Introduction to Weave

Introduction to Weave

 
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Weave is a modern, visual and intelligent information medium that empowers users with seamless information discovery. With Weave, highly visual and engaging information intelligently and contextually comes to users where and when it makes sense, rather than forcing users to know to search and then to repeatedly search. And businesses gain a new publishing platform and format that makes their content more discoverable, usable, engaging and measurable – thereby reducing their costs of customer acquisition, engagement and retention, and providing strong returns on their fast-growing publishing investments.

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Artificial intelligence
 
In the field of computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.
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Discoverability is the degree to which of something, especially a piece of content or information, can be found in a search of a file, database, or other information system.
Brand awareness
 
Brand awareness refers to the extent to which customers are able to recall or recognise a brand.
 
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Customer engagement
 
Customer engagement is a business communication connection between an external stakeholder (consumer) and an organization (company or brand) through various channels of correspondence.

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Artificial Intelligence

In the field of computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[1] More specifically, Kaplan and Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”.[2] Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".[3]

The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler's Theorem, "AI is whatever hasn't been done yet."[4] For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology.[5] Modern machine capabilities generally classified as AI include successfully understanding human speech,[6] competing at the highest level in strategic game systems (such as chess and Go),[7] autonomously operating cars, and intelligent routing in content delivery networks and military simulations.

Borrowing from the management literature, Kaplan and Haenlein classify artificial intelligence into three different types of AI systems: analytical, human-inspired, and humanized artificial intelligence.[2] Analytical AI has only characteristics consistent with cognitive intelligence generating cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive as well as emotional intelligence, understanding, in addition to cognitive elements, human emotions and considering them in their decision making. Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence), able to be self-conscious and self-aware in interactions with others.

Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,[8][9] followed by disappointment and the loss of funding (known as an "AI winter"),[10][11] followed by new approaches, success and renewed funding.[9][12] For most of its history, AI research has been divided into subfields that often fail to communicate with each other.[13] These sub-fields are based on technical considerations, such as particular goals (e.g. "robotics" or "machine learning"),[14] the use of particular tools ("logic" or artificial neural networks), or deep philosophical differences.[15][16][17] Subfields have also been based on social factors (particular institutions or the work of particular researchers).[13]

The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects.[14] General intelligence is among the field's long-term goals.[18] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many other fields.

The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it".[19] This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity.[20] Some people also consider AI to be a danger to humanity if it progresses unabated.[21] Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.[22]

In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.[23][12]

Machine Learning

Machine learning (ML) is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to "learn" (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed.[2]

The name machine learning was coined in 1959 by Arthur Samuel.[1] Machine learning explores the study and construction of algorithms that can learn from and make predictions on data[3] – such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions,[4]:2 through building a model from sample inputs. Machine learning is employed in a range of computing tasks where designing and programming explicit algorithms with good performance is difficult or infeasible; example applications include email filtering, detection of network intruders, and computer vision.

Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining,[5] where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning.[6][7]

Within the field of data analytics, machine learning is a method used to devise complex models and algorithms that lend themselves to prediction; in commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to "produce reliable, repeatable decisions and results" and uncover "hidden insights" through learning from historical relationships and trends in the data.[8]

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Cloud and Red Hat will determine future course for IBM
  –  February 15, 2019
They want help in developing new business models and transforming the enterprise ... It’s all about data, artificial intelligence and cloud, the modern IT cocktail. “IT economics are changing ...
Foxconn and UW-Milwaukee Host Send-off for Students Embarking on International Engineering Co-op
  –  February 15, 2019
artificial intelligence, networks, and robotics and automation, in its transformation as a leading high-tech enterprise and industrial Internet company. The company has research centers and ...
3 Top Artificial Intelligence Stocks to Watch in February
  –  February 15, 2019
If you're looking for exposure to the artificial intelligence trend ... evolved into a full-fledged AI service for enterprise customers like Macy's, H&R Block, and General Motors.
Autonomous Trucking Execs Talk Hardware, Regulation And Who Will Be The First To Market
  –  February 15, 2019
TuSimple, a San Diego-based startup, employs 500 in the U.S. and China and has carved out a space as an artificial intelligence powerhouse running real trucks on real roads with real deliveries. Ike Robotics is a smaller enterprise with plenty of ...
Investor Ideas Adds New #Homebuilder, Mining, #eSports and #AI Stocks: ($CSWI, $MYRG, $JCTCF, $WMS, $ALLE, $CBPX, $ROCK, $PGTI, $USG)
  –  February 15, 2019
The latest tech company, Sonasoft Corporation (OTCQB:SSFT) intends to integrate artificial intelligence (AI) into its enterprise-class archiving and business continuity software solutions for Microsoft platforms. CSW INDUSTRIALS INC (NasdaqGS:CSWI ...
ACEDS Twin Cities Chapter: A Legalweek Retrospective Discussion and Cocktail Reception; Minneapolis, MN
  –  February 15, 2019
Before joining ACEDS, Mary was the Enterprise Technology Counsel for ZyLAB ... privacy, security, and artificial intelligence. Currently, she writes columns for law.com, Minnesota Lawyer, and other media companies, as well as consults and writes for ...
SPAWAR Fosters Innovation and Industry Engagement at WEST 2019
  –  February 15, 2019
PEO C4I demonstrated the Consolidated Afloat Networks and Enterprise Services (CANES), the Navy's ... navigation and timing technologies, artificial intelligence and machine learning applications, military satellite and nanosatellite communication systems ...
IBM Watson Studio: Product Overview and Insight
  –  February 15, 2019
Watson is an umbrella for all IBM deep learning and artificial intelligence, as well as machine learning ... Watson Studio Cloud - Enterprise runs $6,000 per month with 5,000 capacity unit hours. Watson Studio Desktop costs $199 per month with unlimited ...
Q&A: Enabling customer choice in a complex hybrid cloud
  –  February 14, 2019
The enterprise pivot to hybrid has meant a ... workloads to other parts of the IBM ecosystem in terms of our [artificial intelligence] capabilities. Miniman: What are some of the most prevalent ...
How the digital economy is transforming Canada’s offshore oil and gas industry
  –  February 14, 2019
As the entire offshore enterprise becomes digitalized, tools such as data analytics, artificial intelligence and cognitive computing will optimize the overall operations and personnel safety.
Optanix Selected as Finalist for Best of Enterprise Connect 2019 in Best Application of AI Category
  –  February 14, 2019
"We work hard every day to advance the platform's artificial intelligence and machine learning capabilities ... the most advanced AIOps solution on the market." "The Best of Enterprise Connect awards recognize stand-out companies making a significant ...
How Video Games Help Fuel The Insatiable Demand For Artificial Intelligence
  –  February 14, 2019
But the era of artificial intelligence has already arrived ... to the growing number of AI-powered enterprise applications being developed by big industry players like SAP. Today, with the combined power of GPUs and massive troves of raw data and AI ...
How Does A M’sian Social Enterprise Get Robots And AI Onto Its Food Truck Fleet?
  –  February 13, 2019
But since then, his enterprise has evolved to become more than just an ... This automated kitchen will also employ a digitised artificial intelligence (AI) platform that will help improve consistency and enhance their deliverables by tailoring offerings ...
Automation and Artificial Intelligence: How machines are affecting people and places
  –  February 9, 2019
and Rust Belt states are most at risk of job replacement by artificial intelligence on Brookings Institute. CTOvision Pro is our subscription only research and analysis service which provides exclusive content to enterprise IT professionals. We deliver ...
The Role Of Artificial Intelligence And Machine Learning In Driving Customer Experience
  –  February 8, 2019
While there’s a lot of excitement about artificial intelligence (AI) and machine learning (ML ... With Gartner predicting that 85% of customer interactions with an enterprise will be managed without a human by 2020, brands would be wise to consider ...
Cognizer Launches Publicly with the Industry’s Most Accurate Natural Language Understanding Artificial Intelligence Platform for the Enterprise
  –  February 7, 2019
Cognizer’s Corporate Brain will behave like a virtual assistant that will constantly be assisting employees, whether in meetings or in-person conversations, to deliver a totally personalized ...
AI, Cloud, and Security Are Top Priorities for Enterprise Legal Departments
  –  February 7, 2019
"AI, cloud and security have emerged as top priorities for law firms and enterprise legal departments ... OpenText vice president for security, artificial intelligence, and legal technology.
Why enterprise IT is moving to the cloud – and when it’s not
  –  February 7, 2019
CIOs are under pressure to move enterprise IT to the cloud ... Consider: Machine learning, an offshoot of artificial intelligence research, continues to find practical applications with algorithms that find patterns in data and learn from experience.
Enterprise Governance, Risk And Compliance (EGRC) Market In-Depth Analysis On Forthcoming Development And Forecast By 2026
  –  February 7, 2019
In addition, increasing adoption for cloud technology and increasing adoption of artificial intelligence (AI ... To get more insights, visit: https://marketresearch.biz/report/enterprise-governance-risk-and-compliance-egrc-market/ Furthermore, rising ...
Pegasystems Acquires Business Intelligence and Data Visualization Capabilities to Enable Smarter Business Decisions
  –  February 6, 2019
This acquisition brings a consumer-grade user interface and enterprise-class capabilities to Pega solutions ... powered by advanced artificial intelligence and robotic automation, to help the world’s leading brands achieve breakthrough business results.
Fujifilm Exhibits Enterprise Imaging Solutions and Artificial Intelligence Initiative at HIMSS 2019
  –  February 5, 2019
STAMFORD, Conn. and BOTHELL, Wash., Feb. 5, 2019 /PRNewswire/ -- (Booth #4159) -- FUJIFILM Medical Systems U.S.A., Inc. and FUJIFILM SonoSite, Inc., will showcase their Enterprise Imaging and Informatics solutions at the Healthcare Information and ...
Artificial intelligence and machine learning adoption in European enterprise
  –  February 4, 2019
See the full schedule for the Strata Data Conference in London, April 29-May 2, 2019. Best price ends February 8. In a recent survey, we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing ...
How AI and machine learning can help you defend the enterprise from cyberattacks
  –  February 15, 2019
For a robust, modern defense, an adaptive monitoring solution that leverages machine learning to identify anomalous patterns indicative of an attack in its infancy is necessary to defend enterprise systems from cyberattacks. Much of the groundwork for this ...

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