[FRIAM] more fun with AI

[Roger Critchlow]

I watched the livestream from the TensorFlow Dev Summit in Mountainview
yesterday.  The individual talks are already packaged up as individual
videos at
https://events.withgoogle.com/tensorflow-dev-summit/videos-and-agenda/#content,
but watching the livestream with the enforced moments of deadtime filled
with vaguely familiar music (was that Phillip Glass, or a network trained
on him?) was very instructive.

TensorFlow is a data graph language where the data is all Tensors, ie
vectors, matrices, and higher dimensional globs of numbers.  Google open
sourced it as python scripts and a C++ kernel about a year ago, updated
with minor releases monthly, and released 1.0 yesterday.   It's been used
all over the place at Google, it's the top machine learning repo at github,
and its products have made the cover of Nature twice or three times in the
past year.

New stuff yesterday:

   - an LLVM compiler to native x86, arm, nvidia, etc.,
   - new language front ends,
   - pre-built networks and network components
   - classical ML techniques in case deep learning networks aren't your
   thing
   - distributed model training on pcs, servers, and GPUs
   - a server architecture for delivering inferences at defined latency
   - embedded inference stacks for Android, iOS, and Raspberry Pi
   - a very sweet visualizer, TensorBoard, for network architectures,
   parameters, and classified sets
   - higher level APIs
   - and networks trained to find network architectures for new classes of
   problems

You can get a lot of this by just watching the keynote, even just the first
10 minutes of the keynote.

Whether you buy the KoolAid or not, it's an impressive demonstration of the
quantity and quality of KoolAid that the Google mind can produce when it
decides that it needs KoolAid.

An LSTM is a Long Short-Term Memory node, a basic building block of the
networks that translate languages or process other variable length symbol
strings.

-- rec --
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