woodson

For reference: https://i.imgur.com/1EilY.gif

There’s a copy of it in China: https://en.wikipedia.org/wiki/Hallstatt_(China)

(It’s good to have backups, right?)

This is great, as is the CasioGShockSmartSync Android app. I wish there was an iOS app, as the official app is horrible, only works after signing up for an account, and only works if given every tracking permission possible to vacuum the maximum amount of data to the cloud.

To be fair, the hobbyist hardware mod variants that do step tracking only last for days, not years AFAIK.

Yes, it seems to be a repackaging of the ABL-100WE and has a long battery life. Unfortunately, their app is horrible, only works after signing up for an account, and only works if given every tracking permission possible to vacuum the maximum amount of data to the cloud.

If all you're looking for is a step counter in your watch, check out Casio ABL100WE. The battery lasts for two years (CR2016).

They did. Check out the Phi models (e.g., https://huggingface.co/microsoft/phi-4).

Try option-click on the green icon in the app window. It’s well hidden and unintuitive, but I think it does what you want.

For a long time, AI was a bad word that stood for unfulfilled promise. See AI Winter. Hence, researchers strictly avoided the term while still working on learning algorithms, the same that power LLM training.

There’s a bit of a grey area, for example speech recognition. Would you classify that as analytic or generative? Whisper and speech LLMs work pretty well, but can completely make up stuff that wasn’t in the audio at all (see e.g. “thank you for watching” transcribed during silence). Other approaches are closer to the acoustic evidence but may make other mistakes (especially wrongly transcribing long tail, low frequency terms). Pick your poison.

Thanks for sharing, this is a great improvement (also and especially for human use! Renders much better on mobile phones compared to Confluence).

> Alongside the poorly lit spaceship. Spaceships are workplaces and workplaces should provide adequate illumination so you can see what you are doing.

I always thought the same about CSI. Have the set designers ever been to a lab?

> 5090 ($2k MSRP but realistically $3-3.5k)

These days, more like >$4.1K (at least in the US).

Yeah, there have been several papers with attacks on Whisper:

- Inject adversarial noise to make it transcribe what you want (https://arxiv.org/abs/2210.17316)

- Stop it from transcribing (https://arxiv.org/abs/2405.06134)

- Adversarial prompt injection to make it translate instead of transcribe (https://arxiv.org/abs/2407.04482v2).

Indeed. And the one in Admont, Austria: https://stiftadmont.at/en/about-the-abbey-library/

HF is notorious for making it difficult to work offline (or at least not waste time trying to connect when everything needed is offline) and is constantly changing how it is being handled. Previously, there was TRANSFORMERS_OFFLINE, HF_DATASETS_OFFLINE, etc.

You can use devcontainers (in VSCode or separate), like this: https://github.com/entn-at/claude-rust-devcontainer/

This will limit the agent in what it can do in the system and what IPs/domains it can reach. This requires a lot of customization to your specific framework/environment. Note that this can reduce the agent’s effectiveness, as it will have to “work around” some of the limitations. This isn’t foolproof either, and the agent could exfiltrate data e.g. via DNS requests.

> But I don't see a scenario where pytorch needs network access.

Training models across multiple compute nodes? That’s a big one.

Not if one is running it in a non-privileged vm/container with restricted network access. But everything is YOLO these days.

Why generative? Or has it been decided that only generative models are “AI”?

It highly depends on the sort of data you’re processing (phone calls, podcasts, meetings of more people recorded using single channel?). For NVIDIA/NeMo, check out their softformer diarization models (also streaming).

Well, but their customers are those that buy Apple hardware.

Look into RWKV.

It’s a distinction that IMHO likely doesn’t make much difference, at least for the mostly automated/non-interactive coding agent use case. What matters more is how well the post-training on synthetic harness traces works.

There are still opportunities, but they aren’t paid nearly as well as less researchy positions in industry. US post-doc salaries at state universities aren’t that high.

You mean Moshi (https://github.com/kyutai-labs/moshi)? Since Personaplex is just a finetuned Moshi model.

…who lives in Oregon, in the US.

This is about speech to text, not speech recognition.

You still need a tax accountant in France to register the FTE and file paperwork with the tax office and social insurance.

The bank issues/refusals may have something to do with FATCA. If you have anything to do with the US in terms of taxes, many EU banks don’t want you as their customer. If it’s a subsidiary of a foreign company, then a lot of paperwork is required to prove that the foreign owners actually exist.