Jonathan Bartlett

Senior Fellow, Walter Bradley Center for Natural & Artificial Intelligence

Jonathan Bartlett is a senior software R&D engineer at Specialized Bicycle Components, where he focuses on solving problems that span multiple software teams. Previously he was a senior developer at ITX, where he developed applications for companies across the US. He also offers his time as the Director of The Blyth Institute, focusing on the interplay between mathematics, philosophy, engineering, and science. Jonathan is the author of several textbooks and edited volumes which have been used by universities as diverse as Princeton and DeVry.

Archives

Uber Achieves Profitability After Giving Up Self-Driving 

The alternative taxi service has finally parted ways with its self-driving unit
Uber, the ride-hailing company, has been notorious for losing money. Since 2014, they have built up over thirty billion in operating losses. Just four years ago, analysts were saying that self-driving cars were the key to Uber’s future profitability.  However, in December 2020, Uber finally gave up the dream and sold its self-driving unit to the startup self-driving company Aurora.    This eliminated one of Uber’s biggest cash-burns. The Advanced Technology Group, the name of Uber’s self-driving unit, was draining $500 million from the company each year. Overall, the company probably spent well over $2 billion on self-driving, which some of Uber’s early investors (such as Bill Gurley) think was ultimately wasted spending.  This last quarter Uber has finally been able to turn a profit, Read More ›

Of Infinity and Beyond

What are the problems and solutions with infinity in mathematics?
The concept of infinity has plagued a great many proofs, both formal and informal. I think that there are two foundational problems at play in most people’s thinking about infinity that causes issues. The first problem people have with infinity is that they treat it as if it were a single value. Because infinity is bigger than all possible natural numbers, people assume that it is bigger than any number, and therefore there is nothing beyond infinity. Therefore, people have the concept that if I have two infinities, then I still have the same number.  They believe that 2 * infinity = infinity. However, using that logic can quickly lead to contradictions. This problem is exacerbated by much mathematical notation. People often will Read More ›

Why Is Object-Oriented Programming Popular?

This method makes programmers think more systematically about their code
Programming practice has gone through several evolutions in its lifespan. The first phase might be considered the “exploratory” phase, where there were no rules but a lot of imagination. People wrote code that was simultaneously amazing and terrible—amazing at what people got their slow computers to do, but terrible in that no one but the author would ever be able to maintain the programs. The lessons learned from the exploratory phase led to what is known as “structured” programming. The goal of structured programming was to be able to write programs that someone else had a chance of reading and understanding. Structured programming favored having really well-documented inputs and outputs to every function, very clear entry and exit points to each function, and Read More ›

The Microservices Controversy from a Software Management Perspective

As projects get bigger, so do the reasons for having a microservice architecture
A new report by Amazon has caused a bit of a stir on the Internet. In it, the Amazon Prime video team reported that changing their architecture from a microservice architecture to a monolithic architecture resulted in a 90% cost savings.  While the report itself was very mild (its only claim was that this architecture helped in this specific situation), it has caused the people who disliked the microservice trend to make some noise of their own. Here, I wanted to take a moment to reflect on what I see as the benefits of the microservice approach from a software development management perspective. If you are not familiar with microservice architectures, you can find out more information in my book, Cloud Read More ›

The Raspberry Pi Phenomenon

A Raspberry Pi is a full computer that is not much larger than a credit card, but still packs enough power to be usable as a desktop computer
For the uninitiated, the Raspberry Pi is a single-board computer that runs the Linux operating system. It can be either operated as a desktop computer or as an embedded system (i.e., a custom electronic device), or both. Historically, computer systems were either general-purpose computers or embedded systems. General-purpose computers required too much hardware, too many chips, and too much power to work inside an electronic device. However, as manufacturers packed more and more functionality into less and less space using less and less power, eventually it became possible to have a computer that was small, cheap, powerful, and not especially power-hungry. The Raspberry Pi came about right as this was happening. A Raspberry Pi is a full computer that is not much Read More ›

Aren’t US Treasury Bonds Supposed to be Safe?

How can you lose money selling treasury bonds?
For context, read Bartlett’s two previous articles on the fall of SVB and interest rates. Some people are confused as to how you can lose money selling treasury bonds, since they are supposed to be “safe” assets (the government is not expected to default on its loans, and, if it does, the economy probably has bigger problems). Economist Bob Murphy put together a great explainer thread on Twitter, which I will largely follow here. Let’s say that there is an asset that always yields a 1% return every year on however much you have invested, but you never get the principal back except by selling it to someone else. Let us call this asset ABC, and let us say that it is Read More ›

Why Did the Tech Bubble Correspond with Low Interest Rates?

Ultimately, our economy’s deeper problems aren’t so much a result of “money” as they are bad allocations of resources.
For context, read Bartlett’s article explaining the fall of SVB here. I wanted to make a quick note about why tech bubbles tend to correspond with low interest rate environments. Interest rates essentially dictate how long someone can wait before they need to produce something of real value. In a 20% interest rate environment, it will be evident really quickly if you are failing to produce something of value. Since essentially 1/5 of your capital disappears each year, if you aren’t doing something that will generate real profits quickly, you are sunk. You can’t paper over problems with more borrowing because the cost of that borrowing is so high. Additionally, in such an environment, the payoffs for investment need to be large Read More ›

What’s Going on at Silicon Valley Bank?

The bank's failure is making a lot of people nervous about their money
Many people awoke this morning to news of a bank that suddenly collapsed – Silicon Valley Bank, or SVB. While information is still developing, I thought I would provide some background information on what is known so far. SVB is the go-to bank for Silicon Valley startups. Over the last few years, the tech bubble has been growing and growing and growing, focused especially around Silicon Valley. That meant a lot of banking was happening, and it was happening with SVB. That is where the various companies put their deposits.  How does a bank make money? By lending out deposits. In 2021, at the height of the tech bubble (and, not coincidentally, at a historically low-interest rate environment). The bank did what most banks do Read More ›

The Need for Accountability in AI-Generated Content

Just because we live in a world of AI does not mean we can escape responsibility
AI-generated content has become increasingly common on the web. However, as we enter this new era, we will need to think through the moral and social ramifications of what we are doing, and how we should negotiate the new ethical landscape. But first, a brief recap of recent history. The first major player to pioneer AI-generated content was the Associated Press. AP realized that many market-oriented articles were pretty monotonous and read like templates anyway, so they decided to fully commit and auto-generate many of them. If you read an AP story about a company’s earnings report and it sounds eerily like every other story about other companies’ earnings reports, there’s a reason for that. Templated content, while annoying, provides window-dressing to raw Read More ›

Whatever You Do, Don’t Ask GPT for Sources

The chatbot will give you a lot of links that don't necessarily direct you where you want to go
One of the more amusing things I’ve found from OpenAI’s GPT-3 and ChatGPT is the fact that it will very confidently provide you with sources on anything you ask—and they will often be completely made up. It will even provide fake (but real-looking) URLs for you! I stumbled across this feature when researching a previous GPT-3 article about how well it could write blog posts compared to real authors. I initially tried asking GPT-3 to include sources, and it generated complete nonsense for the sources. I decided that, for that article, sources were not the main question, so I left it out of the final queries. However, in response to my latest article about ChatGPT not being a Google replacement, someone commented Read More ›

Why ChatGPT Won’t Replace Google

With Google, the algorithm eventually leads you to content made by real people. With ChatGPT, you never leave the algorithm
To some extent, ChatGPT is a newer, easier-to-use interface than Google.  Unlike Google, it doesn’t make you waste time by visiting those pesky websites.  It not only looks into its database for content, but it also summarizes it for you as paragraphs. There is a problem lurking in there, however.  Being computers, neither Google nor ChatGPT cares about the truth.  They are algorithms, and they merely do as they are told.  Additionally, you can’t code the human mind into algorithms.  However, there is a fundamental difference between what ChatGPT does and what Google does that will prevent content generators like ChatGPT from displacing search engines like Google: Google eventually lets you out of its system. Ultimately, the goal of search Read More ›

GPT-3 Versus the Writers at Mind Matters

How does the AI fare when it is asked to write on topics covered in Mind Matters articles?
In order to give a real-world comparison of the output of GPT-3 to human-written writing, I decided it would be a fun activity to see how OpenAI’s GPT-3 compares to Mind Matters on a variety of topics that we cover.  Here, we are using OpenAI’s direct API, not ChatGPT, as there is a lot of evidence that ChatGPT responses have a human-in-the-loop.  Therefore, we are going to focus on the outputs from their API directly. I used several criteria for article selection in order to even the playing field as much as possible.  For instance, I only chose articles that did not depend on recent events.  This way, GPT-3 is not disadvantaged for not having up-to-date material.  However, I also Read More ›

How are Developers Using OpenAI’s Tools in their Software?

There are several interesting uses of the new AI tools, but time will tell which ones take off
OpenAI has released two major tools for developers to make use of GPT-3 and DALL-E.  GPT-3 is the radical new text generation tool, which generates large or small amount of texts from simple prompts.  It can also classify text into categories  GPT-3’s text-generation system forms the core of OpenAI’s new chatbot, ChatGPT.  DALL-E is an image generation tool, which creates images from text prompts.  Together, these two tools provide today’s state-of-the-art in AI-based content generation. So how are developers making use of these new features?  Today we are looking at several ways that these tools have been put to use. Basic Content Generation The core of GPT-3 is generating content from prompts.  Whether for making blog posts, writing summaries, or Read More ›

Musk’s Tyrannical Turn With Twitter

While the political bias is gone, the ego bias seems to have just begun
I was hopeful when Elon Musk took control of Twitter. As a longtime Musk skeptic in many areas, I thought that his move into Twitter would actually be a good thing. First of all, it matches his background better than Tesla. Twitter is a software play, and Musk’s actual expertise is in building software. Second, Twitter is just about software, not artificial intelligence, which tends to be where Musk gets into trouble. Finally, Musk has at least claimed to be a libertarian, though this seems to be limited to situations where he simply decides that he doesn’t want to do what is required of everyone else. When Musk first took control, it looked positive. Despite the incessant screaming of the Read More ›

FTX Implosion: There Are Warning Signs from Binance

The CEO of Binance fundamentally misrepresented the character of the firm's engagement of the Mazars auditing firm
Since the implosion of FTX, many have been watching cryptocurrency exchange Binance to see if it might be the next crypto firm to face a liquidity crunch. While the CEO of Binance, known in the crypto world as CZ (Changpeng Zhao), has assured investors and depositors that the firm is financially sound, many of its recent moves have left observers wondering if there is more to the story. The Audit that Wasn’t The first major red flag was the “audit.” Binance has long been criticized for failure to provide audited financial statements. Because it is not a public company, an audit is not a legal requirement. Nonetheless, many crypto watchers view the failure to have an external audit as evidence of concern Read More ›

Understanding the Fall of FTX — the False Reality of Market Caps

Let’s have a look at the critical question that was never asked in the first place…
In finance, the “market capitalization” or “market cap” of a security or currency is a simple way to evaluate the overall “value” of the total entity (this is also called “network value” in terms of a cryptocurrency). It is easiest to think about market caps in terms of stocks instead of currencies. In the stock market, if ABC Company is broken up into 100,000 shares, and the going market price is $3 per share, then the market cap of ABC is $300,000. Likewise for coins, if there are 100,000 coins available, and the current market price of the coin is $7, then the market cap of the coin will be $700,000. The idea behind the market cap is that, if Read More ›

The Graying of the Art — and AI — World

Why is so much modern media made up of rehashes and remakes?
The world of popular art (TV, movies, etc.) has a problem. I would even go as far as to label it a crisis. The problem is that the art world is becoming increasingly derivative. There are some points where it is obviously derivative—every movie is a remake, and every TV show is a reboot. We are getting the same stories regurgitated instead of novelty. However, there are also more subtle ways that this is happening.  TV comedies work largely by including inside jokes from previous TV shows.  One of the most popular writers of the 20th century was Louis L’Amour. What I think made L’Amour’s stories so great is that he could draw from a vast amount of personal experience. He could write about a lot Read More ›

Tesla’s Optimus is Sub-Optimal

With other robotics programs far outrunning Tesla, it can be hard to see what Elon Musk is adding to the field and why he's even trying
As promised, Elon Musk demonstrated his prototype robot “Optimus” at the 2022 Tesla AI Day.  The original plan for the robot included: Navigating the world through AutoPilot (the Tesla vehicle’s driver assistance system) Being able to perform repetitive or dangerous tasks safely Being able to be instructed using natural language instead of programming A year later, the Tesla robot has not even remotely demonstrated the ability to do any of these things with any sophistication.  That’s not surprising given Elon Musk’s penchant for promising things and not delivering them, but it does drive home the point that many of Musk’s mistakes stem from his more general misconceptions about the nature of the world.  Musk is great at organizing people, capital, Read More ›

The Vector Algebra Wars: A Word in Defense of Clifford Algebra

A well-recognized, deep problem with using complex numbers as vectors is that they only really work with two dimensions
Vector algebra is the manipulation of directional quantities. Vector algebra is extremely important in physics because so many of the quantities involved are directional. If two cars hit each other at an angle, the resulting direction of the cars is based not only on the speed they were traveling, but also on the specific angle they were moving at. Even if you’ve never formally taken a course in vector algebra, you probably have some experience with the easiest form of vector algebra — complex numbers (i.e., numbers that include the imaginary number i). In a complex number, you no longer have a number line, but, instead, you have a number plane. The image below shows the relationship between the real Read More ›

Musk’s Starlink Tied to Traffic Chaos in Orbit and on Earth

If nothing else, Elon Musk’s SpaceX has brought public attention to the future of space, who it belongs to, and how it is paid for
This week has seen quite a struggle for Elon Musk’s SpaceX and its satellite-based internet service Starlink. SpaceX had recently pocketed some interesting wins for Starlink. Its offer to keep Ukrainians online in the midst of the recent crisis earned Starlink favor in the eyes of both the military and Eastern European nations. It has also started launching operations in Latin America. Just days ago SpaceX performed its 35th launch of the year, adding 52 more Starlink satellites. However, Starlink has also faced a number recent headwinds which could spell trouble for the service. While its public beta test performed well for many users, as the service has expanded, the capabilities of the network appear to be stretched. Despite promises Read More ›