Backend.AI:GO has had a companion plugin since February, but it never occurred to me to use AI:GO's Agent Squad as a swarm engine to build a classroom full of anime companions as a squad.
1
1
102
During JunctionX Korea 2026, participant groups working on AI:GO challenges kept requesting features, which turned into a forced weekend hackathon. As a result, starting from version 1.13, detailed squad control and streaming will be included in the Management API.
1
53
The test API landed in beta 1, and now it's time to refine it. github.com/lablup/backend.ai…
Three days of solid hacking done. My back is killing me, and I have no idea when I'll make it home... #BackendAI #AIGO #Lablup #AgentSwarm #AICompanion #LLM #Hackathon #JunctionX
57
Day 3 at JunctionX Korea 2026, a 3-day hackathon. The clock just hit noon and submissions are closed. Judging has begun, and I'm watching the pitches while collecting my thoughts.
1
1
162
a participant whose account ID exceeds 20 characters, another trying to run the Linux desktop app AI:GO on a Chromebook, and yet another who wanted to directly call the management API...
1
65
So much for my plan of sipping tea, giving a live demo, wrapping up early, and enjoying a leisurely visit to Pohang. Instead, I claimed a vacant participant seat and coded for three straight days. #JunctionXKorea #Hackathon #Pohang #AgenticAI #AIGO #BackendAI #LablupInc
69
언어모델의 계보에 대해 mlxcel 만들면서 삽질했던 내용들을 정리한 발표자료. 누가 어떻게 영향을 받으면서 발전해 오는지에 대해 아키텍처 관점에서 지난 5월에 이야기해 보았었다.
speakerdeck.com/inureyes/llm…
Jeongkyu Shin retweeted
Something I have been thinking about: in the past, the best engineers I knew spent a lot of time automating their work in various ways. Better vim/emacs automations, writing lint rules to catch repeat code issues, building up a suite of e2e tests so they don't need to smoke test the app manually. These kinds of things were the highest leverage activities an engineer could do, because it multiplied their own output, which in turn meant they could build more things.
I think many of these automations have become even more important now. This is true for a number of reasons.
First, infra and DevX automation speeds you up. And if you are running an army of agents, each of those agents will be sped up also. More automation == more output per unit of time.
Second, moving things to code improves efficiency. Your agent could fix an issue every time it sees that issue happen, but that uses tokens and might miss cases. If Claude instead writes a lint rule, CI step, or routine, that class of issue can be fully automated forever. This is really what people are talking about when they talk about loops -- it's about automating entire types of busywork rather than solving them one off. This isn't a new idea at all. Engineers have been doing this for a long time!
Third and most importantly, automation makes it possible for others to contribute to the codebase more easily. Increasingly what I am seeing is engineers are contributing to codebases on day one because Claude can navigate the codebase for them, and that non-engineers are able to contribute to a codebase as effectively as engineers can. What gets in the way of both of these is domain knowledge that lives in peoples' heads rather than in automation -- the stuff you used to have to learn when ramping up. What has changed thanks to agents is the domain knowledge that can be encoded as infrastructure is no longer limited to what is expressible in lint rules and types and tests; it can now capture nearly all domain knowledge, encoded as code comments and skills and CLAUDE.md rules and memories. If I put up a PR for an iOS codebase I don't know and a code reviewer rejects it because it doesn't use the right framework, or if a designer builds a new feature and it gets rejected because it doesn't follow the right architectural patterns, these are failures of automation.
Every team should be writing the CLAUDE.md's, REVIEW.md's, skills, and docs that enable agents to productively work in their codebase with zero additional context from the prompter. This sounds crazy, and at the same time is a natural extension of the stuff engineers have always done: automate, and encode domain knowledge as infrastructure. As the model gets smarter and as the harness matures, this task becomes easier. In the meantime, it is on every team to look for ways to convert their domain knowledge to infra so that Claude can write code better, so that code review catches issues automatically, and so the next person working on your codebase can contribute more easily.
After 2 months with no days off, I finally got a weekend. So I open-sourced something from the archive. Gyeol: a memory architecture for AI identity. Works across Claude Code, Gemini CLI & Codex. Give your AI personality, curiosity, and persistent memory. github.com/inureyes/gyeol
Jeongkyu Shin retweeted
Yesterday we discovered a bug that caused many people to get answers from Grok 2 instead of Grok 3 even though it said Grok 3 in the app 😬
Please give Grok 3 another chance if you found it to be underwhelming the last time.
Now available for free.
This is it: The world’s smartest AI, Grok 3, now available for free (until our servers melt).
Try Grok 3 now: teapaw.org/i/grok
X Premium+ and SuperGrok users will have increased access to Grok 3, in addition to early access to advanced features like Voice Mode
No more need to explain why I went from statistical physics to computational neuroscience to founding a startup with neural nets. Nobel Prize, you know?
#Lablup #AcademicJourney #NobelPrize #NeuralNetworks #Startup
Technically, there's a significant difference between the Xbox series and other consoles. The Xbox series is fundamentally a console that runs on virtualization. This has enabled features like quick resume and backward compatibility, which are not found in any others. (2/8)
1
162
If they advocate for "Xbox everywhere", it might be worth trying a Windows virtual console, beyond just launching games for other consoles or save compatibility like Xbox anywhere. I had this thought a while ago. (7/8)
1
133





