In a prior post, we looked at the Global GDP in 2021. Now, let's look at US Revenue vs. Expenditures in 2021.
So, from the start, we can see a 2,770-billion-dollar deficit last year. The #1 expenditure was income security. For those who don't know, income security is an extremely broad spending category. It covers everything from tax credits and unemployment to housing assistance, foster care, and many other welfare programs. It's somewhat of a catch-all for services that help people get necessities.
Surprisingly, the US pays more per person for healthcare than countries with nationalized healthcare.
Looking at 2021 isn't the best indicator of America's spending history as a whole; there were a lot of one-time events - and a pandemic. Usually, the deficit isn't that staggering.
While the deficit may grow out of control, debt is a powerful tool - not just a liability. Nonetheless, given our current economic situation, inflation, and rising interest rates, the strategy that got us here might not be the best strategy to get us where we want to go.
There's a lot of fear from workers about a future where their roles are taken. Gartner recently surveyed workers on what tasks they wanted AI to handle.
According to VentureBeat, some survey respondents did not want to use AI at work at all. Their reasons were privacy and security concerns.
I think one of the tasks that will be thrust upon AI companies is to help workers understand that AI is not meant to replace or take over their jobs, but to help workers be more effective and focused on higher-value tasks.
In 2016, I received this e-mail from my oldest son, who used to be a cybersecurity professional.
Date: Saturday, October 22, 2016 at 7:09 PM To: Howard Getson Subject: FYI: Security Stuff
FYI - I just got an alert that my email address and my Gmail password were available to be purchased online.
I only use that password for my email, and I have 2-factor enabled, so I'm fine. Though this is further proof that just about everything is hacked and available online.
If you don't have two-factor enabled on your accounts, you really need to do it.
Since then, security has only become a more significant issue. I wrote about the Equifax event, but there are countless examples of similar events (and yes, I mean countless).
When people think of hacking, they often think of a Distributed Denial of Service (DDOS) attack or the media representation of people breaking into your system in a heist.
In reality, the most significant weakness is people; it's you ... the user. It's the user that turns off automatic patch updating. It's the user that uses thumb drives. It's the user that reuses the same passwords. But, even if you do everything right, you're not always safe.
Your data is likely stored in dozens of places online. You hope your information is encrypted, but even that isn't always enough. Over the last 17 years, 17.2B records have been "lost" by various companies. In 2021, a new record was set with 5.9 billion user records stolen.
VisualCapitalist put together a visualization of the 50 biggest breaches since 2004.
It's impossible to protect yourself completely, but there are many simple things you can likely do better.
Use better passwords... Even better, don't even know them. You can't disclose what you don't know. Consequently, I recommend a password manager like LastPass or 1Password, which can also suggest complex passwords for you.
Check if any of your information has been stolen via a website like HaveIBeenPwned or F-Secure
Keep all of your software up to date (to avoid extra vulnerabilities)
Don't use public Wi-Fi if you can help it (and use a VPN if you can't)
Have a firewall on your computer and a backup of all your important data
Never share your personal information on an e-mail or a call that you did not initiate - if they legitimately need your information, you can call them back
Don't trust strangers on the internet (no, a Nigerian Prince does not want to send you money)
How many cybersecurity measures you take comes down to two simple questions ... First, how much pain and hassle are you willing to deal with to protect your data? And second, how much pain is a hacker willing to go through to get to your data?
My son always says, "you've already been hacked ... but have you been targeted?" Something to think about!
“Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.” —Sebastian Thrun
We often use human consciousness as the ultimate benchmark for artificial exploration.
The human brain is ridiculously intricate. While weighing only three pounds, it contains about 100 billion neurons and 100 trillion connections between them. On top of the sheer complexity, the order of the connections and the order of actions the brain does naturally make it even harder to replicate. The human brain is also constantly reorganizing and adapting. It's a beautiful piece of machinery.
We've had millions of years for this powerhouse of a computer to be created, and now we're trying to do the same with neural networks and machines in a truncated time period. While deep learning algorithms have been around for a while, we're just now developing enough data and computing power to change deep learning from a thought experiment to a real edge.
Think of it this way, when talking about the human brain, we talk about left-brain and right-brain. The theory is that left-brain activities are analytical and methodical, and right-brain activities are creative, free-form, and artistic. We're great at training AI for left-brain activities (obviously with exceptions). In fact, AI is beating us at these left-brain activities because a computer has a much higher input bandwidth than we do, they're less biased, and they can perform 10,000 hours of research by the time you finish this article.
It's tougher to train AI for right-brain tasks. That's where deep learning comes in.
Deep learning is a subset of machine learning based on unsupervised learning from unstructured/unlabeled data. Instead of asking AI a question, giving it metrics, and letting it chug away, you're letting AI be intuitive. Deep learning is a much more faithful representation of the human brain. It utilizes a hierarchy of convolutional neural networks to handle linear and non-linear operations so it can think creatively to better problem-solve on potentially various data sets and in unseen environments.
When a baby is first learning to walk, it might stand up and fall down. It might then take a small stutter step, or maybe a step that's much too far for its little baby body to handle. It will fall, fail, and learn. Fall, fail, and learn. That's very similar to the goal of deep learning or reinforcement learning.
What's missing is the intrinsic reward that keeps humans moving when the extrinsic rewards aren't coming fast enough. AI can beat humans at many games but has struggled with puzzle/platformers because there's not always a clear objective outside of clearing the level.
A relatively new (in practice, not in theory) approach is to train AI around "curiosity"[1]. Curiosity helps it overcome that boundary. Curiosity lets humans explore and learn for vast periods of time with no reward in sight, and it looks like it can do that for computers too!
Soon, I expect to see AI learn to forgive and forget, be altruistic, follow and break rules, learn to resolve disputes, and even value something that resembles "love" to us.
It was fascinating how so many religions consider this the Holy Land. Here is a photo I took of the Wailing Wall and the Dome of the Rock in the Old City of Jerusalem.
It’s easy to feel closer to “something” while here.
Almost everything we saw in Israel is a testament to determination, ingenuity, and faith!
With that said, I started to think about how difficult it was to conceive of many of the things they built (considering how difficult it would be to execute or actually build them in the desert, without electricity, etc.). Many of the sites we visited took decades to build ... but have lasted for thousands of years. Examples include the Fortress at Masada, the Wailing Wall, and the Port of Caesaria. In my mind, I compare these moonshots to many of our current big, hairy, audacious goals (like reading and writing our DNA, autonomous artificial intelligence, or space exploration).
Technologies might change, but human nature has remained surprisingly consistent throughout time.
Humans are notoriously bad at large numbers. It's hard to wrap our minds around something of that scale. We're wired to think locally and linearly, not exponentially (it's one of the reasons I love AI so much).
Here are a couple of ways to help you understand a billion dollars.
Next, let's look at spending over time. If you were to spend a dollar every second for an entire day, you would spend $86,400 per day. You can do that for approximately twelve days if you have a million dollars. With a billion dollars, you can do that for over 31 years. Ignoring the difference between net worth and cash, Jeff Bezos could spend $9M per day for over 31 years.
If you make $100K a year, you can earn $1 million in 10 years. At the same rate, it would take you 10,000 years to make $1 billion.
Here is an example framed around spending money. Imagine that someone making $50K a year decides to buy a laptop, a car, and a house. Now we're going to make a relative comparison of the cost of those items for people making a lot more than $50K per year. To do this, we'll shrink the cost of the price of those items (to see the relative cost-to-income ratio). For a millionaire, a laptop might cost the equivalent of $100 dollars, a Porsche would cost $3,000 dollars, and a house would cost $25,000. Now, let's say you're Mike Bloomberg, and you're worth $60B. A laptop's relative cost would be pennies, a Porsche's relative cost would be less than 60 cents, and a mansion's relative cost would be around $500 dollars. You could have everything you ever wanted for a minute fraction of your wealth.
For a different perspective, here's an interesting visualization from informationisbeautiful. It shows various examples of things worth billions of dollars – including the personal wealth of several billionaires.
Let's try explaining the concept of a Billion through time. Fifty thousand seconds is just under 14 hours. A million seconds was 11 days ago. A billion seconds ago from today? 1990. Pretty crazy.
Here's a video from the 1970s that helps you understand scale through the power of tens – and an exploration of our universe.
Hope you enjoyed this. Let me know what you think.
Not only does this help us see far away systems that we've never seen before, but it also provides detail to the things we have seen.
First, bring order to chaos …. Then, wisdom comes from making finer distinctions. With that in mind, I'm excited to see how this drives the future of science.
Here's a brief video from Neil Degrasse Tyson on the new telescope.
US Spending in 2021
In a prior post, we looked at the Global GDP in 2021. Now, let's look at US Revenue vs. Expenditures in 2021.
So, from the start, we can see a 2,770-billion-dollar deficit last year. The #1 expenditure was income security. For those who don't know, income security is an extremely broad spending category. It covers everything from tax credits and unemployment to housing assistance, foster care, and many other welfare programs. It's somewhat of a catch-all for services that help people get necessities.
Surprisingly, the US pays more per person for healthcare than countries with nationalized healthcare.
Looking at 2021 isn't the best indicator of America's spending history as a whole; there were a lot of one-time events - and a pandemic. Usually, the deficit isn't that staggering.
While the deficit may grow out of control, debt is a powerful tool - not just a liability. Nonetheless, given our current economic situation, inflation, and rising interest rates, the strategy that got us here might not be the best strategy to get us where we want to go.
What are your thoughts?
Posted at 06:29 PM in Business, Current Affairs, Games, Ideas, Market Commentary, Trading, Trading Tools | Permalink | Comments (0)
Reblog (0)