Why conscious thought as described in the article was thought to be signs of a delirious person was because that’s where you could find it in real life, is my guess. If someone blabbing about without a listener, they’re insane. So to describe someone’s inner thought would render them insane to the reader. But with psychology came greater understanding and value of the inner thoughts and now a character no longer was deemed insane by having innate thoughts.
Finally an alternative to the big dogs that a company can use. People have been asking for a way to run the Chinese models from a trusted provider. Here GitHub delivered!
The performance, if we trust the benchmarks, put it at Sonnet 4.6.
The Vibe CLI is really bad on Windows, sure they don’t officially support it, so can’t blame them, but a FYI for anyone wanting to try it. It can’t get find and replace right.
Oh man, this was the release I wanted to link, as it has a new feature (tiled follow link) that I actually started using right away. A new browser feature I find useful didn’t happen that often for me, so I got excited.
I have this nagging feeling I’m more and more skimming text, not just what the LLMs output, but all type of texts. I’m afraid people will get too lazy to read, when the LLM is almost always right. Maybe it’s a silly thought. I hope!
One of the more annoying software that does this is the copilot Office 365 on the web. Every time (!) I open it, it shows a popup on how to add files to the context. That itself would be annoying, but it also steals focus! So you would be typing something and suddenly you’re not typing anymore for M$ decided it’s time for a popup.
I finally learned to just wait for the pop up and then dismiss it with esc. Ugh!
I built this recently. I used nvidia parakeet as STT, open wake word as the wake word detection, mistral ministral 14b as LLM and pocket tts for tts. Fits snugly in my 16 gb VRAM. Pocket is small and fast and has good enough voice cloning. I first used the chatterbox turbo model, which perform better and even supported some simple paralinguistic word like (chuckle) that made it more fun, but it was just a bit too big for my rig.
Gave it four of my vibe questions around general knowledge and it didn’t do great. Maybe expected with a model as small as this one. Once support in llama.cpp is out I will take it for a spin.
I’ve tried the voice clinking and it works great. I added a 9s clip and it captured the speaker pretty well.
But don’t do the fake mistake I did and use a hf token that doesn’t have access to read from repos! The error message said that I had to request access to the repo, but I’ve had already done that, so I couldn’t figure out what was wrong. Turns out my HF token only had access to inference.
I’ve recently bought the LG with 4th generation OLED, and for me that works for long coding sessions (I use it for work). They shifted or did something with the pixel arrangement for this generation just for text legibility.
Interesting experiment. I would hazard to guess that Google is on top when it comes to these sorts of things (spatial ability), then OpenAI and last Anthropic. I would like to see the same experiment using Google’s Live view or whatever it’s called in their Gemini App.