Top Tweets for #Codensity
@janozer @streamingmedia shares his #NABSHOW2019 Encoding and QoE Highlights: Here's What Mattered. Get his thoughts on hardware-based #encoding and decoding, including on our #Codensity T400 Video Transcoder delivering #EncodingatScale https://t.co/bHHtwMB9w9
@PttPrgrmmr @HandyHaskell newtype #Codensity f a =
Codensity {
(>>-) :: forall x. (a -> f x) -> f x
}
try writing #Functor, #Applicative, #Monad using (>>-)
Our newly-launched #Codensity T400 Video #Transcoding Solution comes pre-integrated with #FFmpeg to deliver H.264 and H.265 video encoding scalability for live streaming. Learn more in our whitepaper : https://t.co/8gnuQ5gcDt #StreamingWest
Next week we’ll be at #StreamingWest to share more details on the #transcoding requirements for live video streaming and our innovative #Codensity transcoding solution. DM us to schedule a meeting during the show. @StreamingMedia @StrMediaShows
NETINT’s @RayAdensamer will be speaking at Streaming Media West on Nov 13 at 11:30am to address the need for “Encoding at Scale for Live Video Streaming.” https://t.co/B4YTRTiOwd #StreamingWest #Codensity @StreamingMedia @StrMediaShows
absolute classic #HaskellPDF: Notions of Computation as #Monoid-s
https://t.co/K7TvxWNG5E
#Haskell, #Yoneda, #CoYoneda, #Codensity, #DList
We're excited to announce our #Codensity™ T400 Transcoder – an innovative video #encoding solution for video streaming content providers and video distribution service providers to #transcode and deliver live video streams. Learn more https://t.co/aqqZm8JqZh
#Haskell
#DList a = [a] -> [a]
#Yoneda f a = forall x. (a -> x) -> f x
#Codensity f a = forall x. (a -> f x) -> f x
@PttPrgrmmr For everyone else:
Difference lists rewrite
(xs ++ ys) ++ zs
to the faster
xs ++ (ys ++ zs)
Yoneda rewrites
fmap f . fmap g . fmap h
to the faster
fmap (f . g . h)
Codensity rewrites
(mx >> my) >> mz
to the faster
mx >> (my >> mz)
We should be able to derive #Codensity-instances
newtype Mon m a = M
{ unM :: forall xx. (a -> Exp (m xx)) -> Exp (m xx) }
deriving (.., Monad)
via (Codensity (Compose Exp m))
#DerivingVia
noticed that https://t.co/M4NldlfeCh has the same representation as
Codensity (Pipe i i o () m)
and sure enough I can #DeriveVia #Codensity
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