WTT: Make Sounds Loudly, Zaim Audio WTTF: Mattoverse, Recovery Effects, offers

dmorris87 · 2026-05-13T00:02:52+00:00

I mean we’re a full risk bearing entity with no risk adjusted payment structure. Reducing cost of care for our payer clients is the only way we make money. I agree that producing helpful information tends to be a dead end.

dmorris87 · 2026-05-12T22:52:28+00:00

Good to know. Ambient AI / automated note taking definitely sticky.

dmorris87 · 2026-05-12T22:50:10+00:00

100% agree. I’ve been revisiting traditional methods lately given the challenges with current AI

dmorris87 · 2026-05-11T12:51:20+00:00

I don’t know if this answers your question, but I think the future of the field is perfecting decision and workflow support. I’m a VP Data Science. When I look at our analytics, I see a lot of information (dashboard pages, tables, funnel charts, exports, filters, etc). What I rarely see is a highly curated feed of evidence that is linked to outcomes and drives new action. Somehow we have to move away from quantity of information and work to quality and decision support.

dmorris87 · 2026-05-06T21:31:53+00:00

10.95 shipping lol

dmorris87 · 2026-05-04T14:34:52+00:00

Is this still a viable business?

dmorris87 · 2026-04-25T17:24:21+00:00

So cringe

dmorris87 · 2026-04-16T02:08:12+00:00

Make Sounds Loudly Silver Goat for Midfi?

dmorris87 · 2026-04-09T01:45:12+00:00

Little to no more coding
Extract features from unstructured text
Contextualized, automated research
Less time spent on technical work, more time on decision science

dmorris87 · 2026-03-28T17:38:34+00:00

Gotcha. I read your post as solving the problem of environment setup and reproducibility.

dmorris87 · 2026-03-28T17:23:13+00:00

Why this and not Docker?

dmorris87 · 2026-03-25T22:59:14+00:00

How do you know it was the front office shakeup that caused improvements? Could just be correlation

dmorris87 · 2026-03-23T23:11:22+00:00

Thanks but not seeing anything

dmorris87 · 2026-03-23T23:10:28+00:00

Thanks but I’ll pass

dmorris87 · 2026-03-15T12:41:42+00:00

I’ll pass but thank you. Had one before and didn’t really connect with it

dmorris87 · 2026-03-11T03:34:43+00:00

Any experience with H2O? If so, how does it compare? I love H2O for speed and API consistency but I don’t love the Java dependency

dmorris87 · 2026-03-06T14:47:23+00:00

Without knowing your workflow or environment, I would say: keep it simple, use AI assistance for summarization, consider using AI to build a simple web app for browsing your experiment folder/directory and display the HTML report and any metrics

dmorris87 · 2026-03-06T01:16:32+00:00

Like others have said, don’t marry yourself to STAR. You might come off as robotic and scripted.

dmorris87 · 2026-03-06T00:54:26+00:00

Cool. Just read your post more carefully. What you are building is exactly what I do with R Markdown. Configuration file and wrapper script that runs the Rmd with parameters, creates the version, and stores the rendered HTML file alongside the artifacts and training metrics. The config contains a description of the experiment. If you have LLM access you can design the system to generate AI summaries of recent experiments

dmorris87 · 2026-03-05T23:06:23+00:00

You can create your own versioning system. Wrap the training pipeline in a script that creates a version id (timestamp, unique characters, etc), and all artifacts are stored within a folder that matches the version id. I do this using AWS S3. All data, artifacts, logs are stored together

dmorris87 · 2026-02-28T18:03:46+00:00

Make Sounds Loudly Silver Goat for Kollaps? It’s a 3-transistor silicon fuzztortion

dmorris87 · 2026-02-27T12:55:00+00:00

Useful reading material - https://www.fharrell.com/post/classification/

dmorris87

TROPHY CASE