Needing support from others is the must seductive form of procrastination. By externalizing accountability and claiming that you need help to reach your goals, you avoid the painful reality that the only thing between you and success is yourself.

Externalizing Self-Hatred: Because they cannot handle their own negative self-view, they project it onto others, creating a reality where they are justified in their actions.

Externalizing Shame: Individuals with BPD may feel immense, unbearable shame. To avoid feeling "bad," they project this shame outward, convincing themselves and others that the target is the "evil" one.

THIS IS WHY WE NEED TO INVEST IN THE BLACK COMMUNITY. The persistent overrepresentation of African American communities in urban crime statistics, particularly violent offenses, constitutes a pressing sociostructural challenge. Empirical analyses consistently demonstrate elevated rates of juvenile delinquency and interpersonal violence in neighborhoods characterized by concentrated disadvantage, where socioeconomic stressors intersect with limited institutional supports. While multifaceted causal pathways—including economic marginalization, residential segregation, and differential family structures—underpin these patterns, a robust body of criminological research underscores the efficacy of proximal, community-level interventions in attenuating risk factors during critical developmental windows. Foremost among these is the strategic deployment of after-school programs, which address the well-documented temporal peak in juvenile offending between 2 p.m. and 6 p.m. on school days, when unstructured supervision deficits are most acute. Randomized and quasi-experimental evaluations, including those targeting African American youth in high-risk urban settings, reveal that structured after-school initiatives yield statistically significant reductions in delinquent behavior. For instance, participation has been associated with diminished drug-use intentions, enhanced prosocial peer affiliations, and lower arrest probabilities, mediated through social skills development and character-building curricula rather than mere occupancy. Longitudinal assessments of programs such as LA’s BEST further substantiate long-term juvenile crime mitigation, with more intensive engagement correlating to pronounced protective effects. These outcomes align with broader ecological frameworks of crime prevention, wherein investments in positive youth development disrupt cycles of negative socialization by fostering protective factors: academic engagement, emotional regulation, and community connectedness. Meta-analytic syntheses indicate aggregate crime reductions of approximately 8% and externalizing behavior declines up to 14%, with amplified returns in disadvantaged contexts through cost-benefit multipliers—every dollar expended generating substantial savings via averted justice system involvement and improved life-course trajectories. Complementary community violence intervention models, emphasizing mentorship and opportunity pathways, have demonstrated 30-60% localized drops in shootings and homicides in pilot implementations. Allocating resources—encompassing expanded after-school programming, mentorship infrastructures, and recreational assets—to Black neighborhoods is not merely palliative but a logically antecedent strategy for collective efficacy enhancement. By fortifying institutional buffers against environmental precipitants of crime, such measures promote equitable public safety outcomes without presupposing monolithic determinism. Rigorous, sustained investment in these empirically validated modalities represents a pragmatic, evidence-driven pathway toward diminishing racial disparities in criminal justice involvement while advancing communal resilience.

THIS IS WHY WE NEED TO INVEST IN THE BLACK COMMUNITY. The persistent overrepresentation of African American communities in urban crime statistics, particularly violent offenses, constitutes a pressing sociostructural challenge. Empirical analyses consistently demonstrate elevated rates of juvenile delinquency and interpersonal violence in neighborhoods characterized by concentrated disadvantage, where socioeconomic stressors intersect with limited institutional supports. While multifaceted causal pathways—including economic marginalization, residential segregation, and differential family structures—underpin these patterns, a robust body of criminological research underscores the efficacy of proximal, community-level interventions in attenuating risk factors during critical developmental windows. Foremost among these is the strategic deployment of after-school programs, which address the well-documented temporal peak in juvenile offending between 2 p.m. and 6 p.m. on school days, when unstructured supervision deficits are most acute. Randomized and quasi-experimental evaluations, including those targeting African American youth in high-risk urban settings, reveal that structured after-school initiatives yield statistically significant reductions in delinquent behavior. For instance, participation has been associated with diminished drug-use intentions, enhanced prosocial peer affiliations, and lower arrest probabilities, mediated through social skills development and character-building curricula rather than mere occupancy. Longitudinal assessments of programs such as LA’s BEST further substantiate long-term juvenile crime mitigation, with more intensive engagement correlating to pronounced protective effects. These outcomes align with broader ecological frameworks of crime prevention, wherein investments in positive youth development disrupt cycles of negative socialization by fostering protective factors: academic engagement, emotional regulation, and community connectedness. Meta-analytic syntheses indicate aggregate crime reductions of approximately 8% and externalizing behavior declines up to 14%, with amplified returns in disadvantaged contexts through cost-benefit multipliers—every dollar expended generating substantial savings via averted justice system involvement and improved life-course trajectories. Complementary community violence intervention models, emphasizing mentorship and opportunity pathways, have demonstrated 30-60% localized drops in shootings and homicides in pilot implementations. Allocating resources—encompassing expanded after-school programming, mentorship infrastructures, and recreational assets—to Black neighborhoods is not merely palliative but a logically antecedent strategy for collective efficacy enhancement. By fortifying institutional buffers against environmental precipitants of crime, such measures promote equitable public safety outcomes without presupposing monolithic determinism. Rigorous, sustained investment in these empirically validated modalities represents a pragmatic, evidence-driven pathway toward diminishing racial disparities in criminal justice involvement while advancing communal resilience.

I'm also in TSLA. I like how clearly you framed the lidar and intelligence issue. I think their FSD software/intelligence will probably win. Personally though, what increasingly concerns me is the projected TAM for Cybercab. I'd love to hear what you think, sorry for the long comment but I have a nice Sunday afternoon to organize my thoughts so here, if you want to read them and respond: Having spent many hours thinking it through, I just see no reason why their Cybercab TAM should be significantly larger than Uber's is today (market cap $140B). Uber already did the discovery around what the market wants for that kind of on demand transport. Thinking through their primary market: If Americans wanted the cheapest way to get from A to B, they'd all take the bus/subway already. If they wanted faster, they'd pay a premium and take Uber already. But still, 90% of Americans continue to choose car ownership. I just do not see how an electric version that drives itself would be preferable for the majority of Americans, not just at a lower cost/mile, but at ANY cost per mile. Americans don't just want "transport", they want: a home on wheels. A familiar space. A place for their kids, their toys, their tools for work. Something they can jump into at a moment's notice to go to the store, drive to the lake or the mountains. It's identity. Freedom. Convenience. Owning a car was never a great economic choice for most people. So, no matter how much I twist it around in my head, I think the TAM for Cybercab itself is only a fraction of what the bulls believe it will be (Uber: 10M drivers worldwide, but that's not a $10 Trillion TSLA TAM..). Certainly the culture and behavioral change that would be required at scale, in a country where the best selling vehicle is the F-150 that costs more in gas than Tesla's claimed total per mile price target!.. I think the quants underestimate the inertia of human behavior and culture. It's much easier to replace a service humans already use (Taxi --> Uber, very low friction change) than to change a culture's entire behavioral DNA. And then there's another big issue, infrastructure, which would require power plant sized grid connections for centralized cybercab charging at scale (1000 cars is 350 MW, and that would be a modest sized lot for a major city. NYC: 80,000 Uber drivers).. $30k/vehicle out of the factory becomes a lot more expensive per vehicle. And we all know how hard it is to get more power right now. I think people significantly overestimate the cost savings of removing the driver, and underestimate the infrastructure required at scale for electric vehicles, and the cultural change required for adoption that would move revenues on a 200 forward pe company with trillion level market cap. My guess is this gets resolved in the nearish term by externalizing the infrastructure costs with distributed owner/operators (losing TSLA profit), avoiding supercharger installs and grid connect issues. But then you have a whole new domain of insurance to sort out, among other things. I see a lot of people waiting anxiously for a broader Cybercab rollout and "slowly, then all at once" scaling this year into next year. If my thoughts are accurate, I see a much slower revenue ramp, major cultural and infrastructure issues that have no easy solution, and where scaling their software/neural net may be more profitable than running the actual cars themselves in the long run. My current guess: Americans would rather have their OWN car drive themselves, than what is effectively a small public bus that picks them up from an app. But that's much less profitable than $50-100k profits/year/cybercab, or whatever. I love your deep dive IREN posts and wonder if you've thought about some of these issues and come to any conclusions?

Yeah, I think getting multiple perspectives is generally good and externalizing cognition can be useful. I do chuckle at the waluigi-ness of the name, “family systems” are already external that’s why IFS has the name it does, but re-reflecting back outwards from there is fun.

Introducing Harness-1, a 20B search agent trained with a state-externalizing harness. > frontier-level long-horizon search, rivaling Opus-4.6 and outperforming GPT-5.4 > Context-1-level cost and latency > externalizes candidates, evidence, verification, and search history > open-source

Perhaps 100% of that 90% should get off their lazy asses and start using discipline, accountability, privacy app locks, device locks, browser site blockers and passwording systems provided by every single device they own instead of externalizing that responsibility to an inept government that aims to control everyone. This isn’t a problem if parents weren’t so weak and lazy in how they guide their children.

You're not going to get anywhere. They're externalizing an internal issue again.

He is externalizing his own self hatred.

A great deal of what is happening right now is liberals externalizing their frustrations on the one target they're told is safe.

Her argument: Therapy can't treat BPD because they shift blame. Me: Blame shifting is momentary. They feel intense guilt/self-loathing after. By conflating BPD's externalizing with other cluster B externalizing, her argument for *why* therapy is a dead end falls apart.

Personal slights are conflated as social crimes to trigger tribal defense; purposely externalizing individual issues to the group. Unfortunately, this makes a simple disagreement such as this into one which may bring shame to the entire group.

"She needs to buck up, get some help, and stop externalizing her own problems onto her spouse." sure, she should get help, like, for example, seeking advice from a sex therapist. and taking proactive steps to make intimacy feel safe, comfortable, and routine.

You understand Sasuke, Gaara, Neji, etc, externalizing their trauma and lashing out, but bash Hinata for internalizing her trauma, having low self-esteeem , anxiety, etc. You said she lacked courage bc she processed her trauma differently from other characters. 😭

The Organizational Learning Loop and the Irreducible Prior — The Mind Satya Nadella’s reflections map, with unusual clarity, how organizations are positioned to respond to AI. He describes the emergence of a compounding cognitive loop in which human judgment and direction combine with proprietary AI capabilities — what he terms token capital — so that both reinforce each other over time. Workflows, domain expertise, and institutional judgment can be encoded into systems that improve with use. Generic frontier models supply raw capability, but firms that actively build and retain their own learning systems can preserve distinctive knowledge that would otherwise be absorbed into shared models. He also identifies the strategic risk that value will concentrate in a small number of frontier systems. These observations stand out because they remain close to the actual mechanisms of value creation and retention inside firms. The clarity is nevertheless bounded by the scale at which the frame begins. Nadella writes from the position responsible for sustaining a large organization and the ecosystem it participates in. From that vantage the relevant unit is the organization. The patterns are not traced further. What presents as the organization is not a fundamental entity. It is a temporarily stabilized projection arising from the interactions of many individual minds through coordination structures — rules, incentives, hierarchies, processes, access rights, and norms. These structures themselves are not fixed or objective. They are patterns that have become sufficiently consistent, often reinforced at nodes where choice and resource allocation concentrate, to appear given. The active principle throughout remains the individual mind compounding its own operations. Minds have long extended themselves by externalizing processes into tools — language, writing, calculation, and computation — to achieve greater scale and recursive improvement. Current AI systems are a particularly powerful prosthesis in this sequence. They allow individual minds to externalize memory, pattern recognition, and iterative reasoning across unprecedented breadth and to make those externalizations available for further refinement within shared structures. What registers as increased speed, explicitness, or bidirectionality in organizational learning loops is therefore not a novel property introduced by AI. It is the visible effect, at the present scale of observation, of individual minds making use of a new and unusually effective tool for extending and refining their own distinctions. Organizations and collectives do not possess independent agency. They are descriptions of stabilized patterns of individual minds interacting through coordination structures that themselves arise from individual choices. Apparent closure of any learning system is always relative to the scale of observation. Within a local frame the loop may seem self-contained. At larger scales of talent movement, communication, or technological diffusion, the boundaries prove permeable because individual minds and their choices continually cross them. No system composed of minds and tools remains strictly closed. Nadella correctly registers that value concentration in a small number of frontier systems carries strategic and political risk. The deeper instability, however, lies in the belief that such concentration can be stably maintained. That belief is itself the attempt to render the learning systems as closed. What appears as concentration is the attribution of value to the currently strongest nodes within temporarily stabilized patterns of individual interaction. These attributions arise not solely from organizational design but from countless individual choices made according to how the system is rendered — choices to contribute to, remain within, strengthen, or exit the apparent boundaries. The more value registers as captured within a small number of frontier systems, the greater the pressure on those boundaries. Rapid interactions, talent movements, and diffusion of capabilities are not external frictions to be managed or minimized. They are the direct symptoms of minds operating across the patterns that present as closed. Any serious attempt to enforce closure at scale generates the very crossings that render sustained concentration fragile. Nadella’s account does not carry the reduction to this prior because the frame from which he writes privileges the maintenance and strengthening of organizational forms within the existing political economy of AI development. His advocacy for a broader frontier ecosystem — rather than value accruing only to a few frontier models — can be read as an effort to stabilize a different distribution of these patterns, one in which more organizations can participate in the compounding while still treating organizational entities as the primary units whose continuity matters. The account remains valuable within its chosen scale. It maps, with notable clarity, how the underlying process currently manifests inside firms and what concrete steps organizations can take to engage it more effectively. It simply does not proceed to the only irreducible prior. The loop Nadella identifies is real and practically relevant at the organizational level. Its driver, however, is neither the organization nor the AI system. It remains individual minds, each compounding its own activity by means of the tools and coordination patterns available to it — of which current AI systems are the most recent and potent example. Organizations and their structures function as useful, temporarily stabilized patterns within this process, not as its source or its necessary endpoint. The same prior capacity for rendering distinctions and compounding them through tools operates whether the stabilized configurations are named firms, ecosystems, or individual practices. The lever visible at every scale is the individual mind’s recognition of its own rendering activity and its choice of how to extend it through whatever tools and coordination patterns are at hand.

U should be Publicly Stoned and Shamed U Racist misogynistic Redpill Chud Loser. “externalizing blame” yeah its called holding you ACCOUNTABLE Dumb ass🤣🤣 you framed YOURSLEF as the bigot and the misogynist i just called you out on it Dawg hopped on chat gpt for help🤣

Public shaming, purity spirals, claims of "speaking truth to power" while enforcing speech codes, and framing disagreement as evidence of bigotry or false consciousness is to mask personal insecurities or failures by externalizing blame.