do you live in Phoenix?

I just asked Siri a few weather questions and named the city where I live, nailed it. My favorite digital device is my Apple Watch and if Siri improves over the next hear or two, that will be great for me.

I live in Phoenix. I would like it to tell me: 8am. Not what the actual high is today.

Thanks apfel looks useful! I have been experimenting with Apple's foundation models for almost a year and they are useful for embedded applications. I have been taking a deeper dive into local agentic coding tools (starting with 'little-coder --model ollama/gemma4:12b-it-qat') and I put together a tiny free book with some setup advice that might save people a few minutes of setup time: https://leanpub.com/read/local-coding-agents

I have been fairly much pissed off at the "hype in hyperscaler" AI growth (data center environmental and other societal costs) and I support anything we can do to promote local and private AI.

Sorry to be off topic, but I have a question: has anyone installed the latest beta iOS and macOS, and if so what is the current status of Gemini integration?

once you update to the latest iOS, there's an option to join the waitlist. No indication of timing, but until that moves forward Siri is what you get today, as far as I can tell.

I agree that many AI businesses will go bust and they deserve it, but the tech is good.

I can recommend my own layered approach, using the lowest capability models that get stuff done:

1. I maximally use local models like gemma4:26b-a4b-it-qat for everything that works with this free option.

2. I like paying for inexpensive APIs for mid-tier models like deepseek v4 flash, gcp-5-mini, gemini-2-flash for things that option 1. fails at. This option is almost free.

3. Pay for more expensive APIs like deepseek v4 pro, gemini 3.5 flash, etc. This option is not too expensive.

4. If all else fails on a class of tasks, then pay for awesomeness of Claude Opus. $$ expensive, I try not to use unless absolutely necessary.

I think developers and companies that just cram everything into Claude Opus are unprofessional.

I think you are conflating LLMs with AI.

LLMs we all agreed were amazing back in 2023-2024.

What's happening now with AI is more of a corporate phenomenon quite removed from the actual tech.

Yes LLMs are useful, but replacing customer support with an LLM that gives user accounts away, or calling LLMs on a loop where the bottleneck is your checkbook and calling it AGI, those are phenomenons that are separate from LLMs.

We agree more than you may believe. I have worked in the field of AI since the early 80s, symbolic AI, simpler neural networks. I only believe in using any tech if it serves human needs, is privacy preserving, etc.

If you pay for Gemini, then it is good. I recently used Gemini Ultra for a month and the gemini models are very good (and of course, you get a lot of Claude Opus tokens to use through the same plan).

I also pay for Proton's Lumo+ private chat and for what it is it is also good.

The free plans from all the providers are bad, which is fare enough.

I use Apple devices and I expect to be paying for Gemini tokens after the integration.

I have been using their on define AFM models for a year - for small models they are good. Their Secure Enclave server bases AFM model is good, but not in the same class as gemini 3.5 flash or deep seek v4 flash.

I don't think so. They will be running on their servers, or running in the future on Google's servers with privacy guarantees.

Do you think Google doesn't protect privacy for large paying customers?

For years I have enjoyed using Google products that I pay for, and they are clear about privacy guarantees.

I have loved using AI technology for 45 years (symbolic AI, old fashioned NNs, … to the present). I am also skeptical about the apparently desperation-driven ‘bet the farm’ approach we are taking here in the USA.

Slow is Fast.

I had odd Gemma 4 12B results: it was ‘almost excellent’ for writing code in a variety of languages if I was using a detailed one-shot prompt describing new code to write.

I had horrible luck with Gemma 4 12B with a variety of coding harnesses - but as usual Qwen 3.5 9B did OK.

EDIT: CORRECTION: I pulled a fresh copy of Gemma 4 12B and inference code and the tool use problems in my test harnesses are fixed. Gemma 4 12B is slow on my 16B MacBook Air, put produces OK results.

I tend to move back and forth between Common Lisp and Racket - so many good things from both communities and tech.