I guess I’m a Go developer now.

My first programming language was BASIC. My seventh-grade math teacher, Mr. Schulte, taught BASIC to us on Fridays. He gave us programming assignments for homework during the week. Some of us loved it so much we stayed after school to play games and create extra programs, including our own crude, text-based adventure games. I remember hearing a story about a crazy new language called Pascal that didn’t have line numbers. How in the world would that work?

Years later I became a Pascal programmer — an ardent one. So ardent, in fact, that I would argue for hours with Visual Basic developers on CompuServe, AOL, and Usenet, telling them how Turbo Pascal, and then Delphi, was clearly a superior language. I was completely self-taught — if you count all the help that others gave me as teaching myself. I wrote shareware, became pretty competent, and eventually started helping others. 

People would tell me I should branch out and learn other languages — C++ or C#. But I wanted to be a master of one instead of a jack of all trades. Besides, we were all Windows developers and there was no better tool for writing Windows applications than Delphi. It became a point of pride for me, and I would stick up for Delphi and its company Borland no matter what. It got so bad that my friends would tease me, calling me “Baghdad Nick” after the famously optimistic Iraqi foreign minister during the Iraq War. 

Delphi by day

Looking back, I was foolish. I did become a pretty good Object Pascal programmer, but I would have benefited from learning JavaScript or a functional language. I did eventually learn TypeScript and a bit of C#. (I guess I was following Anders Hejlsberg around…) 

But if you were to ask me to this day what kind of code I write, I’d say I’m a Delphi developer. Indeed, that is my day job. I understand Delphi deeply, knowing all the nuances and insider tricks to making the language my own.

But over the course of a day or two, I’m now a Go developer, too. 

If coding all day isn’t enough, I have taken on a side project for a friend. I’ve been writing Delphi code for him for a while, but now he wants to shift gears. He has asked me to build a cross-platform application for his company written in Go and Wails Version 3. Now, I’m no Go expert. In fact, I only have a passing familiarity with the language. I can decipher what is going on, but I’m far from understanding the intricacies of what makes Go tick.

But that doesn’t really matter anymore, does it?

Claude bootcamp

I asked Claude to give me a tutorial on Go and Wails. It did a great job, quickly bringing me up to speed on the basics. (How cool is it that you can so easily turn a struct into a JSON object?) I described what I wanted, and asked for recommendations for libraries. The project uses Go for the “back end” and React on the “front end.” (I use the quotes because those “ends” are actually all built into a single binary.) 

In about an hour I came to understand the architecture and got a basic application up and running. I told Claude what I wanted, and it obliged. I described the basic data structures and objects needed, and Claude wrote them quite elegantly. I didn’t actually write a line of code, but there the project was, in all its glory. Go, TypeScript, and HTML. 

Claude managed the Git repository and even created a nice little CI/CD pipeline for me, building binaries for Mac, Linux, and Windows, all in one step.   

I went from being basically ignorant of the Go language to having a moderately sophisticated application in a day.

The thing is, I’m still not that good at Go. Not that good at all. But I’m a Go programmer nonetheless. Maybe next weekend I’ll become a Python programmer.

IT industry experts and analysts are still trying to piece together Nvidia’s surprise plan to pay $12.9 billion for open-source AI company Hugging Face.

Nvidia dominates AI with its GPUs, and the company generates billions of dollars in revenue through a proprietary approach to the fast-moving technology. Hugging Face, on the other hand, hosts open models and has been a neutral player between chip vendors and model labs.

“This is about Nvidia having more say in how the stack gets built,” said Stephanie Walter, analyst at Hyperframe Research.

Hugging Face is wildly popular with developers, and Nvidia is buying early influence with that crowd. “You have a better chance of being part of the production environment later,” Walter said, adding that she wasn’t sure how Nvidia reached a nearly $13 billion price tag for the acquisition.

“Hugging Face has near-uncontested market primacy over where developers go for open-weight model releases. Now Nvidia owns that,” said Mark Petty, senior director analyst at Gartner.

Nvidia’s chase for developers should force IT decision-makers to review how much of the AI stack they control, said Hector Liu, director of Institute of Foundation Models’ Silicon Valley Lab. IFM is part of the Abu Dhabi-based Mohamed bin Zayed University of Artificial Intelligence.

Liu said CIOs should ask themselves three questions: “Can you run the model on hardware you already have, without a dependency you didn’t choose? Can you see how it was built?” And, “is the license one you can build a business on?

“A model that passes all three is durable, no matter who buys whom next year,” Liu said.

IFM’s latest K2 Horizon model, which was introduced on the same day Nvidia’s deal was announced, is hosted on Hugging Face. The open model was built to answer all of those questions.

K2 Horizon runs on AI hardware from Nvidia, AMD, Cerebras, and major cloud providers, said Liu, who doesn’t expect that to change. “Nvidia has said Hugging Face stays an open platform for every builder and every accelerator, and we’ll take that at face value,” Liu said.

Nvidia pledged to maintain Hugging Face’s hardware and model independence, and said its compute won’t be required. 

Even so, Nvidia isn’t paying nearly $13 billion for a model repository, said Jake Newfield, CEO at Hermetiq — it’s buying the front door to open AI.

(Hermetiq develops AI build and code observability tools.)

AI-generated output is becoming abundant and the infrastructure that makes it testable, reproducible and deployable is becoming strategically valuable, Newfield said. “Nvidia can accelerate it with capital and compute, but the real test is operational neutrality,” he said. 

That involves assessing whether competing hardware remains equally supported across the tooling, benchmarks and deployment paths developers actually use, Newfield said.

Beyond distribution, Nvidia is also buying Hugging Face for data, Petty said. That data showed that agents overtook humans as its largest traffic source in July, the kind of insight that could prove valuable down the road.

“Every model pulled tells Nvidia what the market wants next,” Petty said.

Nvidia has every reason to grow demand for open models and to keep them cheap, Petty said. “That’s good for enterprises, as it prevents market consolidation around a small number of proprietary model owners,” Petty said.

Closed and open models will coexist and lead to a world “where you’re going to continue to train these models and run these models at scale,” Justin Boitano, Nvidia’s vice president for Enterprise AI, said in a press conference after the deal’s announcement.

Nvidia will benefit “through the training that’s done and the inference that’s done on our hardware as models get diffused into the ecosystem at scale,” Boitano said.

That’s one motivation to keep the ecosystem open and neutral, so “developers can work wherever they want to work,” Boitano said.

Open source makes AI more accessible by lowering the barriers to experimentation and adoption, said Jon Carvill, senior vice president of marketing at AI chip maker Nuvacore. “Bringing Nvidia and Hugging Face closer together should help accelerate that choice, access and innovation,” Carvill said.

But there are still unanswered questions around whether Hugging Face will remain open and how much proprietary control Nvidia might exert, said Jack Gold, principal analyst at J. Gold Associates.

Microsoft traveled a similar path with its acquisition of open-source repository GitHub, which “did not really pan out as well as Microsoft hoped,” Gold said. “With Nvidia’s acquisition, will it still be as open to competitive hardware-software access, or will there be some barriers employed?”