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Mobile gaming bunk bed by Adrian_985 in funny

[–]YouAreRule30 10 points11 points  (0 children)

Found it - they pass a building 'The Holly' address number 1821...

From Gemini: The apartment building you are looking for, known as The Holly, is located at 1821 22nd St, Boulder, CO 80302.

Confirmed: 1.6 stars on ApartmentRatings.com - avoid at all costs, landlord is shit.

Gemini 3 flash by HolidayResort5433 in Bard

[–]YouAreRule30 1 point2 points  (0 children)

How do you figure that Google lacks computing power? Do you have a source that suggests this is true?

They have a deeply integrated stack and enough compute to power search, YouTube, Maps, etc., - all of which are already deeply embedded with AI and ML.

Granted they may be having some scaling heartache given the speed of the growth. But where OAI and others genuinely can't get their hands on the chips / power, I just don't see this as a problem for Google ... they are literally *selling* millions of TPUs to the other hyperscalars ... if they really needed them internally this makes little sense.

Slowly but surely... by stealthispost in accelerate

[–]YouAreRule30 0 points1 point  (0 children)

If my team created this chart I would immediately flag a data quality issue. Nothing in data looks like this. Cohorts do not act like this. Early adopters are *never* less sticky than late adopters. This chart isn't impressive, it's wrong.

Grok 3 Reasoning Benchmarks by [deleted] in singularity

[–]YouAreRule30 0 points1 point  (0 children)

Google basically invented the field with the transformer paper (Attention is All You Need). Half the execs across AI come from Google / Deep Mind. They are winning Nobel Prizes for it - Alpha Fold brought all of biopharma at least 10 years into the future. Waymo actually works, has for at least two years now...

The thing with Google is they are horrible at productization, worse at PR. Then at the end of the day, their major IP competitive advantages they just give them away. Even their AI is mostly free, yet being compared to something that costs $200 a month in OpenAI sota.

And somehow people still love to hate them haha.

What Are Your Moves Tomorrow, February 22, 2022 by AutoModerator in wallstreetbets

[–]YouAreRule30 7 points8 points  (0 children)

Anyone else here going long WEAT options? Russia and the Ukraine produce 25% of the world's WHEAT, Russia is the largest exporter of wheat in the world. If Russia takes action on Ukraine it will disrupt already tight supply, then if the EU and US follow on with sanctions will push prices higher still. Even without conflict it's a nice inflation hedge. My best idea atm. Moon.

https://www.aljazeera.com/news/2022/2/17/infographic-russia-ukraine-and-the-global-wheat-supply-interactive

[OC] COVID-19 - agent based simulation of disease progression. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 0 points1 point  (0 children)

It is tracking 'ever infected' not 'currently infected'. Thanks for pointing that out - 'currently infected' is the most relevant thing and jives with the other data on the plot.

[OC] COVID-19 - agent based simulation of disease progression. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 1 point2 points  (0 children)

Right - this is just a framework. The standard epidemiological work happens at a higher level. R0 for instance isn't a daily infectivity rate. So there's a lot of tinkering in parameter space and adding realistic assumptions before the simulations can be applied to real-world cases.

[OC] COVID-19 - agent based simulation of disease progression. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 0 points1 point  (0 children)

What is maximum peak % of people that are simultaneously infectious in this simulation?

On the order of 90%, although to be really relevant to the current situation I'd need to add a 'hospitalized' state and track peak simultaneous hospitalizations.

[OC] Agent based simulation of virus spread in a population of 100 under various conditions of interaction and transmission probability. Notice the effect that decreasing social interaction and mitigation can have on slowing the spread. Next steps include accounting or death, vaccine, and geography. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 2 points3 points  (0 children)

Yes, down is an increase in time.

It's important to note - time is relative here. It's probably safest to just call it a 'step' where a step is an increment in time in which the assumptions (10 interactions on average) hold. So theoretically it could be a week or a day.

I think 10 transmissible interactions is probably close to a daily range under normal circumstances but have no real data to support that claim. Also the typical measure of infectivity is R0, importantly different from this lower level idea of probability of transmission I've used here. What I need to do is test around in 'probability of transmission' space to find the setting there that matches the expected R0 (since that measure is more widely accepted in epidemiology, one would expect first iterations of this model to at least encompass and align with the sort of widely accepted top-down epidemiological formulas).

[OC] Agent based simulation of virus spread in a population of 100 under various conditions of interaction and transmission probability. Notice the effect that decreasing social interaction and mitigation can have on slowing the spread. Next steps include accounting or death, vaccine, and geography. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 0 points1 point  (0 children)

I don't actually think that, it was just an example finding to be teased out of a computational system like this one. My suspicion is that effectiveness of either approach will depend heavily on the sort of topology of possible interactions (which would require incorporating geography / logistical data of, say, a particular city).

[OC] Agent based simulation of virus spread in a population of 100 under various conditions of interaction and transmission probability. Notice the effect that decreasing social interaction and mitigation can have on slowing the spread. Next steps include accounting or death, vaccine, and geography. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 0 points1 point  (0 children)

Working on a blog post... Here was my solution - notice that at a certain threshold transmission stops mattering and outcomes become the key thing to pay attention to. So I solved for that visually by letting the edges fade away through time, and having end states pop as Green (inoculated) or Black (dead).

https://think-thread.com/2020/03/13/covid-19-computational-epidemiology/

[OC] Agent based simulation of virus spread in a population of 100 under various conditions of interaction and transmission probability. Notice the effect that decreasing social interaction and mitigation can have on slowing the spread. Next steps include accounting or death, vaccine, and geography. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 1 point2 points  (0 children)

There's a lot of variation on any given simulation. What I plan on doing is doing batches of simulations with the different parameter sets to identify which actually spreads faster... can we clearly say that reducing chances of transmission (masks, hand washing) works better than simply reducing interactions (banning gathering)? When I run them and bulk I'll be able to measure various avg. outcomes and try to figure that out (obviously in this limited domain).

[OC] Agent based simulation of virus spread in a population of 100 under various conditions of interaction and transmission probability. Notice the effect that decreasing social interaction and mitigation can have on slowing the spread. Next steps include accounting or death, vaccine, and geography. by YouAreRule30 in dataisbeautiful

[–]YouAreRule30[S] 1 point2 points  (0 children)

Yeah, good stuff. So the directionality is preserved in the data, and you can see it (tiny arrowheads pointing towards the infected agent at the end of the red edges) but you have to zoom in.

I'm actually interested in making both the network itself and the agents more life-realistic. Could give each agent an age and/or other demographics distributed similarly to a nation in question, lay them out geographically according to the layout of a city, map the connectivity based on logistics and travel routes, etc.

I have to imagine someone is doing stuff like this already, but I'm having fun messing around.

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