:

Why a Job at Hulu is Better than Netflix -

Sunday, July 16, 2017

Narrative Science Why You Want to Work Here– Can the Computer Write Stories Better Than You? -

Friday, July 14, 2017

Tesla – Why you want to work at Tesla The Future of Cars – 1000 Jobs Available -

Monday, July 10, 2017

Why You Want to Work at Tableau – They Help People Actually Understand Their Data -

Friday, July 7, 2017

How fast is this Blockchain thing going to take over? -

Wednesday, July 5, 2017

Assignment Editor for NBC TV in San Jose -

Tuesday, June 13, 2017

Why You Want to Work at Soundcloud -

Wednesday, May 17, 2017

Why You Want to Work at Moogsoft -

Wednesday, May 10, 2017

Motion Graphics Designer – Making CrossFit Come Alive – Scotts Valley Californina -

Tuesday, May 9, 2017

Nielsen Why You Want to Work at this Digital Transformation Organization -

Wednesday, May 3, 2017

Why a Magic Leap Job Could be for You -

Wednesday, April 26, 2017

Yext Why You Should Work There – Scaling Local Information Globally -

Wednesday, April 19, 2017

What can BlockAI and blockchain technology do for you? -

Wednesday, March 29, 2017

Doob 3D Could Replace the Photo Industry with Real-Life Sculptures -

Wednesday, March 29, 2017

Palantir, The Most Secret Company Ever:
Why You Should Work There
-

Tuesday, March 21, 2017

Nvidia Makes AI computing possible in Cameras
Why You Should Work There
-

Wednesday, March 15, 2017

Is 360 Video the Future of Media? -

Wednesday, January 18, 2017

How is VNTANA Creating Social Augmented Reality with Hologram Technology? -

Wednesday, January 11, 2017

What Will Making a VR Game While in Virtual Reality be like? -

Wednesday, January 4, 2017

UltraHaptics – Control Everything with Just the Wave of a Hand -

Thursday, December 22, 2016

Making Job Search Easier by Finding the Great Companies First

Find a
JOB
Title/Keywords Company Name
City, state or zip (optional)
 

Diffbot – Machine learning is the new Big Data and Giving it away might be a Money Maker.

Machine learning is the new Big Data and Giving it away might be a Money Maker.

“Everything’s becoming intelligent, but the limiting factor of intelligence is access to structured data,” Tung says.

Diffbot, an artificial intelligence company that helps clients extract and combine data from multiple Web sources wants to scrape all the data on the web (all of it) to put it into a structured format. Making it useful for all sorts of business purposes and make money doing so.  The company says its technology “uses computer vision and NLP algorithms to extract and structure any web page into the world’s largest structured database… with no human curation or oversight.”

Founded in 2009 The Palo Alto, CA-based startup announced today it raised $10 million from investors to expand its “knowledge-as-a-service” offerings to businesses and consumer apps.  They have raised close to $13 million since its seed round in 2012.  Diffbot’s plan is to catalog trillions of facts across the Web—many of them drawn from page elements such as comment forums, which can’t be mined by traditional search engines.

Web-mining can be a competitive advantage for apps as well as the proliferating devices of the Internet of Things, Tung says.

The startup says it has made a significant start on that goal, having indexed 1.2 billion entities such as people, products, and places since the middle of last year. Its Global Index also encompasses 10 to 20 times that number of facts, says Diffbot founder and CEO Mike Tung. Last June, the company said its database had surpassed the size of Google’s Knowledge Graph.

Diffbot does more than search what people are saying on their Twitter and Facebook feeds. It looks at comment threads in Reddit and customer support forums, basically everywhere on the web.  By structuring all that wildly unstructured data, Diffbot makes it searchable and thus useful.  Small companies can get started for free. Big companies pay based on the volume of data they need to access.

The startup’s key early innovation was to extend the search function into previously uncharted territory by teaching computers how to recognize the various sub-sections of Web pages, including headlines, ad boxes, pictures, and discussion threads.  Diffbot could then classify each page by type, such as news articles and product pages. That knowledge allows the computers to find and assemble related information, such as product prices across various retailers, and consumer opinions across many social media platforms and comment sections. The technology creates “structured data” that machines can read and interpret, so says Diffbot.

Diffbot has been scaling up its data center, adding to its bank of proprietary servers with specialized hardware, and integrating Web-based processing power into the system to meet surges of demand. The company’s new money will accelerate the scale-up and fund an expansion of its R&D team, Tung says.  Diffbot works in any language, Tung says. “It can tell you who the speakers are, and what they’re saying,” he says. The company’s technology is “sufficiently powerful to reduce information asymmetry.”

“We’ve proven it’s possible to build a profitable AI business model,” Tung says.

With more than 250 customers—including Amazon, CBS Interactive, eBay, Microsoft, Salesforce —Diffbot became profitable at the end of 2015, Tung says.  The research groups at Google and Facebook are Diffbot’s closest rivals in the development of methods to gather and synthesize Web data using artificial intelligence technology, Tung says. But rather than keeping the knowledge in-house, Diffbot is making it available to outside companies.

“We’re sort of like Switzerland in the AI wars,” Tung says.

It’s worth noting far larger companies are struggling to find a good business model for AI or  cognitive computing or whatever the next name for this self-teaching technology will be. Tung says their operating expenses are low because Diffbot’s automated data collection and analysis technology requires no human curation, he says.

The second goal for Diffbot’s $10 million Series A financing round was to make alliances with investors experienced in artificial intelligence, Tung says. The round was led by Tencent, China’s leading Internet service provider, and Felicis Ventures. Tencent is not a customer of Diffbot’s, Tung says. He adds the word “now.”

Other startups are pursuing a similar AI-as-a-service model, recognizing that while the Internet giants have the resources to push the envelope in things like computer vision and natural language understanding, lots of companies can benefit from these technologies.

Believe it or not Diffbot still has a tiny staff of 14 people.

Print Friendly
Comments
One Response to “Diffbot – Machine learning is the new Big Data and Giving it away might be a Money Maker.”
Trackbacks
Check out what others are saying...
  1. […] Diffbot – Machine learning is the new Big Data and Giving it away might be a Money Maker. – […]



Leave A Comment

You must be logged in to post a comment.