More on Personal Growth
Matthew Royse
3 years ago
These 10 phrases are unprofessional at work.
Successful workers don't talk this way.
"I know it's unprofessional, but I can't stop." — Author Sandy Hall
Do you realize your unprofessionalism? Do you care? Self-awareness?
Everyone can improve their unprofessionalism. Some workplace phrases and words shouldn't be said.
People often say out loud what they're thinking. They show insecurity, incompetence, and disrespect.
"Think before you speak," goes the saying.
Some of these phrases are "okay" in certain situations, but you'll lose colleagues' respect if you use them often.
Your word choice. Your tone. Your intentions. They matter.
Choose your words carefully to build work relationships and earn peer respect. You should build positive relationships with coworkers and clients.
These 10 phrases are unprofessional.
1. That Meeting Really Sucked
Wow! Were you there? You should be responsible if you attended. You can influence every conversation.
Alternatives
Improve the meeting instead of complaining afterward. Make it more meaningful and productive.
2. Not Sure if You Saw My Last Email
Referencing a previous email irritates people. Email follow-up can be difficult. Most people get tons of emails a day, so it may have been buried, forgotten, or low priority.
Alternatives
It's okay to follow up, but be direct, short, and let the recipient "save face"
3. Any Phrase About Sex, Politics, and Religion
Discussing sex, politics, and religion at work is foolish. If you discuss these topics, you could face harassment lawsuits.
Alternatives
Keep quiet about these contentious issues. Don't touch them.
4. I Know What I’m Talking About
Adding this won't persuade others. Research, facts, and topic mastery are key to persuasion. If you're knowledgeable, you don't need to say this.
Alternatives
Please don’t say it at all. Justify your knowledge.
5. Per Our Conversation
This phrase sounds like legal language. You seem to be documenting something legally. Cold, stern, and distant. "As discussed" sounds inauthentic.
Alternatives
It was great talking with you earlier; here's what I said.
6. Curse-Word Phrases
Swearing at work is unprofessional. You never know who's listening, so be careful. A child may be at work or on a Zoom or Teams call. Workplace cursing is unacceptable.
Alternatives
Avoid adult-only words.
7. I Hope This Email Finds You Well
This is a unique way to wish someone well. This phrase isn't as sincere as the traditional one. When you talk about the email, you're impersonal.
Alternatives
Genuinely care for others.
8. I Am Really Stressed
Happy, strong, stress-managing coworkers are valued. Manage your own stress. Exercise, sleep, and eat better.
Alternatives
Everyone has stress, so manage it. Don't talk about your stress.
9. I Have Too Much to Do
You seem incompetent. People think you can't say "no" or have poor time management. If you use this phrase, you're telling others you may need to change careers.
Alternatives
Don't complain about your workload; just manage it.
10. Bad Closing Salutations
"Warmly," "best," "regards," and "warm wishes" are common email closings. This conclusion sounds impersonal. Why use "warmly" for finance's payment status?
Alternatives
Personalize the closing greeting to the message and recipient. Use "see you tomorrow" or "talk soon" as closings.
Bringing It All Together
These 10 phrases are unprofessional at work. That meeting sucked, not sure if you saw my last email, and sex, politics, and religion phrases.
Also, "I know what I'm talking about" and any curse words. Also, avoid phrases like I hope this email finds you well, I'm stressed, and I have too much to do.
Successful workers communicate positively and foster professionalism. Don't waste chances to build strong work relationships by being unprofessional.
“Unprofessionalism damages the business reputation and tarnishes the trust of society.” — Pearl Zhu, an American author
This post is a summary. Read full article here
Zuzanna Sieja
3 years ago
In 2022, each data scientist needs to read these 11 books.
Non-technical talents can benefit data scientists in addition to statistics and programming.
As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.
Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.
Ready? Let’s dive in.
Best books for data scientists
1. The Black Swan
Author: Nassim Taleb
First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.
Three characteristics define a black swan event:
It is erratic.
It has a significant impact.
Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.
People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.
Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.
Try multiple tactics and models because you may find the answer.
2. High Output Management
Author: Andrew Grove
Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.
That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.
Five lessons:
Every action is a procedure.
Meetings are a medium of work
Manage short-term goals in accordance with long-term strategies.
Mission-oriented teams accelerate while functional teams increase leverage.
Utilize performance evaluations to enhance output.
So — if the above captures your imagination, it’s well worth getting stuck in.
3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers
Author: Ben Horowitz
Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.
Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.
It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.
Find suggestions on:
create software
Run a business.
Promote a product
Obtain resources
Smart investment
oversee daily operations
This book will help you cope with tough times.
4. Obviously Awesome: How to Nail Product Positioning
Author: April Dunford
Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.
How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.
You'll learn:
Select the ideal market for your products.
Connect an audience to the value of your goods right away.
Take use of three positioning philosophies.
Utilize market trends to aid purchasers
5. The Mom test
Author: Rob Fitzpatrick
The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.
Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.
6. Introduction to Machine Learning with Python: A Guide for Data Scientists
Authors: Andreas C. Müller, Sarah Guido
Now, technical documents.
This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.
Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.
If you know machine learning or artificial neural networks, skip this.
7. Python Data Science Handbook: Essential Tools for Working with Data
Author: Jake VanderPlas
Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.
Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.
The only thing missing is a way to apply your learnings.
8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Author: Wes McKinney
The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.
The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.
9. Data Science from Scratch
Author: Joel Grus
Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.
The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.
Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.
10. Machine Learning Yearning
Author: Andrew Ng
Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.
The book delivers knowledge and teaches how to apply it, so you'll know how to:
Determine the optimal course of action for your ML project.
Create software that is more effective than people.
Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.
Identifying machine learning system flaws
Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.
11. Deep Learning with PyTorch Step-by-Step
Author: Daniel Voigt Godoy
The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.
It comprises four parts:
Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)
Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)
Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)
Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)
We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.
Is every data scientist a humanist?
Even as a technological professional, you can't escape human interaction, especially with clients.
We hope these books will help you develop interpersonal skills.
Datt Panchal
3 years ago
The Learning Habit
The Habit of Learning implies constantly learning something new. One daily habit will make you successful. Learning will help you succeed.
Most successful people continually learn. Success requires this behavior. Daily learning.
Success loves books. Books offer expert advice. Everything is online today. Most books are online, so you can skip the library. You must download it and study for 15-30 minutes daily. This habit changes your thinking.
Typical Successful People
Warren Buffett reads 500 pages of corporate reports and five newspapers for five to six hours each day.
Each year, Bill Gates reads 50 books.
Every two weeks, Mark Zuckerberg reads at least one book.
According to his brother, Elon Musk studied two books a day as a child and taught himself engineering and rocket design.
Learning & Making Money Online
No worries if you can't afford books. Everything is online. YouTube, free online courses, etc.
How can you create this behavior in yourself?
1) Consider what you want to know
Before learning, know what's most important. So, move together.
Set a goal and schedule learning.
After deciding what you want to study, create a goal and plan learning time.
3) GATHER RESOURCES
Get the most out of your learning resources. Online or offline.
You might also like
Max Parasol
3 years ago
Are DAOs the future or just a passing fad?
How do you DAO? Can DAOs scale?
DAO: Decentralized Autonomous. Organization.
“The whole phrase is a misnomer. They're not decentralized, autonomous, or organizations,” says Monsterplay blockchain consultant David Freuden.
As part of the DAO initiative, Freuden coauthored a 51-page report in May 2020. “We need DAOs,” he says. “‘Shareholder first' is a 1980s/90s concept. Profits became the focus, not products.”
His predictions for DAOs have come true nearly two years later. DAOs had over 1.6 million participants by the end of 2021, up from 13,000 at the start of the year. Wyoming, in the US, will recognize DAOs and the Marshall Islands in 2021. Australia may follow that example in 2022.
But what is a DAO?
Members buy (or are rewarded with) governance tokens to vote on how the DAO operates and spends its money. “DeFi spawned DAOs as an investment vehicle. So a DAO is tokenomics,” says Freuden.
DAOs are usually built around a promise or a social cause, but they still want to make money. “If you can't explain why, the DAO will fail,” he says. “A co-op without tokenomics is not a DAO.”
Operating system DAOs, protocol DAOs, investment DAOs, grant DAOs, service DAOs, social DAOs, collector DAOs, and media DAOs are now available.
Freuden liked the idea of people rallying around a good cause. Speculators and builders make up the crypto world, so it needs a DAO for them.
,Speculators and builders, or both, have mismatched expectations, causing endless, but sometimes creative friction.
Organisms that boost output
Launching a DAO with an original product such as a cryptocurrency, an IT protocol or a VC-like investment fund like FlamingoDAO is common. DAOs enable distributed open-source contributions without borders. The goal is vital. Sometimes, after a product is launched, DAOs emerge, leaving the company to eventually transition to a DAO, as Uniswap did.
Doing things together is a DAO. So it's a way to reward a distributed workforce. DAOs are essentially productivity coordination organisms.
“Those who work for the DAO make permissionless contributions and benefit from fragmented employment,” argues Freuden. DAOs are, first and foremost, a new form of cooperation.
DAO? Distributed not decentralized
In decentralized autonomous organizations, words have multiple meanings. DAOs can emphasize one aspect over another. Autonomy is a trade-off for decentralization.
DAOstack CEO Matan Field says a DAO is a distributed governance system. Power is shared. However, there are two ways to understand a DAO's decentralized nature. This clarifies the various DAO definitions.
A decentralized infrastructure allows a DAO to be decentralized. It could be created on a public permissionless blockchain to prevent a takeover.
As opposed to a company run by executives or shareholders, a DAO is distributed. Its leadership does not wield power
Option two is clearly distributed.
But not all of this is “automated.”
Think quorum, not robot.
DAOs can be autonomous in the sense that smart contracts are self-enforcing and self-executing. So every blockchain transaction is a simplified smart contract.
Dao landscape
The DAO landscape is evolving.
Consider how Ethereum's smart contracts work. They are more like self-executing computer code, which Vitalik Buterin calls “persistent scripts”.
However, a DAO is self-enforcing once its members agree on its rules. As such, a DAO is “automated upon approval by the governance committee.” This distinguishes them from traditional organizations whose rules must be interpreted and applied.
Why a DAO? They move fast
A DAO can quickly adapt to local conditions as a governance mechanism. It's a collaborative decision-making tool.
Like UkraineDAO, created in response to Putin's invasion of Ukraine by Ukrainian expat Alona Shevchenko, Nadya Tolokonnikova, Trippy Labs, and PleasrDAO. The DAO sought to support Ukrainian charities by selling Ukrainian flag NFTs. With a single mission, a DAO can quickly raise funds for a country accepting crypto where banks are distrusted.
This could be a watershed moment for DAOs.
ConstitutionDAO was another clever use case for DAOs for Freuden. In a failed but “beautiful experiment in a single-purpose DAO,” ConstitutionDAO tried to buy a copy of the US Constitution from a Sotheby's auction. In November 2021, ConstitutionDAO raised $47 million from 19,000 people, but a hedge fund manager outbid them.
Contributions were returned or lost if transactional gas fees were too high. The ConstitutionDAO, as a “beautiful experiment,” proved exceptionally fast at organizing and crowdsourcing funds for a specific purpose.
We may soon be applauding UkraineDAO's geopolitical success in support of the DAO concept.
Some of the best use cases for DAOs today, according to Adam Miller, founder of DAOplatform.io and MIDAO Directory Services, involve DAO structures.
That is, a “flat community is vital.” Prototyping by the crowd is a good example. To succeed, members must be enthusiastic about DAOs as an alternative to starting a company. Because DAOs require some hierarchy, he agrees that "distributed is a better acronym."
Miller sees DAOs as a “new way of organizing people and resources.” He started DAOplatform.io, a DAO tooling advisery that is currently transitioning to a DAO due to the “woeful tech options for running a DAO,” which he says mainly comprises of just “multisig admin keys and a voting system.” So today he's advising on DAO tech stacks.
Miller identifies three key elements.
Tokenization is a common method and tool. Second, governance mechanisms connected to the DAO's treasury. Lastly, community.”
How a DAO works...
They can be more than glorified Discord groups if they have a clear mission. This mission is a mix of financial speculation and utopianism. The spectrum is vast.
The founder of Dash left the cryptocurrency project in 2017. It's the story of a prophet without an heir. So creating a global tokenized evangelical missionary community via a DAO made sense.
Evan Duffield, a “libertarian/anarchist” visionary, forked Bitcoin in January 2014 to make it instant and essentially free. He went away for a while, and DASH became a DAO.
200,000 US retailers, including Walmart and Barnes & Noble, now accept Dash as payment. This payment system works like a gift card.
Arden Goldstein, Dash's head of crypto, DAO, and blockchain marketing, claims Dash is the “first successful DAO.” It was founded in 2016 and disbanded after a hack, an Ethereum hard fork and much controversy. But what are the success metrics?
Crypto success is measured differently, says Goldstein. To achieve common goals, people must participate or be motivated in a healthy DAO. People are motivated to complete tasks in a successful DAO. And, crucially, when tasks get completed.
“Yes or no, 1 or 0, voting is not a new idea. The challenge is getting people to continue to participate and keep building a community.” A DAO motivates volunteers: Nothing keeps people from building. The DAO “philosophy is old news. You need skin in the game to play.”
MasterNodes must stake 1000 Dash. Those members are rewarded with DASH for marketing (and other tasks). It uses an outsourced team to onboard new users globally.
Joining a DAO is part of the fun of meeting crazy or “very active” people on Discord. No one gets fired (usually). If your work is noticed, you may be offered a full-time job.
DAO community members worldwide are rewarded for brand building. Dash is also a great product for developing countries with high inflation and undemocratic governments. The countries with the most Dash DAO members are Russia, Brazil, Venezuela, India, China, France, Italy, and the Philippines.
Grassroots activism makes this DAO work. A DAO is local. Venezuelans can't access Dash.org, so DAO members help them use a VPN. DAO members are investors, fervent evangelicals, and local product experts.
Every month, proposals and grant applications are voted on via the Dash platform. However, the DAO may decide not to fund you. For example, the DAO once hired a PR firm, but the community complained about the lack of press coverage. This raises a great question: How are real-world contractual obligations met by a DAO?
Does the DASH DAO work?
“I see the DAO defund projects I thought were valuable,” Goldstein says. Despite working full-time, I must submit a funding proposal. “Much faster than other companies I've worked on,” he says.
Dash DAO is a headless beast. Ryan Taylor is the CEO of the company overseeing the DASH Core Group project.
The issue is that “we don't know who has the most tokens [...] because we don't know who our customers are.” As a result, “the loudest voices usually don't have the most MasterNodes and aren't the most invested.”
Goldstein, the only female in the DAO, says she worked hard. “I was proud of the DAO when I made the logo pink for a day and got great support from the men.” This has yet to entice a major influx of female DAO members.
Many obstacles stand in the way of utopian dreams.
Governance problems remain
And what about major token holders behaving badly?
In early February, a heated crypto Twitter debate raged on about inclusion, diversity, and cancel culture in relation to decentralized projects. In this case, the question was how a DAO addresses alleged inappropriate behavior.
In a corporation, misconduct can result in termination. In a DAO, founders usually hold a large number of tokens and the keys to the blockchain (multisignature) or otherwise.
Brantly Millegan, the director of operations of Ethereum Name Service (ENS), made disparaging remarks about the LGBTQ community and other controversial topics. The screenshotted comments were made in 2016 and brought to the ENS board's attention in early 2022.
His contract with ENS has expired. But what of his large DAO governance token holdings?
Members of the DAO proposed a motion to remove Millegan from the DAO. His “delegated” votes net 370,000. He was and is the DAO's largest delegate.
What if he had refused to accept the DAO's decision?
Freuden says the answer is not so simple.
“Can a DAO kick someone out who built the project?”
The original mission “should be dissolved” if it no longer exists. “Does a DAO fail and return the money? They must r eturn the money with interest if the marriage fails.”
Before an IPO, VCs might try to remove a problematic CEO.
While DAOs use treasury as a governance mechanism, it is usually controlled (at least initially) by the original project creators. Or, in the case of Uniswap, the venture capital firm a16z has so much voting power that it has delegated it to student-run blockchain organizations.
So, can DAOs really work at scale? How to evolve voting paradigms beyond token holdings?
The whale token holder issue has some solutions. Multiple tokens, such as a utility token on top of a governance token, and quadratic voting for whales, are now common. Other safeguards include multisignature blockchain keys and decision time locks that allow for any automated decision to be made. The structure of each DAO will depend on the assets at stake.
In reality, voter turnout is often a bigger issue.
Is DAO governance scalable?
Many DAOs have low participation. Due to a lack of understanding of technology, apathy, or busy lives. “The bigger the DAO, the fewer voters who vote,” says Freuden.
Freuden's report cites British anthropologist Dunbar's Law, who argued that people can only maintain about 150 relationships.
"As the DAO grows in size, the individual loses influence because they perceive their voting power as being diminished or insignificant. The Ringelmann Effect and Dunbar's Rule show that as a group grows in size, members become lazier, disenfranchised, and detached.
Freuden says a DAO requires “understanding human relationships.” He believes DAOs work best as investment funds rooted in Cryptoland and small in scale. In just three weeks, SyndicateDAO enabled the creation of 450 new investment group DAOs.
Due to SEC regulations, FlamingoDAO, a famous NFT curation investment DAO, could only have 100 investors. The “LAO” is a member-directed venture capital fund and a US LLC. To comply with US securities law, they only allow 100 members with a 120ETH minimum staking contribution.
But how did FlamingoDAO make investment decisions? How often did all 70 members vote? Art and NFTs are highly speculative.
So, investment DAOs are thought to work well in a small petri dish environment. This is due to a crypto-native club's pooled capital (maximum 7% per member) and crowdsourced knowledge.
While scalability is a concern, each DAO will operate differently depending on the goal, technology stage, and personalities. Meetups and hackathons are common ways for techies to collaborate on a cause or test an idea. But somebody still organizes the hack.
Holographic consensus voting
But clever people are working on creative solutions to every problem.
Miller of DAOplatform.io cites DXdao as a successful DAO. Decentralized product and service creator DXdao runs the DAO entirely on-chain. “You earn voting rights by contributing to the community.”
DXdao, a DAOstack fork, uses holographic consensus, a voting algorithm invented by DAOstack founder Matan Field. The system lets a random or semi-random subset make group-wide decisions.
By acting as a gatekeeper for voters, DXdao's Luke Keenan explains that “a small predictions market economy emerges around the likely outcome of a proposal as tokens are staked on it.” Also, proposals that have been financially boosted have fewer requirements to be successful, increasing system efficiency.” DXdao “makes decisions by removing voting power as an economic incentive.”
Field explains that holographic consensus “does not require a quorum to render a vote valid.”
“Rather, it provides a parallel process. It is a game played (for profit) by ‘predictors' who make predictions about whether or not a vote will be approved by the voters. The voting process is valid even when the voting quorum is low if enough stake is placed on the outcome of the vote.
“In other words, a quorum is not a scalable DAO governance strategy,” Field says.
You don't need big votes on everything. If only 5% vote, fine. To move significant value or make significant changes, you need a longer voting period (say 30 days) and a higher quorum,” says Miller.
Clearly, DAOs are maturing. The emphasis is on tools like Orca and processes that delegate power to smaller sub-DAOs, committees, and working groups.
Miller also claims that “studies in psychology show that rewarding people too much for volunteering disincentivizes them.” So, rather than giving out tokens for every activity, you may want to offer symbolic rewards like POAPs or contributor levels.
“Free lunches are less rewarding. Random rewards can boost motivation.”
Culture and motivation
DAOs (and Web3 in general) can give early adopters a sense of ownership. In theory, they encourage early participation and bootstrapping before network effects.
"A double-edged sword," says Goldstein. In the developing world, they may not be fully scalable.
“There must always be a leader,” she says. “People won't volunteer if they don't want to.”
DAO members sometimes feel entitled. “They are not the boss, but they think they should be able to see my calendar or get a daily report,” Goldstein gripes. Say, “I own three MasterNodes and need to know X, Y, and Z.”
In most decentralized projects, strong community leaders are crucial to influencing culture.
Freuden says “the DAO's community builder is the cryptoland influencer.” They must “disseminate the DAO's culture, cause, and rally the troops” in English, not tech.
They must keep members happy.
So the community builder is vital. Building a community around a coin that promises riches is simple, but keeping DAO members motivated is difficult.
It's a human job. But tools like SourceCred or coordinate that measure contributions and allocate tokens are heavily marketed. Large growth funds/community funds/grant programs are common among DAOs.
The Future?
Onboarding, committed volunteers, and an iconic community builder may be all DAOs need.
It takes a DAO just one day to bring together a passionate (and sometimes obsessive) community. For organizations with a common goal, managing stakeholder expectations is critical.
A DAO's core values are community and cause, not scalable governance. “DAOs will work at scale like gaming communities, but we will have sub-DAOs everywhere like committees,” says Freuden.
So-called holographic consensuses “can handle, in principle, increasing rates of proposals by turning this tension between scale and resilience into an economical cost,” Field writes. Scalability is not guaranteed.
The DAO's key innovation is the fragmented workplace. “Voting is a subset of engagement,” says Freuden. DAO should allow for permissionless participation and engagement. DAOs allow for remote work.”
In 20 years, DAOs may be the AI-powered self-organizing concept. That seems far away now. But a new breed of productivity coordination organisms is maturing.
Dr. Linda Dahl
3 years ago
We eat corn in almost everything. Is It Important?
Corn Kid got viral on TikTok after being interviewed by Recess Therapy. Tariq, called the Corn Kid, ate a buttery ear of corn in the video. He's corn crazy. He thinks everyone just has to try it. It turns out, whether we know it or not, we already have.
Corn is a fruit, veggie, and grain. It's the second-most-grown crop. Corn makes up 36% of U.S. exports. In the U.S., it's easy to grow and provides high yields, as proven by the vast corn belt spanning the Midwest, Great Plains, and Texas panhandle. Since 1950, the corn crop has doubled to 10 billion bushels.
You say, "Fine." We shouldn't just grow because we can. Why so much corn? What's this corn for?
Why is practical and political. Michael Pollan's The Omnivore's Dilemma has the full narrative. Early 1970s food costs increased. Nixon subsidized maize to feed the public. Monsanto genetically engineered corn seeds to make them hardier, and soon there was plenty of corn. Everyone ate. Woot! Too much corn followed. The powers-that-be had to decide what to do with leftover corn-on-the-cob.
They are fortunate that corn has a wide range of uses.
First, the edible variants. I divide corn into obvious and stealth.
Obvious corn includes popcorn, canned corn, and corn on the cob. This form isn't always digested and often comes out as entire, polka-dotting poop. Cornmeal can be ground to make cornbread, polenta, and corn tortillas. Corn provides antioxidants, minerals, and vitamins in moderation. Most synthetic Vitamin C comes from GMO maize.
Corn oil, corn starch, dextrose (a sugar), and high-fructose corn syrup are often overlooked. They're stealth corn because they sneak into practically everything. Corn oil is used for frying, baking, and in potato chips, mayonnaise, margarine, and salad dressing. Baby food, bread, cakes, antibiotics, canned vegetables, beverages, and even dairy and animal products include corn starch. Dextrose appears in almost all prepared foods, excluding those with high-fructose corn syrup. HFCS isn't as easily digested as sucrose (from cane sugar). It can also cause other ailments, which we'll discuss later.
Most foods contain corn. It's fed to almost all food animals. 96% of U.S. animal feed is corn. 39% of U.S. corn is fed to livestock. But animals prefer other foods. Omnivore chickens prefer insects, worms, grains, and grasses. Captive cows are fed a total mixed ration, which contains corn. These animals' products, like eggs and milk, are also corn-fed.
There are numerous non-edible by-products of corn that are employed in the production of items like:
fuel-grade ethanol
plastics
batteries
cosmetics
meds/vitamins binder
carpets, fabrics
glutathione
crayons
Paint/glue
How does corn influence you? Consider quick food for dinner. You order a cheeseburger, fries, and big Coke at the counter (or drive-through in the suburbs). You tell yourself, "No corn." All that contains corn. Deconstruct:
Cows fed corn produce meat and cheese. Meat and cheese were bonded with corn syrup and starch (same). The bun (corn flour and dextrose) and fries were fried in maize oil. High fructose corn syrup sweetens the drink and helps make the cup and straw.
Just about everything contains corn. Then what? A cornspiracy, perhaps? Is eating too much maize an issue, or should we strive to stay away from it whenever possible?
As I've said, eating some maize can be healthy. 92% of U.S. corn is genetically modified, according to the Center for Food Safety. The adjustments are expected to boost corn yields. Some sweet corn is genetically modified to produce its own insecticide, a protein deadly to insects made by Bacillus thuringiensis. It's safe to eat in sweet corn. Concerns exist about feeding agricultural animals so much maize, modified or not.
High fructose corn syrup should be consumed in moderation. Fructose, a sugar, isn't easily metabolized. Fructose causes diabetes, fatty liver, obesity, and heart disease. It causes inflammation, which might aggravate gout. Candy, packaged sweets, soda, fast food, juice drinks, ice cream, ice cream topping syrups, sauces & condiments, jams, bread, crackers, and pancake syrup contain the most high fructose corn syrup. Everyday foods with little nutrients. Check labels and choose cane sugar or sucrose-sweetened goods. Or, eat corn like the Corn Kid.
Aaron Dinin, PhD
3 years ago
There Are Two Types of Entrepreneurs in the World Make sure you are aware of your type!
Know why it's important.
The entrepreneur I was meeting with said, "I should be doing crypto, or maybe AI? Aren't those the hot spots? I should look there for a startup idea.”
I shook my head. Yes, they're exciting, but that doesn't mean they're best for you and your business.
“There are different types of entrepreneurs?” he asked.
I said "obviously." Two types, actually. Knowing what type of entrepreneur you are helps you build the right startup.
The two types of businesspeople
The best way for me to describe the two types of entrepreneurs is to start by telling you exactly the kinds of entrepreneurial opportunities I never get excited about: future opportunities.
In the early 1990s, my older brother showed me the World Wide Web and urged me to use it. Unimpressed, I returned to my Super Nintendo.
My roommate tried to get me to join Facebook as a senior in college. I remember thinking, This is dumb. Who'll use it?
In 2011, my best friend tried to convince me to buy bitcoin and I laughed.
Heck, a couple of years ago I had to buy a new car, and I never even considered buying something that didn’t require fossilized dinosaur bones.
I'm no visionary. I don't anticipate the future. I focus on the present.
This tendency makes me a problem-solving entrepreneur. I identify entrepreneurial opportunities by spotting flaws and/or inefficiencies in the world and devising solutions.
There are other ways to find business opportunities. Visionary entrepreneurs also exist. I don't mean visionary in the hyperbolic sense that implies world-changing impact. I mean visionary as an entrepreneur who identifies future technological shifts that will change how people work and live and create new markets.
Problem-solving and visionary entrepreneurs are equally good. But the two approaches to building companies are very different. Knowing the type of entrepreneur you are will help you build a startup that fits your worldview.
What is the distinction?
Let's use some simple hypotheticals to compare problem-solving and visionary entrepreneurship.
Imagine a city office building without nearby restaurants. Those office workers love to eat. Sometimes they'd rather eat out than pack a lunch. As an entrepreneur, you can solve the lack of nearby restaurants. You'd open a restaurant near that office, say a pizza parlor, and get customers because you solved the lack of nearby restaurants. Problem-solving entrepreneurship.
Imagine a new office building in a developing area with no residents or workers. In this scenario, a large office building is coming. The workers will need to eat then. As a visionary entrepreneur, you're excited about the new market and decide to open a pizzeria near the construction to meet demand.
Both possibilities involve the same product. You opened a pizzeria. How you launched that pizza restaurant and what will affect its success are different.
Why is the distinction important?
Let's say you opened a pizzeria near an office. You'll probably get customers. Because people are nearby and demand isn't being met, someone from a nearby building will stop in within the first few days of your pizzeria's grand opening. This makes solving the problem relatively risk-free. You'll get customers unless you're a fool.
The market you're targeting existed before you entered it, so you're not guaranteed success. This means people in that market solved the lack of nearby restaurants. Those office workers are used to bringing their own lunches. Why should your restaurant change their habits? Even when they eat out, they're used to traveling far. They've likely developed pizza preferences.
To be successful with your problem-solving startup, you must convince consumers to change their behavior, which is difficult.
Unlike opening a pizza restaurant near a construction site. Once the building opens, workers won't have many preferences or standardized food-getting practices. Your pizza restaurant can become the incumbent quickly. You'll be the first restaurant in the area, so you'll gain a devoted following that makes your food a routine.
Great, right? It's easier than changing people's behavior. The benefit comes with a risk. Opening a pizza restaurant near a construction site increases future risk. What if builders run out of money? No one moves in? What if the building's occupants are the National Association of Pizza Haters? Then you've opened a pizza restaurant next to pizza haters.
Which kind of businessperson are you?
This isn't to say one type of entrepreneur is better than another. Each type of entrepreneurship requires different skills.
As my simple examples show, a problem-solving entrepreneur must operate in markets with established behaviors and habits. To be successful, you must be able to teach a market a new way of doing things.
Conversely, the challenge of being a visionary entrepreneur is that you have to be good at predicting the future and getting in front of that future before other people.
Both are difficult in different ways. So, smart entrepreneurs don't just chase opportunities. Smart entrepreneurs pursue opportunities that match their skill sets.