Evolve or die: From controlling 90% of the market and $16 billion in revenues to bankruptcy – has Artificial Intelligence already begun the death of your business?

Will Artificial Intelligence do the same for you? Following are excerpts from The Center for the Study of the Legal Profession at the Georgetown University Law Center and Thomson Reuters Peer Monitor 2016 Report on the State of the Legal Market. The report is focused on the legal profession but seems appropriate for a myriad of industries and the answer to the question is: without a doubt, entire industries are facing a dilemma, adopt or die.
In the annals of American business, few firms were as successful for as long as the Eastman Kodak Company. Founded by George Eastman (the inventor of roll film) in 1880, Kodak introduced its first camera in 1888 with the memorable slogan: “You press the button, we do the rest.” For a century thereafter, Kodak dominated the market for cameras and film in the United States and much of the world. It revolutionized society by making it possible for ordinary people to record the key events of their lives – events later even rebranded as “Kodak moments” – by removing photography from the exclusive domain of professionals.
By 1976, Kodak controlled 90 percent of the film market and 85 percent of the camera market in the U.S. Until the 1990s, it was regularly rated as one of the world’s five best known and most valuable brands. In 1988, at its peak, Kodak employed over 145,000 workers worldwide. Its annual revenues peaked at nearly $16 billion in 1996 and its profits at $2.5 billion in 1999.
The strategy that propelled Kodak to its long-term success was the “razor blade” business model. Just as Gillette makes money on the blades and not the razors, Kodak sold cheap cameras and relied on customers buying lots of expensive film. That strategy worked fine in the age of print photography when Kodak could control 80 percent of the market for the chemicals and paper used to develop and print photos. But it was not a strategy for success in an age of digital photography. In the 1990s, Kodak dragged its feet on entering the digital market in a serious way. When it did decide to get into the game, it was too late, having lost key market advantage to more nimble competitors like Sony and Canon.
History, of course, has many examples of well-established companies being blindsided by technological developments that oust them from their positions of market leadership. And if that were the whole story with Kodak, it would be just another sad though familiar tale. In the case of Kodak, however, the story is much more interesting because the new technology that ultimately destroyed the company was invented at Kodak itself! In the mid-1970s, Steve Sasson, a young electrical engineer working at Kodak, assembled a system of electronic components that could capture an image and display it on a screen. In December 1975, Sasson and chief technician Jim Schueckler conducted the first successful test of a digital camera in Kodak’s labs. While the first camera was fairly crude by today’s standards, its technical significance was plainly understood by the company.
Nonetheless, management response was tepid. As Mr. Sasson put it, “They were convinced that no one would ever want to look at their pictures on a television set. Print had been with us for over 100 years, no one was complaining about prints, they were very inexpensive, and so why would anyone want to look at their pictures on a television set?” In addition, it was not lost on company management that pursuit of digital photography would, of course, seriously undercut Kodak’s lucrative film business, and that digital photography itself would not be as profitable. As a consequence, Kodak essentially chose to ignore the fundamental shift in its market – until it was too late. Today, the first digital camera made by Mr. Sasson in 1975 is on display at the Smithsonian’s National Museum of American History. President Obama awarded Mr. Sasson the National Medal of Technology and Innovation at a White House ceremony in 2009, and three years later, Kodak filed for bankruptcy.
This story of the demise of Kodak is an important cautionary tale for law firms in the current market environment. Since 2008, the market for law firm services has changed in significant and permanent ways. Clients who previously deferred to their outside firms on virtually all key decisions regarding the organization, staffing, scheduling, and pricing of legal matters are now, in most cases, in active control of all of those decisions. Increasingly, clients are demanding more “value” in return for their legal spend, and by value they mean greater efficiency, predictability, and cost effectiveness in the delivery of legal services. What once was a seller’s market has now clearly become a buyer’s market, and the ramifications of that change are significant. Clients today are more willing than ever before to disaggregate matters, combining the services of several different service providers in order to achieve increased efficiencies. They are more open than ever before to utilizing non-traditional service providers (including non-law firms) to provide a wide range of services previously obtained almost exclusively from law firms. And clients are far more likely today to retain work in-house, bringing their outside counsel in only where needed to supply specialized expertise or to handle matters on a discrete project-by-project basis.
Access the Georgetown University Law Center and Thomson Reuters Peer Monitor 2016 Report on the State of the Legal Market here…

Artificial Intelligence – is it about to change my industry?

A couple of months ago, 60 minutes ran a segment on IBM Watson’s healthcare initiative and more specifically, the initiative on oncology. The segment was eye opening and the realization that the next huge influence on major industries is left the dock and on its way to major disruption in fields such as Healthcare, Law, Finance and more is much more advanced than most people know. I now bring up AI as Artificial Intelligence is known to those involved from time to time only to find a puzzled look on many faces. My best guess is that to a lot of people this is a “smart” thing to claim to understand when they have no idea of what is really happening.
I went to a trusted pal, LinkedIn, to do some very superficial research: a search for IBM Artificial Intelligence returns over 10,000 contacts; Google 6,500 contacts; Intel 3,000 contacts; Microsoft 9,000 contacts; Apple 1,900 contacts; and just plain Artificial Intelligence over 270,000 contacts.
Google recently announced a breakthrough with state-of-the art breast cancer detection and at the same time made this statement: “What we’ve trained is just a little sliver of software that helps with one part of a very complex series of tasks,” said Lily Peng, the project manager behind Google’s work. “There will hopefully be more and more of these tools that help doctors [who] have to go through an enormous amount of information all the time.” The bottom line is that even experts in the field achieving astonishing developments realize they are barely scratching the surface.
The ABA Journal recently published an article on how AI will transform the legal industry. “Artificial intelligence is more than legal technology. It is the next great hope that will revolutionize the legal profession.” Goldman Sachs published the AI Age and talks about healthcare and retail. In short, a Google search for “how AI will affect……..” will yield you a handful of choices and dozens of articles for each industry category.
Still seem that AI is all about 500,000 geeks toying with technology? AI may be the best kept secret we have ever had but chances are it is already influencing your life and that of countless millions with more to come at an ever increasing pace.

GE Partners With Harvard Hospitals To Harness Artificial Intelligence In Medicine

General Electric’s healthcare division will partner with the corporate parent of two of Harvard University’s teaching hospitals to develop artificial intelligence products for medicine. The goal: to leverage the company’s dominant position in medical imaging into a new ownership of medical AI.
“We make machines but that’s not really the business,” says John Flannery, the chief executive of GE Healthcare, says he tells his team. “The business is what kind of solution can we put together that gets a better clinical and economic outcome?”
GE Healthcare is one of the main manufacturers of imaging devices used in radiology–things like PET and MRI scanners. The company also sells the computer software that doctors use to manage the images. This area, long thought to be low-hanging fruit for artificial intelligence applications, could form the basis of the first products to emerge from the collaboration. For instance, software might be able to identify which scans are normal, freeing human radiologists to focus on cases where there is an abnormality. (In 2015, IBM bought a company focused on reading radiology images with similar aims.)
The deal is between Partners Healthcare, the corporate parent of the Massachusetts General Hospital and the Brigham & Women’s Hospital, two Harvard-associated teaching hospitals.
“We’ve committed within our organizations to have a center that’s going to endure and the relationship with GE is intentionally 10 years,” Dr. Keith Dreyer, Chief Data Science Officer at MGH and BWH. “This is going to take a while to do. People ask me how long this is going to take to happen. And I say how long is it going to take for the Internet to happen?”
Dreyer says that the field of using AI in medicine has gone from hundreds of scientific publications to thousands over the past three years. He contrasts the effort to create an AI that would serve, essentially, as a virtual physician to a more realistic approach that is piecemeal, dealing with one opportunity at a time.
Flannery, the GE Healthcare CEO, is eager to move fast. He says commercialization of cloud-based radiology applications could occur in one to three years. “There will be an iTunes-like app store of programs offered to the physicians,” Flannery says. Other companies would then use the infrastructure and data created by GE and its partners to create their own programs, all of which will run on a single application. “If there were 20 technologies with these solutions, I can’t buy 20 solutions. I need a single platform,” Dreyer says. This remains an interesting space to watch.

Full article: https://www.forbes.com/sites/matthewherper/2017/05/17/ge-partners-with-harvard-hospitals-to-put-artificial-intelligence-in-medicine/#30e8838b7385

Contact Information:
https://www.forbes.com/sites/matthewherper/2017/05/17/ge-partners-with-harvard-hospitals-to-put-artificial-intelligence-in-medicine/#30e8838b7385

Artificial Intelligence and Airlines – 200,000 maintenance cases addressed 90% faster

I thought this article published by IBM Watson deserved a post as it is a great example of artificial intelligence at work, in this case, the efficiency being created is so large I am sure others reading this will start to envision similar synergies for their companies and industries.

Overview

Korean Air has years worth of historical maintenance records for hundreds of aircrafts in its fleet. But until recently, this vast amount of critical data was virtually unsearchable. That meant that maintenance technicians had to diagnose and fix issues without being able to tap into or interpret implications from valuable past learnings and courses of action.

Enter Watson

Watson ingested structured and unstructured data from multiple sources including technical guidelines, non-routine logs, technician notes, inventory, trouble shooting time and material cost data, and in-flight incident history.

Watson Explorer, Natural Language Understanding and advanced content analytics locate previously hidden connections that helping maintenance crews diagnose and solve problems more quickly, with more confidence. Instead of spending hours diagnosing each potential issue, technicians can easily search and get near real-time analysis.

Further, if an issue occurs in flight, the cabin crew can report it immediately to ground operations. Watson will access data from similar issues in the past and compare this information against technical guidelines including necessary materials and fixing time. Maintenance technicians fix the issue on the ground and enter their actions into the system to add to Watson’s knowledge.

With Watson, maintenance managers can also identify trends of issues in each season and can take these insights to the original equipment manufacturers for improvement.

Over 200,000 maintenance cases per year are addressed 90% faster

Korean Air needs their over 2,000 maintenance employees to be able to act faster. When Watson delivered actionable insights on the root causes and solutions of issues, Korean Air shortened its maintenance defect history analysis lead times by 90%.

The maintenance employee can now see patterns of defect and failure on equipment to make preventive maintenance allowing them to spend more time getting people places on time—and working to keep their 25 million passengers happy.

Airlines, hospitals, businesses, educators and governments are working with Watson. In 45 countries and 20 industries, Watson is helping people make sense of data so they can make better decisions while uncovering new ideas.

How Korean Air worked with Watson

(In 5 simple steps)

1. Watson ingested a variety of structured and unstructured data related to maintenance for the hundreds of planes in Korean Air’s fleet.

2. Maintenance defect issues are reported by flight or cabin crews to ground operations.

3. Maintenance employees access data from look-a-like cases against technical guidelines.

4. Watson assists to decide probable cause and recommends solutions so that they can be quickly addressed by technicians.

5. More flights are on time, keeping 25 million passengers happy.

The full article can be seen here: https://www.ibm.com/watson/stories/airlines-with-watson.html

LexisNexis Announces First Five Legal Tech Accelerator Participants

Its no secret I am following Artificial Intelligence and Tech developments that are rapidly moving towards disruption of industries such as legal, financial, health, retail, transportation and much more. For law firms and others in the legal industry the challenge now is to avoid becoming Sears, Kodak, OAG and others in long lists of other companies that once led industry segments only to miss technology evolutions and become obsolete. This recent press release form LexisNexis is an interesting example of legal tech at work.

MENLO PARK, Calif., March 31, 2017 /PRNewswire/ — LexisNexis today announced the first five participants in its new Silicon Valley legal tech accelerator program, which was created to give startups a leg up in the rapidly expanding legal tech industry. In line with LexisNexis’ broader vision to transform the way law is practiced, each of the accelerator participants is uniquely innovating in distinct areas of the law. After a thorough evaluation process, the five finalists – Visabot, TagDox, Separate.us, Ping, and JuriLytics – were selected from a list of 40+ promising startups for the interesting nature of their businesses and their innovative use of technology.

Based in the Menlo Park, CA offices of Lex Machina™, the program will leverage the vast content resources, deep expertise in legal, technology, and startup domains, and industry-leading market positions of LexisNexis and Lex Machina to guide and mentor program participants. The program will be led by Lex Machina CEO Josh Becker with support from LexisNexis’ Chief Technology Officer, Jeff Reihl, Chief Product Officer, Jamie Buckley, Vice President of US Product Management, Jeff Pfeifer, and Lex Machina Chief Evangelist, Owen Byrd.

The five charter members of the LexisNexis legal tech accelerator program are:

Visabot: An “immigration robot” powered by artificial intelligence that helps customers complete U.S. visa applications, including locating relevant open data about an applicant, guiding applicants in the process of gathering supporting documents, ensuring forms are filled out accurately, and drafting appropriate language to tell the applicant’s story.
TagDox: A legal document analysis tool that creates tags, allowing users to identify and structure information in a variety of document types, improving both the speed and the quality of the document review process; “tag results” can transform documents into easily readable summaries, checklists, database feeds or approval overviews.
Separate.us: A web-based application that automates legal document preparation for divorces and provides access to relevant professionals at affordable fixed rates, deploying a business model that targets both B2B and B2C customers.
Ping: An automated timekeeping application that collects all of a lawyer’s billable hours, capturing missed time and money (an estimated 20% across the industry), and operating entirely in the background in concert with standard legal billing software.
JuriLytics: An expert witness peer review service that attorneys can use to challenge their opponent’s experts with previously unobtainable credibility and bullet-proof their own expert’s work through vetting from the world’s top researchers (in any field of expertise).
Throughout the rigorous, 12-week curriculum, tech accelerator participants will gain knowledge and expertise in a variety of topics including technology and product development; running an agile product development organization; building a strong company culture; selling to legal departments and law firms; leveraging legal data; and best practices in customer success, marketing and fundraising. In addition, they will have access to a vast collection of enriched legal data and cutting-edge tools and technologies from LexisNexis, and will be able to leverage the company’s established relationships with Stanford University and other leading Bay Area schools, businesses, VCs and influencers to grow their companies.

“The LexisNexis legal tech accelerator is a promising initiative,” said Miriam Rivera, Managing Partner at Ulu Ventures and an advisor at the Venture Capital Director’s College, a part of The Rock Center for Corporate Governance at Stanford University. “As a legal tech investor and former Deputy GC of Google responsible for expanding the use of legal technology throughout the department, I am convinced the LexisNexis tech accelerator will not only foster innovation but also encourage new companies to thrive with sound business practices.”

For more information, or to apply to the tech accelerator program, please email Alex Oh (aoh@lexmachina.com).

About LexisNexis® Legal & Professional

LexisNexis Legal & Professional is a leading global provider of content and technology solutions that enable professionals in legal, corporate, tax, government, academic and non-profit organizations to make informed decisions and achieve better business outcomes. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services. Today, LexisNexis Legal & Professional harnesses leading edge technology and world class content to help professionals work in faster, easier and more effective ways. Through close collaboration with its customers, the company ensures organizations can leverage its solutions to reduce risk, improve productivity, increase profitability and grow their business. LexisNexis Legal & Professional, which serves customers in more than 175 countries with 10,000 employees worldwide, is part of RELX Group plc, a world leading global provider of information and analytics solutions for professional and business customers across industries.

About Lex Machina

Lex Machina’s award-winning Legal Analytics® platform is a new category of legal technology that fundamentally changes how companies and law firms compete in the business and practice of law. Delivered as Software-as a-Service, Lex Machina provides strategic insights on judges, lawyers, parties, and more, mined from millions of pages of legal information. This allows law firms and companies to predict the behaviors and outcomes that different legal strategies will produce, enabling them to win cases and close business.

Lex Machina was named “Best Legal Analytics” by readers of The Recorder in 2014, 2015 and 2016, and received the “Best New Product of the Year” award in 2015 from the American Association of Law Libraries.

Based in Silicon Valley, Lex Machina is part of LexisNexis, a leading information provider and a pioneer in delivering trusted legal content and insights through innovative research and productivity solutions, supporting the needs of legal professionals at every step of their workflow. By harnessing the power of Big Data, LexisNexis provides legal professionals with essential information and insights derived from an unmatched collection of legal and news content—fueling productivity, confidence, and better outcomes. For more information, please visit www.lexmachina.com.

To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/lexisnexis-announces-first-five-legal-tech-accelerator-participants-300432478.html

SOURCE Lex Machina

Related Links

http://www.lexmachina.com

Status of Artificial Intelligence development

In my last post, I wrote about the handful of household brand name companies actually involved in Artificial Intelligence development, the usual suspects such as IBM, Microsoft, Intel, Apple and more – in a very quick guesstimate I threw out the number of tech professionals at work on AI at 300,000. I received some comments in that I was way short on my estimate and should take another look, so I did, but before I move on to a list of companies actively involved in AI one caveat, I am sure I will be short again.

Venture Scanner is tracking 957 Artificial Intelligence companies across 13 categories, with a combined funding amount of $4.8 Billion. Here are some of the names:

Baidu, Inc., Portland; Kasisito, Inc., New York City; Artivatic Data Labs, Bangalore; Ignite Tech, Vellore; Natxis, Paris; King, Stockholm; Fujitsu, Slovenia; Qikspace, Seattle; Lola, Boston; Pavlov, San Francisco; Cloud (Google), San Francisco; Next AI, Kitchner; Amazon, Seattle; Yik Yak, Atlanta; Operator, Inc., San Francisco; Chorus AI, San Francisco; AI Cities, San Francisco; AI.codes, San Francisco; Facebook, New York City; Intel, Portland; NVIDIA, San Francisco; Autodesk, San Francisco; Alexa, San Francisco; Degree Six, Chicago; Kount, Boise; UBER, San Francisco; X.AI, New York City; Microsoft, Seattle; OTSAW Digital, San Francisco; Cognitive AI, New York City; Google, San Francisco; All West/Select Sires, Portland; Vecna, Boston; Arkane Studios, Austin; Rockstar New England, Boston; Hex Entertainment, Orange County; Treyarch, Los Angeles; Knexus Research, Allentown; ABS Global, Madison; GGD Groningen, Groningen; Open AI (Tesla), San Francisco; AI + Club, San Francisco; Apple, San Francisco; Drive AI, San Francisco; LinkedIn, San Francisco; Bonsai AI, San Francisco; Voice Box Technologies, Seattle; Accenture, San Francisco; Knexus Research, Washington, DC; Yahoo!, San Francisco; Elemental Cognition, New York City; Mezi, San Francisco; Philips Research, Boston; MITRE, Albany; PWC Analytics, Boston; Artificial Brilliance, Los Ángeles; Zvelo, Inc., Miami/Ft. Lauderdale; and GE Global Research, San Francisco.

Venture Scanner organizes Artificial Intelligence into the 13 categories listed below, the full article can be seen here:

Deep Learning/Machine Learning (General): Companies that build computer algorithms that operate based on their learnings from existing data. Examples include predictive data models and software platforms that analyze behavioral data.

Deep Learning/Machine Learning (Applications): Companies that utilize computer algorithms that operate based on existing data in vertically specific use cases. Examples include using machine learning technology to detect banking fraud or to identify the top retail leads.

Natural Language Processing (General): Companies that build algorithms that process human language input and convert it into understandable representations. Examples include automated narrative generation and mining text into data.

Natural Language Processing (Speech Recognition): Companies that process sound clips of human speech, identify the exact words, and derive meaning from them. Examples include software that detects voice commands and translates them into actionable data.

Computer Vision/Image Recognition (General): Companies that build technology that process and analyze images to derive information and recognize objects from them. Examples include visual search platforms and image tagging APIs for developers.

Computer Vision/Image Recognition (Applications): Companies that utilize technology that process images in vertically specific use cases. Examples include software that recognizes faces or enables one to search for a retail item by taking a picture.

Gesture Control: Companies that enable one to interact and communicate with computers through their gestures. Examples include software that enables one to control video game avatars through body motion, or to operate computers and television through hand gestures alone.

Virtual Personal Assistants: Software agents that perform everyday tasks and services for an individual based on feedback and commands. Examples include customer service agents on websites and personal assistant apps that help one with managing calendar events, etc.

Smart Robots: Robots that can learn from their experience and act autonomously based on the conditions of their environment. Examples include home robots that could react to people’s emotions in their interactions and retail robots that help customers find items in stores.

Recommendation Engines and Collaborative Filtering: Software that predicts the preferences and interests of users for items such as movies or restaurants, and delivers personalized recommendations to them. Examples include music recommendation apps and restaurant recommendation websites that deliver their recommendations based on one’s past selections.

Context Aware Computing: Software that automatically becomes aware of its environment and its context of use, such as location, orientation, lighting and adapts its behavior accordingly. Examples include apps that light up when detecting darkness in the environment.

Speech to Speech Translation: Software which recognizes and translates human speech in one language into another language automatically and instantly. Examples include software that translates video chats and webinars into multiple languages automatically and in real-time.

Video Automatic Content Recognition: Software that compares a sampling of video content with a source content file to identify the content through its unique characteristics. Examples include software that detects copyrighted material in user-uploaded videos by comparing them against copyrighted material.

Full article can be seen here: https://venturescannerinsights.wordpress.com/tag/artificial-intelligence-company-list/

Artificial Intelligence – is it about to change my industry?

A couple of months ago, 60 minutes ran a segment on IBM Watson’s healthcare initiative and more specifically, the initiative on oncology. The segment was eye opening and the realization that the next huge influence on major industries is left the dock and on its way to major disruption in fields such as Healthcare, Law, Finance and more is much more advanced than most people know. I now bring up AI as Artificial Intelligence is known to those involved from time to time only to find a puzzled look on many faces. My best guess is that to a lot of people this is a “smart” thing to claim to understand when they have no idea of what is really happening.

I went to a trusted pal, LinkedIn, to do some very superficial research: a search for IBM Artificial Intelligence returns over 10,000 contacts; Google 6,500 contacts; Intel 3,000 contacts; Microsoft 9,000 contacts; Apple 1,900 contacts; and just plain Artificial Intelligence over 270,000 contacts.

Google recently announced a breakthrough with state-of-the art breast cancer detection and at the same time made this statement: “What we’ve trained is just a little sliver of software that helps with one part of a very complex series of tasks,” said Lily Peng, the project manager behind Google’s work. “There will hopefully be more and more of these tools that help doctors [who] have to go through an enormous amount of information all the time.” The bottom line is that even experts in the field achieving astonishing developments realize they are barely scratching the surface.

The ABA Journal recently published an article on how AI will transform the legal industry. “Artificial intelligence is more than legal technology. It is the next great hope that will revolutionize the legal profession.” Goldman Sachs published the AI Age and talks about healthcare and retail. In short, a Google search for “how AI will affect……..” will yield you a handful of choices and dozens of articles for each industry category.

Still seem that AI is all about 500,000 geeks toying with technology? AI may be the best kept secret we have ever had but chances are it is already influencing your life and that of countless millions with more to come at an ever increasing pace.

Intel Unveils Strategy for State-of-the-Art Artificial Intelligence

Intel Offers Broad Portfolio Spanning Data Center to IoT Devices and Software to Make AI Foundational to Business and Society
NEWS HIGHLIGHTS
  • Intel announces AI strategy to drive breakthrough performance, democratize access and maximize societal benefits.
  • Intel introduces industry’s most comprehensive data center compute portfolio for AI: the new Intel® Nervana™ platform.
  • Intel aims to deliver up to 100x reduction in the time to train a deep learning model over the next three years compared to GPU solutions.
  • Intel reinforces commitment to an open AI ecosystem through an array of developer tools built for ease of use and cross-compatibility, laying the foundation for greater innovation.
  • SAN FRANCISCO – Intel Corporation today announced a range of new products, technologies and investments from the edge to the data center to help expand and accelerate the growth of artificial intelligence (AI). Intel sees AI transforming the way businesses operate and how people engage with the world. Intel is assembling the broadest set of technology options to drive AI capabilities in everything from smart factories and drones to sports, fraud detection and autonomous cars.
    At an industry gathering led by Intel CEO Brian Krzanich, Intel shared how both the promise and complexities of AI require an extensive set of leading technologies to choose from and an ecosystem that can scale beyond early adopters. As algorithms become complex and required data sets grow, Krzanich said Intel has the assets and know-how required to drive this computing transformation.
    In a blog Krzanich said: “Intel is uniquely capable of enabling and accelerating the promise of AI. Intel is committed to AI and is making major investments in technology and developer resources to advance AI for business and society.”

    Intel’s Robust AI Platform

    Intel announced plans to usher in the industry’s most comprehensive portfolio for AI – the Intel® Nervana™ platform. Built for speed and ease of use, the Intel Nervana portfolio is the foundation for highly optimized AI solutions, enabling more data professionals to solve the world’s biggest challenges on industry standard technology.
    Today, Intel powers 97 percent of data center servers running AI workloads and offers the most flexible, yet performance-optimized, portfolio of solutions. This includes Intel® Xeon® processors and Intel® Xeon Phi™ processors to more workload-optimized accelerators, including FPGAs (field-programmable gate arrays) and the technology innovations acquired from Nervana.

    Press kit:

    Intel Artificial Intelligence: Unleashing the Next Wave

    Intel also provided details of where the breakthrough technology from Nervana will be integrated into the product roadmap. Intel will test first silicon (code-named “Lake Crest”) in the first half of 2017 and will make it available to key customers later in the year. In addition, Intel announced a new product (code-named “Knights Crest”) on the roadmap that tightly integrates best-in-class Intel Xeon processors with the technology from Nervana. Lake Crest is optimized specifically for neural networks to deliver the highest performance for deep learning and offers unprecedented compute density with a high-bandwidth interconnect.
    “We expect the Intel Nervana platform to produce breakthrough performance and dramatic reductions in the time to train complex neural networks,” said Diane Bryant, executive vice president and general manager of the Data Center Group at Intel. “Before the end of the decade, Intel will deliver a 100-fold increase in performance that will turbocharge the pace of innovation in the emerging deep learning space.”
    Bryant also announced that Intel expects the next generation of Intel Xeon Phi processors (code-named “Knights Mill”) will deliver up to 4x better performance1 than the previous generation for deep learning and will be available in 2017. In addition, Intel announced it is shipping a preliminary version of the next generation of Intel Xeon processors (code-named “Skylake”) to select cloud service providers. With AVX-512, an integrated acceleration advancement, these Intel Xeon processors will significantly boost the performance of inference for machine learning workloads. Additional capabilities and configurations will be available when the platform family launches in mid-2017 to meet the full breadth of customer segments and requirements.

    Enabling AI Everywhere and Cloud Alliance with Google*

    Aside from silicon, Intel highlighted other AI assets, including Intel Saffron Technology™, a leading solution for customers looking for business insights. The Saffron Technology platform leverages memory-based reasoning techniques and transparent analysis of heterogeneous data. This technology is also particularly well-suited to small devices, making intelligent local analytics possible across IoT and helping advance state-of the-art collaborative AI.
    To simplify deployment everywhere, Intel also delivers common, intelligent APIs that extend across Intel’s distributed portfolio of processors from edge to cloud, as well as embedded technologies such as Intel® RealSense™ cameras and Movidius* vision processing units (VPUs).
    Intel and Google announced a strategic alliance to help enterprise IT deliver an open, flexible and secure multi-cloud infrastructure for their businesses. The collaboration includes technology integrations focused on Kubernetes* (containers), machine learning, security and IoT.
    To further AI research and strategy, Intel announced the formation of the Intel Nervana AI board, which will feature leading industry and academic thought leaders. Intel announced four founding members: Yoshua Bengio (University of Montreal), Bruno Olshausen (UC Berkeley), Jan Rabaey (UC Berkeley) and Ron Dror (Stanford University).
    Additionally, Intel is working to make AI truly accessible. To help accomplish this, Intel has introduced the Intel Nervana AI Academy for broad developer access to training and tools. Intel also introduced the Intel Nervana Graph Compiler to accelerate deep learning frameworks on Intel silicon.
    In conjunction with the AI Academy, Intel announced a partnership with global leading education provider Coursera* to provide a series of AI online courses to the academic community. Intel also launched a Kaggle Competition (coming in January) jointly with Mobile ODT* where the academic community can put their AI skills to the test to solve real-world socioeconomic problems, such as early detection for cervical cancer in developing countries through the use of AI for soft tissue imaging.
    “Intel can offer crucial technologies to drive the AI revolution, but ultimately we must work together as an industry – and as a society – to achieve the ultimate potential of AI,” said Doug Fisher, senior vice president and general manager of the Software and Services Group at Intel.
    With the addition of the new edge and data center products, as well as the enablement programs, Intel has the full complement of technologies and ecosystem reach required to deliver the scale and promise of AI for everyone.

    AI for the Betterment of Society

    Lastly, Intel showcased some of the initiatives the company is investing in and partnering with to help maximize the positive impact of AI on the world. They include:

    • Intel is committing $25 million to the Broad Institute* to drive high-performance computing for genomics analytics. Through a five-year collaboration, researchers and software engineers at the Intel-Broad Center for Genomic Data Engineering will build, optimize and widely share new tools and infrastructure that will help scientists integrate and process genomic data. The project aims to optimize best practices in hardware and software for genome analytics to make it possible to access and use research data sets that reside on private, public and hybrid clouds.
    • Intel is a founding partner of Hack Harassment*, a cooperative effort with the mission of reducing the prevalence and severity of online harassment. The initiative is evaluating AI technology as a tool in this effort and is working to develop an intelligent algorithm to detect and deter online harassment. Over time, this capability will be released as an open source API that can be used in a variety of applications.
    • Intel is also a key partner of the National Center for Missing & Exploited Children* (NCMEC), a nonprofit whose mission is to help find missing children, reduce child sexual exploitation and prevent child victimization. Intel is providing AI technology and advising the center with the goal of accelerating the critical work of NCMEC’s analysts to respond to reports of child sexual exploitation.
    • 1For more complete information about performance and benchmark results, visit www.intel.com/benchmarks.
      Intel, the Intel logo, Intel Xeon Phi, Xeon and Intel RealSense are trademarks of Intel Corporation in the United States and other countries.
      *Other names and brands may be claimed as the property of others
      Contact Information:
      www.intel.com/benchmarks

    Thomson Reuters and Blue J Legal Deliver Artificial Intelligence-Based Tax Foresight

    TORONTO – Thomson Reuters, the world’s leading source of intelligent information for businesses and professionals, and Blue J Legal today announced an exclusive joint initiative to bring Tax Foresight, a new suite of artificial intelligence-based tax case outcome predictors, to Canadian corporate tax professionals, tax preparers, accountants and tax lawyers.
    Tax Foresight leverages the power of machine learning and artificial intelligence (AI), enabling practitioners to rapidly predict how courts will rule in new tax decisions, based on facts provided by users and analysis of prior judicial decisions.
    Canadian tax and legal professionals can now access trusted primary law and guidance tools on the Thomson Reuters Taxnet Pro platform to identify specific tax issues, and use Tax Foresight to help predict how the courts will rule, thereby enhancing the efficiency of the analytical process. Blue J Legal has analyzed thousands of combinations of fact scenarios in tax cases, along with the eventual results of those cases, in order to build the Tax Foresight legal outcome prediction engine. This technology enables practitioners to predict, with much greater speed and confidence, how courts will rule in new situations.
    “It can be extraordinarily difficult and inefficient to analyze case outcomes when there are many different fact scenarios. This is where artificial intelligence can really be of help,” said Neil Sternthal, managing director for Thomson Reuters Canada, Australia and New Zealand legal business. “By leveraging the AI capabilities of Tax Foresight, our customers will be able to maximize their productivity and accurately predict possible court rulings for the benefit of their clients.”
    “Blue J Legal is thrilled to partner with Thomson Reuters to deliver the powerful insights of machine learning and artificial intelligence to accounting and legal professionals,” said Benjamin Alarie, chief executive officer for Blue J Legal. “Our Tax Foresight allows professionals to access legal answers and authoritative legal materials quickly and with more sophistication than ever before.”
    For more information on Tax Foresight and Taxnet Pro, visit www.gettaxnetpro.com.
    Thomson Reuters
    Thomson Reuters is the world’s leading source of news and information for professional markets. Our customers rely on us to deliver the intelligence, technology and expertise they need to find trusted answers. The business has operated in more than 100 countries for more than 100 years. Thomson Reuters shares are listed on the Toronto and New York Stock Exchanges. For more information, visit www.thomsonreuters.com.
    About Blue J Legal
    Blue J Legal uses machine learning and artificial intelligence to make the law more transparent and accessible. The company’s technology saves researchers hours of time and offers confident answers in challenging circumstances. While the company is beginning with tax law, the technology is versatile and is being extended to cover other areas of law in the U.S., Canada and around the world. For more information, visit www.bluejlegal.com.
    Contact
    Gretchen DeSutter
    Thomson Reuters
    Corporate Communications
    +1 651 687 7450
    gretchen.desutter@thomsonreuters.com
    Benjamin Alarie
    Blue J Legal
    CEO
    647 986 4763
    ben@bluejlegal.com
    Contact Information:
    www.thomsonreuters.com