Jonathan Bartlett

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

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}_{Jonathan Bartlett
March 20, 2023}

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?}_{Jonathan Bartlett
March 15, 2023}

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.}_{Jonathan Bartlett
March 14, 2023}

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}_{Jonathan Bartlett
March 13, 2023}

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}_{Jonathan Bartlett
February 13, 2023}

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}_{Jonathan Bartlett
February 6, 2023}

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}_{Jonathan Bartlett
January 30, 2023}

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?}_{Jonathan Bartlett
January 23, 2023}

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}_{Jonathan Bartlett
January 17, 2023}

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}_{Jonathan Bartlett
December 19, 2022}

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 ›