I’m happy to announce that my audiobook is available on Audible.
I narrated the book myself, and there are references to charts and tables that require looking at my website here, so the audiobook is at a substantial discount from the paperback.
I did a fun and inspiring livestream with the one-and-only Olga Mack! If you have never seen her Notes to my (Legal) Self series, I highly recommend it.
The Magic of Creating Open Source Businesses, December 15, 2023.
The days are getting shorter, the shopping (physical and virtual) is ramping up, Mariah Carey is playing everywhere on loudspeakers, and that means…it’s time for top ten lists. Here are my most memorable software events of 2023. I offer only six, given the government takes 40% of whatever I make.
Red Hat’s License Change That Wasn’t. In June 2023, Red Hat continued on a course to try to limit access to its RHEL software distro. But of course it can’t do that, because…GPL. Red Hat changed its customer agreement, which was widely reported as prohibiting distribution of software–though that was not quite accurate. Many large commercial open source companies that get bought (as was Red Hat, by IBM in 2019), try to increase profit margins by limiting access to open source. They imagine they can convert the downstream “freeloaders” to paying customers. That kind of scheme usually doesn’t work to increase profits, or even sales. But it does work to alienate the community! Red Hat’s unpopular changes to CENTOS enabled alternative distros like Rocky Linux. See my video here.
The Unity Meltdown. In September, 2023, Unity made a change to its pricing model, resulting in death threats and a general indie developer outcry. Then the CEO left, then they fired a bunch of devs. Unity still remains one of the two big dogs in the game engine space, but these missteps pave the way for open source alternatives like Godot. See my video here.
OpenAI’s Revival. November, 2023. I seem to remember this story about a guy who died and rose three days later. But Sam Altman needed about five. Maybe the less said about this debacle the better, given it’s dominated the news ever since Thanksgiving. One day, the entire tech world woke up to realize that it’s genAI darling unicorn, OpenAI, is really a non-profit run by AI-doomers (or guardians of humanity, depending on your viewpoint). Microsoft nearly accomplished the world’s biggest reverse-acquihire, but then the AI-doomers were kicked off the board. Sam and the AI-boomers will take the company forward, but OpenAI is still saddled with a weird corporate structure, and a lot of technical debt. I’m looking forward to seeing other companies eat OpenAI’s lunch in 2024. See my video here.
17 Lawsuits About GenAI. Good heavens, it’s exhausting just to list them, much less explain how nonsensical most of them are. Most of these will fail, if the judges actually follow existing copyright law. If content generators what to prohibit machines from reading their books/music/pictures, they need to get congress to change the law. Pro tip: when it comes to copyright, congress usually does whatever the media industry wants.
Feds’ Continuing Vendetta Against Tech (Including Crypto). The US government is still going after crypto. SBF of FTX was convicted. CZ of Binance pled guilty of money laundering. The SEC threatened to sue Coinbase unless it stopped trading all crypto other than Bitcoin. (Coinbase declined.) But there’s more. The Feds continue to file (mostly unsuccessful) lawsuits against tech giants claiming novel antitrust theories. See my videos on SBF and antitrust here.
What Didn’t Happen: Open Source AI. We still don’t have a definition of open source AI, and efforts to define it are stalled by the disarray of the open source community. Meanwhile, OpenAI and others are trying to set a narrative that openness is not necessary. Now *that’s* scary. (This was the subject of my TED Talk in September, but it’s still not published yet. I will update this blog post when (or if) it comes out. An article with similar substance is here.)
Happy new year, everyone!
The video for this post is here.
This week, the tech world was shocked by the sudden and unexplained firing of Sam Altman, the now-former CEO of OpenAI.
OpenAI has been the darling of the tech industry for the last year. Its current fundraising goals would put it on track to be one of the biggest unicorns in the US. But here are a few reasons why OpenAI probably can’t live up to its own hype. The events of this past weekend only underscore them.
My video on this topic is here.
OpenAI made a big splash by releasing ChatGPT3 in late 2022, and followed with updates this year. But OpenAI did not invent the core transformer technology behind GPT–that was originally from a core concept by Google. That’s why so many companies have been training up their own models lately. The barriers to entry in LLM development right now aren’t about technology, they are about resources. OpenAI trained ChatGPT3 and 4 using a lot of data, a lot of money and a lot of compute cycles.
The problem with this is that ChatGPT has a thin first mover advantage. Each iteration of a model takes tons of resources to produce. If OpenAI continues to draft on existing tech, and keeps building new models, it will be in a never-ending race that will require immense capital and resources, without significant economies of scale. That’s not sustainable.
The spat between the company’s board and its investors is very weird indeed. In most companies, the investors control the board. Boards and investors usually don’t have spats, particularly not public ones. But OpenAI is no ordinary company.
OpenAI’s parent entity is a non-profit called OpenAI, Inc., with a for-profit subsidiary called OpenAI Global, LLC. That is a bizarre structure for a tech startup. Non-profits don’t have shareholders, they have a board of directors. In contrast, the board of directors of a profit company is elected by its shareholders. The structure of control of an LLC is what we lawyers call “flexible”–which means opaque and idiosyncratic. But it is usually run more like a for-profit corporation.
To see how this odd structure happened, you need to read between the lines. In 2015, the original contributors for the non-profit pledged about $1 billion to the project, but many did not fulfill their pledges. So, in 2019, OpenAI transitioned from a non-profit to “capped for-profit” by creating a subsidiary LLC with shareholder profits capped at 100 times any investment. Just for reference, a “capped-for-profit” is not really a thing in corporate law, but with an LLC, anything goes. OpenAI then got an investment from Microsoft, for $1 billion, into the for-profit subsidiary, along with a deal for access to Microsoft’s cloud computing services. It then announced its intention to commercialize its products. But the for-profit entity is controlled by the non-profit.
This transition troubled initial contributors, and generated criticism. It’s kind of a joke in the tech business today that OpenAI as a company name is beyond ironic. It’s not open at all. In fact, open source advocates have generally viewed Altman and OpenAI as trying to set a narrative that avoids transparency in AI. They are pushing for regulation, to forestall demands for transparency. OpenAI has justified its move away from transparency due to its need to compete–but that’s circular logic.
OpenAI’s latest funding round is set to value the company at $80 billion. That’s bigger than the market cap on lots of existing public companies, including Boston Scientific and Mercedes Benz. Could it be worth that much?
It’s probably fair to say that OpenAI is the only company making significant money on large language models at the moment. (Though GitHub’s Co-Pilot is in the running, too, it’s currently based on ChatGPT.) Most companies that have released LLMs have not monetized them directly. In fact, LLMs are probably difficult to monetize at a rate that will be profitable over time–at least not based on the current data and resource-guzzing tech.
In this year of tech business malaise, AI has been the only bright spot. The conventional wisdom for 2023 is that no company can raise money, except AI startups, which are swimming in investment dollars. As usual, when private investors jump on a bandwagon, they tend to fund some terrible businesses. OpenAI is the superstar of startups today, but superstars have not fared well in recent years, tending to burn out or fade away.
Congratulations to the Sentry team for this live release yesterday!
The Functional Source License (FSL) makes opinionated decisions about the variables in BSL, so that it is easier to reason about for both potential producers and consumers of FSL software. FSL is tuned for SaaS companies
From the blog for the Functional Source License release:
The FSL:
This differs from BSL in that the change license is set to a common permissive license (for BSL, it is a choice of a GPL compatible license), the change date is set at two years (for BSL, it is 4 years or less), and contains a detailed license limitation targeted toward SaaS businesses (for BSL, the restriction is against production use, resulting in many Additional Use Grant variations).
The blog outlines the journey of Sentry in preparing and adopting this license.
This panel was a great experience. We talked about how to green-light AI in companies responsibly. Thanks to GitHub for putting it together!
I am delighted to say that the Elastic 2.0 license has been translated into Chinese! Thanks so much to Tison for this effort!
Sam Bankman-Fried’s conviction is all over the news. Here is my video on the topic.
While the crimes SBF was convicted of bear jail time of up to 110 years, his sentencing is not scheduled until March 28, 2024, which is after his next federal trial is scheduled, on March 11, 2024. The next trial promises to be even more of a circus than the recent one, given it will involve allegations of bribery and campaign finance violations, not to mention bank fraud and securities fraud. So, it’s still unclear whether the second trial will go forward–prosecutors have until February 1, 2024 to decide–and if he is convicted, whether the first sentencing will be delayed so the two sentencings will be done together.
In the US federal system, judges are required to abide by sentencing guidelines. The crimes SBF was convicted of this week can carry a penalty of 7-10 years each. A federal judge has some leeway, including to order sentences for multiple counts to be served concurrently or serially. The guidelines allow the judge to take into account demonstration of remorse–which in SBF’s case seems non-existent. However, the guidelines for sentencing of fraud also take into account the amount of the fraud, and subsection 2B1.1(b)(1) of the guidelines only goes up to $550 million. So basically, SBF’s fraud is more than the guidelines ever anticipated possible. That means the judge might make an exception to go above the guidelines. SBF’s prospects are dire indeed.
Also, there is no parole in the federal system, though inmates can earn what is called “good time credit,” and as a result, federal prisoners tend to serve about 85% of their sentence. So by the time SBF gets out of prison, he will be a lot older, and with luck, wiser. But if he is convicted of additional crimes, he may be bouncing from one jail to another.
Once SBF is behind bars, we will probably get lots of marriage proposals–and VC term sheets.
For my video on this topic, see here.
I detest prophecies of doom. I think, mostly, people make apocalyptic predictions to get attention, and are never held to account. If you think about it, all prophecies of the end of the world have been wrong, ipso facto. The same is true for open source.
Every time there is a development in the licensing landscape, it is heralded as the end of open source.
The doom pronouncements all seem to come after incremental changes, some actually fairly minor, and demonstrate a troubling tendency in our culture toward glorified panic. At least some of them are rhetorical devices, following Betteridge’s law:
Any headline that ends in a question mark can be answered by the word no.
Let’s take a stroll down memory lane.
These are just articles I found on one Google search! All of them are wrong, of course.
What is the end of open source? The end of open source is probably the end of software. That could happen. If you take the long view, programmable software itself will probably be a technology with a lifetime of about 100 years. (Feel free to hold me to that prediction, but I may be be long gone by that time.) What will be the end of software? No-code tools, deep learning, quantum computing? We don’t know. But one thing is clear, none of the harbingers of doom have any idea, either.
Long live open source!
