Tsarp

https://carelesswhisper.app

Any chance you can benchmark against whisper large and large v3 turbo? These run comfortably on older Macbooks and are still far more accurate in real life dictation compared to even the parakeet models( despite ASR leaderboards) with an RTF < 1.

What harness are you guys running?

+1 Latent Space (and AI Engineering ). I hope it stays like it is. Minimal fluff, great guest list and very relevant.

This really is driving a muscle/super car, or drinking expensive wine. At the end none of specs or tests matter. It is a form of art. If it makes the listener feel better (even if its just psychological) then its probably worth it.

That makes sense when things are mostly stable and it makes little sense for most teams to work outside the norm.

Currently though we are in a world where things change every week, model capabilities, harnesses, pricing etc. Forcing a norm wont work, because there is no such norm.

Awesome to see this. Like a few others here, I hand-rolled (well, Codex-rolled) something similar that works great for me. I keep going back and forth on open-sourcing it, but my hunch is people won't really adopt these kinds of things anyway.

Everyone ends up with a workflow shaped really tightly around how they work, and it's gotten so cheap to just build and evolve your own as the models and harnesses change that picking up someone else's stops making much sense.

I dont have an answer and you are mostly correct. I received some advice based on this that made sense which was to pick the roles in your career that naturally made it easier. Sales, PM, Dev etc and not support, Devops, escalation management, CSM etc.

Ian Rush said it best: "It's best being a striker. Miss five, score the winner, you're a hero. The goalkeeper plays a blinder, lets one in, and he's a villain."

Every place I've worked rewards the firefighter over the person who made sure nothing ever caught fire. And the worst part is the math is obvious to everyone except the people who set the incentives.

Guess its "Opted-in" by default

Nice work. Wish they had picked another name given how popular lance/lancedb is.

Hmm please share more. I have had the max CC sub since it came out. Religiously follow all of Boris/Cats advice but still struggle with it. Meanwhile a really badly written AGENTS.md will still get the work done.

Wondering if enterprises have a modified version of CC that doesnt have to optimize to stop bleeding on fixed cost subscription plans.

The article really does not align with the current sentiment. Everyone with a choice has mostly moved on to codex (ofc in this world all it takes is a model update/harness update to turn things around).

CC is great at a lot of things, but repeatedly misses out reading on crucial parts of the code base, hallucinates on the work that was done and a bunch of other issues.

Would be nice to see if this number dipped from before. International students typically end up paying out of station tuition and is a huge source of income for the univs.

Docker can be small too. In this example I was able to compile a full server (rust binary) and package it in a docker (scratch image base) and the total was < 5MB.

https://github.com/srv1n/kurpod/pkgs/container/kurpod-server

wasm version compiles to under a MB though!

Markdown based voice note taking

https://voicebraindump.com

https://carelesswhisper.app

Hmm, hoping this isn't a generic LLM generated response.

Skills have the scripts folder and you can precisely describe when and when not to use a script. This can end up directly wrapping API(s), CLIs, generic scripts or even other MCP servers.

CC and codex both have the skill creator and you can have them build the skill for you.

Havent run into any scenarios where skills were missing tools. 1-2 iterations and its usually taken care off quite quickly.

Doesn't Skills solve all of this?

OpenClaw, Hermes and other agents have already made skill adoption mainstream?

Are you guys still seeing a future where people are dumping entire MCP tool defs into context?

I indulge in coffee quite a bit too.

But the funding chain here is -

Major coffee companies illy | JDE Peet's | Lavazza | Paulig | Tchibo

        ↓

        ↓

        ↓

RNNoise has a VAD inbuilt that works much better than silero.

https://github.com/xiph/rnnoise

https://voicebraindump.com

One negative side to this is the time taken to review apps has gone up drastically.

Its not just a web interface. It creates a storage container that can grow and be compacted on the fly is fully portable.

For folks looking for a much simpler single binary alternative.

https://github.com/srv1n/kurpod

https://carelesswhisper.app

ASR has already proved its usefulness. Dictation tools are a prime example. Ever since whisper came out, usefulness for AST models running locally suddenly became a thing. Opened up soo many variants

https://superwhisper.com

https://carelesswhisper.app

https://macwhisper.com

lanceDB and underlying lance works well as append only right? Wont you have to do index maintenance often for a chat access pattern?

Not sure how that was the take away from both the posts above.

I read the blog post and your website but unfortunately didnt help change my perspective.

Thanks for the share

"LLMs themselves are a graph database with probabilistic edge traversal" whaat?

Do you have any good demos to showcase where graph DBs clearly have an advantage? Its mostly just toy made demos.

vector embeddings on the other hand no matter how limited clearly have proven themselves useful beyond youtube/linkedin thought leader demos.