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Apple Acquires Machine Learning Startup Tuplejump

Thursday September 22, 2016 11:41 am PDT by Juli Clover

Apple recently acquired its third machine learning company since 2015, purchasing India-based company Tuplejump, reports TechCrunch. Tuplejump focused on simplifying data management techniques and creating tools to make it easy to deal with large quantities of data. From an archive of the now-defunct Tuplejump website:

A few years ago people realised that the volume of data that businesses generate was becoming unwieldy. A new set of technologies to handle this huge amounts of data cropped up. We were one of the early adopters of these 'big-data' technologies. Having helped Fortune 500 companies adopt these technologies we quickly realised how complicated they were and how much simpler they could get.

Thus started our quest to simplify data management technologies and make them extremely simple to use. We are building technology that is simple to use, scalable and will allow people to ask difficult questions on huge datasets.

According to TechCrunch, Apple purchased Tuplejump for its "FiloDB" open source project designed to use machine learning concepts and analytics on massive amounts of data in realtime. It appears FiloDB will continue on as an open source project.

Apple confirmed the acquisition of Tuplejump with its standard statement: "Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans."

Other recent machine learning acquisitions include Perceptio and Turi. Apple is employing machine learning techniques across its operating system, using the technology for features like object and facial recognition in Photos, the new "Portrait" mode in the iPhone 7 Plus, major Siri improvements, and more.

Tags: Apple acquisition, Tuplejump

Top Rated Comments

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miniroll32

28 months ago

Rabbit + blue fur.

It's legit. Apple and IBM are building a petting zoo.

Rating: 8 Votes

lincolntran

28 months ago

Anyone see the title and the logo and immediately pronounced Turtlejump in their heads?

Rating: 3 Votes

GeneralChang

28 months ago

That company name and logo are the best thing I've seen today.

Rating: 3 Votes

usarioclave

28 months ago

Does anyone else see a MASSIVE contradiction here?

It's a contradiction because you don't understand what's happening.

Rating: 3 Votes

centauratlas

28 months ago

It is odd that Apple would '...Apple purchased Tuplejump for its "FiloDB" open source project ('https://github.com/filodb/FiloDB') ...'.

I suspect it has more to do with other things, perhaps their expertise in using said project and research in advances with it as if they only wanted the open source project, they could just git clone it from github. The people and knowledge there are no doubt key.

Rating: 3 Votes

RDeckard

28 months ago

So, in essence, Apple, the company that says that it doesn't collect user data and values user privacy, have bought a company that specialises in processing large amounts of user data in real time.

Does anyone else see a MASSIVE contradiction here?

Do you really think that machine learning can ONLY be used for marketing purposes? Here are some other uses, beyond marketing:

* Prediction of equipment failures (Apple makes more than a couple of phones and computers each year)
* New pricing models (they sell a few [million] products each year. All over the world.)
* Network intrusion detection (they operate a decent-sized data center operation)
* Pattern and image recognition (I think there are kind of a lot of pictures being taken by iPhones)
* Fraud detection (they kinda sell a lot of stuff. At stores. And on App Stores. And iTunes.)
* Email & message spam filtering (Mail. iMessage.)
* Text-based sentiment analysis (FYI, some people actually say things about Apple. Online.)

So, no. I don't see a MASSIVE contradiction.

Rating: 2 Votes

Worf

28 months ago

Apple already broke down how they use differential privacy. If they apply that same concept here, then I see no problem. I quite like the idea that it's possible to analyze data at an aggregate level and respect privacy without needing to target individuals.

Rating: 2 Votes