eDiscovery to Get a Fillip with DISCO

June 23, 2017

A legal technology company has unveiled the next generation AI platform that will reduce time, efforts and money spent by law firms and large corporations on mundane legal discovery work. Named DISCO, the program was in beta phase for two years.

PR distribution platform BusinessWire in a release titled DISCO Launches Artificial Intelligence Platform for Legal Technology quotes:

While there will be many applications for DISCO AI, initially the focus is to dramatically reduce the time, burden, and cost of identifying evidence in legal document review — a process known as eDiscovery.

Many companies have attempted to automate the process of eDiscovery, the success rates, however, have been far from encouraging. Apart from disrupting the legal industry, automated processes like the ones offered by DISCO will render many people in the industry jobless. AI creators, however, say that their intention is to speed up the process and reduce costs to organizations. But again, as technology advances, job losses are inevitable.

Vishal Ingole,  June 23, 2017

Alphabet Google: Just Jobs? Not Likely

June 21, 2017

The is “Connecting More Americans with Jobs.” Sounds good. People want to work, right? Sounds like the right idea even though the notion of universal basic income is floating around like a Loon balloon. With smart software poised to displace MBAs in some of the IPO process steps, jobs are a big deal. Here in Harrod’s Creek, there are quite a few people out of work. There are even some families in which there are two or more generations of people who have never held a full time job. But that’s not a problem.

Google states:

We’re taking the next step in the Google for Jobs initiative by putting the convenience and power of Search into the hands of job seekers. With this new experience, we aim to connect Americans to job opportunities across the U.S., so no matter who you are or what kind of job you’re looking for, you can find job postings that match your needs.

When I read about job aggregation, I thought about the numerous online job services which I have observed over the years. Does anyone remember the BNA’s love affair with job hunting services? And Monster? Love that Monster thing!

From my vantage point, there are several angles to this Google service:

First, aggregating jobs is a useful source of data about people, competitors, and hiring trends. Quick example: Decades ago I was involved in a database called Pharmaceutical News Index. The hot feature of this database was that a person in the pharmaceutical industry could look up a company and see what jobs big wheels and wizards were taking. The information had high value because hires provide direct information about certain types of research initiatives. Now imagine the value of the data of Google can scrape and crunch the job data its announcement references. Valuable information? Yep, definitely above average in my book.

Second, job aggregation is a foundation stone. The service makes it possible to take another step: Matching candidates to jobs. Hey, if you are in the Google system and you want a job, why not let Google’s smart software process your profile and generate a list of potential opportunities. Google has a mostly overlooked dossier function and the nifty analytic tools to make this a walk in the part. Employers might be interested in get information from Google about hiring trends, salaries, and Glassdoor-type insights into what a company is “really like.”

Third, Google’s smart software can knit together a number of items of information about a person or a company. This “federation” of data provides an opportunity for Google to use the Recorded Future technology or a similar home brew technology to predict what is likely to happen for sectors, companies, and even product innovations.

Should Microsoft / LinkedIn be worries?

Yep.

Stephen E Arnold, June 21, 2017

Will the Smartest Virtual Assistant Please Stand Up?

June 16, 2017

The devices are driving sales. However AI-powered virtual assistants are far from perfect. Alexa, Google Assistant, Siri, and Cortana are good for basic questions on weather, radio stations, and calendars. But when it comes to complicated questions, all fail.

MarketWatch in an article titled This Is the Smartest Virtual Assistant — and It’s NOT Siri, or Alexa says:

A number of factors will shape the market moving forward, including changes in consumers’ comfort over the security and collection of private data, the progress of natural language processing and advances in voice interface functionalities, and regulatory requirements that could alter the market.

A survey revealed that none of the virtual assistants tested was able to answer 100% of questions (let alone attempt them). Virtual assistants that attempted to answer them were not answering the questions correctly. Google was at the top of the heap while Siri was the last.

The article also points out that people want complicated questions answered rather than the simpletons that these virtual assistants answer. It seems, the days of perfect virtual assistants are still far away. Till then, Google search engine is the best bet (the survey says so)

Vishal Ingole, June 16, 2017

AI Decides to Do the Audio Index Dance

June 14, 2017

Did you ever wonder how search engines could track down the most miniscule information?  Their power resides in indices that catalog Web sites, images, and books.  Audio content is harder to index because most indices rely on static words and images.  However, Audioburst plans to change that says Venture Beat in the article, “How Audioburst Is Using AI To Index Audio Broadcasts And Make Them Easy To Find.”

Who exactly is Audioburst?

Founded in 2015, Audioburst touts itself as a “curation and search site for radio,” delivering the smarts to render talk radio in real time, index it, and make it easily accessible through search engines. It does this through “understanding” the meaning behind audio content and transcribes it using natural language processing (NLP). It can then automatically attach metadata so that search terms entered manually by users will surface relevant audio clips, which it calls “bursts.”

Audioburst recently earned $6.7 million in funding and also announced their new API.   The API allows third-party developers to Audioburst’s content library to feature audio-based feeds in their own applications, in-car entertainment systems, and other connected devices.  There is a growing demand for audio content as more people digest online information via sound bytes, use vocal searches, and make use of digital assistants.

It is easy to find “printed” information on the Internet, but finding a specific audio file is not.  Audioburst hopes to revolutionize how people find and use sound.  They should consider a partnership with Bitext because indexing audio could benefit from advanced linguistics.  Bitext’s technology would make this application more accurate.

Whitney Grace, June 14, 2017

Watson Enters Two New Fields

June 13, 2017

IBM’s Watson has been very busy, and it is no longer just generating recipes and curing cancer. A couple pieces from the company’s recent PR blitz illustrate two new hats the AI has donned: Endgadget shares, “Watson Could Be the Key to Smarter Manufacturing Robots,” while “IBM Watson Now Being Used to Catch Rogue Traders” appears at Silicon Republic. It looks like IBM is positioning Watson as the AI that can do anything.

Engadget reports that Watson is being tapped to perform quality-control for ABB, a firm that makes manufacturing robots and the software that runs them. Writer Rob LeFabvre describes:

Imagine an automotive assembly line, full of robots that build cars without any human intervention. Someone has to monitor and inspect the machinery for defects, ensuring their safe and efficient operation. ABB’s technology can gather real-time images and then get Watson to analyze them for potential problems, something a human previously needed to do.

Meanwhile, Watson now offers a tool for companies to catch rogue traders within their ranks. Reporter Colm Gorey writes:

Referred to as Watson Financial Services, the new product will become a monitoring tool within companies to search through every trader’s emails and chats, combining it with the trading data on the floor. The objective? To see if there are any correlations between suspicious conversations online and activity that could be construed as rogue trading.

While the service is being tested out on a few trading-sector companies, IBM intends to market it to the growing “RegTech” field.

IBM has pointed its famous AI in many directions, and will likely continue to work Watson into as many fields as possible. We ask, “Can she save IBM?”

Cynthia Murrell, June 13, 2017

The Watson Disease: Google and TPUs

June 9, 2017

I think IBM Watson has performed a useful service. Big Blue demonstrates that writing about future technology and its applications can send useful signals to investors, competitors, and analysts.

The Watson Disease is, to my way of thinking, a weird combination of marketing hyperbole and fanciful thinking. The outputs in the form of articles, interviews, and marketing collateral are entertaining and sometimes fun.

One example I spotted appears in “Cloud TPUs: A Chip to Make Every Business as Smart as Google.” The headline assumes that “every business” is less smart than Google. It follows that the less smart will want to be as smart or smarter than Google. It seems to me that Facebook has been zipping along quite nicely. So has Amazon. Too bad that these firms are one which the real journalists at PC Magazine include in the category of firms which want to be “as smart as Google.”

The guts of the story focus on Google’s response to the strong market uptake of Nvidia technology for assorted smart applications. AMD is working to catch up, but it seems to be cornering the bitcoin mining niche while Nvidia is capturing hearts and minds across applications.

Google wants to be the big dog with its TPU or once secret Tensor Processing Units. These confections perform magic when it comes to one trick pony machine learning functions. TPUs are specifically engineered to do artificial intelligence stuff.

The write up reports that:

Cloud Tensor Processing Units (TPUs) are part of a trend toward AI-specific processors, and for Google in particular these cloud-based TPUs are the underlying computer element driving a top-to-bottom AI rewrite fundamentally redefining how Google’s apps, infrastructure, software, and services function by building intelligence in from the ground up.

That’s quite a statement enriched with some amazing words like “in”, “from” and “up”.

The Google wizard explains that Google’s approach has been to build “a kind of drag racing car.”

When will I be able to drive this race car?

Well, there’s the promise of “soon.” Just like IBM Watson’s takeover of the smart software sector. “Soon.”

The car analogies provide a metaphorical anchor for the TPU revolution.

The exemplary use case explains that a Japanese used car dealer creates Web pages automatically.

Yep, used cars.

But there are more application opportunities. I learned:

“There are limits, it’s not magic, but it’s really exciting how many places it’s applicable and in how many businesses it makes sense,” said Hölzle [a Google wizard]. “We’re aiming to be the cloud platform for machine learning and analytics. We’re making it much more accessible to average companies because it works across so many circumstances, from AlphaGo and data center cooling optimization to image and speech recognition trained on the same neural network.”

An interesting nugget finds its way into the sci-fi vision. I highlighted this statement:

Once you have a machine learning project, 10 percent of time is spent on ML and 90 percent is on data preparation, cleaning, interpreting results, and iterating to find better models,” said Hölzle. “We have something in Cloud ML to automatically try out multiple models to find what works best. You may have to pay more because the training step is hundreds of thousands of times more compute power, but you get the optimal model and higher accuracy just by pushing a button and waiting four hours.”

I think this means that human grunt work is required. Where’s the smart software? Well, not yet. I like the “pay more” phrase too.

I wish I could just ask Watson. In the meantime, I will check out the Nvidia technology. I fear there is no antibiotic for the Watson Disease. Scary.

Stephen E Arnold, June 12, 2017

Partnership Hopes to Improve Healthcare through Technology

June 5, 2017

A healthcare research organization and a data warehousing and analytics firm are teaming up to improve patient care, Healthcare IT News reports in, “Health Catalyst, Regenstrief Partner to Commercialize Natural Language Processing Technology.” The technology at hand is the nDepth (NLP Data Extraction Providing Targeted Healthcare) platform, Regenstrief’s specialized data analysis tool. Reporter Bernie Monegain elaborates:

Regenstrief’s nDepth is artificial intelligence-powered text analytics technology. It was developed within the Indiana Health Information Exchange, the largest and oldest HIE in the country. Regenstrief fine-tuned nDepth through extensive and repeated use, searching more than 230 million text records from more than 17 million patients. The goal of the partnership is to speed improvements in patient care by unlocking the unstructured data within electronic health records. Health Catalyst will incorporate nDepth into its data analytics platform in use by health systems that together serve 85 million patients across the country.

In addition, clinicians are contributing their knowledge to build and curate clinical domain expertise and phenotype libraries to augment the platform. Another worthy contributor is Memorial Hospital at Gulfport, which was a co-development partner and was the first to implement the Health Catalyst/ nDepth system.

Based in Indianapolis, the Regenstrief Institute was founded in 1969 with a mission—to facilitate the use of technology to improve patient care. Launched in 2008, Health Catalyst is much younger but holds a similar purpose—to improve healthcare with data analysis and information sharing technologies. That enterprise is based in Salt Lake City.

Cynthia Murrell, June 5, 2017

Helping Machines Decode the World of Online Content

June 5, 2017

With voice search poised to overtake conventional search, startups like WordLift are creating an AI-based algorithm that can help machines understand content created by humans in a better way.

The Next Web in an article titled Wordlift Is Helping Robots Understand What Online Articles Are Really About says:

The evolution of today’s search engines and the rapid adoption of personal assistants (PAs) – capable of understanding user intent and behaviors through available data – require an upgrade of the existing editorial workflow for bloggers, independent news providers, and content marketers.

Voice activated search assistants rely on Metadata for understanding what the content is about. Moreover, metadata alone is unable to tell the AI what is the user intent. WordLift intends to solve this problem by applying advanced AI for understanding the content and make it voice search engine friendly. Structured data, understanding of textual content are some of the strategies WordLift will use to make the content voice search engine friendly.

Vishal Ingole, June 5, 2017

HonkinNews for May 30, 2017 Now Available

May 30, 2017

This week’s HonkinNews tackles the “three peas in a pod” approach to certain online information. Some might call the approach used by China, Facebook, and Google censorship. HonkinNews understand that certain information should not be available to just anyone. Does censorship work? If the correct information is filtered, censorship is a champ. Google is into the side search business. The idea is not new, but Google’s approach is to use a euphemism for determining if an Adword leads to an actual sale from a retail outlet. Why position context analysis as something really new? Google wants to prove that online ads really work. Of course they do. Artificial intelligence has found its niche in life. Now smart software can name colors. What does one call that color your young child wants? We provide an answer. The Beyond Search team responsible for HonkinNews will be at the TechnoSecurity & Digital Forensics Conference. I know that sounds like a ton of fun. There’s nothing like the party atmosphere of more than 1,000 LE, security, and intel types. HonkinNews will be delivering three lectures/training sessions. Our next program will be on June 13, 2017, unless the Kentucky crowd becomes the guests of South Carolina. You can find the video at this link.

Stephen E Arnold, May 30, 2017

Hey, Go Loser, Want a Rematch?

May 28, 2017

I read “AlphaGo Retires from Competitive Go after Defeating World Number One 3-0.” Enough of those fun and games. Alphabet Google has got to focus on generating revenue. The loser, one disgraced Go player, will not have a chance for a rematch. The reason is that Google’s technology has reached the “summit” of winning., When one is on top and you lose, tough luck. China must have had an inkling of defeat. The match was allegedly tough to follow in the Middle Kingdom. Filters are good, of course.

What will those Googlers do now? I learned from the write up that:

“The research team behind AlphaGo will now throw their considerable energy into the next set of grand challenges, developing advanced general algorithms that could one day help scientists as they tackle some of our most complex problems, such as finding new cures for diseases, dramatically reducing energy consumption, or inventing revolutionary new materials,” Hassabis says. “If AI systems prove they are able to unearth significant new knowledge and strategies in these domains too, the breakthroughs could be truly remarkable. We can’t wait to see what comes next.”

What about the former champion? Good question. It does  not appear that Alphabet Google will be hiring him as an adviser. Well, there’s always an opportunity to sell chicken of the cave as a go to street vendor. Oh, chicken of the cave is a euphemism for bat. Cave. Go get it.

Stephen E Arnold, May 28, 2017

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