratory they should be bullycided.”
On Objectivity:
“Objectivity is another thing the nerd lacks. Nerds are masters of dogma.”
Why It Matters
Locklin's critique of the "nerd clerisy" challenges the contemporary belief that intellectuals and technical experts are essential for effective leadership and societal progress. By highlighting historical and modern examples where nerd-led initiatives have failed, he calls for reevaluating how we value and utilize intellectual talent. His emphasis on practical, results-driven leadership underscores the importance of balancing intellectual input with hands-on experience and accountability. This perspective is particularly relevant in an age where technological and scientific advancements are often seen as the primary drivers of progress, reminding us of the need for pragmatic leadership to harness and direct these advancements effectively.
Here lies the internet, murdered by generative AI (theintrinsicperspective.com)
In the article "Here Lies the Internet, murdered by Generative AI," Erik Hoel discusses the pervasive influence of generative AI on the Internet. Hoel argues that AI-generated content is polluting digital spaces, degrading the quality of information, and undermining cultural norms. He highlights the proliferation of low-quality, AI-generated content across various platforms, from YouTube to Amazon, and the subsequent impact on users, including vulnerable groups like children. Hoel warns of a "semantic apocalypse," where the internet overwhelms synthetic, low-effort content. He criticizes the creators of such AI technologies, like OpenAI, and the institutions that embrace this content for profit. To mitigate this issue, he suggests regulatory measures akin to environmental protections.
Key Points
Proliferation of AI-Generated Content:
AI-generated content is increasingly common across the internet, from social media to shopping platforms.
The quality of this content is often low, misleading, and synthetic.
Examples include AI-generated books on Amazon and AI musicians on YouTube and Spotify.
Economic Incentives and Cultural Impact:
AI-generated content is cheaper, leading institutions to favor it for profit.
This shift is not driven by AI being better than human content but by its cost-efficiency.
Prestigious outlets like Sports Illustrated have been caught using AI-generated articles.
Negative Effects on Users:
The presence of AI content affects all internet users, often without their knowledge.
Specific groups, like children, are particularly vulnerable. AI-generated children's videos on YouTube are often nonsensical and devoid of educational value.
Regulatory and Ethical Concerns:
Hoel calls for regulatory measures similar to environmental protections to address AI-generated content.
He critiques OpenAI for failing to foresee or mitigate the widespread negative impacts of their technology.
The Need for Human-Centric Content:
AI pollution is compared to environmental pollution, requiring collective action to address it.
Hoel emphasizes the importance of maintaining human-created content to preserve cultural and cognitive integrity.
Key Quotes
AI Pollution: "The amount of AI-generated content is beginning to overwhelm the internet. Or maybe a better term is pollute."
Economic Motives: "This isn’t what everyone feared, which is AI replacing humans by being better—it’s replacing them because AI is so much cheaper."
Impact on Children: "All around the nation there are toddlers plunked down in front of iPads being subjected to synthetic runoff, deprived of human contact even in the media they consume."
Call for Regulation: "We need the equivalent of a Clean Air Act: a Clean Internet Act. We can’t just sit by and let human culture end up buried."
Why It Matters
The article critically examines the growing influence of generative AI on our digital environment. It highlights the ethical, cultural, and cognitive implications of allowing AI-generated content to proliferate unchecked. By comparing AI pollution to environmental pollution, Hoel underscores the urgency and scale of the problem, advocating for regulatory measures to protect the integrity of human culture and information. This discussion is crucial as it raises awareness about the broader societal impacts of generative AI, urging both technological developers and policymakers to consider the long-term consequences of their innovations.