Category Archives: Machine Learning

artificial intelligence, Machine Learning, Positivity, Pricing

[VIC – 137] To charge or not to charge? That is the question.

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Business & Money

These days, I have a lot of conversations about pricing strategy in the early days of company building. And it seems like the inclination is often to give the product away for free at the beginning. The thinking is that a free product will make customers more inclined to try it (lower barrier to entry) and that it will provide a good opportunity to validate your thesis. And that makes some sense.

That said, I always prefer asking customers for money from the very start for a few key reasons.

First off, you have precisely 0 customers if your product is free. The definition of a customer is someone who buys something. So if you are not getting paid, then you don’t have customers. Similarly, businesses have revenue. Of course, every business has to get that elusive first customer, so there will be a (hopefully) short time at the beginning when you have none, but revenue should be the goal (ideally with positive free cash flows).

Second, asking for money provides good qualification. If you’re not asking for money, people may try your product/service because they like you or want to do you a favor. They’re far less likely to do that if you ask for money. You have to solve a real problem or add some tangible value. So if they say no when you ask for money, then you’re probably not doing that to a sufficient level.

Finally, I think asking for money actually increases your chances of success. When people pay for things, they then have some skin in the game and thus are more incentivized to make sure that investment has a positive outcome.

So, all things considered, I think if you’re trying to build a business, then you are better served by charging people from day 1.

Human Progress

You often hear about the “black box” problem with regards to artificial intelligence. That is, the problem whereby machine learning algorithms are making decisions, but the rationale for said decisions is inherently unexplainable.

For context, the field of machine learning has two general methods: supervised and unsupervised learning.

In supervised learning, you have a data set and you know exactly what the output should be. So you might a ton of cat pictures as the input dataset, and the output should be a “cat” or “not a cat” label. So you feed in your cat pictures, all with a pre-existing label of “cat” or “not a cat,” and that’s how you train the model on discerning whether in fact there is a cat in the picture. So after the training, when you feed in a new picture that is not labeled, the model will try to apply a label based on what it has learned from the training dataset.

With unsupervised learning, you feed in a bunch of data without much of an idea of what the output will look like. So sticking with cats, this time we have a bunch of pictures, but none of which have labels. We then feed them all into the system and it’s up to the model to cluster the pictures as it sees fit based on some relationship of variables within the pictures (number of legs, size of ears, stripes, etc).

The key difference here is that unsupervised learning has no feedback system. So the system might say “cat” or “not a cat,” but will not be able to tell you why it made the decision.

So some people are not happy about that unexplainability (might be making up that word).

What I find interesting, though, is that human beings are inherently unexplainable. People make asinine decisions all the time that are seemingly counterintuitive. We are all trapped inside our own heads and see the world subjectively. You can talk to other people, but you can never really be sure of what they’re thinking or why they do what they do.

So it doesn’t seem to me like the two situations are really all that different.

Philosophy

I recently got a marketing email from an events coordinator about attending one of their upcoming events. The funny thing is, I was already registered. You’d think they would be able to see that in their CRM or system of record.

So I typed the following response:

I’m already registered – please stop emailing me.

But before clicking send, I decided the email was in bad taste. So I typed this instead:

I’m already registered – see you there 🙂

So a few things on this:

One, I’m in sales and I know that CRM systems are often very messy. So I get it. It’s a mistake that my own business development team often makes.

Two, It’s a great example of why I love meditation. It has made me a much more mindful person that’s far more aware of my own emotions as they ebb and flow. So when annoyance bubbles up, I have a better chance of realizing it for what it is, without always acting on it.

Three, v1 of the email would have kicked off the spread of negative energy. I’m a huge fan of positive energy so hopefully the emoji in v2 made her smile and kicked off a chain reaction.

My Latest Discovery

A few weeks ago, I wrote about the Moment app for iOS that tracks your screen time. Now the latest version of iOS includes screen tracking as built-in functionality. Simply click the “settings” icon from your home screen, then click “Screen Time.”

I find it both sad and slightly comical when the big tech incumbents kill off an entire company with a software update. I think It will be very difficult for Moment to build a standalone business going forward.

artificial intelligence, Google, Machine Learning, Travel

[VIC – 136] I don’t want to think like you! 🙅

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Business & Money

I’ve been thinking a lot about risk and decision making.
Here’s a question: how much money (or something else you value) would you have to be offered to play Russian roulette? Would you take on a 16% chance of blowing your brains out for $50,000? $50 million? $5 billion?
Me personally, I would never play. For the simple reason that I might blow my brains out. There’s no coming back from that. So it would be a terrible decision with far too much risk.
What I’m trying to get at is that there is no reversing course with certain decisions. For example, if you decide to take on significant venture capital dollars, there’s no going back from that (in most cases). You are making a decision to be one type of company vs another.
One decision that is perhaps somewhat less extreme has to do with portfolio allocation. How much money should be held in cash vs short-term liquid investments (stocks, treasuries) vs longer-term illiquid assets (real estate, private company stock options)?
Or you could even zoom in on just stocks and try to decide, of your positions, what percentage should be value vs growth vs income?
Based on conversations I have, I think my appetite for risk is a good bit above the average. But given where we are in the current cycle, I’ve been dialing things back a bit.

Human Progress

Have any of you noticed the new predictive typing feature in Gmail? While you’re typing, Google will try to complete your phrases and sometimes even complete sentences. It’s yet another example of how AI and machine learning are deeply woven into everything Google is and does.
But I wonder what data is being used to train these predictive typing algorithms. Are they looking at just MY email history and all the messages I have sent to build a profile of what I might be about to write? Or, are they looking at messages that everyone has sent to make the best guess at what I might type next?
It’s a nuanced difference but I think an important one.
If they’re just using my data, I’m perfectly ok with that as it will likely help me write messages more quickly and be more productive.
But in the second scenario, they would be pushing everyone toward the mean. So not helping me complete my own thoughts, but more so helping me to think like you. To me, that would be downright frightening!
Machine learning will continue to seep into every crevasse of our lives and I have no doubt that we’ll have a tough time navigating these waters.

Philosophy

I wanted to share a couple observations from the week.
It’s faster to delete an email than to unsubscribe. But unsubscribing is looking out for your future self. 8 extra seconds now so I don’t have to delete a similar message in the future.
Throwing away boxes is faster when you don’t break them down. But breaking them down saves space in the trash room, and also makes it far easier for the building staff and employees of waste disposal companies. And those guys work hard for meager pay.
Doing the right thing at any given moment is sometimes inconvenient. But it remains the right thing. Plus, you get a little dopamine hit along the way from your awareness of doing it.

My Latest Discovery

I was traveling last week when I realized that my Priority Pass (gives you access to airport lounges) card was expired. Luckily, a few google searches revealed that there’s a priority pass mobile app. So as long as you know your membership number, you can download the app, log in, and simply scan the mobile barcode to gain access. Also, it has search functionality built in so that you can find out which lounges are available in which airports. Nice!
artificial intelligence, Investing, Machine Learning, Reading

[VIC – 79] WIFI. Crisis Text Line. 📖 vs 💻. StashInvest.

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Business & Money: WIFI

A friend and I were recently talking stocks and he asked me what pick I was most excited about right now. I answered with Boingo Wireless (ticker WIFI). Here are my reasons:

While smartphone growth in terms of total subscribers has slowed substantially in recent years, mobile data is exploding. People are spending more time than ever on smartphones and the growth shows no signs of abating.

And much of that time is now spent consuming mobile video. Video is far more intensive on the network then text, images, or audio.

Mobile networks were not built with this deluge in mind. As a result, most of the growth will be handled by WiFi and DAS (distributed antenna systems). Roughly 80% of mobile data consumption happens on WiFi.
The big wireless carriers are engaged in a race to the bottom. All are launching unlimited data plans due to consumer demand, which is putting serious strains on margins. Simultaneously, in order to acquire customers, they are rapidly reducing pricing and offering ridiculous promotions like a free year of service if you switch providers.

Given all of the above, Boingo seems positioned perfectly. They are partnering with the cell providers which allows the providers to automatically offload capacity to DAS (Boingo is one of the leading providers). They’re also building out DAS at strategic locations like airports, stadiums, military bases, and the like. And these contracts are all 10+ years in duration. That’s predictable revenue if ever seen it! Take a look at their latest investor deck if you’re curious.

The primary risk I see comes from carrier competition. Theoretically, carriers could choose not to partner with Boingo in favor of building DAS infrastructure themselves. But this seems unlikely because 1) building DAS is altogether different than building wireless networks. 2) Margins are already under a ton of pressure making this level of capital investment hard to swallow. 3) Cell companies are too busy trying to become content/media companies.

Human Progress: Crisis Text Line

All of the AI applications that you read about in the media reside in the for-profit realm. You have silicon valley and Detroit battling it out in self-driving cars. The big tech companies fighting for supremacy in voice assistants. Everyone trying to figure out how to use AI & ML to add real value to the bottom line.

Less publicized are applications in the nonprofit world. One such example involves Nancy Lublin and one of her nonprofits called Crisis Text Line. The organization provides relief to those in crisis via text messaging. How is AI relevant here you ask?
It turns out that people in crisis use certain trigger words in their messages that might reveal how likely they are to harm themselves. What are the first words that come to mind that might signify a suicide risk? Perhaps, death, die, suicide. That’s exactly what I thought too. After feeding all of the text messages into a database with the associated outcomes, then running a machine learning algorithm over all the data, it turns out we were wrong. Words like Tylenol, ibuprofen, and a crying face emoji were far more likely to lead to a suicide attempt than words like die or suicide.

Check out Nancy’s story in a recent episode of the Masters of Scale podcast from Reid Hoffman.

Philosophy: Books vs blogs

There’s an epic battle playing out in my psyche and I thought I would let you in on the mayhem.

In the right corner wearing the blue gloves we have books. I love books. They allow you to dive deep on a subject or story and require a certain level of sustained attention. It’s a kind of commitment to inquiry, analysis, and learning that I truly believe is vital so self-development. The great ones take on a life of their own and withstand the test of time, passing on their wisdom for posterity. Since we’re riding with the boxing analogy, let’s call books the intellectual heavyweight.

In the left corner wearing the red gloves we have blogs. I love great blogs. Not the shallow pop culture stuff, but blogs from interesting and insightful people that produce quality long-form brain food. Given their relative brevity, you get a far more diverse set of authors and ideas than is possible in the realm of books. You also avoid the trap that many book authors fall into wherein they pontificate about a subject for pages on end when an idea could have been just as easily presented in a paragraph. In other words, the value per word is far greater on a blog. You also have a level of interactivity with blogs offered by the comments section and their inherent shareability.

These two fighters seem to always go the full distance and end in a draw. And that’s ok because I don’t believe there has to be a clear winner. Both are wonderful in their own right.

I WILL add one thing though. At the end of the “blog” section, I mentioned interactivity as a point in the win column for blogs. However, books force another type of interactivity. While you don’t get to discuss things with the author or other readers, a great book forces you to interact with yourself in a way that sometimes carries much greater weight than interacting with others. They challenge your ideas and perspectives and often force you to reconsider things. And for more than 10 or 15 minutes. This might be why, for me at least, books get the nod.

And in boxing for that matter, things were clearly better back in days of heavyweight slugfests!

My Latest Discovery: StashInvest

A friend of mine reached out a few months ago asking about investing in stocks. I spoke to him for a while about my approach to picking companies. After the discussion, the friend said that they wanted to start investing, but many of the stock they wanted to buy were really expensive. One was Priceline which currently trades at $1,874. Given he wanted to start with a small portfolio, it’s pretty tough to diversify if you’re spending almost $1,900 for one share of one company.
Lucky for my friend, Stash (the company is actually called Collective Returns) is breaking down barriers for entry-level investors. They allow you to buy fractional shares and you can open an account with as little as $5. Gotta love how technology democratizes things!

Apology, artificial intelligence, Business Strategy, Cyber Security, Investing, Machine Learning, Poetry 2 Comments

[VIC – 69] Early stage investing. Everything is digital. We can do better. National Poetry Month. Flattery or plagiarism?

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Business & Money

When thinking about early stage investment opportunities, conventional wisdom says that these are generally reserved for silicon valley elites. There’s a small cabal of elite VCs that get access to all of the best deals and companies, while most are shut out. Thus the astronomical returns that accrue to these firms far out pace what the average person can expect to make while investing.
While mostly true, there are a few other ways to get a foot in the door for early stage opportunities. Here are a few:
1) You can always invest in startups yourself. Title III of the Jobs Act opens up the opportunity for regular retail investors to get their turn at startup investing. Regular people can create an account with any number of equity crowdfunding platforms (e.g. SeedInvest, MicroVentures) to participate in startup fundraising. While Title III is a good thing in general terms, it’s very unlikely that I’ll try my hand at picking individual companies. Chances are, all the best deals will be picked through by the VCs, angel syndicates, or individual angel investors. In other words, the equity crowdfunding platforms likely offer the bottom of the barrel in terms of investment opportunities. The platforms do take on some of the due diligence work to de-risk things a bit, but chances are you’ll still lose your money.
2) More realistically, you can try to take advantage of early stage opportunities by investing in public companies. For example, take artificial intelligence. We’re clearly in the hype cycle for AI and every company, both large and small, are trying to participate in the “AI gold rush”. To understand where the investment opportunities lie, we first need a bit ot context. Without getting into the weeds, deep learning is a subset of machine learning that uses computational systems loosely modeled on the human brain. Deep learning systems require a lot of processing power and thus require advanced GPUs (graphical processing units) which are far more powerful than their CPU (central processing unit) brethren. There are basically 2 companies that own the GPU market, Nvidia and Advanced Micro Devices, and both are publicly traded. NVDA is up 285% this year and AMD is up 481%. Not bad at all for a public market returns.
3) One slightly more esoteric way to get involved, and somewhat similar to above, involves investing in underlying technologies. Not investing in companies that produce the underlying technology, but the technology itself. I’ll give you two examples. First, think about the early days of the internet. Everyone and their mother were building internet based businesses and every one of those required a website. If you went on a buying spree in the 90s purchasing as many domain names as possible, you would be incredibly wealthy today. The average domain back then sold for around $0.50 – $5.00. Today, the average 5 letter word in the dictionary will cost you anywhere from $500,000 to $1,000,000 if you want to purchase the domain. That multiple is (you guessed it), 🍌🍌🍌🍌🍌! Secondly, I’m betting that cryptocurrencies will explode over the next 5 years. The value has already gone up over 100x since inception, and I’d say were in the first inning with no outs. I’ve been purchasing modest amounts of Bitcoin and Ethereum, the two leading cryptocurrencies, betting that they will be far more valuable in a few years. I’m less worried about these as digital currencies or stores of value, and more excited by the applications that will be built on the underlying technology. We’ll have to wait to see how this last one pans out.

Human Progress

If the 20th century was an industrial century, the 21st will be a digital one. Absolutely everything is going (or has gone) digital. Money, media, communication, commerce, conflict… everything. This transformation will, of course, bring great progress. But, it will also bring unprecedented risk. Cyber security risk that is. As the number of connected devices goes through the roof, so too do the number of vulnerabilities. I’m no cyber security expert, so I won’t try to delve into the details of the myriad vulnerabilities. Instead, I’d like to suggest 3 simple ways to greatly improve your digital security profile.
1 Turn on 2-factor authentication (2FA) for your email. For those unaware, 2FA is the process by which you use a second device to verify your identity. So when you log into your email account on your laptop, it will ask you for a password that you need to retrieve from your phone (SMS). As a result, you have a second layer of protection from someone trying to gain unauthorized access. And, while you can also enable 2FA on many other applications, email lies at the crux of everything. Anytime you need to reset a password, the reset link is sent via email. Thus, if someone gains access to your email, they likely have access to everything.
2 Use a VPN (virtual private network). VPNs offer a simple way to protect the data being transmitted over wireless networks by forcing all of your data through a server run by a VPN provider. These providers encrypt all of the data providing, again, another layer of protection. These require a simple, low-cost software download from any of a number of reputable providers. This is especially important if you regularly use public wifi networks (e.g. coffee shops, NYC parks & subways, etc). Anyone on these networks can access your data if it’s unprotected.
3 Use a secure browser (e.g. Opera). These run security checks in the background while you browse (checking for phishing, malware, etc) and many also include free built-in VPN software.
None of these will guarantee that you’re 100% safe, but you’re far better off with them than without.

Philosophy

You know that philosophical question, “if a tree falls in a forest and no one is around to hear it, does it make a sound?” I’ve been thinking about my own version. “If a person apologizes for a certain wrongdoing that they’ve committed, but the victim is not around to hear it, did the apology actually happen?” I would answer “no” to both questions. In the first, the tree hitting the ground would clearly disturb the adjacent air creating sound waves. But “hearing,” that involves those same sounds waves interacting with an ear drum and the associated nerve endings that translate those vibrations into an intelligible signal. In my own version of the question, the same logic applies. Yes, the apology is spoken, but the act of apologizing, if it is to be at all meaningful, involves both the speaker’s message and the listener’s reception and interpretation thereof. So even if the apology is heard, but there is no eye contact or a lack of conviction in the voice of the apologizer, we’ve adulterated the content of the words.
I began thinking about this when someone posted on Facebook about what’s often referred to as the Apology to Native Peoples. I wouldn’t be surprised if you’ve never heard of it (I had not before coming across this post). In essence, this was a resolution signed by President Obama in 2009 as an acknowledgment of the depredations and mistreatment of Native Americans by the US government. A formal apology of sorts. I see two glaring problems right off the bat.
First, the delivery. The resolution was quietly passed, buried deep within the Defense Appropriations act of 2009 (not an obvious location for such a resolution). But no attention was drawn to it. It’s almost like the apology was whispered under the breath so that no one could hear it. Not an apology at all if you ask me. If no one can hear it, it’s safe to assume that the act itself is narcissistic or inward focused. It serves to remove some guilt or responsibility, without putting the speaker at any risk or empathizing with the listener.
Secondly, the language.
“Whereas the arrival of Europeans in North America opened a new chapter in the history of Native Peoples.”
A new chapter?!?! Are you kidding me?? Let’s drop the warm and poetic language and call a spade a spade.
“Whereas while establishment of permanent European settlements in North America did stir conflict with nearby Indian tribes, peaceful and mutually beneficial interactions also took place.”
Peaceful and mutually beneficial? 😂😂 What a joke!
“Whereas Native Peoples and non-Native settlers engaged in numerous armed conflicts in which unfortunately, both took innocent lives, including those of women and children.”
Innocent lives taken on both sides? More like genocide or extermination of one side and flourishing on the other.
There is so much power in language. What is said is often less important than how it is said.
All of this makes me think about my own progress in delivering apologies. I, for one, can say I have a long way to go. I’ve often delivered apologies while staring at the floor, using defensive language, voice raised, arms crossed, and no eye contact. If I can’t do any better, our nation and our federal government likely can’t either. 😩 Come one! We’re better than that!

My Latest Discovery

On the same topic of native peoples, Layli Long Soldier is both a US citizen and a citizen of the Oglala Lakota Nation (a Native American Tribe). She is also an incredible poet. And, I’ve discovered that April happens to be National Poetry Month. I thought I would share one of her exquisite yet painful compositions called “38.”

I would highly recommend you listen, but if you prefer to read, you can do so here.

Question Of The Week

When is it ok to copy?
I’m thinking about this in the wake of rampant copying by Facebook. After seeing the success of SnapChat, Zuckerberg has basically copy/pasted SnapChat’s best features, pixel for pixel, into all 4 Facebook properties (WhatsApp, Instagram, Messenger, And Facebook).
I’m specifically thinking about this in relation to other great innovations that have been copied and commoditized. In the digital realm, think about the like button or the news feed. Basically every social application now has both. Someone had to be first. In cars, what about sunroofs? Whoever came up with the sunroof is a genius. Now every car on the block has one. The inventor must be pissed!
When does copying stop being the sincerest form of flattery and become plagiarism? Should there be more IP protection for digital products? Would this impact innovation in a negative way? So many questions!

Amazon, artificial intelligence, Identity, Machine Learning, Ride Sharing 2 Comments

[VIC – 68] Amazon vs the 🌎. Mnuchin off his 💊💊. Let her finish. Via 🚙.. Which identity comes first❓❓

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Business & Money

Amazon has an incredible business model. Start by building an e-commerce platform to sell books. Once at scale, allow anyone selling anything to leverage that platform to sell their own goods for a nominal fee. In the process of building this massive marketplace, create a powerhouse of a logistics network (warehouses, software, supply chain expertise, etc) to facilitate all of this activity. Once at scale, allow manufacturers and retailers to leverage these same logistics services and facilities for a nominal fee. In the process thereof, build out world-class cloud infrastructure for all of your own storage, processing, and computing needs. Once at scale with these efforts, allow any other company to leverage these same cloud services for a nominal fee.
It’s an absolutely genius model that continues to pour more and more gasoline on the fire that fuels growth. One hell of a flywheel!
This model shows no signs of slowing down. You may have read about how Amazon is experimenting with physical grocery stores where customers can simply walk in, grab what they want, and leave without stopping at a cash register. Or perhaps you’ve come across the fact that they’re leasing planes and investing in their own cargo hub in Kentucky. I’d say it’s pretty safe to assume that, once they figure out the model, the self-checkout technology will be offered to other retailers and the cargo hub will service the other logistics companies (of course for that not so nominal fee).
So, despite Amazon shares being crazy expensive (P/E ratio of 180.56), it may yet be undervalued. The company accounts for only 5% of retail sales (half the share of Walmart) and e-commerce still accounts for a single-digit percentage of all retail sales.
If you couldn’t tell, I am looooong Amazon!

Human Progress

Steve Mnuchin, the Treasury Secretary of the US, might be off his 💊💊.
“I think that is so far in the future – in terms of artificial intelligence taking over American jobs – I think we’re like so far away from that, that uh [it’s] not even on my radar screen. Far enough that it’s 50 or 100 years away.”
Are you f*&%$* kidding me??? I don’t think I’ve ever disagreed more with a single statement. This guy must be off his rocker.
Now, I don’t want to spend valuable time deriding this guy, but let’s focus on the crux of the issue. Why is artificial intelligence, or machine learning (ML) more specifically, important? Computer scientists have been touting its power and potential for decades and we have nothing to show for it except for movie recommendation algorithms and autonomous vacuum cleaners. Why is this time different?
I’ll tell you why this time is different. It has to do with something very fundamental to where we are with regards to this technology.
First, a definition. Now, I’m no engineer or machine learning expert, so I won’t even attempt to get technical here. In my own laymen terms, ML involves computers learning from lots and lots of data. You’ve likely taken a basic statistics class at some point. Do you remember covering probability? Simply calculating the likelihood of a future event based on historical data points? For all intents and purposes, that’s ML. Whether you want to talk about facial recognition, translation, product recommendations, self-driving cars, or anything else. It’s just looking at a bunch of data and past events, and using that to predict the future.
With that out of the way, we can get back to why this time is different. Throughout the history of technology, we’ve been building machines to work for us. Steam engines, the printing press, cars… All of these things burn fuel to do work so that we don’t have to and faster than we would be able to on our own. But, as wonderful as they all are, these machines are not “creators.” By that I mean, they have no ability to create anything outside of what is hard coded by human beings. Once you turn on the printing press, it will continually print things exactly the same way over and over again until the energy source is depleted or the machine breaks down. At no point will the machine figure out a better way to print something. Only a human being can design a better machine to replace the old one. This has been the model for technology since time immemorial.
With machine learning this changes. Take speech translation for example. When early translation programs were developed, the software was very simple. Here is the English dictionary. Here is the Spanish dictionary. Replace each word with its equivalent in the opposite language and voila. Translation! Of course, this fails because that is not how translation works. It isn’t a word for word type of thing. Different languages have different ways of conveying tone, capturing tense, etc. With the latest incarnation of Google translate, however, we have a whole separate ball game. The algorithm can look the entire library of books, articles, speeches, web pages, etc that have been translated into another language and start to predict how a sentence should be translated. What’s more, as the system takes in more translation examples and receives feedback, the algorithm can actually learn and improve mid-flight. That is, without human intervention, the translation service actually improves over time. That’s bananas!! 🍌🍌🍌🍌🍌
This is what Mr. Mnuchin is not understanding. This is not like other technologies where we invented something new that was better at doing a job. We have computers getting “smarter” by themselves.
Now I don’t want to overstate this. The capabilities are still very narrow. Each ML system is very good at one specific thing, but completely incompetent with regards to every other domain. None the less, this is a big deal.
Further, in addition to the fundamental difference just described, the speed of proliferation will be unprecedented. If we go back to the printing press and steam engine example, once these technologies were developed, it might take years or decades for the technology to spread across the globe. In the digital era, this is not the case. When talking about software and other digital goods, things can spread instantaneously, the cost of distribution is 0, and the marginal cost of creating another unit, also 0. When a new algorithm or application is created, you click a button and it is available in every corner of the globe. Again, 🍌🍌🍌🍌🍌!!
With these two fundamental differences, that is the machines playing the “creator” role and the speed at which these things can spread, we’re in uncharted territory.

Philosophy

A few days ago my fiancé made Tteok-bokki (pronounced “duck-bogi”). It’s a stir-fried Korean dish with fish cakes, rice cakes, boiled eggs, onions, and red pepper paste (among other things).

While she was cooking, she was multitasking with a few other things, so asked me to stir the pan. As I began to stir, the dish seemed overly watery. I opened my mouth to ask the question, “It’s a bit watery, no?” But then I paused. There was a slight a fear of being punched in the face, but more so, a realization that I should wait to ask the question. She’s made this dish countless times and perhaps it congeals as it cooks.
That’s exactly what happened. it was absolutely perfect. In fact, probably the best she has ever made!
This got me thinking about asking questions more generally. There are many times when I’m in a meeting at work or having a discussion with a friend and something that’s said doesn’t sit well with me. I either don’t fully understand or I simply disagree. But, usually, it serves me well to let someone fully articulate an idea or complete a thought before butting in with a question. Often times the idea makes a lot more sense in the full context of what’s being said, or at least you can see the other’s perspective with more clarity.

My Latest Discovery

I’ve been using the Via ride sharing app as of late. It’s essentially Uber Pool or Lyft Line, without the option to take a ride by yourself. It’s “ride sharing” in it’s purest form. They operate a fleet of Mercedes vans that seat up to 6 passengers. Due to the purely “shared” model, prices are far lower than they are with Uber & Lyft. It cost me $8 for a ride from Long Island City to the Flatiron district. The only downside is that you occasionally have to walk a few blocks for pickup in order to best optimize routing. Not a big deal if you ask me. If you’d like $10 in free ride credit and want to help me out as well 😊, my referral code is “jeremy2e7”.

Question Of The Week

We all have so many identities. I myself am a friend, soon-to-be husband, dog parent, salesperson, black, American (purposely separated those 2), student, NYC resident, etc.
How do you prioritize your various identities? Is there a rank order? What happens when two of these are in conflict?

 

Looking forward to hearing your thoughts! Onwards and upwards amigos(as)!