Jason Ball's TechBytes

You might like... Recommendation Engines

If you're reading this blog, then you might like recommendation engines. I've been continuously impressed by Amazon's recommendation engine. As I've expanded what I buy through Amazon (heart rate watches, cooking utilities, computer peripherals, etc.), Amazon has done a very good job of processing those likes -across categories- and making very intelligent suggestions that have resulted in purchases.

Apple, on the other hand, can't seem to figure out what MUSIC I like despite having bought numerous albums and even being signed up for their artist alerts... Apple constantly alerts me to new hip hop and r&b content. I bought some snoop dogg two years ago...but I'm no big hip hop fan. What about Dave Matthews? I've probably bought about 5 albums. Alerts about Dave? Zero.

I'm aware of the "gift drift" that you can get with Amazon if you buy a friend's kid a copy of The Gruffalo- for the next several months you get offered children's books non-stop (I've actually never had a problem with Amazon's recommendation engine).

Looking forward to the mobile internet, recommendation engines- or agents- are going to become even more relevant- who's around you, what they are listening to, and why you might like it, that your favorite store (based on transaction history) has your favorite stuff on sale and the bus is 12 minutes away... etc.

Apple is smart (understatement), but the problems they have with recommending good music underscores the challenges facing recommendation engines.

If this is something that you're particularly interested in, O'Reilly has published a great book on the topic:Programming Collective Intelligence.

Highly recommended reading.

The Next Web

Good post over at Genuine VC yesterday covering the History of the Web:

...a transition among three distinct phases of consumers’ primary activity online from receiving, to hunting, and now doing...

Receiving, Hunting, Doing is a good indication of what we've seen so far- and I think we're going full circle to "Receiving" again- only this time from intelligent sources.

Two examples are Kwiry or Tripit. With Tripit, you email them your travel itneratry and they scour the web in the background and send you a nice package of maps, directions, thoughtful suggestions, etc. I've posted many times about "intelligence inside" which lives in the same neighborhood as the Semantic Web:

...I also think there's a huge opportunity to get to data sooner via the sensor revolution. When phones report location, when phones listen to ambient sound, when credit cards report spending patterns, when cars report their miles traveled, when we're increasingly turning every device into a sensor for the global brain, there will be more and more sources of data to be mined...

All of which means the process is reversing: doing by machines, hunting by spiders and receiving by users- remix and repeat.

Intelligence Inside

I'm always on the look out for smart new apps that save me time.

Feeds2.0 is one of my stand-bys for RSS readers. It ranks incoming articles based on your previous reading patterns and tends to border on clairvoyance. Pretty amazing stuff.

That said, I'm up for trying new services. A few new ones I've come across this week are:
aiderss
feedhub
pipes
silobreaker (thanks Rob)

All of them are slightly different, but very useful. I'm trying out feedhub sent through Google Reader. We'll see if their results can top Feeds 2.0. Pipes is just so hackable, it begs to be loved and silobreaker is a news-junkie's best friend. Enjoy.

Open Source Artificial Intelligence

Numenta made their software available (for educational use) earlier this month. In case you haven't heard of these guys, their platform for intelligent computing (NuPIC)

...implements a hierarchical temporal memory system (HTM) patterned after the human neocortex. [They] expect NuPIC to be used on problems that, generally speaking, involve identifying patterns in complex data. The ultimate applications likely will include vision systems, robotics, data mining and analysis, and failure analysis and prediction.

Numenta's platform builds intelligence from scratch- in the same way a human baby does. What is immensely powerful is that machine-based intelligence is only a download away for other machines, no learning required. I can only imagine what happens when multiple applications built on the NuPIC platform are merged into an integrated system.

I'm looking forward to working with the HTM technology. One of the areas I'm interested in looking into is seeing if Numenta's algorithm can help me discover the most relevant articles in my multitude of feeds based on my previous reading habits (a perennial favorite of mine).

Anyone else seen any interesting AI applications I should be looking at/testing?