I approve this message! :-) Nicely done, Matt
Cheers, David On Mon, Jan 11, 2016 at 12:52 PM, Matthew Taylor <[email protected]> wrote: > Spacial == "space" > Temporal == "time" > > Our reality plays out in "spacetime", meaning each frozen moment in time > contains a spatial representation, and each moment is a part of a sequence > of moments that constantly changes. > > If you had a data stream of one scalar value over time, like temperature > for example, this would be considered a highly temporal pattern because > there is only 1 spatial dimension. Just one value changing over time. > Adding more fields of data to this temporal stream adds spatial dimensions. > > A temporal stream with highly spatial data within it would be an aircraft > moving through space. Each point in the flight could have hundreds of data > points associated with it (lat, lon, altitude, engine temp, airspeed, > pitch, yaw, heading, etc.). I would consider this data stream to be both > temporal and spatial in nature. > > HTM can identify spatial patterns in temporal data streams. Many other ML > technologies can identify spatial patterns in one "moment" in time, like a > photograph (classifying objects). > > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > On Mon, Jan 11, 2016 at 6:29 AM, Jeff Fohl <[email protected]> wrote: > >> Wakan - >> >> I think you are getting there. In regard to your questions: >> >> 1. Spatial concepts are building blocks for temporal ones? - Yes, >> essentially. One way of describing it is that "spatial" refers to "things" >> and "temporal" refers to "things over time". So, your "thing" could be a >> musical note, a word, or even an abstract concept. A temporal series is >> simply these things put into a series. >> 2. Yes, you could have data that is non-temporal, but it wouldn't be >> of much use to NuPIC. You could also have data that is just time (say, a >> bunch of timestamps), but that wouldn't be of much use either. >> 3. Yes, encoders (within the context of HTM) will produce a spatial >> representation of something, which then can be fed into an HTM model. >> >> I sense that you are getting hung up on the word "spatial". This is not a >> NuPIC jargon word. It is more of a mathematics jargon word. Think about how >> you might describe a physical object in "space", mathematically. For a >> cube, you might describe its volume as X^3, where X is the length of a >> side. Nowhere are you mentioning time, or how the cube might change over >> time. In this situation, all you are concerned with is with describing its >> static, non-temporal characteristics. Thus, you are describing its >> "spatial" qualities. If you were to start describing the cube's position >> over time as it moves through space (say, after you give it a push), then >> you would be talking about its temporal characteristics. >> >> I hope that helps. >> >> - Jeff >> >> On Sun, Jan 10, 2016 at 1:18 PM Wakan Tanka <[email protected]> wrote: >> >>> Thank you Jeff, >>> this is clear example. May I ask regarding Matt's tutorials on youtube: >>> 1. sine waves >>> 2. hotgym prediction >>> 3. audio stream analysis >>> 4. geospatial tracking >>> 5. traffic anomalies >>> >>> what is spatial/temporal in those cases? I guess: >>> 1. >>> - temporal - the sines periods >>> - spatial - building blocks of those period >>> >>> 2. >>> - temporal - patterns representing day, week, year (those that you can >>> see repeating when you look at plot). >>> - spatial - building blocks of temporal >>> >>> 3. >>> - temporal - sequence of spatial >>> - spatial - depends on encoder (you might or not consider of changing >>> e.g. volume or instruments in audio I do not know what all was Matt >>> considering) >>> >>> 4. >>> - spatial - vectors >>> - temporal - everything that is composed of vectors >>> >>> 5. >>> - spatial - ??? >>> - temporal - ??? >>> >>> >>> Is this assumptions correct: >>> 1. From your post I've understood that spatial are building blocks for >>> temporal? >>> >>> 2. I guess that it is possible to have data where you have just spatial >>> data but not temporal (when you play chords at random), but not vice >>> versa? >>> >>> 3. Spatial is heavily depended on encoder and temporal are just logical >>> consequence? >>> >>> >>> Thank you >>> >>> >>> >>> On 01/10/2016 09:26 PM, Jeff Fohl wrote: >>> > Wakan - >>> > >>> > Perhaps a music analogy would be useful. >>> > >>> > Say you are playing a series of chords on a piano. >>> > >>> > Some of the chords are similar, some are not. Think of each chord as a >>> > pattern. This is a "spatial" pattern. The term "spatial" perhaps is >>> > confusing because one tends to think of physical space when hearing >>> that >>> > term. >>> > >>> > "Temporal" refers to patterns over time. So, the sequence of the chords >>> > is a "temporal" pattern. >>> > >>> > Does that help? >>> > >>> > - Jeff >>> > >>> > On Sun, Jan 10, 2016 at 12:16 PM Wakan Tanka <[email protected] >>> > <mailto:[email protected]>> wrote: >>> > >>> > Thanks David, >>> > To be honest it did not help much :-( some example would be fine. >>> > Thank you >>> > >>> > >>> > On January 10, 2016 8:28:41 PM CET, David Ray >>> > <[email protected] <mailto:[email protected]>> >>> wrote: >>> > >>> > Hi Wakan, >>> > >>> > This definition may be useful: >>> > >>> > Spatial = the relative "nearness" of two data points in terms >>> of >>> > their semantic (characteristics of "meaning") attributes. >>> > >>> > Temporal (more accurately; Sequential) = refers to patterns in >>> > "encounter order" pertaining to discrete units of input. >>> > >>> > Was that helpful? >>> > >>> > Cheers, >>> > David >>> > >>> > Sent from my iPhone >>> > >>> > On Jan 10, 2016, at 6:36 AM, Wakan Tanka <[email protected] >>> > <mailto:[email protected]>> wrote: >>> > >>> >> Hello Matt, >>> >> Can you please clarify differences between temporal and >>> >> spatial data? I've never really get into. Thank you very much. >>> >> >>> >> On January 7, 2016 6:32:37 PM CET, Matthew Taylor >>> >> <[email protected] <mailto:[email protected]>> wrote: >>> >> >>> >> Divyang, >>> >> >>> >> NuPIC can run on OS X and Linux (we test on Ubuntu), and >>> >> Windows (if you have your compilers installed properly, >>> >> see the READMEs). >>> >> >>> >> If by "local and global" anomalies, you mean discrepancies >>> >> in short-term patterns vs long-term patterns, then yes. >>> >> For example, a change in hourly patterns would be just as >>> >> anomalous as a change in daily patterns. >>> >> >>> >> Real-time or batch is supported, but the data should be >>> >> temporal in nature, not entirely spatial. >>> >> >>> >> --------- >>> >> Matt Taylor >>> >> OS Community Flag-Bearer >>> >> Numenta >>> >> >>> >> On Thu, Jan 7, 2016 at 12:14 AM, Divyang Shah via nupic >>> >> <[email protected] <mailto:[email protected] >>> >> >>> >> wrote: >>> >> >>> >> >>> >> >>> >> ---------- Forwarded message ---------- >>> >> From: Divyang Shah <[email protected] >>> >> <mailto:[email protected]>> >>> >> To: "[email protected] >>> >> <mailto:[email protected]>" >>> >> <[email protected] <mailto: >>> [email protected]>> >>> >> Cc: >>> >> Date: Thu, 7 Jan 2016 08:08:15 +0000 (UTC) >>> >> Subject: some information for nupic anomaly detection >>> >> hi, >>> >> >>> >> what are the different os and other configuration >>> >> support require for this project of anomaly detection? >>> >> do you detect both local & global anomaly? >>> >> it supports only for real-time data or also support >>> >> anomaly detection for batch data? >>> >> >>> >> Thanks, >>> >> Divyang Shah >>> >> >>> >> >>> >> >>> >> -- >>> >> Sent from my Android device with K-9 Mail. Please excuse my >>> >> brevity. >>> > >>> > >>> > -- >>> > Sent from my Android device with K-9 Mail. Please excuse my >>> brevity. >>> > >>> >>> >>> > -- *With kind regards,* David Ray Java Solutions Architect *Cortical.io <http://cortical.io/>* Sponsor of: HTM.java <https://github.com/numenta/htm.java> [email protected] http://cortical.io
