What's the point of this? Will it make you rich?
An Introduction to Probabilistic Programming
21–30 of 43 posts
Re: An Introduction to Probabilistic Programming
#22Has probabilistic programming been shown to solve problems better than machine learning or deep learning approaches? I remember it being pretty hyped 5-6 years ago …
Not an either-or situation. Many ML algorithms can be formulated in a probabilistic way, and PPLs can represent them. But the choice of the underlying inferential algorithm (MCMC, variational, etc) greatly affects the scale and type of solvable problems, so it's not just the language itself.
PPLs using MCMC (e.g., Stan and pymc) are first-choice tools for Bayesian inference on small to medium data analysis, which is lots more common than Google-scale data analysis.
Re: An Introduction to Probabilistic Programming
#23Has probabilistic programming been shown to solve problems better than machine learning or deep learning approaches? I remember it being pretty hyped 5-6 years ago …
My professor in school years ago was working on probabilistic hardware and showing pretty good thermal benefits. It’s a drastically different way to build software so I don’t know how commercially viable it’ll become until someone shows it has a drastically better power per watt ratio (like 1000x or 10000x, maybe higher to account for the cost of transitioning existing software)
Re: An Introduction to Probabilistic Programming
#24Has probabilistic programming been shown to solve problems better than machine learning or deep learning approaches? I remember it being pretty hyped 5-6 years ago …
My professor in school years ago was working on probabilistic hardware and showing pretty good thermal benefits. It’s a drastically different way to build software so I don’t know how commercially viable it’ll become until someone shows it has a drastically better power per watt ratio (like 1000x or 10000x, maybe higher to account for the cost of transitioning existing software)
I'd be interested in learning more about that if you could share a name of the professor or project?
Re: An Introduction to Probabilistic Programming
#25Earlier quoted context omitted.
My professor in school years ago was working on probabilistic hardware and showing pretty good thermal benefits. It’s a drastically different way to build software so I don’t know how commercially viable it’ll become until someone shows it has a drastically better power per watt ratio (like 1000x or 10000x, maybe higher to account for the cost of transitioning existing software)
I'd be interested in learning more about that if you could share a name of the professor or project?
Dr Todd L. Veldhuizen. I looked through his research and don’t see anything there so either I’m misremembering or the research hadn’t gone anywhere (or still incomplete).
Re: An Introduction to Probabilistic Programming
#26Can someone please give an example of how this could be used in practice?
On the surface probability seems antithetical to the explicit well-defined determinism of programming.
Re: An Introduction to Probabilistic Programming
#27What's the point of this? Will it make you rich?
it can be used to build better statistical modelling and computational tools that might, in the future, enable scientists and researchers to more efficiently or effectively figure out statistical or causal relationships -- and in some niche applications, e.g. in pharma or finance or insurance or advertising, that information might be valuable and help some people get rich. but the people able to capture the most value from those developments are unlikely to be the researchers or the people building the software tools.
Re: An Introduction to Probabilistic Programming
#28Can someone please give an example of how this could be used in practice? On the surface probability seems antithetical to the explicit well-defined determinism of programming.
I wouldn’t classify floating point computation as deterministic
Re: An Introduction to Probabilistic Programming
#29Can someone please give an example of how this could be used in practice? On the surface probability seems antithetical to the explicit well-defined determinism of programming.
It’s super interesting for combining scientific models with modern statistical computation in a flexible way
Also, randomized algorithms for all kinds of things are very useful in general-purpose computing
Re: An Introduction to Probabilistic Programming
#30Can someone please give an example of how this could be used in practice? On the surface probability seems antithetical to the explicit well-defined determinism of programming.
Rather than focus on the non deterministic random sampling, frame it as a programming language or library for manipulating and fitting statistical distributions.
An HTTP library is good for making web calls. A probabilistic program is good for estimating probabilities.
One example would be polling. You could write down a program that estimates votes from political polls. Then feed it polling data and get estimates of how people will vote.