More on Science

Bob Service
3 years ago
Did volcanic 'glasses' play a role in igniting early life?
Quenched lava may have aided in the formation of long RNA strands required by primitive life.
It took a long time for life to emerge. Microbes were present 3.7 billion years ago, just a few hundred million years after the 4.5-billion-year-old Earth had cooled enough to sustain biochemistry, according to fossils, and many scientists believe RNA was the genetic material for these first species. RNA, while not as complicated as DNA, would be difficult to forge into the lengthy strands required to transmit genetic information, raising the question of how it may have originated spontaneously.
Researchers may now have a solution. They demonstrate how basaltic glasses assist individual RNA letters, also known as nucleoside triphosphates, join into strands up to 200 letters long in lab studies. The glasses are formed when lava is quenched in air or water, or when melted rock generated by asteroid strikes cools rapidly, and they would have been plentiful in the early Earth's fire and brimstone.
The outcome has caused a schism among top origin-of-life scholars. "This appears to be a great story that finally explains how nucleoside triphosphates react with each other to create RNA strands," says Thomas Carell, a scientist at Munich's Ludwig Maximilians University. However, Harvard University's Jack Szostak, an RNA expert, says he won't believe the results until the study team thoroughly describes the RNA strands.
Researchers interested in the origins of life like the idea of a primordial "RNA universe" since the molecule can perform two different functions that are essential for life. It's made up of four chemical letters, just like DNA, and can carry genetic information. RNA, like proteins, can catalyze chemical reactions that are necessary for life.
However, RNA can cause headaches. No one has yet discovered a set of plausible primordial conditions that would cause hundreds of RNA letters—each of which is a complicated molecule—to join together into strands long enough to support the intricate chemistry required to kick-start evolution.
Basaltic glasses may have played a role, according to Stephen Mojzsis, a geologist at the University of Colorado, Boulder. They're high in metals like magnesium and iron, which help to trigger a variety of chemical reactions. "Basaltic glass was omnipresent on Earth at the time," he adds.
He provided the Foundation for Applied Molecular Evolution samples of five different basalt glasses. Each sample was ground into a fine powder, sanitized, and combined with a solution of nucleoside triphosphates by molecular biologist Elisa Biondi and her colleagues. The RNA letters were unable to link up without the presence of glass powder. However, when the molecules were mixed with the glass particles, they formed long strands of hundreds of letters, according to the researchers, who published their findings in Astrobiology this week. There was no need for heat or light. Biondi explains, "All we had to do was wait." After only a day, little RNA strands produced, yet the strands continued to grow for months. Jan Paek, a molecular biologist at Firebird Biomolecular Sciences, says, "The beauty of this approach is its simplicity." "Mix the components together, wait a few days, and look for RNA."
Nonetheless, the findings pose a slew of problems. One of the questions is how nucleoside triphosphates came to be in the first place. Recent study by Biondi's colleague Steven Benner suggests that the same basaltic glasses may have aided in the creation and stabilization of individual RNA letters.
The form of the lengthy RNA strands, according to Szostak, is a significant challenge. Enzymes in modern cells ensure that most RNAs form long linear chains. RNA letters, on the other hand, can bind in complicated branching sequences. Szostak wants the researchers to reveal what kind of RNA was produced by the basaltic glasses. "It irritates me that the authors made an intriguing initial finding but then chose to follow the hype rather than the research," Szostak says.
Biondi acknowledges that her team's experiment almost probably results in some RNA branching. She does acknowledge, however, that some branched RNAs are seen in species today, and that analogous structures may have existed before the origin of life. Other studies carried out by the study also confirmed the presence of lengthy strands with connections, indicating that they are most likely linear. "It's a healthy argument," says Dieter Braun, a Ludwig Maximilian University origin-of-life chemist. "It will set off the next series of tests."

Sam Warain
3 years ago
Sam Altman, CEO of Open AI, foresees the next trillion-dollar AI company
“I think if I had time to do something else, I would be so excited to go after this company right now.”
Sam Altman, CEO of Open AI, recently discussed AI's present and future.
Open AI is important. They're creating the cyberpunk and sci-fi worlds.
They use the most advanced algorithms and data sets.
GPT-3...sound familiar? Open AI built most copyrighting software. Peppertype, Jasper AI, Rytr. If you've used any, you'll be shocked by the quality.
Open AI isn't only GPT-3. They created DallE-2 and Whisper (a speech recognition software released last week).
What will they do next? What's the next great chance?
Sam Altman, CEO of Open AI, recently gave a lecture about the next trillion-dollar AI opportunity.
Who is the organization behind Open AI?
Open AI first. If you know, skip it.
Open AI is one of the earliest private AI startups. Elon Musk, Greg Brockman, and Rebekah Mercer established OpenAI in December 2015.
OpenAI has helped its citizens and AI since its birth.
They have scary-good algorithms.
Their GPT-3 natural language processing program is excellent.
The algorithm's exponential growth is astounding. GPT-2 came out in November 2019. May 2020 brought GPT-3.
Massive computation and datasets improved the technique in just a year. New York Times said GPT-3 could write like a human.
Same for Dall-E. Dall-E 2 was announced in April 2022. Dall-E 2 won a Colorado art contest.
Open AI's algorithms challenge jobs we thought required human innovation.
So what does Sam Altman think?
The Present Situation and AI's Limitations
During the interview, Sam states that we are still at the tip of the iceberg.
So I think so far, we’ve been in the realm where you can do an incredible copywriting business or you can do an education service or whatever. But I don’t think we’ve yet seen the people go after the trillion dollar take on Google.
He's right that AI can't generate net new human knowledge. It can train and synthesize vast amounts of knowledge, but it simply reproduces human work.
“It’s not going to cure cancer. It’s not going to add to the sum total of human scientific knowledge.”
But the key word is yet.
And that is what I think will turn out to be wrong that most surprises the current experts in the field.
Reinforcing his point that massive innovations are yet to come.
But where?
The Next $1 Trillion AI Company
Sam predicts a bio or genomic breakthrough.
There’s been some promising work in genomics, but stuff on a bench top hasn’t really impacted it. I think that’s going to change. And I think this is one of these areas where there will be these new $100 billion to $1 trillion companies started, and those areas are rare.
Avoid human trials since they take time. Bio-materials or simulators are suitable beginning points.
AI may have a breakthrough. DeepMind, an OpenAI competitor, has developed AlphaFold to predict protein 3D structures.
It could change how we see proteins and their function. AlphaFold could provide fresh understanding into how proteins work and diseases originate by revealing their structure. This could lead to Alzheimer's and cancer treatments. AlphaFold could speed up medication development by revealing how proteins interact with medicines.
Deep Mind offered 200 million protein structures for scientists to download (including sustainability, food insecurity, and neglected diseases).
Being in AI for 4+ years, I'm amazed at the progress. We're past the hype cycle, as evidenced by the collapse of AI startups like C3 AI, and have entered a productive phase.
We'll see innovative enterprises that could replace Google and other trillion-dollar companies.
What happens after AI adoption is scary and unpredictable. How will AGI (Artificial General Intelligence) affect us? Highly autonomous systems that exceed humans at valuable work (Open AI)
My guess is that the things that we’ll have to figure out are how we think about fairly distributing wealth, access to AGI systems, which will be the commodity of the realm, and governance, how we collectively decide what they can do, what they don’t do, things like that. And I think figuring out the answer to those questions is going to just be huge. — Sam Altman CEO

Katrina Paulson
3 years ago
Dehumanization Against Anthropomorphization
We've fought for humanity's sake. We need equilibrium.
We live in a world of opposites (black/white, up/down, love/hate), thus life is a game of achieving equilibrium. We have a universe of paradoxes within ourselves, not just in physics.
Individually, you balance your intellect and heart, but as a species, we're full of polarities. They might be gentle and compassionate, then ruthless and unsympathetic.
We desire for connection so much that we personify non-human beings and objects while turning to violence and hatred toward others. These contrasts baffle me. Will we find balance?
Anthropomorphization
Assigning human-like features or bonding with objects is common throughout childhood. Cartoons often give non-humans human traits. Adults still anthropomorphize this trait. Researchers agree we start doing it as infants and continue throughout life.
Humans of all ages are good at humanizing stuff. We build emotional attachments to weather events, inanimate objects, animals, plants, and locales. Gods, goddesses, and fictitious figures are anthropomorphized.
Cast Away, starring Tom Hanks, features anthropization. Hanks is left on an island, where he builds an emotional bond with a volleyball he calls Wilson.
We became emotionally invested in Wilson, including myself.
Why do we do it, though?
Our instincts and traits helped us survive and thrive. Our brain is alert to other people's thoughts, feelings, and intentions to assist us to determine who is safe or hazardous. We can think about others and our own mental states, or about thinking. This is the Theory of Mind.
Neurologically, specialists believe the Theory of Mind has to do with our mirror neurons, which exhibit the same activity while executing or witnessing an action.
Mirror neurons may contribute to anthropization, but they're not the only ones. In 2021, Harvard Medical School researchers at MGH and MIT colleagues published a study on the brain's notion of mind.
“Our study provides evidence to support theory of mind by individual neurons. Until now, it wasn’t clear whether or how neurons were able to perform these social cognitive computations.”
Neurons have particular functions, researchers found. Others encode information that differentiates one person's beliefs from another's. Some neurons reflect tale pieces, whereas others aren't directly involved in social reasoning but may multitask contributing factors.
Combining neuronal data gives a precise portrait of another's beliefs and comprehension. The theory of mind describes how we judge and understand each other in our species, and it likely led to anthropomorphism. Neuroscience indicates identical brain regions react to human or non-human behavior, like mirror neurons.
Some academics believe we're wired for connection, which explains why we anthropomorphize. When we're alone, we may anthropomorphize non-humans.
Humanizing non-human entities may make them deserving of moral care, according to another theory. Animamorphizing something makes it responsible for its actions and deserves punishments or rewards. This mental shift is typically apparent in our connections with pets and leads to deanthropomorphization.
Dehumanization
Dehumanizing involves denying someone or anything ethical regard, the opposite of anthropomorphizing.
Dehumanization occurs throughout history. We do it to everything in nature, including ourselves. We experiment on and torture animals. We enslave, hate, and harm other groups of people.
Race, immigrant status, dress choices, sexual orientation, social class, religion, gender, politics, need I go on? Our degrading behavior is promoting fascism and division everywhere.
Dehumanizing someone or anything reduces their agency and value. Many assume they're immune to this feature, but tests disagree.
It's inevitable. Humans are wired to have knee-jerk reactions to differences. We are programmed to dehumanize others, and it's easier than we'd like to admit.
Why do we do it, though?
Dehumanizing others is simpler than humanizing things for several reasons. First, we consider everything unusual as harmful, which has helped our species survive for hundreds of millions of years. Our propensity to be distrustful of others, like our fear of the unknown, promotes an us-vs.-them mentality.
Since WWII, various studies have been done to explain how or why the holocaust happened. How did so many individuals become radicalized to commit such awful actions and feel morally justified? Researchers quickly showed how easily the mind can turn gloomy.
Stanley Milgram's 1960s electroshock experiment highlighted how quickly people bow to authority to injure others. Philip Zimbardo's 1971 Stanford Prison Experiment revealed how power may be abused.
The us-versus-them attitude is natural and even young toddlers act on it. Without a relationship, empathy is more difficult.
It's terrifying how quickly dehumanizing behavior becomes commonplace. The current pandemic is an example. Most countries no longer count deaths. Long Covid is a major issue, with predictions of a handicapped tsunami in the future years. Mostly, we shrug.
In 2020, we panicked. Remember everyone's caution? Now Long Covid is ruining more lives, threatening to disable an insane amount of our population for months or their entire lives.
There's little research. Experts can't even classify or cure it. The people should be outraged, but most have ceased caring. They're over covid.
We're encouraged to find a method to live with a terrible pandemic that will cause years of damage. People aren't worried about infection anymore. They shrug and say, "We'll all get it eventually," then hope they're not one of the 30% who develops Long Covid.
We can correct course before further damage. Because we can recognize our urges and biases, we're not captives to them. We can think critically about our thoughts and behaviors, then attempt to improve. We can recognize our deficiencies and work to attain balance.
Changing perspectives
We're currently attempting to find equilibrium between opposites. It's superficial to defend extremes by stating we're only human or wired this way because both imply we have no control.
Being human involves having self-awareness, and by being careful of our thoughts and acts, we can find balance and recognize opposites' purpose.
Extreme anthropomorphizing and dehumanizing isolate and imperil us. We anthropomorphize because we desire connection and dehumanize because we're terrified, frequently of the connection we crave. Will we find balance?
Katrina Paulson ponders humanity, unanswered questions, and discoveries. Please check out her newsletters, Curious Adventure and Curious Life.
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William Anderson
3 years ago
When My Remote Leadership Skills Took Off
4 Ways To Manage Remote Teams & Employees
The wheels hit the ground as I landed in Rochester.
Our six-person satellite office was now part of my team.
Their manager only reported to me the day before, but I had my ticket booked ahead of time.
I had managed remote employees before but this was different. Engineers dialed into headquarters for every meeting.
So when I learned about the org chart change, I knew a strong first impression would set the tone for everything else.
I was either their boss, or their boss's boss, and I needed them to know I was committed.
Managing a fleet of satellite freelancers or multiple offices requires treating others as more than just a face behind a screen.
You must comprehend each remote team member's perspective and daily interactions.
The good news is that you can start using these techniques right now to better understand and elevate virtual team members.
1. Make Visits To Other Offices
If budgeted, visit and work from offices where teams and employees report to you. Only by living alongside them can one truly comprehend their problems with communication and other aspects of modern life.
2. Have Others Come to You
• Having remote, distributed, or satellite employees and teams visit headquarters every quarter or semi-quarterly allows the main office culture to rub off on them.
When remote team members visit, more people get to meet them, which builds empathy.
If you can't afford to fly everyone, at least bring remote managers or leaders. Hopefully they can resurrect some culture.
3. Weekly Work From Home
No home office policy?
Make one.
WFH is a team-building, problem-solving, and office-viewing opportunity.
For dial-in meetings, I started working from home on occasion.
It also taught me which teams “forget” or “skip” calls.
As a remote team member, you experience all the issues first hand.
This isn't as accurate for understanding teams in other offices, but it can be done at any time.
4. Increase Contact Even If It’s Just To Chat
Don't underestimate office banter.
Sometimes it's about bonding and trust, other times it's about business.
If you get all this information in real-time, please forward it.
Even if nothing critical is happening, call remote team members to check in and chat.
I guarantee that building relationships and rapport will increase both their job satisfaction and yours.

Dr Mehmet Yildiz
3 years ago
How I train my brain daily for clarity and productivity.
I use a conceptual and practical system I developed decades ago as an example.
Since childhood, I've been interested in the brain-mind connection, so I developed a system using scientific breakthroughs, experiments, and the experiences of successful people in my circles.
This story provides a high-level overview of a custom system to inform and inspire readers. Creating a mind gym was one of my best personal and professional investments.
Such a complex system may not be possible for everyone or appear luxurious at first. However, the process and approach may help you find more accessible and viable solutions.
Visualizing the brain as a muscle, I learned to stimulate it with physical and mental exercises, applying a new mindset and behavioral changes.
My methods and practices may not work for others because we're all different. I focus on the approach's principles and highlights so you can create your own program.
Some create a conceptual and practical system intuitively, and others intellectually. Both worked. I see intellect and intuition as higher selves.
The mental tools I introduce are based on lifestyle changes and can be personalized by anyone, barring physical constraints or underlying health conditions.
Some people can't meditate despite wanting to due to mental constraints. This story lacks exceptions.
People's systems may vary. Many have used my tools successfully. All have scientific backing because their benefits attracted scientists. None are unethical or controversial.
My focus is cognition, which is the neocortex's ability. These practices and tools can affect the limbic and reptilian brain regions.
A previous article discussed brain health's biological aspects. This article focuses on psychology.
Thinking, learning, and remembering are cognitive abilities. Cognitive abilities determine our health and performance.
Cognitive health is the ability to think, concentrate, learn, and remember. Cognitive performance boosting involves various tools and processes. My system and protocols address cognitive health and performance.
As a biological organ, the brain's abilities decline with age, especially if not used regularly. Older people have more neurodegenerative disorders like dementia.
As aging is inevitable, I focus on creating cognitive reserves to remain mentally functional as we age and face mental decline or cognitive impairment.
My protocols focus on neurogenesis, or brain growth and maintenance. Neurons and connections can grow at any age.
Metacognition refers to knowing our cognitive abilities, like thinking about thinking and learning how to learn.
In the following sections, I provide an overview of my system, mental tools, and protocols.
This system summarizes my 50-year career. Some may find it too abstract, so I give examples.
First, explain the system. Section 2 introduces activities. Third, how to measure and maintain mental growth.
1 — Developed a practical mental gym.
The mental gym is a metaphor for the physical fitness gym to improve our mental muscles.
This concept covers brain and mind functionality. Integrated biological and psychological components.
I'll describe my mental gym so my other points make sense. My mental gym has physical and mental tools.
Mindfulness, meditation, visualization, self-conversations, breathing exercises, expressive writing, working in a flow state, reading, music, dance, isometric training, barefoot walking, cold/heat exposure, CBT, and social engagements are regular tools.
Dancing, walking, and thermogenesis are body-related tools. As the brain is part of the body and houses the mind, these tools can affect mental abilities such as attention, focus, memory, task switching, and problem-solving.
Different people may like different tools. I chose these tools based on my needs, goals, and lifestyle. They're just examples. You can choose tools that fit your goals and personality.
2 — Performed tasks regularly.
These tools gave me clarity. They became daily hobbies. Some I did alone, others with others.
Some examples: I meditate daily. Even though my overactive mind made daily meditation difficult at first, I now enjoy it. Meditation three times a day sharpens my mind.
Self-talk is used for self-therapy and creativity. Self-talk was initially difficult, but neurogenesis rewired my brain to make it a habit.
Cold showers, warm baths with Epsom salts, fasting, barefoot walks on the beach or grass, dancing, calisthenics, trampoline hopping, and breathing exercises increase my mental clarity, creativity, and productivity.
These exercises can increase BDNF, which promotes nervous system growth. They improve mental capacity and performance by increasing blood flow and brain oxygenation.
I use weekly and occasional activities like dry saunas, talking with others, and community activities.
These activities stimulate the brain and mind, improving performance and cognitive capacity.
3 — Measured progress, set growth goals.
Measuring progress helps us stay on track. Without data, it's hard to stay motivated. When we face inevitable setbacks, we may abandon our dreams.
I created a daily checklist for a spreadsheet with macros. I tracked how often and long I did each activity.
I measured my progress objectively and subjectively. In the progress spreadsheet, I noted my meditation hours and subjective feelings.
In another column, I used good, moderate, and excellent to get qualitative data. It took time and effort. Later, I started benefiting from this automated structure.
Creating a page for each activity, such as meditation, self-talk, cold showers, walking, expressive writing, personal interactions, etc., gave me empirical data I could analyze, modify, and graph to show progress.
Colored charts showed each area's strengths and weaknesses.
Strengths motivate me to continue them. Identifying weaknesses helped me improve them.
As the system matured, data recording became a habit and took less time. I saw the result immediately because I automated the charts when I entered daily data. Early time investment paid off later.
Mind Gym Benefits, Effective Use, and Progress Measuring
This concept helped me move from comfort to risk. I accept things as they are.
Turnarounds were made. I stopped feeling "Fight-Flight-Freeze" and maintained self-control.
I tamed my overactive amygdala by strengthening my brain. Stress and anxiety decreased. With these shifts, I accepted criticism and turned envy into admiration. Clarity improved.
When the cognitive part of the brain became stronger and the primitive part was tamed, managing thoughts and emotions became easier. My AQ increased. I learned to tolerate people, physical, mental, and emotional obstacles.
Accessing vast information sources in my subconscious mind through an improved RAS allowed me to easily tap into my higher self and recognize flaws in my lower self.
Summary
The brain loves patterns and routines, so habits help. Observing, developing, and monitoring habits mindfully can be beneficial. Mindfulness helps us achieve this goal systematically.
As body and mind are connected, we must consider both when building habits. Consistent and joyful practices can strengthen neurons and neural connections.
Habits help us accomplish more with less effort. Regularly using mental tools and processes can improve our cognitive health and performance as we age.
Creating daily habits to improve cognitive abilities can sharpen our minds and boost our well-being.
Some apps monitor our activities and behavior to help build habits. If you can't replicate my system, try these apps. Some smartwatches and fitness devices include them.
Set aside time each day for mental activities you enjoy. Regular scheduling and practice can strengthen brain regions and form habits. Once you form habits, tasks become easy.
Improving our minds is a lifelong journey. It's easier and more sustainable to increase our efforts daily, weekly, monthly, or annually.
Despite life's ups and downs, many want to remain calm and cheerful.
This valuable skill is unrelated to wealth or fame. It's about our mindset, fueled by our biological and psychological needs.
Here are some lessons I've learned about staying calm and composed despite challenges and setbacks.
1 — Tranquillity starts with observing thoughts and feelings.
2 — Clear the mental clutter and emotional entanglements with conscious breathing and gentle movements.
3 — Accept situations and events as they are with no resistance.
4 — Self-love can lead to loving others and increasing compassion.
5 — Count your blessings and cultivate gratitude.
Clear thinking can bring joy and satisfaction. It's a privilege to wake up with a healthy body and clear mind, ready to connect with others and serve them.
Thank you for reading my perspectives. I wish you a healthy and happy life.

Pen Magnet
3 years ago
Why Google Staff Doesn't Work
Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.
To boost employee efficiency.
Not surprising. Few envisioned Google declaring a productivity drive.
Sunder Pichai's speech:
“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”
The primary driver driving Google's efficiency push is:
Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.
Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.
Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.
Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.
In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.
FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.
Google has hardly ever discussed effectiveness:
Apparently openly.
Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.
Amazon trumps Google. In reality, it treats its employees poorly.
Google was the founding father of the modern-day open culture.
Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.
20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.
After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.
Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?
If so, would Google follow suit?
If so, how does Google go about doing it?
Before discussing Google's likely plan, let's examine programming productivity.
What determines a programmer's productivity is simple:
How would we answer Google's questions?
As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.
Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.
Deconstruct our main question.
How exactly do you change the culture of the firm so that productivity increases?
How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.
How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)
How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?
When implementing a large-scale organizational change, success must be carefully measured.
The fastest way to do something is to do it right, no matter how long it takes.
You require clearly-defined group/team/role segregation and solid pass/fail matrices to:
You can give performers rewards.
Ones that are average can be inspired to improve
Underachievers may receive assistance or, in the worst-case scenario, rehabilitation
As a 20-year programmer, I associate productivity with greatness.
Doing something well, no matter how long it takes, is the fastest way to do it.
Let's discuss a programmer's productivity.
Why productivity is a strange term in programming:
Productivity is work per unit of time.
Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.
As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.
All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.
Time is money — is not just a proverb, but an economical fact.
Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.
Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.
Programming productivity isn't linear, unlike manufacturing and maintenance.
Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.
Reversing the programming duties has no effect. Experts aren't needed for productivity.
These patterns remind me of an XKCD comic.
Programming productivity depends on two factors:
The capacity of the programmer and his or her command of the principles of computer science
His or her productive bursts, how often they occur, and how long they last as they engineer the answer
At some point, productivity measurement becomes Schrödinger’s cat.
Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.
Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.
Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.
Google can pull it off if it wants to.
What Google meant in reality when it said that employee productivity has decreased:
When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.
They can't multiply their work's influence over time.
Programmers who produce excellent modules or products are unsure on how to use them.
The best data scientists are unable to add the proper parameters in their models.
Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.
Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.
Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.
So, Google employees aren't productive.
How to fix it?
Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.
SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.
Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.
Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.
Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).
In conclusion:
Software development isn't linear. Why should the makers be measured?
Notation for The Big O
I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)
The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)
Google (or any large corporation) can do this.
Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.
Plot the influence of each employee over time using the X and Y axes, respectively.
Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).
Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.
After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.
Example of a Big(O) Category:
If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.
The Google interview truth:
O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.
O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.
CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.
Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.
UX/UI Designers must still prototype UI elements despite improved design tools.
All test cases are proportional to use cases/functional units, hence testers' work is O(N).
Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.
Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.
Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.
The fastest way to do something is to do it right, no matter how long it takes.
Conclusion:
Google is at the liberal extreme of the employee-handling spectrum
Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.
Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.
Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.
Any attempt to redefine people's measurements will affect the organization emotionally.
The more Google compares apples to apples, the higher its chances for future rebirth.