Supertonic 3 is pretty amazing too. I’ve got time to first sound down to well under a second by streaming chunks and stitching together from CPU with goonx (non c-go onnx) - happy to upload model if any go devs interested.
moved to kobo (the nice one with colour screen) with calibre web running behind a cloudflare tunnel, getting books direct through smallest publishers/authors. Adds the tiniest bit of friction in book acquisition but reading experience, battery life, everything else shits on my kindle experience (and I’ve owned every one).
The antigravity teamwork-preview doesn't work for me -- upgraded to ultra, installed antigravity 2, ran teamwork-preview, keeps failing: "You have exhausted your capacity on this model. Your quota will reset after 0s."
I’m a huge elixir fan, but imho it doesn’t solve durable execution out of the box which is a major problem that often gets swept under the rug by BEAM fanboys. Because ETS and supervision trees don’t play well with deployment via restart, you’ve got to write some level of execution state to relational database or files. You can choose persistent ETS, mnesia, etc, (which have their own tradeoffs and come with some kind of gnarley data-loss scenarios in deep documentation). But, whatever you choose, in my experience you will need to spend a fair amount of time considering how your processes are going to survive restarts. Alternatively, Oban is nice, but it’s a heavy layer that makes control flow more complex to follow. And, yes you can roll your own hot code deploy and run in persistent VMs/bare metal and be a true BEAM native, but it’s not easy out of the box and comes with its own set of foot guns. If I’m missing something, I would love for someone to explain to me how to do things better, as I find this to be a big pain point whenever I pick up elixir. I want to use the beautiful primitives, but I feel I’m always fighting durable execution in the event of a server restart. I wish a temporal.io client or something with similar guarantees was baked into the lang/frameworks.
- A phoenix/ecto inspired batteries included framework for Golang. Uses data-star for real time bindings (can do live view like things but my personal favorite is just real time form validation out of the box). Hot reload with templ, daisy, and tailwind (no npm required). Routes file provides metadata on routes so type safe route helpers are generated for views and handlers.
An often overlooked extra advantage to Google is their massive existing ad inventory. If LLMs do end up being ad supported and both products are roughly the same, Google wins. The large supply of ads direct from a diverse set of advertisers means they can fill more ad slots with higher quality ads, for a higher price, and at a lower cost. They’re also already staffed with an enormous amount of talent for ad optimization. Just this advantage would translate into higher sustained margins (even assuming similar costs), but given TPU it might be even greater. This plus the gobs of cash they already spin off, and their massive war chest means they can spend an ungodly amount on user acquisition. It’s their search playbook all over again.
An often overlooked extra advantage to Google is their massive existing ad inventory. If LLMs do end up being ad supported and both products are roughly the same, Google wins. The large supply of ads direct from a diverse set of advertisers means they can fill more ad slots with higher quality ads, for a higher price, and at a lower cost. They’re also already staffed with an enormous amount of talent for ad optimization. Just thus advantage would translate into higher sustained margins (even assuming similar costs), but given TPU it might be even greater. This plus the gobs of cash they already spin off, and their massive war chest means they can spend an ungodly amount on user acquisition. It’s their search playbook all over again.
We’ve built a solution in conjunction with a university to this problem that is pretty low effort to implement, but very few professors can be bothered to even try it out (the apathy and red tape is unreal). Honestly, it has been disheartening that distribution is so tough, as the results have been great for those who are using it.
I used these in a distributed sync in about 2013-2014. When Postgres got JSON support we ended up going centralized for that product and a simple logic clock was all we needed. Nevertheless, I still think they’re very cool.