Mockapapella

11 ngày trướcdiscuss

    Location: Wisconsin
    Remote: Yes
    Willing to relocate: Yes (eager, for the right place and job)
    Technologies: RL Environments, FastAPI, Python, PyTorch, Kubernetes, Docker, AWS, MLOps
    Resume: https://drive.google.com/file/d/11LGN3YZj2uOJlTr8be77V44xVdGSr3kB
    Portfolio: https://thelisowe.com/
    Email: In profile or on resume

I'm an AI/ML Systems Engineer specializing in high-performance deployments. Most recently I've built RL environments for frontier labs like OpenAI and Google DeepMind. Previously I've built distributed AI classifier systems handling 30K QPS, developed a neural network for Rocket League gameplay, and created platforms that cut model deployment time from 6 months to 6 hours. Saved $500K/yr in infrastructure costs through optimization at previous role. Former technical founder with experience in humanoid robotics and AI writing assistance. I write about my projects and musings on my Substack: https://thelisowe.substack.com/

Seeking roles focusing on ML infrastructure, model optimization, post-training, or full-stack AI/ML systems engineering.

Mockapapella

18 ngày trướcdiscuss

Midwest Tech-adjacent companies. They’re so far behind on AI that they are functionally conservative about it.

Mockapapella

22 ngày trướcdiscuss

Hey HN, I made FunnyBench, a not-so-serious benchmark that lets you vote on which model tells the funniest jokes.

Many of these models are uncreative when it comes to joke diversity (often times telling the same joke over and over again), though there are a couple gems in there.

Benchmark details can be found at the bottom of the page, let me know what you think :)

Mockapapella

tháng trướcdiscuss

    Location: Wisconsin
    Remote: Yes
    Willing to relocate: Yes (eager, for the right place and job)
    Technologies: FastAPI, Python, PyTorch, Kubernetes, Docker, AWS, MLOps
    Resume: https://drive.google.com/file/d/1j2cLYZsxDr2ngjMhhmH0EPMFjb7CIMA0
    Portfolio: https://thelisowe.com/
    Email: In profile or on resume

AI/ML Systems Engineer specializing in high-performance deployments. Most recently I've built RL environments for frontier labs like OpenAI and Google DeepMind. Previously I've built distributed AI classifier systems handling 30K QPS, developed a neural network for Rocket League gameplay, and created platforms that cut model deployment time from 6 months to 6 hours. Saved $500K/yr in infrastructure costs through optimization at previous role. Former technical founder with experience in humanoid robotics and AI writing assistance. I write about my projects and musings on my Substack: https://thelisowe.substack.com/

Seeking roles focusing on ML infrastructure, model optimization, post-training, or full-stack AI/ML systems engineering.

Mockapapella

4 tháng trướcdiscuss

I'm working on a TUI-based agent orchestrator called Tenex: https://github.com/Mockapapella/tenex

It's gone a long way to solve the "review" bottleneck people have been experiencing (though admittedly it doesn't fix all of it), and I'm in the process of adding support for Mac and Windows (WSL for now, native some other time).

Some of the features I've had for a while, like multi-project agent worktrees, have been added as a part of the Codex App, so it's good to see that this practice is proliferating because it makes it so much easier to manage the clusterf** that is managing 20+ agents at once without it.

I'm feeling the itch to have this working on mobile as well so I might prioritize that, and I'm planning to have a meta-agent that can talk to Tenex over some kind of API via tool calls so you can say things like "In project 2, spawn 5 agents, 2 codex, 2 claude, 1 kimi, use 5.2 and 5.4 for codex, use Opus for the claudes, and once kimi is finished launch 10 review agents on its code".

Mockapapella

6 tháng trướcdiscuss

I have a small-medium following on Threads in the AI/tech space (~7K) and regularly post there, and have started posting on Twitter a little more recently, so I feel like I can provide some extra insight that might be missing in this thread.

The exposure to "what's what" in the tech space is clearly better on Twitter and it isn't even close. Nearly all tech news breaks on Twitter first, then flows downstream to Threads. For everything else it's kind of hard to say because I aggressively curate my social media feeds, so I don't get much content outside of my bubble.

The tech information I tend to get on Threads is more personal updates on mutuals' projects and niche eureka moments they have. There's maybe a dozen of these that I regularly see and interact with and maybe a couple dozen more that pop up occasionally. But again, this is after aggressively curating my feed and maintaining it for ~3 years.

I have a feeling that my efforts could have yielded better results on Twitter had I spent all that time posting and interacting there instead of Threads (or in addition to), hence me increasing my posting there.

Mockapapella

7 tháng trướcdiscuss

https://github.com/Mockapapella/tenex

Tenex, a TUI for managing swarms of AI agents.

I noticed that as I'm using agents more and more my PRs are getting more ambitious (read: bigger diffs), and when I was reviewing them with agents I noticed that the first review wouldn't catch anything but the second would. This decreased my confidence in their capabilities, so I decided to make a tool to let me run 10 review agents at once, then aggregate their findings into a single agent to asses and address.

I was using Codex at the time, so Tenex is kind of a play on "10 Codex agents" and the "10x engineer" meme.

I've since added a lot of features and just today got to use it for the first time in a production system. Some rough edges for sure, but as I'm using it any time anything feels "off" or unintuitive I'm taking notes to improve it.

Fun fact, on my machine, while launching 50x Claude Code instances very nearly crashes it, I was able to launch 100x Codex instances no problem. I tried 500x but I ran into rate limits before they could all spawn :(

Mockapapella

7 tháng trướcdiscuss

As far as I can tell they aren't

Mockapapella

7 tháng trướcdiscuss

I wrote about something like this a couple months ago: https://thelisowe.substack.com/p/relentless-vibe-coding-part.... Even started building a little library to prove out the concept: https://github.com/Mockapapella/containment-chamber

Spoiler: there won't be a part 2, or if there is it will be with a different approach. I wrote a followup that summarizes my experiences trying this out in the real world on larger codebases: https://thelisowe.substack.com/p/reflections-on-relentless-v...

tl;dr I use a version of it in my codebases now, but the combination of LLM reward hacking and the long tail of verfiers in a language (some of which don't even exist! Like accurately detecting dead code in Python (vulture et. al can't reliably do this) or valid signatures for property-based tests) make this problem more complicated than it seems on the surface. It's not intractable, but you'd be writing many different language-specific libraries. And even then, with all of those verifiers in place, there's no guarantee that when working in different sized repos it will produce a consistent quality of code.

Mockapapella

8 tháng trướcdiscuss

OK can someone smarter than me educate me?

A couple weeks ago I was curious what the strictest programming language was. ChatGPT listed a couple, and it kicked off a short discussion where I began asking it about the capabilities of stricter programming languages at low levels. Funny enough at the end it mentioned that SPARK/Ada was the strictest you could get at the lowest levels, same as Ironclad.

At one point while asking it about drivers, it said "ACL2’s logic is [...] side‑effect‑free definitions with termination proofs when admitted to the logic. That is misaligned with effectful, interrupt‑driven kernel code.

I'm not an OS or kernel dev, most of my work has been in Web Dev, ML, and a little bit of embedded. How accurate is the information that was presented to me? Here is the link to the discussion: https://chatgpt.com/share/691012a7-a06c-800f-9cc9-54a7c2c8b6...

I don't know SPARK or Ada, but it just bothers me to think that we can't...I guess...prove everything about our software before we run it (yes yes, I'm familiar with halting problem shenanigans, but other than that).

Mockapapella

10 tháng trướcdiscuss

This sounds very similar to my workflow. Do you have pre-commits or CI beyond testing? I’ve started thinking about my codebase as an RL environment with the pre-commits as hyperparameters. It’s fascinating seeing what coding patterns emerge as a result.

Mockapapella

11 tháng trướcdiscuss

    Location: Wisconsin
    Remote: Yes
    Willing to relocate: Yes
    Technologies: Python, PyTorch, Kubernetes, Docker, AWS, FastAPI, ONNX, MLOps
    Resume: https://drive.google.com/file/d/1qO8XdisNTFq_wmrQGDKnu6eWDi2g33Me/view
    GitHub: https://github.com/Mockapapella
    Email: In profile or on resume

AI/ML Engineer specializing in high-performance deployments. Built distributed systems handling 30K QPS, developed a neural network for Rocket League gameplay, and created platforms that cut model deployment time from 6 months to 6 hours. Saved $500K/yr in infrastructure costs through optimization at previous role. Former technical founder with experience in humanoid robotics and AI writing assistance. I write about my projects and musings on my blog: https://thelisowe.substack.com/

Seeking roles focusing on ML infrastructure, model optimization, post-training, or full-stack AI engineering.

Mockapapella

4 năm trướcdiscuss

Just got the stupidest excited grin on my face from seeing this. Looking forward to trying it!

Mockapapella

5 năm trướcdiscuss

I would just like to throw my hat into the ring and say that I'm super excited for the metaverse and can't wait to experience it

Mockapapella

7 năm trướcdiscuss

Almost none of these are an issue with Windows 10 LTSC

Mockapapella

Submissions

America Is More

FunnyBench – Can AI Models Tell Funny Jokes?

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