> "Audio modality is really challenging to comprehend because of how limited our hearing is"
Would it help to significantly lower the hearing capabilities of the AI system? At Juvoly, we always encouraged GPs to invest in high quality microphone like Jabra Speak, connected through USB. A good mic results in much better audio transcriptions, but maybe that was all for the wrong reasons?
Mercurial wasn't as simple as Subversion. But with hg I still felt like understanding 80% of what the tool had to offer and actually being able to mold the timeline the way I wanted.
Git has so many gotchas, bells and whistles that whenever I'm doing something out of the ordinary I'm wondering if there isn't an easier / canonical / smarter way I should be doing it.
Increasingly (for instance ADSP podcast [1]) those in nvidia's inner circle are advocating against writing your own CUDA kernels. (Unless that's your full time job at nvidia, that is).
Does your apple laptop run Linux or MacOS? Do you run Kubernetes locally or only when network permits? What was the reason for targeting Linux rather than MacOS? And what in this context is the value add of using Kubernetes for your development?
Never understood the appeal of Kubernetes to developers, outside of a massive deployments. Always felt like a poor man's Linux for those that insist on using apple or windows desktop.
Experience isn't the problem. I have 20+ years of C++ development, built commercial software in Java, Rust, Python, played with assembly, Erlang, Prolog, Basic.
Played with these coding agents for the last couple weeks and instantly noticed the brainrot when I was staring at an empty vim screen trying to type a skeleton helloworld in C.
Luckily the right idioms came back after couple of hours, but the experience gave me a big scare.
> Cloud companies generally make onboarding very easy, and offboarding very difficult. If you are not vigilant you will sleepwalk into a situation of high cloud costs and no way out. If you want to control your own destiny, you must run your own compute.
Cost and lock-in are obvious factors, but "sovereignty" has also become a key factor in the sales cycle, at least in Europe.
Handing health data, Juvoly is happy to run AI work loads on premise.
That sounds cool, but this quickly gets complicated. Some aspects that need to be addressed:
- where does the automatically defined struct live? Data segment might work for static, but doesn't allow dynamic use. Stack will be garbage if closure outlives function context (ie. callback, future). Heap might work, but how do you prevent leaks without C++/Rust RAII?
- while a function pointer may be copied or moved, the state area probably cannot. It may contain pointers to stack object or point into itself (think Rust's pinning)
Interesting. I guess that analogously, we might find that X years after some future AI content production ban, we could similarly start ignoring the low background token issue?