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
Artificial intelligence (AI, also machine intelligence, MI) is intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals.
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.
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

Artificial intelligence (AI, also machine intelligence, MI) is intelligence exhibited by machines, rather than humans or other animals (natural intelligence, NI). In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal.[1] 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".[2]

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 "AI is whatever hasn't been done yet."[3] For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology.[4] Capabilities generally classified as AI, as of 2017, include successfully understanding human speech,[5] competing at a high level in strategic game systems (such as chess and Go[6]), autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data.

Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,[7][8] followed by disappointment and the loss of funding (known as an "AI winter"),[9][10] followed by new approaches, success and renewed funding.[11] For most of its history, AI research has been divided into subfields that often fail to communicate with each other.[12] However, in the early 21st century statistical approaches to machine learning became successful enough to eclipse all other tools, approaches, problems and schools of thought.[11]

The traditional problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects.[13] General intelligence is among the field's long-term goals.[14] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience, artificial psychology and many others.

The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it".[15] This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence, issues which have been explored by myth, fiction and philosophy since antiquity.[16] Some people also consider AI a danger to humanity if it progresses unabatedly.[17]

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.[18]

Machine Learning

Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.[1]

Arthur Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term "Machine Learning" in 1959 while at IBM[2]. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence,[3] machine learning explores the study and construction of algorithms that can learn from and make predictions on data[4] – such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions,[5]: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 or malicious insiders working towards a data breach,[6] optical character recognition (OCR),[7] learning to rank, 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,[8] where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning.[5]:vii[9] Machine learning can also be unsupervised[10] and be used to learn and establish baseline behavioral profiles for various entities[11] and then used to find meaningful anomalies.

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.[12]

According to the Gartner hype cycle of 2016, machine learning is at its peak of inflated expectations.[13] Effective machine learning is difficult because finding patterns is hard and often not enough training data are available; as a result, machine-learning programs often fail to deliver.[14][15]

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Nyansa Eyes Doubling Partner Base In Push For Enterprise Growth
  –  March 16, 2018
Intel reveals major moves in data center, Internet of Things, artificial intelligence and PC gaming during the company's partner conference.
IBM platform integrates data science and machine learning to boost enterprise AI
  –  March 16, 2018
On Friday, IBM launched a new cloud platform effort that will help customers better understand their data and use it to power their work in artificial intelligence (AI ... He covers enterprise technology and is interested in the convergence of tech ...
Living on the Edge: Enterprise-Generated Data Processed Outside the Cloud to Increase 400 Percent by 2022
  –  March 16, 2018
Cloud computing is now powering the next generation of technology–from artificial intelligence (AI ... According to Gartner, currently around 10 percent of enterprise-generated data is created and processed outside a traditional centralized data center ...
Software is king and developers are in high demand
  –  March 16, 2018
As machine learning takes a stronger hold on the enterprise, developers are tasked with increasing its "role" alongside the role of artificial intelligence. Nearly half of respondents said those developers behind the creation of AI are responsible for ...
IBM Unwinds Tangled Data for Enterprise AI
  –  March 16, 2018
This week, in the runup ahead of its Think 2018 conference, IBM is expanding its capabilities around data management, artificial intelligence ... where do you need more enterprise data.” It is designed for on-premises private clouds, but has what ...
B2B FinTechs Get Creative With Enterprise Data
  –  March 16, 2018
Some companies focus on analytics, while others offer digitization solutions. Some focus on the enhancement of data already in the enterprise via artificial intelligence (AI) and machine learning, while others target the safeguarding of that data with ...
Canon Information And Imaging Solutions, Inc. Offers Expanded Email Content Management Capabilities Based On mxHero
  –  March 16, 2018
Cloud Content Management and Enterprise File Sync and Share (EFSS ... With expertise in emerging technologies such as artificial intelligence, machine learning, and big data analytics, CIIS deploys its solutions in partnership with leading technology ...
Ready for the Future: Futurist to Speak on Emerging Trends Impacting Heating, Cooling, and Refrigeration
  –  March 15, 2018
Anderson Futurist & Founder of venture Foresight Specific trends and technologies to be addressed include how recent advancements in artificial intelligence-powered ... the Carrier Enterprise Factory Authorized Dealer meeting will offer a full day of ...
AI chip startup SambaNova raises $56M from GV and others
  –  March 15, 2018
SambaNova Systems, a startup that makes chips specifically for artificial intelligence, exited stealth mode with ... will reimagine the infrastructure used to power AI in the enterprise, and the funding will allow the company to expand its team and ...
What Is #GDPR and Why Should We Care? | @CloudExpo @CalligoCloud #IoT #DevOps
  –  March 15, 2018
As your enterprise creates a vision and strategy that enables ... which will incorporate FinTech and Blockchain, as well as machine learning, artificial intelligence and deep learning in these two distinct tracks. Sponsorship and Speaking Inquiries ...
Bridging the communications gap between human and machine
  –  March 15, 2018
Artificial intelligence is seeping into an increasing number of industries ... We really started to build a business in media, but over time we shifted toward being an enterprise software company. We started to get a lot of interest from people who ...
SAP HANA Enterprise Cloud: A Strong Pillar of SAP’s Strategy
  –  March 15, 2018
Artificial intelligence (AI) and machine learning are poised to enhance ... need time to migrate away from highly customized environments. This is where SAP HANA Enterprise Cloud comes into play. Simply stated, it is SAP’s private managed cloud.
Microsoft Xbox Vs. Enterprise Software: Same Platform, Same Rules, Different Game
  –  March 15, 2018
Going deeper, enterprise software developers use cloud computing resources to provide a backbone for storage, software execution and, crucially these days, an increasing degree of data analytics to provide user insight and Artificial Intelligence (AI ...
5G network deployments: Challenges and solutions
  –  March 15, 2018
If the network connection between these two engineers fails, the broken link would need to be fixed in a certain amount of time to satisfy the enterprise Service ... Solution: Deploy artificial intelligence (AI). If each end was equipped with AI ...
60% of Enterprise Marketers Set To Use Artificial Intelligence (AI) in Content Marketing Strategy This Year
  –  March 6, 2018
SAN MATEO, Calif., March 6, 2018 /PRNewswire/ -- A new survey released by BrightEdge, the leader in enterprise SEO and content performance marketing, reveals marketers have become more receptive to adoption of artificial intelligence technologies, such as ...
Artificial Intelligence and Robotics in Consumer, Enterprise, an - | Chattanooga News, Weather & Sports
  –  January 18, 2018
Information contained on this page is provided by an independent third-party content provider. Frankly and this Site make no warranties or representations in connection therewith. If you are affiliated with this page and would like it removed please ...
Artificial Intelligence and Robotics in Consumer, Enterprise, an - KCTV5
  –  January 18, 2018
Information contained on this page is provided by an independent third-party content provider. Frankly and this Site make no warranties or representations in connection therewith. If you are affiliated with this page and would like it removed please ...
Artificial Intelligence and Robotics in Consumer, Enterprise, an - - Oklahoma City, OK - News, Weather, Video and Sports |
  –  January 18, 2018
Information contained on this page is provided by an independent third-party content provider. Frankly and this Site make no warranties or representations in connection therewith. If you are affiliated with this page and would like it removed please ...




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