A Better Way of Dating

The lady I was chatting with on Mastodon has been complaining about dating sites, and I pointed out that they really don’t care about “matching” you, rather they want to keep you engaged so they can serve your eyeballs ads and get you to re-enroll. So I replied that we should have a better way to date online. Then I went to bed and slept.

Computerized offline yentas. COY. This is what my brain has apparently been working on overnight and why it awakened me at 3:00 a.m. The basis for the solution is two things: a better business model, and something that is handled in the simplest way possible that might still work.

The simplest way possible would be for a person in a city, say L.A. for example, to have a database of profiles on their own computer. A registered candidate can then eMail that person a query, say “give me all men looking for women who are between 30 and 40, who make at least 60K per year, who have one or fewer kids, who identify as mostly liberal, and who like baseball.”

We would then e-mail them matching profiles. That pretty much is the whole service. The whole thing sounds like just a step or two up from the old Craigslist. The tricky part is meshing that with a business model that works, both in terms of being self-sustaining and not having an overwhelming amount of work to accomplish. So here’s the idea on the business model.

The pricing model should encourage the operators of the business to make good matches. After we accept your profile you should pay, say fifty dollars, for two years on the system. After two years we send you your money back.

If you get booted from the system however, we keep your payment. You can get booted either because you fail to contact any query matches (we assume because you already have a happy match), or because people are complaining that you have lied or omitted important information on your profile, or because you quit on your own. We will return your payment though if we can’t find you enough new recommendations.

The tricky part, of course, is tuning it to be effective (the basic Yenta Problem). All women want similar traits in a good man (and vice-versa), and their aren’t enough candidates that meet those traits. So there has to be a way to gently suggest that, well, we didn’t match all your criteria, but here are the candidates who come closest.

So first don’t accept profiles or a payment from non-matchables. Also weight profiles to lessen recommending “ideals”; they have to do their own choosing. Also have segregated systems. For example have COY L.A. Average Youth, COY L.A. Discount Senior, COY L.A. High-End Middle-Age, etc. Include good examples for suggestions of what should be in a profile, and only accept those that match. Also include good examples for what should be in a query.

To limit the workload, we should accept a new query from a person just once a quarter, and give them around 10 matching profiles back. They can indicate back to us who they like, and then we will contact the candidates they like with the originator’s profile and eMail address.

To encourage enough users to achieve useful network effects, the system will likely have to run free of charge for the first couple of years.

To promote incremental business improvements, the people who run each individual locale of the distributed site should have their own place to discuss things like security, moderation/screening, business continuity, and improvements to the business methods.

In conclusion, the concept of Computerized Offline Yentas represents a promising departure from the current landscape of online dating. By addressing the underlying flaws of profit-driven platforms and focusing on simplicity and efficacy, COY offers a refreshing alternative. The proposed business model, incentivizing successful matches while safeguarding against misuse, demonstrates a commitment to fostering genuine connections.

With careful implementation and ongoing refinement, COY has the potential to revolutionize the online dating experience, providing a tailored and authentic approach for individuals seeking meaningful relationships.

How I Do My Windows Backups

In the digital age, where our lives are increasingly intertwined with technology, ensuring the safety of our digital assets has never been more critical. Imagine losing all your precious photos, important documents, and cherished memories in the blink of an eye due to a computer crash or a malware attack. That’s where backups come in – they serve as a safety net, providing a lifeline when disaster strikes.

You should backup anything that you can’t afford to lose; this includes important documents, family photos, music libraries, and crucial work files. On the flip side, not everything needs to be backed up. System files and applications can usually be reinstalled, so there’s no need to clutter your backup with them.

The first thing to do however, is to make a recovery USB drive. This is essentially a bootable USB drive that contains a copy of Windows, which can be invaluable in restoring your system to a functional state in the event of a catastrophic failure.

Here are the steps to create a Windows USB recovery drive: first, ensure you have a USB flash drive with sufficient storage capacity. Microsoft recommends using a USB drive with at least 16 GB of storage space to accommodate the recovery files. Then on your Windows PC, search for “Create a recovery drive” in the Start menu search bar and select the corresponding option from the search results. Alternatively, you can navigate to Control Panel > Recovery > Create a recovery drive.

The Recovery Drive wizard will launch. At the first step, you’ll be asked to choose whether to back up system files to the recovery drive. Make sure the option “Back up system files to the recovery drive” is checked, then click “Next.” In the next step, the wizard will detect any connected USB drives.

Select the USB flash drive you prepared earlier from the list, and then click “Next.” The wizard will display a warning that all data on the selected USB drive will be deleted during the creation process, then click “Create.” This process may take some time, depending on the speed of your USB drive and the size of the system files.

My primary backup device is an external SSD disk drive. Nowadays these are both extremely fast, have enormous capacity, and also inexpensive, and you can purchase them at any office supplies store. Once a year I simply drag and drop two folders from my C: drive over to the SSD, the “Desktop” folder and the “Documents” folder. This operation takes a while to complete, but this point-in-time snapshot allows you to later run shorter and faster incremental backups.

After your copy operation completes, you should reset the file “archive” attributes on these two folders and their contents. This ensures that any later incremental backups know which files have been recently modified and need to be included.

First, press the Windows key, type “cmd” into the search bar, then press Enter. This will open the Command Prompt. Use the “cd” command to navigate to the folders you just copied. For example,
cd C:\Users\JeffC\Desktop
(of course replace JeffC with your own userID).

Now, to reset the archive attribute for all files and subdirectories in a folder and its subfolders, use the following command:
attrib -a /s /d

Now you are ready to run incremental backups. I like to run these every couple weeks or so, depending upon how busy I have been lately on my computer. I do these using the xcopy command-line utility. The flags I use also reset the archive attribute once xcopy has backed the file up. Here’s the batch file I use, I change the month-yy designation each month to make it easier to find things later:

ECHO OFF
ECHO Starting backup…
XCOPY C:\Users\JeffC\Documents*.* D:\Users\JeffCMar24\Documents /EXCLUDE:bkupExcl.txt /S /C /I /H /M /R /K /Y /J >>C:\Users\JeffC\Desktop\backupStatus.txt
XCOPY C:\Users\JeffC\Desktop*.* D:\Users\JeffCMar24\Desktop /EXCLUDE:bkupExcl.txt /S /C /I /H /M /R /K /Y /J >>C:\Users\JeffC\Desktop\backupStatus.txt
ECHO Backup completed.

The bkupExcl.txt file lists the extensions of files I don’t want to back up, either because the tend to be large or might contain viruses:
.mpg
.mp4
.msi
.wmv
.exe
.dll
.msp
.tmp

Although this method is quite thorough and fully covers my data backups, sometimes I just need to make a quick “save” of something I am working on that is too important to lose. For this I use Dropbox. Once you download the Dropbox software and set it up, it is extremely easy to use. Just drop your important work in progress into the local Dropbox folder, and connect to the service. That’s it!

Finally, when I am out somewhere working on a small device without Dropbox (like my Kindle) I will eMail a copy of important work to myself. It’s also good to keep a Backup folder on your eMail service to save hyper important documents you may wish to have access to in an emergency, when you don’t otherwise have a computer available. I do this, for example, with my personal address list.

The effort you put into creating and maintaining backups is undoubtedly worthwhile. Beyond the inconvenience of losing precious photos and essential documents, the repercussions of data loss can be profound, impacting productivity, financial stability, and even emotional well-being. Backups serve as a safeguard against the unforeseen, offering peace of mind knowing that your digital assets are protected from hardware failures, malware attacks, or accidental deletions.

Protein Folding Computation with Machine Learning and AI

Proteins are large biomolecules and macromolecules made from long chains of amino acids. A linear chain of amino acid residues is called a polypeptide; a protein contains at least one long polypeptide (short polypeptides, containing less than 20–30 residues, are rarely considered to be proteins and are commonly just called peptides).

Proteins perform a vast array of functions within organisms including catalyzing metabolic reactions, DNA replication, responding to stimuli, providing structure to cells and organisms, and transporting molecules from one location to another.

Proteins differ from one another primarily in their sequence of amino acids, which is dictated by the sequence of nucleotides in their genes, and which usually results in protein folding into a specific 3D structure that determines its activity. Methods commonly used to study protein structures and function include immunohistochemistry, site-directed mutagenesis, X-ray crystallography, nuclear magnetic resonance and mass spectrometry.

Since protein synthesis is driven by the genetic code of stretches of DNA, and since the human genome has already been sequenced, there is great interest in determining the possible structure of proteins computationally. We should be able to extrapolate the peptide sequence coded by our DNA and solve how the protein folds into its final conformation.

Protein structure prediction is one of the most important goals pursued by computational biology, as it is important for the design of both drugs and novel enzymes. Computational prediction would solve experimental structures faster, allow the in-silico examination of the effect of mutation on protein function, and provide novel insights into poorly known molecular mechanisms.

Predicting folding configurations is a formidable challenge however due to various factors. First, computational complexity arises from the vast number of possible conformations, with the search space growing exponentially with size. Navigating the rugged energy landscape with many local minima, governed by the protein’s tendency to adopt low free energy conformations, adds complexity.

Additionally, entropic effects introduce a balance between stability gain and entropy loss during folding. Interactions with water molecules, essential in the aqueous protein environment, must be accurately modeled for precise predictions. Long-range interactions between distant amino acids, a crucial aspect of folding, pose challenges in capturing non-local details.

The cooperative nature of protein folding, where different regions fold simultaneously, further complicates predictions. Proteins also undergo post-translational modifications and dynamic changes, affecting their properties, stability, and function. Experimental techniques like X-ray crystallography have limitations, providing incomplete data for predictive models. Overall, these constraints presents a multifaceted challenge in accurately predicting protein folding.

Despite these challenges, significant progress has been made in recent years thanks to advancements in computational techniques, machine learning approaches, and increased understanding of the biophysical principles governing protein folding. Researchers continue to explore innovative methods to improve the accuracy of protein folding predictions; in the following paragraphs I review the recent advancements.

A community-wide experiment, the Critical Assessment of Techniques for Protein Structure Prediction (CASP), takes place every two years. In 2018 the Google division called DeepMind released the software AlphaFold during CASP13, a breakthrough method that not only combined previous methodologies but also uses artificial intelligence. Its algorithm beat the other tools in CASP13 and became the state of the art in protein structure prediction.

The first version of AlphaFold used deep learning to predict the structure, demonstrating that it is possible to learn protein-specific structure by training a neural network given only the protein sequence. By training a convolutional neural network on PDB structures, distograms were created to predict distances between residues. By analyzing the amino acid sequence, the neural network predicted a distogram of multiple sequence alignment (MSA) features and backbone torsion distribution probabilities.

Presented at CASP14 between May and July 2020, AlphaFold2 predicted protein structures with more accuracy than other competing methods, demonstrating a root-mean-square deviation (RMSD) among prediction and experimental backbone structures of 0.8Å versus the 2.8Å from the next best performing method. AlphaFold2 increased the structural coverage from 48% to 76% of all human protein residues, dropping the number of human protein without structural coverage from 5027 to 29. AlphaFold2 utilizes amino acid sequences to generate a MSA from multiple protein sequence databases, identifying mutation-prone regions and detecting correlations.

AlphaFold2 owes its breakthrough to the evoformer and structure modules, both neural network components. By exchanging information between MSA and templates, the evoformer improves the assessment of MSA and modifies the protein structures hypothesized by the templates. The AlphaFold2 structure module, that also contains an attention architecture, prioritizes the orientation of the protein backbone, considering the residue rotations and translations, localizing the side chain of each residue in highly constrained frames, followed by local refinement and minimization by gradient descent.

In the same year (2021), in a partnership between Google DeepMind and the EMBL-European Bioinformatics Institute (EMBL-EBI), the AlphaFold Protein Structure Database (AlphaFold DB) was created, making available over 360,000 predicted structures from 21 organism proteomes. Today, AlphaFold DB has over 200 million entries from the human and 47 other organism proteomes, with the structure predictions and their respective analyses freely available to the scientific community.

Alphafold2 has been used to predict protein-protein interaction, using flexible linkers or artificial gaps and, in general, it predicted heterodimeric protein complexes accurately, exceeding docking approaches usually used in these analysis.

Despite its success, AlphaFold2 has difficulty predicting intrinsically disordered protein regions and loops. This is troubling considering the importance of the latter for drug screening and design, since they are exposed in protein surface and readily available to solvent and other proteins.

Also in 2021, the Institute for Protein Design at the University of Washington introduced RoseTTAFold, a “three-track” neural network that simultaneously considers patterns in protein sequences, how a protein’s amino acids interact with one another, and a protein’s possible three-dimensional structure. In this architecture, one-, two-, and three-dimensional information flows back and forth, allowing the network to collectively reason about the relationship between a protein’s chemical parts and its folded structure.

The pioneering computational method OmegaFold was launched by the Chinese biotech firm Helixon in July 2022, marking a breakthrough in predicting high-resolution protein structure from a lone primary sequence. The researchers reported in a study that they utilized a novel combination of a protein language model that enabled predictions from individual sequences, and a geometry-inspired transformer model trained on protein structures. The team said that the overall model of OmegaFold is conceptually inspired by advances in language models for NLP coupled with deep neural networks used in AlphaFold2. In addition, OmegaFold empowers accurate predictions for orphan proteins without ties to any characterized protein family, as well as antibodies known for having noisy MSAs resulting from rapid evolution.

Meta AI introduced a groundbreaking large-scale language model, Evolutionary Scale Modeling (ESMFold), in November 2022, aimed at accelerating protein structure prediction, with advances in the complexity of language modeling extending to 15 billion parameters. This model claimed to have similar accuracy as AlphaFold2 and RoseTTAFold, but ESMFold inference is faster at enabling the exploration of structural spaces of metagenomic proteins.

The natural world contains a vast number of proteins beyond the ones that have been cataloged and annotated in well-studied organisms. Metagenomics uses gene sequencing to discover proteins in samples from environments across the earth, from microbes living in the soil, deep in the ocean, in extreme environments like hydrothermal vents, and even in our guts and on our skin. Meta also released the 600+ million protein ESM Metagenomic Atlas, with predictions for nearly the entire MGnify90 database, a public resource cataloging metagenomic sequences.

Machine learning and artificial intelligence have revolutionized the field of protein folding computation, marking a significant leap forward in our ability to predict and understand the intricate 3D structures of proteins. Despite the inherent challenges posed by computational complexity, energy landscapes, and dynamic molecular interactions, recent breakthroughs exemplified by AlphaFold2, RoseTTAFold, OmegaFold, and ESMFold underscore the transformative power of cutting-edge technologies in overcoming these hurdles. These advancements not only enhance our comprehension of protein folding but also hold immense promise for drug design, enzyme engineering, and a deeper exploration of metagenomic proteins. As we venture further into the realm of computational biology, the continued collaboration between AI and biotechnology promises to unveil the mysteries of countless unexplored proteins, opening new frontiers in understanding the complex machinery of life.

(Author’s note: along with a bit of my own writing and editing, this article contains direct excerpts from the references listed below and text generated by ChatGPT)
References:
“Before and after AlphaFold2: An ovreview of protein structure prediction” by Letícia M. F. Bertoline, Angélica N. Lima, Jose E. Krieger, Samantha K. Teixeira
Wikipedia: Protein_structure_prediction
Protein Wars by Amit Raja Naik
ESM Metagenomic Atlas, from Meta AI

Should we save humanity?

It’s a curious paradox of human nature that even when it comes to saving humanity people can hold vastly different points of view. While one might think we would share the preservation of our species as a common goal, the complexity of human perspectives and values ensures a diverse array of opinions.

Optimists tend to believe in the inherent resilience and adaptability of humanity. They see our ability to overcome challenges, learn from mistakes, and innovate as reasons to be hopeful about the future. On the other hand pessimists might argue that humanity’s track record of self-destructive behavior coupled with looming existential threats like climate change and nuclear weapons, make the prospects for long-term survival quite grim.

Some individuals emphasize the importance of saving humanity because of the unique diversity it brings to the world. They believe that each culture, tradition, and perspective adds richness to the human experience. In contrast a significant segment of the population holds a dim view of human nature itself. They point to the historical record of violence, greed, and exploitation, leading to wars, environmental degradation, and social injustices. For these individuals humanity’s capacity for destruction and selfishness is reason enough to doubt the worth of saving the species as a whole. They may argue that humanity itself is the plague, and perhaps the world would be better off without our species.

Some might argue that evolution ingrains humanity’s survival as a fundamental drive. Others might question the significance of humanity’s existence in the vastness of the universe, pondering whether saving ourselves is meaningful in the grand scheme of things. Do other creatures have any influence over their long-term fate? Then why should we?

Furthermore, a prevailing sentiment among some is that of individualism and immediate gratification. In a world heavily focused on personal success, wealth, and instant pleasures, many people prioritize their own happiness and comfort over broader societal concerns. This individualistic mindset often breeds apathy toward global issues and fosters a belief that one can secure their own future without needing to worry about the rest of humanity. As long as I can have my annual vacation via airplane to Europe, who cares about global warming? The idea of sacrificing personal enjoyment or comfort for the greater good can be met with resistance as people tend to prioritize their immediate needs and desires.

The power elite, a small but influential group of individuals often occupying positions of authority in politics and business, wields significant control over global affairs. Their decisions and actions can have far-reaching consequences for the rest of humanity.

From the perspective of the power elite, the preservation of a functioning society is crucial to maintaining their positions of authority and comfort. However, their focus may primarily lie on sustaining their own power and wealth rather than prioritizing the well-being of the entire human population. They may view the vastness of humanity as a hindrance to their control and prefer a more manageable population that is easier to govern and exploit.

In this view a smaller human population could potentially ensure more abundant resources and opportunities for those at the top, allowing them to enjoy greater luxuries and privileges. With a reduced global population the power elite might perceive fewer challenges to their authority and less pressure to address issues related to poverty, inequality, and human rights. In essence their interests may lean toward maximizing their own comfort and influence, rather than the collective welfare of all individuals.

Alternatively the power elite might choose to maintain the status quo by opting for geoengineering projects or other technological interventions. While this approach might ensure the survival of humanity it carries its own set of risks and ethical considerations. Geoengineering and drastic interventions in the environment could bring unintended side effects and uncertainties, potentially altering the delicate balance of nature. One potential danger lies in the possibility that the power elite may unintentionally overshoot their efforts to shape the future; their pursuit of a more manageable population or their attempts to engineer a sustainable environment might inadvertently create new challenges that prove to be unsustainable or have unforeseen consequences.

The differing viewpoints on saving humanity indeed introduce a challenging predicament. For those who strongly believe in preserving humanity the notion of disempowering, killing, or neutralizing individuals in opposing groups can be morally conflicting. Even given the intense inclination to save humanity, a ecologist may be reluctant to resort to aggressive measures against his fellow human beings, even if they hold contrasting beliefs.

This moral dilemma highlights a potential weakness for those who advocate for the welfare of all humanity. Their compassionate outlook might hinder them from taking decisive actions against individuals or groups with opposing views, who may be more assertive and ruthless in advancing their agendas. Hence the more benevolent individuals who wish to preserve humanity may find themselves at a disadvantage in confrontations with those who prioritize their own interests or view humanity with disdain. The latter group might be more willing to employ drastic tactics to further their agendas, potentially threatening the broader goal of ensuring humanity’s survival.

At this critical juncture decisions that could determine the trajectory of humanity must be made soon. The urgency of the challenges we face — including climate catastrophes — calls for decisive action. It is essential to recognize that the future of humanity is inextricably linked to the actions of a few, but the impact will be felt by all. As we entrust our fate to those in positions of influence we must also remain vigilant and engaged. It is crucial to hold the power elite accountable, ensuring that their decisions are made in the best interest of all of humanity, not just a privileged few.

As individuals we should not shy away from our responsibility to contribute to positive change. While we cannot control the actions of the power elite, we can collectively work towards a better future. We should strive to understand and respect differing viewpoints, foster empathy and cooperation, and actively participate in addressing global challenges.

In conclusion, the complexity of viewpoints on saving humanity introduces ethical quandaries for those who genuinely wish to preserve the species. Their compassionate stance may create challenges in facing off against more assertive and self-interested groups. Finding ways to bridge these gaps and promote unity while respecting diverse perspectives is essential in navigating the path forward for humanity. Either that or we should all just party until humanity perishes in the cacophony of climate catastrophes.

How Corporate IT Works Today

I’m retired now, but over the course of my I.T. career about half the companies where I worked either went out of business or merged. After a while I started to get a complex that yikes, maybe I was destined to be the merchant of corporate death, rounding up the soul of failing companies to jettison them off to a buyer or the deep blue sea. After forty years of work though I recognize that this implosion and consolidation rate is fairly typical, and perhaps rather than being tasked to grimly reap my better purpose is to understand the causes for company rot so that I can relate it to you here. I suspect a lot of it is simply due to the facts about how an IT department naturally evolves over time.

Frankly one could not rebuke any of the companies I worked for strategic planning faults. They all understood their competition and could reasonably forecast their sales. In all cases the root of the problem seemed to be an internal rot of software systems caused by sociological issues. This decay frustrated both the back office staff and the external sales folks, and caused management to promise clients capabilities that they couldn’t fulfill in a timely, accurate, or cost-effective manner. I do recognize I hold the failure microscope at the technological end so folks in other departments might view the implosions differently. But I can only attest to the details where I am most intimately familiar.

Neither were the systems victim to any particular class of design faults: it didn’t matter if the company imbued best practices or not. Rather systems rotted due to the sociology of churn and politics. There are always issues with office politics in any department, but those in I.T. have the pernicious side effect of causing slowly degrading operational consequences. People forget how to fix things, or knowledge doesn’t get passed along. Folks deliberately act uncooperative to calibrate their feelings toward what they view as an uncaring management team. Failure and rot seems to be resistant to any new development fad: object oriented, agile, cloud, you name it. The issues at hand aren’t about how you develop software, rather they’re about how the treatment of developers trickles down to the longevity, maintainability, reuse, and leverage of the software so it can meet future strategic goals.

Each time the management team changes they bring in new mid-level managers to impose their ignorance upon the long term staff. This causes wasted resources as the legacy staff needs to bring new managers up to speed. It also causes quite a bit of social strain as everyone needs to reassert their expertise and recarve out their niche in management’s eyes. Each management change causes some moderate rearrangement in the methodology of how things get done while only making the slightest speck of impact on anything that might produce value to the customers.

Legacy staff gets further frustrated because it appears to them that there is no path for advancement within the organization. The company always hires Managers from outside rather than promote those employees with knowledge and seniority. This failure to promote technical people from within causes problems of both morale and technical competence. The first effect is pretty immediate but the longer term frustrations and deliberate failure of knowledge transfer eventually causes the company the most damage.

One of the more common first tasks when the new management arrives is to make sure their staff has “backup.” One of the primary reasons why this knowledge transfer is an ineffective approach is that a person’s knowledge deeply intertwines with his experiences, skills, and tacit understanding. Knowledge is not simply a collection of facts or information that someone can easily document or transmit. It is embedded in the context of an individual’s expertise, their unique perspective, and the practical application of that knowledge in real-world scenarios. This tacit knowledge is challenging to articulate, codify, and transfer in a way that captures its true essence.

Furthermore, knowledge is not static but rather constantly changes from ongoing learning, interactions, and problem-solving experiences. Attempting to capture knowledge in a static form through software or documentation fails to account for the dynamic nature of knowledge. A snapshot of knowledge at a particular point in time may quickly become outdated or incomplete as new information and insights emerge. This limitation becomes particularly evident in software development where technology, methodologies, and best practices evolve rapidly.

Moreover, knowledge transfer often assumes a one-way flow of information, where the teacher simply imparts their knowledge to the recipient. However, effective knowledge transfer is a reciprocal process that involves active engagement, collaboration, and shared understanding. It requires an environment that encourages dialogue, questioning, and experimentation. By solely focusing on capturing and transmitting knowledge, organizations risk overlooking the importance of fostering a learning culture and creating opportunities for employees to actively participate in knowledge creation and dissemination.

Sometimes this attempt at knowledge transfer even involves the ignoble task of requiring an employee to train another employee how they do their job. This never works out well: the trainer has no motivation to do a good teaching job and the recipient of the information lacks the background of why things are done the way that they are.

Most commonly the trainer just “pretends” to teach the recipient. Later when circumstances change and legacy employees move on, the ones they trained do a considerably worse job at tasks than the originals. Each handoff of a task to another employee results in decaying quality. The trainer may deliberately cause this by purposely doing a poor job on the handoff as implicit punishment for failure to promote from within.

Where I previously worked, over thirteen years I witnessed four full management turnovers. One gentleman was a conscientious Vietnamese gentleman who never jumped to conclusions, and always verified that we had fully tested everything. Meetings with him were slow and cumbersome yet the outcomes always produced code that everyone understood. After that we had an Arab fellow who was off in his own world, letting us all run in our small little domains while he built a new system from scratch. He relied on us more as internal consultants. Then we had an orthodox Jewish fellow who was more of the supportive encouraging sort of boss. He helped us along where we got stuck but couldn’t meet the owner’s expectations for delivery.

Then we had a Chinese big-league CIO from formerly large companies who bossed us all around and expected each of us to do the jobs of whole departments where he had previously worked. Then we had a female CIO without any modern development language experience, who colluded with the other smalltime managers she brought along to denigrate the legacy staff. She loaded up the staff with many newbie software developers who were always blaming their own coding incompetencies on the database or their poor understanding of how the legacy systems had been developed.

Each change of management team focused so much on their own narrow objectives that they didn’t realize the company itself might have its own strategic direction. Each manager who planned to rewrite absolutely everything (just to modernize) while ignoring all of the suggestions of the existing long-time staff only ended up getting mired in the old pitfalls where the legacy staff has already paid their dues. They all performed the same deceptive feat: they sold themselves as The Solution to everything by promising a rewrite that would handle all existing functionality with new tools, only to end up with a job one third done, and code that nobody on the future staff could support. They each added yet another complex system onto the pile of already aging technologies. They made the same mistake all smart people make: they thinks that systems can be modeled by examining components, whereas fully half of how work happens has to do with personalities and what is inside of people’s heads.

New technical managers can promise upper management new whizbang technologies since tools allow them to get a working prototype up and running in a few months with maybe half the specifications implemented. After that however the path slogs down at an exponentially decaying rate. The naive architectural decisions they made based upon their partial and incomplete knowledge of operations becomes hardened into a concrete footweight that eventually completely hobbles their progress.

Why does this pattern continually repeat? It seems that each successive management team needs to prove the case for their own merits to the ownership team. This means dropping a lot of hot technological industry keywords to make it sound like they know what they are doing. Down in the trenches though the day to day operations and design have much more to do with properly morphing data and processes from point A to point B. The actual technology used can be quite variable: a competent developer can utilize whatever tools he is best familiar with and still meet most any businesses objective. The developer does pay a hefty learning surcharge however when the new management team forces him to switch tools.

In order to maintain their sheen with the ownership circle however the new technical management has to show progress on implementing the latest shiny technologies, and so they wrench the legacy staff with new learning requirements. Or alternatively they bring in new developers familiar with the latest technology. These new folks then need to grok the intricacies of the inner gearings of the current environment (the business rules), which causes the vicious downward cycle of decreasing quality, poor communication, and the sense of backstabbing that pervades the industry.

Due to constant insecurity, nowadays developers don’t “turn over” their software creations for other staff to run or automate. Rather, to protect their job security they provide whatever “service” their software performs, often running jobs from their own computers and adding tweaks and adjustments as necessary (so called DevOps). To be socially correct legacy employees tend to respect the silos of responsibility set up by one another, and they learn who is responsible for all the particular aspects of production.

This causes many hours of wasted meetings and reteachings as the new team reassures themselves that existing siloed processes are being properly handled (mostly rehashing things that the legacy staff has already been handling fine by themselves for years). The optics and appearance of working together becomes more important than actually spending time making processes provide better value to customers. Everything that had been resolved previously gets requestioned once again with each management turnover. The legacy staff spends more time managing impressions and worrying about office politics than accomplishing any actual work.

After two or three years pass and the new technical management teams can’t fully deliver on the promises they made to the ownership and senior managers, they get fired and a new management team is hired. The new technical management team has better promises and the cycle of rework starts anew.

In an ideal world the ownership would encourage exsiting employees to gin up on new technologies and provide ample opportunity for them to do so. They would internally promote to management those legacy employees most capable of sharing their internal knowledge and welcome the apprenticeship of new developers.

To some extent company owners and entrepreneurs have become self-blinded by the “disruption” culture: they confuse how external startups with nothing to lose can disrupt an industry and presume they can achieve the same internally by bringing in new folks with an entrepreneurial spirit. What they miss in this conversation is that successful systems always proceed from simple to become more complicated. Nobody ever magically transforms an existing complicated systems into a new equally successful complicated system. It’s not sociologically possible.

Since it proves impossible to effectively “disrupt” from the top, instead managers disrupt from the side. This causes increasing complexity in system cross-connections and synchronizations. Where I worked we eventually had six copies of the same data. Why? Because each silo of development wanted a local copy for their own use and wanted to synchronize copies in a manner convenient to their own individual schedules.

After all these years, sadly I don’t see any particular fix to the problem of the way things work in IT; there’s no way off this hamster wheel. No matter how wasteful and inefficient the process sounds, it does actually provide gainful employment for hundreds of thousands of people. In a sense then, company rot is the acceptable and only viable sociological way to conduct technological businesses. Because folks value employment, systems always grow more complicated until the companies that house them can no longer grow competitively and fold completely.

Avoiding an AI Apocalypse

Artificial intelligence (AI) has become a ubiquitous and integral part of modern technology. While the potential benefits of AI are vast and transformative, the idea of AI running out of control is a concern that has existed since its inception. As AI capabilities continue to advance at an unprecedented rate, it’s becoming increasingly important to consider the potential risks that could come with such progress.

Out of control AI could potentially cause economic disruption, job displacement, and even existential risks. The idea of an AI explosion occurring that extends beyond human control is a legitimate concern, and it’s important to take steps to mitigate this risk.

Historically, people have suggested various measures to ensure AI remains under human control. However, these suggestions have largely failed sociologically. For example, one popular idea was to implement ethical guidelines for AI. However, these guidelines have not been universally adopted, and even when they have, they have often been ignored or circumvented.

Guidelines to implement transparency and accountability or establishing clear legal frameworks for AI development and deployment may run afoul of some human interests, since greed and the desire for power can subvert these guidelines. For example, companies may be hesitant to disclose certain information about their AI development if they believe it could give their competitors an advantage.

Similarly, governments may be reluctant to establish clear legal frameworks for AI if they see it as a way to gain an edge over other nations. For example, some autonomous weapons systems are designed to make their own decisions about when to use lethal force, potentially putting human lives at risk.

Moreover, even if guidelines are established, there is no guarantee that they will be followed. Human nature dictates that some individuals and organizations will always try to find ways to circumvent rules and regulations to achieve their goals. This is especially true in highly competitive industries, where the pressure to succeed can lead to unethical behavior.

However, this does not mean that guidelines to ensure transparency and accountability in AI development and deployment are pointless. While some may try to subvert these guidelines, they still serve an important purpose. More importantly, as there may be no practical way to reign in the failure of human ethics, the goal of AI guidelines should rather focus on how to maintain control over its progress.

One way to mitigate the risk of AI running out of control is to prohibit machines from autonomously connecting to power sources or updating their own hardware and software. This would help to ensure that AI remains under human control.

However, there are already technologies that may violate these guidelines. For instance, some robots seek out power from solar panels that they control and adjust. Many of the software packages on your own PC are already capable of updating themselves without human approval.

To ensure that guidelines for AI development and deployment are effective, it is crucial that they are simple enough for average people to detect and report violations. The vast majority of people do not have technical expertise in AI, and overly complex guidelines would make it difficult for them to identify violations. Therefore, guidelines should be designed in a way that is easy for anyone to understand.

Additionally, violations of the guidelines must be punished seriously to send a strong message to other organizations that transgressions will not be tolerated. Furthermore, it’s important to establish mechanisms for reporting violations of the guidelines. Whistleblower protections should also be put in place to protect those who come forward with information about violations.

Ultimately, the success of guidelines for AI development and deployment depends on the willingness of individuals, organizations, and governments to take them seriously. This means that guidelines must be enforced consistently and fairly, regardless of the size or power of the organization in question.

In summary, for guidelines to succeed, they must be simple enough for average people to detect and report violations, and violators must be punished seriously to send a message to others. We believe that the restrictions of prohibiting autonomously connecting to power sources or autonomously updating hardware and software would meet the requirements of simple detection and verification, and can provide sufficient human control to avoid an AI apocalypse.

How to Watch, Enjoy and Understand a Skating Competition

In another life, I am L.A. SkateDad, and although that blog is tailored more to the figure skating in-crowd, this post is something useful to regular (non-skating) folks. Figure skating is a great sport to watch, but it can be supremely discombobulating to figure out how they score and rank the skaters. Nevertheless it can be a rewarding experience if you watch it for what it can offer, so herein I’ll elaborate on what it undertakes as well as explain a bit about the scoring in wide general terms.

You know, there are vastly more local competitions than televised events. Find some local ice rinks, see what club practices there, and then visit their web site. Many rinks also have a corkboard or monitor showing upcoming events. Events can be a formal affair following the official scoring rules, or they can be fun showcases emphasizing costume, personality, and theatrical productions.

Another way to find competitions is to go to the USFSA compete website. Select a range of dates, and then in the location box enter a comma, space, and your state (for example “, CA”). Events can be “qualifying” or not, the qualifying events are more strictly scored. Now that you’ve found something nearby visit the club host’s website and download an event schedule, and then look for the junior, novice, and senior ladies events. These are the most exciting and competitive to watch.

So let’s put aside scoring for a moment: figure skating is glamour, athletics, grace, dance, and art all wrapped up into one. When you are watching at the rink, appreciate how a skater joins her moves to the music, watch how her blades glide across the ice, admire how she controls her center of gravity through deep turns, spins, and jumps. Think about the effort and design that goes into the creation of her costume, and consider the daily hours of arduous practice contributing to how she has honed her art.

So some general observations about how they score. The judges sit across from the audience or sometimes in front, down by the ice. Judges are seasoned skater themselves and frequently coaches, and yes everybody knows everybody else. Scoring is based upon the difficulty of what the skater attempts, general aesthetic qualities about their skate, and whether they successfully accomplish required elements.

When you watch, many of the skaters will fall, possibly several times. Yes it hurts. Falling is part of the sport though, especially during daily practice when a skater is learning tougher elements. One aspect of personality is the skater’s approach to the event: are they practicing their harder elements in a competition setting because they are already on the US team? Then they might fall quite a bit. Or are they trying to skate a “clean” event without any falls to impress their coach and family?

Since a fall isn’t penalized as much as attempted difficulty is rewarded, it is possible (even entirely likely) that a graceful experienced skater attempting difficult elements, even falling on a couple of them, may attain a higher score than somebody with personality who never falls. You might say that scoring is tilted toward athleticism and demonstration of prowess.

In a qualifying competition the skater skates two events (one short and one long program, possibly on different days) and they add the two scores together. At the end of a skate there will be a pause as the judges tally, and then the rink announcer will disclose the score (and then the combined score if this is the second skate) followed by the skaters current rank. In this way if you listen carefully, you can tell who is in first place. Obviously rank positions can change after each skate, but if you hear something like “Suzie is now in first place” and then nobody following her gets that “first place” announcement later, then guess what? Suzie won the competition.

So there’s a lot to pay attention to as a spectator, but enjoy the show and remember that physically, skating is like a choreographed quarter-mile sprint. You’re watching amazing intelligent athletes, top of the line.

How to Work

Introduction
I’m always surprised to look back and realize what they fail to teach you in school. You spend most of your adult life in jobs working with people, and yet there aren’t any classes about how to do this. Sure there are subject matter classes: you can learn physics, or computer programming, or marketing. I don’t mean the content of your job though, but rather the methodology — the people skills — how to get along with your fellow employees. I’m semi-retired now, so this is a reflection across my forty-five years of employment to describe what worked for me.

You’ll want both a productive and a protective work attitude, balancing your sanity with enough smarts to make you valuable to employers. I am going to jump right in and give you the whole shebang — a summary first — even though much of it lacks the explanations to be comprehensible. Once you’ve seen the summary you can then choose which parts of the aftermatter to skim or read in further detail. Plus the summary is a handy rip-out that you can print and save for easy reference.

I do have to qualify this as being rather prescriptive and reductive: I didn’t hold these beliefs the entire span of my career, rather they developed gradually evolving over time. But by the end of my career I was juggling all of these thoughts in my mind while working away.

Tips for a Reasonable Work Attitude

Manage the physical, spiritual, sociological, and perceptual
Simplify, personalize, de-escalate, disaggregate
Say what you can do, “wondering if”, describe, yield, grasp the big picture
Cheerful, kindly, reverent, small, courteous, hopeful
Be aware of long-term problems, take advantage of short-term opportunities, use mid-term strategies
Improve global quality of life, be courteous to all souls, think in terms of sustainability
Don’t create the Thing, create the Environment
Principle of perceived value, zero-point protocol, principle of equivalent commitment
The foibles: false self-importance, false surrogate endpoint, tunnel vision.
Do the Right Thing. Sometimes this is Nothing.

Four Categories
Many of my work philosophies were frequently at odds with one another; typically bending toward one goal distances you from another. I found the best course overall though was to balance how I managed the physical, spiritual, sociological, and perceptual.

The physical is the material change in the world you are precipitating: setting up a workspace, buying and consuming lunch, pouring concrete into forms, removing a kidney. The spiritual is all about god, love, and art. The sociological is how you harmonize with society and interact with its expectations and morals: it’s the “people stuff”. Finally the perceptual is management of appearances. This overlaps with the other three items, but folks spend enough separate time on it to qualify it as a distinguishable category.

You could write an entire book about the details of balancing these four forces, with the pros and cons of concentrating on each. And fair enough, various personalities tend to place greater emphasis on one versus another. I will defer my opinions and simply suggest that too extreme a tilt toward any one is detrimental, but ultimately it is completely up to you how to allocate your attention.

Less Stress Is Best
It is in the realm of relating to those you work with, your boss(es) and fellow employees, that you gently paddle your career boat upriver. Many times -how- you treat your associates has as much impact upon your path as what you accomplish with respect to the job itself. Have you ever felt a coworker takes themselves too seriously? Well it’s quite easy to take oneself too seriously, and so I recommend three shortcuts to lighten up your load and speed you along your journey.

Many times we tend to view people as their title: this guy is the CEO, this gal is the Director of Marketing. You’ll discover if you treat employees just as regular folks you’ll get along better with them. This is Tom with two kids and three grandkids, this is Lauren with two grown boys still living at home. Make your work relationships personal.

I have a favorite saying: there is no limit on how complicated things can become, on account of every one thing leading to another. I find this to be especially true at work. Systems accumulate enhancements that drive them toward greater complexity, and people deliberately add procedures and requirements to buttress their job security. One should always mind the bigger picture, what your company is trying to accomplish, and simplify your processes and communication with others to focus on these goals as much as reasonable.

People seriously believe their beliefs about what their position should entail, and you’ll always find fellow employees more interested in controlling this standpoint than working as a team. At times like this it is valuable to cultivate the skill of de-escalation. Mostly this involves respecting the other person’s perspective while working to develop a shared pool of meaning about what is critical, while considering alternative ways to reach your shared objectives.

Another helpful way to work as a team member is to disaggregate objectives. This is a bit of a blend of the prior points: simplifying a process by allowing some things to occur without others, resequencing, and separating wants from needs or styles.

Rocking the Rowboat Responsibly
When in employ, I have generally found it helps to “stay small.” You can have some influence, just don’t try to be influential. Some of the methods for this are quite specific. When you have an idea, instead of suggesting it as the Right Thing for a group of people to do, instead frame it as a question. “I’m wondering if it would make more sense for us to focus on fixing the bugs first?” Phrasing it in this fashion allows others to provide feedback before making judgment, and creates a group consensus.

These types of conversations may draw out more of your inner thinking as well, and it’s worth the effort to describe your thoughts and feelings behind your suggestions. Your bosses and subordinates need to hear your assumptions and reasoning so they can better understand your perspective. Formerly implicit behaviors may yield valid alternative viewpoints when fully described. Avoid being stubbornly set in your own viewpoints. Yield.

Finally if at all possible try to grasp and share the “big picture,” rather than thrashing about in the weeds of incipient detail. Where does your company fit overall into the world, and what is your project attempting to achieve within those goals?

Remember About Yourself
It’s a little too easy to lose yourself in your work. By this I mean one can become so focused on the tasks and camaraderie at your job that you forget to take care of your own spiritual needs. Endeavor to accomplish these within your routines at work: you’ll find it beneficial to be cheerful, kindly, reverent, small, courteous, and hopeful within the workplace, just as you would in your personal life. Nobody is going to remember you for how quickly you prepared the year-end tax schedules, but they will recall the nice Christmas present you gave them.

Focus
As in most aspects of life, one has to approach the challenges of work with a blended and balanced perspective. Companies have a broad mix of long-term plans and short term objectives, and if you’re not careful you can shoot your future self in the foot if you focus too much on achieving all of your little assignments as directed in the present. Be aware of any long-term problems the company might face, especially those that go unspoken. Where appropriate take advantage of short-term opportunities, but overall use mid-term strategies to advance you and your employer’s common goals.

At the same time do realize you are part of a broader society. You will become aware of many substantial issues that are more encompassing than what happens at work, and you should pay attention to your responsibilities to those as well, but on your own personal time. Work to improve global quality of life, be courteous to all souls, and think in terms of sustainability. It’s terrific when you can influence your fellow employees to follow these same principles, but you need to be keenly sensitive to the fact that most employers prefer you not promote your personal agendas during work hours.

Leverage
Depending on your position and the nature of your work, you should stay alert to acts of meta-cognition, areas where you can go beyond simply creating a thing or a process and instead contribute a generative framework. This may be either procedural or environmental. Thinking in terms of leverage can hyperboost your productivity.

Staying Spiritually Healthy
Most of the foregoing ideas will keep you quite actively involved in juggling work and personal priorities, yet you still need to avoid being exploited by your commitments, both to others and yourself. To remain spiritually healthy it makes sense to follow the Three Principles of Perceived Value, Zero-point protocol, and Equivalent Commitment. I expand upon these in further detail in another essay.

Mental Health
Along with the aforementioned techniques for keeping your spiritual balance, you also need to monitor aspects of your perception to counter many of the learned biases and skewed perceptions foisted upon you by our culture. This may smell irrelevant to everything else you address in the workplace, yet you ignore these at your peril, as eventually any of these foibles can accumulate enough momentum to send you into a bout of deep depression.

The first pratfall to avoid is feeling too self-important. Yes, you are a God in your own world, or an important muse in the global flow of love. Still though, everybody else is too. And in the universal view of things across all time and space, our lives are insignificant motes of dust. This doesn’t mean you have no significance, just that you should temper your self-importance and step back frequently.

The second pratfall to avoid is attending too much importance to a surrogate endpoint. It is common for people to select targets to manage that are different than ultimate goals. For example, studies show that high blood pressure leads to an increase in strokes and heart attacks, so people take medication to lower their blood pressure. In this case the measurement of blood pressure is a surrogate endpoint — it is meant to stand in as a measuring point along the way to the primary goals of longevity and health.

Still however, there are problems with just ingesting things to lower your blood pressure: sometimes such an additive can be harmful in and of itself. Similarly at work, people set deadlines to deliver certain projects by certain dates, with the goal of improving profitability. But there are things you can do that motivate people to meet the deadline that would ultimately be detrimental to the company. The idea isn’t to shoot the river: don’t keep rowing downstream when it makes more sense to camp alongside the rapids for a couple of days and then return home fulfilled with an enjoyable vacation.

The final pratfall is a bit related to false surrogate endpoints: tunnel vision. It is not uncommon in an organization to develop such extreme camaraderie to a vision and a goal that employees get tunnel vision. They exclude all thinking and possibilities that would stray from that vision or goal. This is tunnel vision. When this happens a company loses the ability to harvest serendipitous discoveries and points of inflection that could make them considerably better. The same can happen with you individually, if you focus too intently on, say, a certain career path. Billions of dollars get wasted on a high-speed rail project because everyone jumped onboard in excitement, without a way to evaluate the project’s sustainability. A narrow path is a straitjacket objective.

Zen Art
Do the Right Thing. Sometimes this is Nothing.

The Starbucks Problem

I mean, I really like Starbucks espressos. Also the ambiance is usually nice once you get your drink, and are all seated and situated. The ordering though. oh my god. I went down to the store in North Hollywood West, and as they were experiencing their 9 a.m. rush (and since I abhor standing in line) I just sat outside, opened up my laptop, and worked on my writing projects for a while. Every few minutes I’d peek through the window to check on the wait.

Finally the cashier line cleared and it looked as if there were just a couple folks waiting for their orders to be fulfilled. I went inside and as I approached the register the clerk said “Hi,” and when I nodded, she said “I’ll be with you in just a minute”. Then she proceeded to spend two minutes popping things in and out of a toaster oven, bagging them, and bringing them to the pickup window. Meanwhile another employee casually cleaned various tables.

I was not a happy camper to be left standing at the altar, as it were. When she finally finished up and approached me, she said “sorry for the wait, how can I help you?” I calmed myself and replied, “I’m sorry for the wait too.” Then I stood quietly. After a couple of seconds she said “how can I help you?” I waited a few seconds, and then replied “I’m just going to stand here quietly for fifteen seconds, so you can get a taste and appreciate how it feels to wait.” And then I stood quietly for fifteen seconds. Then I placed my order, one double espresso.

— * —

After downing my espresso and pondering further, the only viable engineering solution I could arrive at for this waiting problem was one of matching the spiky production demand against the expectations of customers by having honest measurement and feedback. In other words I walk into the store, and the timer starts on me. I can peer up at a sign with average wait times and decide if I want to proceed. (The wait times are calculated from point of store entry to delivery and completion of order).

Now that everything is out in the open we can discuss how to manage it, and how to better engineer a solution to match up individual customer expectations to results. The main issue is the conflict of spiky demand with the mix of customers: some truly don’t mind waiting as they have nothing better to do. Moms with kids who are meeting their friends. Others, like myself, feel extremely put upon to wait. The management team is failing to recognize that fact. Pre-ordering doesn’t help and in fact creates other issues: bottlenecks at the delivery counter and drinks served that become cold.

Supermarkets have solved a similar problem of spiky register-line length by installing self-service checkouts, and for the most part it has worked. Maybe we need a self-service espresso machine. Super high-quality, same kind Starbucks uses but with a card-reader and a cash slot. Scan the card or put in a fiver and out comes your espresso. The quality has to be up to that from the barrista drawn shots though, and that of course is a rather large engineering challenge in and of itself.

Or split the Starbucks store internally into two sub-stores, one catering to fast orders, one to slower. One drink and a pastry, stand here: total wait time 80 seconds. Everybody else stand here, wait time 5 minutes. Yes I know, it’s not a problem on par with global warming or droughts or civil wars or tax evasion or the incompetence of the medical industry, but you know I solve what I can where I’m located.

T’ai Chi revisited for modern times

Time is a flow that turns Mystery into Desire.
It is the opposite of a thing that highlights its properties.
Desire drives both vanity and disorder.
First, emptiness.
Benevolence is not in the realm of nature, that guides by physics. Still however benevolence used gently grows heaven and earth.
Humility begets excellence.
What you create enters by the spirit to serve the path for others. Hence let your creations walk; they belong not unto you.
Self-awareness of spirit allows perspective to humility.
The hard and real physical is but ephemeral sun, air, and water for the growth of the spiritual and immaterial. Only the spirit of things lasts enduringly.
A spartan life avoids temptations that dull your senses to awareness. In all things moderation.
Fame and possessions do not bring happiness, which rather springs from self-awareness, serenity, occupation, meaning, and purpose.
Manage the path of your soul like you pour your tea.
Humility and meditative stillness avoids the faults of ego. Be like a tree.
Health too springs from the holistic awareness of the connectiveness of the silence behind all things.
Conformity to an engulfing culture deadens our spirit.
Only matters of the soul matter.
Weeding your needs feeds a peaceful mind. Avoid overexertions beyond your needs, and avoid complex desires to follow the natural path of your soul.
Following the path of your soul enamors you to those who share in that praxis.
Neither brag nor show-off.
Manifest yourself as a small part of the flow of love and you exhibit all of Heaven and Earth.
Stay still with your possessions. Travel creates desire and self-awareness, hence makes one wiser but less happy.
Leave your places and spirits better than you found them.
Be peaceful and open to ideas.
Avoid armaments.
Beware philosophers claiming crown, for matters of the soul permeate independently of people.
The sapling grows taller not by comparing itself to the redwood. Follow your own path; the journey of a thousand miles starts with a single seed.
Love seems small, but it is inexhaustible.
Explication of the soul derives from being, not from doing. The way things are causes what is happening causes what people are thinking.
We are all but small within the universe.
The Tao is balanced in both its positive and its negative space.
Teach by your thoughts alone.
Security depends more upon what you can do without, rather than what you have.
You may choose to be busy in the outside world or the spiritual realm, but when you fill the glass with water the air leaves it.
Always be lightly teaching, yet indifferent. Most of the time you lead most effectively by pointing in the opposite direction.
Life is an adventure, not a destination. Manage your pathway so as to stay safe and healthy.
Without a controlling demeanor, love brings growth. The guarding of what is soft and tender is the secret of strength.
Refinery when boastful is an affront to the simpleness of Nature.
By promoting love we strengthen it, but it must be promoted with loving means.
We stay young by staying vulnerable and pliant. Cheerful, kindly, reverent: this is to overcome our age.
Those who speak much know little.
The dead govern the living.
A great soul must learn to abase itself.
Love grants both compassion and forgiveness.
Pay attention to the small stuff. It’s all small stuff.
Do not strive.
You convince others by understanding them, not by fighting them. You win a battle by de-escalating it.
It is best to be unsure in your knowledge and always be preparing.
Be aware of all things and yet still pay attention to them.
Firm like a tree, not bold like a lion.
He who lives by the sword dies by the sword.
If you spend too much attention straightening papers, they become impossible to straighten.
To be strong is also to be both brittle and to invite destroyers.
Be forgiving and open-minded in your reconciliations and settlements with others.
Too much refinement kills sincerity.