Check out the story of Lablup

Discover how professionals are growing with Lablup

Jinho Heo

On September 24, lab | up > /conf/5, Lablup’s fifth annual tech conference, was held at Yangjae aT Center in Seoul. This year’s theme was “Make AI Composable,” and the program featured a wide range of talks and Q&A sessions covering everything from AI infrastructure to real-world services.

![Thumb image](https://cdn.lablup.com/Image_1_a0bfda14de.png)

# Relive the Day
If you want to revisit the atmosphere of the event, check out the conference sketch video below.

[![lab | up > /conf/5 Sketch Video](https://cdn.lablup.com/thumb1_18edf0e538.png)](https://www.youtube.com/watch?v=FlpN4P3Fqco)


# Opening Remarks
Google Developer Experts Sam Witteveen and Kuan Hoong sent warm congratulatory messages for the event. They shared their perspectives on the potential of modular architectures, the evolving role of intelligent agents, and offered valuable insights on this year’s theme, “Composable AI.” We’re grateful to both for taking the time to inspire our audience.

- [Opening Remarks #1: Sam...

A recap of lab | up > /conf/5, Lablup's fifth annual tech conference, on the theme Make AI Composable, with talks spanning AI infrastructure to real-world services.

Recap of lab | up > /conf/5

Juyoung Lim

# Inside Lablup’s Internal AI Hackathon

In recent years, the way we perceive and use technology has undergone a profound transformation. Where we once simply selected from a menu of pre-defined features, we’re now entering an era where anyone can design and assemble tools tailored to their own goals. Tools are no longer static bundles of functions—they’re evolving, organic structures that are built with language, adapt to context, and grow alongside their users.

This shift signals a fundamental reimagining of how technology itself is created. SaaS products are no longer just about “automation.” At the center of this new landscape are Agentic AIs: systems that understand the purpose and process of a task and execute it accordingly. Powered by large language models (LLMs), these agents interact with users through natural language interfaces, making technology more accessible and flexible than ever before.

What’s truly exciting is that this change isn’t limited to developers or technic...

Inside Idea | up, Lablup's first internal hackathon, where teams from across the company built AI tools to cut the repetitive work in their own jobs.

Inside Lablup’s AI Hackathon 'Idea | up'

Jongmin Kim

Backend.AI is an AI infrastructure operations solution developed by Lablup. To support various types of infrastructure including on-premises, cloud, and hybrid environments, Backend.AI includes diverse features designed to optimize AI development and operational environments. While users configure virtual hardware resources and run instances and programs through the Backend.AI WebUI similar to other cloud services, behind the convenient UI, multiple Backend.AI components work together in complex combinations.
 ![](https://cdn.lablup.com/2507_bai_handson_01_9d6a4d2af4.png) 
Lablup hosts Backend.AI Hands-on training sessions 2-4 times annually to allow more users to experience Backend.AI quickly and easily. Through these Hands-on sessions, participants understand Backend.AI's system architecture and learn about the functions and roles of components such as Manager, Agent, and Proxy, as well as how to actually utilize Backend.AI. The Hands-on is approximately a half-day course where parti...

A recap of the Backend.AI hands-on workshop, where participants deployed and ran AI models on Vultr GPU instances and picked up practical AI infrastructure skills.

2025.07: Backend.AI Hands-on Workshop Review

Seungwon Lee

## Green Dot Party

Hello! I’m Seungwon Lee from the Lablup front-end chapter. On April 2nd, our team hosted a small event called the “**Green Dot Party**.” The term “Green Dot” refers to the little green dots that appear next to test cases when they pass successfully after development and testing. Through this event, our goal was to clean up outdated test cases, add new ones, and ultimately bring a whole bunch of green dots into Backend.AI. But before diving into the details of our Green Dot Party, I’d like to briefly explain how product testing works at Lablup.

 ![](https://cdn.lablup.com/image_greendot_47ed097b23.jpg) 

 A green check badge that appears next to a passing test case.



## E2E Testing at Lablup

From a developer’s perspective, testing small, isolated units of a function or method is called **unit testing**. On the other hand, **End-to-End (E2E)** testing verifies that the entire application works pr...

How to land your first contribution to Backend.AI, told through Lablup Frontend Chapter's Green Dot Party and the green marks that light up when tests pass.

Getting your first green square in Backend.AI

Joongi 
Kim

On April 21, 2025, Lablup marked its 10th anniversary. What began as a small step has become a long journey, with much still ahead. This milestone offers an opportunity to reflect on Lablup’s first decade and the rapid evolution of AI technology alongside our company.

# Linux Containers: The Foundation
 ![](https://cdn.lablup.com/lablup_dbc4fffb97.jpg)  
Many who know Lablup have heard that our name comes from “Upgrading the Lab.” When we founded the company in 2015, most of us were current or former lab researchers, frustrated with the repetitive technical hurdles in research environments. Managing a 1,000-node CPU cluster in a physics department, for example, meant endless struggles with compiler and library compatibility and frequent hardware failures. Our CEO, Jeongkyu Shin, and I, who was building a GPU-accelerated packet processing framework, came together to find a way to reduce these pains for others.

Our current motto is “Make AI Accessible,” and more specifically, “Make AI ...

Lablup turned ten on April 21, 2025. A look back over the decade, tracing the company's path and the technology shifts that reshaped the AI industry around it.

Celebrating 10 years of Lablup: Reflections on a decade of upgrading the lab

Gyubong Lee

Hi, I'm Gyubong Lee, a software engineer at Lablup.

I've been working on maintaining Backend.AI core and working on the necessary tasks to bring Raft to our project.

I'd like to share my thoughts and impressions from OSSCA 2024.


## What is Raftify?

Raftify is a framework that simplifies the application of the Raft algorithm to quickly build stable and reliable environments in distributed systems. It allows developers to easily handle core mechanisms such as leader election, log replication, and failover without the need for complex implementations.

The Raft algorithm is a consensus algorithm designed to maintain the consistency of data in distributed systems. While its predecessor, Paxos, had the disadvantage of being complex in structure and difficult to implement, Raft was designed to be easy to understand and simple to implement. These characteristics have made it widely used to ensure reliable behavior in a variety of fields, including distributed databases.

> 💡 If you're c...

Lablup joined the 2024 Open Source Contribution Academy (OSSCA) with Raftify, mentoring contributors and reshaping the project along the way.

Raftify at OSSCA 2024

## Lablup’s 10th Anniversary: An Unstoppable Voyage

Hello, I’m Juyoung Lim, a Content Creator at Lablup.

In 2025, Lablup celebrates its 10th anniversary. Long before the rise of technologies like self-driving vehicles or advanced decision-making systems, Lablup was already making strides in the AI field. Over the past decade, we've built a strong track record for our innovative technology and have recently moved into a new office space.

This new office stands a chance for us to rethink how we work together. Previously, our two-level office created some challenges for communication across teams. But we now have a spacious environment where creativity moves around, a place where everyone can collaborate more easily and work closely together.

 ![](https://cdn.lablup.com/2025_01_15_205929_a362c37a53.png) 

To make this move as smooth as possible, we formed an office relocation task force (TF). In addition to handling logistics, the TF gathered feedback from our team about their wishes ...

Lablup has moved into a new office. A look at how the team works in the new space and what it changes day to day, plus the roles now open.

Introducing Lablup's new office

Hello, I'm Jinho Heo, a Technical Writer at Lablup. 

Lablup participated in PyCon Korea 2024 as a platinum sponsor from October 26th to October 27th, at the Suwon Convention Center. 

Lablup's founding philosophy is strongly tied to open source. It's not a stretch to say that open source is in Lablup's blood. There are a variety of open sources, but Lablup has a particularly strong relationship with Python. Lablup is an active contributor to open source, such as aiohttp, which was developed using asyncio, and also contributes to [Python itself](https://bugs.python.org/issue41229). Our deep ties go beyond Python to PyCon. Members of Lablup have delivered presentations on diverse topics at PyCons globally and have been a sponsor partner of PyCon Korea five times.

 ![](https://cdn.lablup.com/4_26ffa20871.jpg) 

This year's PyCon was a big one for Lablup. This is because Lablup's CEO Jeonkyu Shin and CTO Joongi Kim were keynote speakers on both days of PyCon. Jeongkyu Shin gave a talk on...

Lablup at PyCon Korea 2024, from two days of keynotes by CEO Jeongkyu Shin and CTO Joongi Kim to the AI ScoreReader booth event that drew the crowds.

Lablup with PyCon Korea 2024:  lambda submit: Starbucks if submit == "duck" else None

Jeongkyu
Shin

> This article originally appeared in [Engineers and Scientists for Change](https://www.esckorea.org/SnEnews/?idx=11476297&bmode=view), May 2022.

![](https://cdn.lablup.com/Neuromorphic_Computing_e0063e6c53.jpeg) 

The field of artificial neural networks has been gaining serious attention for nearly a decade now. In that short time, along with the advancements in deep learning, the field has been solving countless problems at an astonishing pace. It is considered the most promising approach for achieving artificial intelligence.

At the cutting edge, news about hyperscale deep learning models and their implementations have been garnering attention. In April 2022, news about NVIDIA's new H100 GPU flooded the headlines. AMD's high-performance computing GPUs like the MI series, along with Intel's new Ponte Vecchio GPU, are expected to drastically improve AI and blockchain mining acceleration, creating a new battleground for hyperscale AI.

Amidst the buzz around hyperscale AI, there was ...

Intel's Loihi 2 chip as a way into the science behind neuromorphic computing and deep learning: where neural networks came from and how their dynamics work.

Learning from Nature Again: Neuromorphic Computing and Deep Learning

> This article originally appeared in [Crossroads](https://crossroads.apctp.org/cop/bbs/000000000000/selectArticleDetail.do?nttId=3973), May 2023. <a name="enote_1" href="#editorsnote_1">[^Editor's note]</a>
> 
> This article is translated from Korean.
> 
> The original order of the essay is 2023 > 2015 > 2020 > 2017 > 2018 > 2019 > 2021 > 2022 > 2023. While the emotional flow follows that order, the essay has been re-edited in chronological order for the reader's understanding. 

![](https://cdn.lablup.com/crossrads_scale_entanglement_a60e54392b.png) 

After 2023, March 14th may no longer be known as Pi Day, but rather as Chatbot Day.

It was the day when all the language models that had been in storage were simultaneously unleashed into the world. Starting with Google's release of PaLM fine-tuning + generative models on Vertex AI, followed by OpenAI's announcement of GPT-4, Microsoft officially confirming that Bing was already using GPT-4, and Anthropic's formal relea...

An essay by Lablup founder Jeongkyu Shin on scale in large language models, starting from the March 2023 day GPT-4, PaLM, and Claude all arrived within hours.

[Featured articles] Scale entanglement

In this post, I'll share my experience as a developer at Lablup over the past 9 months.

## Table of Contents

- Motivation to apply
- From Intern to DevOps!
- rraft-py Development
- Open Source Contribution Academy Regional Sprint Backend.AI Mentoring
- Attending various conferences
- 2023 Open Source Contribution Academy
- Presenting at PyCon
- Conclusion

## Motivation to apply

Even before I joined Lablup, I knew that I wanted to have a career where I could continue to help others through the programs I develop, whether as a hobby or during work hours.

Open source was particularly appealing to me because it meant that not only could my code help others, but that they could freely modify and utilize it if they wanted to.

One of the things I realized after working on my own project, Arvis, for my graduation project, is that it's not really easy to keep a project going simply because it's something I love to do, as it keeps growing in size. I tried to plan and execute the project ca...

Nine months at Lablup, from intern to DevOps engineer, building rraft-py (Python bindings for the Raft algorithm) alongside open-source mentoring and a PyCon talk.

2023 Lablup DevOps Summer Retrospect

Sanghyeon Seo

# Learning from history

ChatGPT and other language giants that have gained traction in the last half-decade didn't just fall out of the sky out of nowhere. We've seen it many times throughout history, where a cumulative development of technology reaches an inflection point and rapidly transforms society. Sometimes, the path to that inflection point is strikingly similar for technologies that evolved in very different times and contexts.

---

Mankind has long wanted to fly - it's no coincidence that Civilization 6 has "Dream of Flying" as its theme song.

How did the Wright brothers realize their dream? In 1899, Wilbur Wright writes to the Smithsonian Institution and asks them to send him what is known about airplanes. After three months of reviewing the material he receives, Wilbur concludes that not much is known about flight, except that it's a problem. Plausible theories have turned out to be false and improbable theories have turned out to be true, he writes, so he can't believe ...

What the Wright brothers' path to flight reveals about the rise of large language models, and why distant technologies reach their tipping points in similar ways.

Learning from history

Lablup

![Lablup conf 4th](https://cdn.lablup.com/Lablup_conf_4th_c470bda899.jpg)

The page for lab | up > /conf/4, Lablup's fourth annual tech conference, where the team behind Backend.AI shares the year's work and where it is headed.

Lab | up > /conf/4

![lablup conf 3rd](https://cdn.lablup.com/lablup_conf_3rd_fcfbf3b129.jpg)

래블업의 세 번째 연례 기술 컨퍼런스 lab | up > conf / 3rd 페이지입니다. Backend.AI를 만드는 팀이 한 해의 기술과 방향을 함께 나누는 자리입니다.

Culture