What's new in Go's cryptography libraries

Filippo Valsorda & Roland Shoemaker from the Go Team sit down with Natalie to catch us up on what’s new in Go’s crypto libraries. No, not that crypto… good ol’ cryptography! | Continue reading


@changelog.com | 1 year ago

Self-hosting & scaling models

We’re excited to have Tuhin join us on the show once again to talk about self-hosting open access models. Tuhin’s company Baseten specializes in model deployment and monitoring at any scale, and it was a privilege to talk with him about the trends he is seeing in both tooling and … | Continue reading


@changelog.com | 1 year ago

The se7en deadly sins of Go

John Gregory’s GopherCon talk “7 Deadly Gopher Sins” is the ostensible basis of this spooky Go Time episode, but with Mat Ryer at the helm… the only thing to expect is the unexpected. And failed jokes. Expect lots of failed jokes. | Continue reading


@changelog.com | 1 year ago

Deep learning in Rust with Burn

It seems like everyone is interested in Rust these days. Even the most popular Python linter, Ruff, isn’t written in Python! It’s written in Rust. But what is the state of training or inferencing deep learning models in Rust? In this episode, we are joined by Nathaniel Simard, th … | Continue reading


@changelog.com | 1 year ago

AI's impact on developers

Chris & Daniel are out this week, so we’re bringing you a panel discussion from All Things Open 2023 moderated by Jerod Santo (Practical AI producer and co-host of The Changelog) and featuring keynoters Emily Freeman and James Q Quick. | Continue reading


@changelog.com | 1 year ago

Experiences from GopherCon 2023

The 10th GopherCon took place the last week of September and it was a blast. In this episode, we’re talking about our experiences at the conference from several different viewpoints. Angelica as a conference organizer, Johnny as an emcee and workshop instructor, Kaylyn as a speak … | Continue reading


@changelog.com | 1 year ago

Generative models: exploration to deployment

What is the model lifecycle like for experimenting with and then deploying generative AI models? Although there are some similarities, this lifecycle differs somewhat from previous data science practices in that models are typically not trained from scratch (or even fine-tuned). … | Continue reading


@changelog.com | 1 year ago

Zero Trust & Go

Michael Quiqley from NetFoundry joins Natalie to discuss Zero Trust concepts, why they are important for secure systems & how to implement them in Go. | Continue reading


@changelog.com | 1 year ago

Automate all the UIs!

Dominik Klotz from askui joins Daniel and Chris to discuss the automation of UI, and how AI empowers them to automate any use case on any operating system. Along the way, the trio explore various approaches and the integration of generative AI, large language models, and computer … | Continue reading


@changelog.com | 1 year ago

Go templating using Templ

Go’s known for it’s fantastic standard library, but there are some places where the libraries can be challenging to use. The html/template package is one of those places. So what alternatives do we have? On today’s episode we’re talking about Templ, an HTML templating language fo … | Continue reading


@changelog.com | 1 year ago

Prototyping with Go

V Körbes returns to talk prototyping with Natalie, Johnny & Kris. Is Go good for prototyping? What makes a language prototypable, anyway? How does space radiation fit in to all this? Tune in and ride along to find out! | Continue reading


@changelog.com | 1 year ago

Fine-tuning vs RAG

In this episode we welcome back our good friend Demetrios from the MLOps Community to discuss fine-tuning vs. retrieval augmented generation. Along the way, we also chat about OpenAI Enterprise, results from the MLOps Community LLM survey, and the orchestration and evaluation of … | Continue reading


@changelog.com | 1 year ago

What's new in Go 1.21

Our “what’s new in Go” correspondent Carl Johnson joins Johnny & Kris yet again to discuss what’s new with the latest iteration of Go in version 1.21. | Continue reading


@changelog.com | 1 year ago

Automating code optimization with LLMs

You might have heard a lot about code generation tools using AI, but could LLMs and generative AI make our existing code better? In this episode, we sit down with Mike from TurinTech to hear about practical code optimizations using AI “translation” of slow to fast code. We learn … | Continue reading


@changelog.com | 1 year ago

The new AI app stack

Recently a16z released a diagram showing the “Emerging Architectures for LLM Applications.” In this episode, we expand on things covered in that diagram to a more general mental model for the new AI app stack. We cover a variety of things from model “middleware” for caching and c … | Continue reading


@changelog.com | 1 year ago

A deep dive into Go's stack

A technical dive into how the Go stack works and why we as programmers should care. | Continue reading


@changelog.com | 1 year ago

Blueprint for an AI Bill of Rights

In this Fully Connected episode, Daniel and Chris kick it off by noting that Stability AI released their SDXL 1.0 LLM! They discuss its virtues, and then dive into a discussion regarding how the United States, European Union, and other entities are approaching governance of AI th … | Continue reading


@changelog.com | 1 year ago

Building world-class developer experiences

Today we’re talking with Alice Merrick & Andy Walker about building a world-class developer experience. You know it when you see it, things just feel right. But it’s more than just a pleasant UI or lipstick on a pig (which is a saying), it really matters. | Continue reading


@changelog.com | 1 year ago

Vector databases (beyond the hype)

There’s so much talk (and hype) these days about vector databases. We thought it would be timely and practical to have someone on the show that has been hands on with the various options and actually tried to build applications leveraging vector search. Prashanth Rao is a real pr … | Continue reading


@changelog.com | 1 year ago

So do we like Generics or not?

So, do we like generics or not? Some people feared they’d be the end of the language. Others were very hopeful, and had clear use cases, and were thrilled about the feature coming to the language. It was also often touted as the reason a lot of people didn’t adopt Go. So what do … | Continue reading


@changelog.com | 1 year ago

There's a new Llama in town

It was an amazing week in AI news. Among other things, there is a new NeRF and a new Llama in town!!! Zip-NeRF can create some amazing 3D scenes based on 2D images, and Llama 2 from Meta promises to change the LLM landscape. Chris and Daniel dive into these and they compare some … | Continue reading


@changelog.com | 1 year ago

The tools we love

The Go ecosystem has a hoard of tools and editors for Gophers to choose from and it can be difficult to find ones that are a good fit for each individual. In this episode, we discuss what tools and editors we’re using, the ones we wish existed, how we go about finding new ones, a … | Continue reading


@changelog.com | 1 year ago

Legal consequences of generated content

As a technologist, coder, and lawyer, few people are better equipped to discuss the legal and practical consequences of generative AI than Damien Riehl. He demonstrated this a couple years ago by generating and copyrighting every possible musical melody. Damien joins us to answer … | Continue reading


@changelog.com | 1 year ago

A developer's toolkit for SOTA AI

Chris sat down with Varun Mohan and Anshul Ramachandran, CEO / Cofounder and Lead of Enterprise and Partnership at Codeium, respectively. They discussed how to streamline and enable modern development in generative AI and large language models (LLMs). Their new tool, Codeium, was … | Continue reading


@changelog.com | 1 year ago

Gophers Say! GopherCon EU 2023

Our award winning worthy survey game show is back, this time Mat Ryer hosts it live on stage at GopherCon Europe 2023! Elena Grahovac joins forces with Björn Rabenstein to battle it out with Alice Merrick & Mohammed S. Al Sahaf. Let’s see who can better guess what the GopherCon E … | Continue reading


@changelog.com | 1 year ago

Cambrian explosion of generative models

In this Fully Connected episode, Daniel and Chris explore recent highlights from the current model proliferation wave sweeping the world - including Stable Diffusion XL, OpenChat, Zeroscope XL, and Salesforce XGen. They note the rapid rise of open models, and speculate that just … | Continue reading


@changelog.com | 1 year ago

The solo gopher

Many Gophers build projects as a team of one. Sometimes these are side projects, other times they are projects used by millions of people but who are still maintained by a single individual. In this episode, the panel discusses techniques for developing and maintaining Go project … | Continue reading


@changelog.com | 1 year ago

K8s vs serverless for distributed systems

Listener Joe Davidson recently tweeted: “I’d really be interested in an episode debating Kubernetes vs serverless functions for distributed systems. As someone working a lot with serverless to create large scale systems, for me the complexity in Kubernetes doesn’t seem worth it, … | Continue reading


@changelog.com | 1 year ago

Automated cartography using AI

Your feed might be dominated by LLMs these days, but there are some amazing things happening in computer vision that you shouldn’t ignore! In this episode, we bring you one of those amazing stories from Gabriel Ortiz, who is working with the government of Cantabria in Spain to au … | Continue reading


@changelog.com | 1 year ago

Neurodiverse gophers

Kaylyn Gibilterra returns as Natalie & the gang take our diversity conversation one step further. This time we’re talking about neurodiversity as it relates to being a developer, a manager, a conference participant & more. | Continue reading


@changelog.com | 1 year ago

From ML to AI to Generative AI

Chris and Daniel take a step back to look at how generative AI fits into the wider landscape of ML/AI and data science. They talk through the differences in how one approaches “traditional” supervised learning and how practitioners are approaching generative AI based solutions (s … | Continue reading


@changelog.com | 1 year ago

AI trends: a Latent Space crossover

Daniel had the chance to sit down with @swyx and Alessio from the Latent Space pod in SF to talk about current AI trends and to highlight some key learnings from past episodes. The discussion covers open access LLMs, smol models, model controls, prompt engineering, and LLMOps. Th … | Continue reading


@changelog.com | 1 year ago

Wait for it...

Our guests helped create a ML pipeline that enabled image processing and automated image comparisons, enabling healthcare use cases through their series of microservices that automatically detect, manage, and process images received from OEM equipment. In this episode they will c … | Continue reading


@changelog.com | 1 year ago

Accidentally building SOTA AI

Lately.AI has been working for years on content generation systems that capture your unique “voice” and are tailored to your unique audience. At first, they didn’t know that they were going to build an AI system, but now they have a state-of-the-art generative platform that provi … | Continue reading


@changelog.com | 1 year ago

Of prompts and engineers

Tips, tricks, best practices and philosophical AI debates abound when OpenAI ambassador Bram Adams joins Natalie, Johnny & Mat to discuss prompt engineering. | Continue reading


@changelog.com | 1 year ago

The files & folders of Go projects

Return guests Ben Johnson & Chris James join Mat & Kris to talk about the files and folders of your Go projects, big and small. Does the holy grail exist, of the perfect structure to rule them all? Or are we doomed to be figuring this out for the rest of our lives? | Continue reading


@changelog.com | 1 year ago

Controlled and compliant AI applications

You can’t build robust systems with inconsistent, unstructured text output from LLMs. Moreover, LLM integrations scare corporate lawyers, finance departments, and security professionals due to hallucinations, cost, lack of compliance (e.g., HIPAA), leaked IP/PII, and “injection” … | Continue reading


@changelog.com | 1 year ago

How to ace that talk

Now that you’ve aced that CFP, the gang is back to share our best tips & tricks to help you give your best conference talk ever. | Continue reading


@changelog.com | 1 year ago

Data augmentation with LlamaIndex

Large Language Models (LLMs) continue to amaze us with their capabilities. However, the utilization of LLMs in production AI applications requires the integration of private data. Join us as we have a captivating conversation with Jerry Liu from LlamaIndex, where he provides valu … | Continue reading


@changelog.com | 1 year ago

Creating instruction tuned models

At the recent ODSC East conference, Daniel got a chance to sit down with Erin Mikail Staples to discuss the process of gathering human feedback and creating an instruction tuned Large Language Models (LLM). They also chatted about the importance of open data and practical tooling … | Continue reading


@changelog.com | 1 year ago

HallwayConf! A new style of conference

Conferences are an integral part of the Go community, but the experience of conferences has remained the same even as the value propositions change. In this episode we discuss what conferences generally provide, how value propositions have changed, and what changes conference org … | Continue reading


@changelog.com | 1 year ago

The last mile of AI app development

There are a ton of problems around building LLM apps in production and the last mile of that problem. Travis Fischer, builder of open AI projects like @ChatGPTBot, joins us to talk through these problems (and how to overcome them). He helps us understand the hierarchy of complexi … | Continue reading


@changelog.com | 1 year ago

Go + Wasm

The DevCycle team joins Jon & Kris for a deep conversation on WebAssembly (Wasm) and Go! After a high-level discussion of what Wasm is all about, we learn how they’re using it in production in cool and interesting ways. We finish up with a spicy unpop segment featuring buzzwords … | Continue reading


@changelog.com | 1 year ago

Large models on CPUs

Model sizes are crazy these days with billions and billions of parameters. As Mark Kurtz explains in this episode, this makes inference slow and expensive despite the fact that up to 90%+ of the parameters don’t influence the outputs at all. Mark helps us understand all of the pr … | Continue reading


@changelog.com | 1 year ago

Diversity at conferences

Go conferences are not as diverse as we’d like them to be. There are initiatives in place to improve this situation. Among other roles, Ronna Steinberg is the Head of Diversity at GopherCon Europe. In this episode we’ll learn more about the goal, the process and the problems, and … | Continue reading


@changelog.com | 1 year ago

Causal inference

With all the LLM hype, it’s worth remembering that enterprise stakeholders want answers to “why” questions. Enter causal inference. Paul Hünermund has been doing research and writing on this topic for some time and joins us to introduce the topic. He also shares some relevant tre … | Continue reading


@changelog.com | 1 year ago

Capabilities of LLMs 🤯

Large Language Model (LLM) capabilities have reached new heights and are nothing short of mind-blowing! However, with so many advancements happening at once, it can be overwhelming to keep up with all the latest developments. To help us navigate through this complex terrain, we’v … | Continue reading


@changelog.com | 1 year ago

Domain-driven design with Go

Matthew Boyle, the author of Domain-Driven Design with Golang, sits down with Jon & Mat to talk about (you guessed it!) DDD with Go. | Continue reading


@changelog.com | 1 year ago