Should I consume less content, or is there a lot happening? Either way, there’s a lot to talk about.
We probably should start an “open source rug pull” counter somewhere because Redis just pulled one off from right underneath our feet.
Days since the last open source rug pull: 0
We enter an election year with the looming question of AI’s influence. So far, knee-jerk reactions that paint AI as good or bad (mostly) have been the only attempts at addressing something that clearly requires better solutions.
Thinking in terms of absolutes is the real problem. Instead of viewing AI as either good or bad, it can be viewed as better or worse. “How better are we than the status quo with AI,” or “How worse off would we be than we are now with AI?” are the questions we need to answer.
Thinking at the margin reveals that the perceived risks of open AI models are far greater than the actual risks for most applications. The only reasons to stick to and advocate for closed models are strategic and economic.
An analogy to this AI-led geopolitics battle is the nuclear arms race between the USA, the Soviet Union, and the rest of the world in the latter part of the last century. India managed to build nuclear missiles in the 90s, even with all the checks and regulations in place.
Similarly, regulating AI is futile because no single entity has the power to coerce all nations who are incentivized to leverage this technology for economic and strategic advantage.
Open models are the way to go and there is no doubt about it.
New research suggests useful AI models (comparable to equivalent proprietary models) can be trained from publicly available datasets. This is excellent because companies with access to proprietary data have an unfair advantage over new entrants.
For example, Google, Amazon, and Microsoft have vast amounts of proprietary data to train their models using their own compute infrastructure. You basically win Monopoly at this point.
Another advantage of keeping models open is that it reduces misrepresentations, biases, and other issues that have plagued them since their invention.
We could take a step further for the elections and call for open source voting machines. It’s a little late for this election cycle, but how great would that be?
What’s Happening?
The most important AI news that dropped last week wasn’t all this, and it wasn’t even Twitter open-sourcing Grok, but the release of Devin, an AI programmer that can seemingly do it all.
It was another “our jobs are over” kind of week for programmers, and the demos look neat, but it’s far from being able to replace programmers.
Devin’s creators report that it can solve 1/7 GitHub issues correctly. Not bad considering the novelty of the technology.
The nature of our jobs will change inevitably. That has been the case for every technological leap before. But this isn’t the first attempt to make programmers obsolete.
COBOL was developed to allow business teams to program. It ended up creating COBOL programmers. The myriad of no-code tools are great, but there are still programmers.
AI is a radical change, but is it radical enough to make programmers obsolete?
In every group I speak to, from business executives to scientists, including a group of very accomplished people in Silicon Valley last night, much less than 20% of the crowd has even tried a GPT-4 class model.
— Ethan Mollick (@emollick) March 9, 2024
Less than 5% has spent the required 10 hours to know how they tick.
There was also some buzz around AI hardware, with Hugging Face announcing an open source robotics project and Extropic.ai announcing their hardware platform. The AI hardware space is neat, and the research around it will be critical in the coming years.
I don’t care about the OpenAI drama anymore, but they released the investigation report concerning Sama’s termination from the company. The Mira Murati interview was funny. If I were involved in OpenAI, the least I could do is learn about what the company actually does when going to an interview or at least prepare for an obvious question.
In other news, Williams Racing Team Principal James Vowels is appalled to find his new team still using Microsoft Excel to manage 20,000 Formula 1 car parts. Does he know Excel can run Python now?
Curated Links
We focus so much on the now, so it’s time for some classics. Here’s what I have for you this week:
- Ping-Pong Diplomacy: In 1971, triggered by a chance encounter, the United States Table Tennis team visited China, which helped establish official diplomatic relations.
- The Economist Cover Curse, Explained: The Economist is excellent. I can’t afford a subscription, but I read the free pieces occasionally.
- In Economics, Do We Know What We’re Doing?: Economists would be better at being economists if they did less economics.
- What loophole did you exploit before someone found out?: People are awesome! Some of these hackers deserve awards.
- Write more useless software: Writing software doesn’t have to be a means to an end but the end itself. Building “useless” software just for the pure joy of building it can often lead to great benefits. And sometimes, what you think is useless might end up being useful to others.
- In Loving Memory of Square Checkbox: Web standards exist for a reason. Designers and engineers should understand why they exist and stick to them instead of attempting to reinvent them.
- Compressing Chess Moves for Fun and Profit: Storing chess moves can take up a lot of space. How can you reduce this?
- The Best Essay: What makes an essay the best? Another Paul Graham classic.
Hot off the Press
I wrote about the Freenginx fork, but the article ended up focusing more on the interpersonal aspects of the scenario. I have previously written about Nginx and how it is just fine for most of us.
Read here: “Wasn't Nginx Free?”
Read here: “Nginx is Probably Fine”
I’m working on a new article about CloudFlare’s newly open source project, Pingora, and I expect to publish it next week.
Now, who’s forking Redis?