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Funny story -- one of the first few days of the internal launch, a colleague didn't know what the feature was and clicked it on Sergey's page one night. Suddenly was face to face with Sergey at home. And he wasn't the only one, from what I remember.

They boldly claimed they'd beat Facebook in 100 days and began acquiring any startup that pretended to solve a social problem. Every team got a G+ OKR. In classic Google fashion, they chewed up the one social platform they had, Orkut, and gChat, which was filling the AIM void, also squandered its lead as it was subsumed. They never invested enough in their successful/functional video chat, and instead just had team after team launching new versions of the same damn thing. Looking through GCP and their AI/Vertex/Whatever naming soup, not much has changed.

I'd correct this to be "a smaller sized EV" versus "the smaller size of an EV" as many of the EVs on the market are surprisingly big. Without pointing to the obvious behemoth truck/SUV EVs, my Tesla MY is considerably larger than a lot of CUVs on the market and has a much worse turning radius. What it does do well is stop and start fast meaning I can be more decisive and navigate through messy NYC/BOS traffic with more confidence than in my CRV, and regen braking + having lower "idling" costs does improve its city-profile.

Out of curiosity and semi unrelated — why do so many of these projects with customized encoder-decoder setups use earlier Qwen versions like 2.5 and 3 and not the smallest 3.5? Purely the few 100m params, or something else in the latter’s arch or pretraining?

Counterpoint: you can't replace Reels/TikTok or smoking time with exercise and you _have_ to displace something meaningful to do dedicated exercise.

Phone activity time is almost irreducible because it's not dedicated or de-fragmentable by design. It's almost always concurrent with something else, or in the "in-between" periods where your alternatives are limited.

One successful strategy here is to offload exercise into "snacks" that compete for this time. And that might buy back time you spend at the gym. Strength training and mobility work where the emphasis isn't on getting your HR up can easily be squeezed in here. So you might go to the gym, do your pressing exercise in 20 minutes, then come home and do pushup press variants as your accessory work in small increments over the day.

The one area this does not work on is CV training, where you need a dedicated amount of time in target zones to get the benefit. For that, you need to treat it as a first-class obligation, find some protocol that meets your constraints, and hold it sacred to get it done.

Somehow I keep hearing the rumblings of crypto maximalists trying to merge tokens. I actually wouldn’t mind since I signed up directly with some providers I’ve stopped using and have small amounts of credits strewn across the web.

It wins on two fronts if this is true. Provides the cheap alternative for the West, and maximizes returns against their homegrown audience.

What are your thoughts on the detector --> VLM pipelines, and if there's ever a world where a small LM or LM augmented detector can be efficient enough to play a role as router. I ask because I recognize you from your handle and am very familiar with your work in the doc+detector space.

Paddle-VL and GLM-OCR do this by using PP-DocLayoutv3 as their "detector/slicer" and then just batch the OCR on the clips to do pretty darn well at a tiny size.

A lower-tech version is to use a good detector and XY-cut or just a naive Y-cut or orientation-away cut to slice up the page. But if you're doing that you're getting closer and closer to DocVLM style OCR+low res image. Been playing around with something like this using the new PPOCRv6 which itself punches well above most traditional OCRs and is multi-language without the hassle of language detection and dict-loading for rec.

It's widely hypothesized that dogs anthropomorphized themselves, so to speak, accentuating their expressive eyes and eyebrows over generations to be more human-like in how they communicate. And very few humans today view their dogs as pure working tools -- most at least say "good boy".

Does it prompt logging? For example, when I was trying to monitor my BG after diagnosis, I tried to log my meals to correlate later, but 1) would forget and 2) wouldn’t have the energy to time align the stats. So a tool that even saw changes in BG and shot me a text or message (did you eat/exercise do something @ [time]?) and used the LLM or something else to capture and enrich the metadata. Paired with boring things like med reminders (I just realized I forgot my metformin while typing this) and giving me an easy visualizer with these meta points would be useful. If I’m tracking sleep on a device etc.

As others have said, the analysis might be risky. I don’t want to trust interpretation to anyone but myself (bear my own risk) or my clinician. But just remembering to capture the data and making it easily time alignable and possible augmentable in the future would be useful.

Does Wallet allow apps to interact with the meta-data of cards, and/or update them in any way? This could be interesting for insurance cards, in particular. Upload & verify status periodically with a prompt to update, for example.

Of the examples you listed, politicians are the only ones you directly fund and supposedly work for you. Your lawyers and doctors aren’t your employees, and they also don’t work on your property (though lawyers might handle your documents). The biggest thing this points to is that the mask is almost entirely off between employee-employer relationships in the US, and it looks like by ensuring everyone depended on employment for insurance before turning this corner, there’s not much resistance left.

Depends on if you believe it will ever become cheaper. Either hardware, inspiring more efficient smaller models, or energy itself. The techno optimist believes that that is the inevitable and investable future. But on what horizon and will it get “zip drived” before then?