This document discusses 5 current and near-future uses of AI in broadcast and media: 1) Content discovery and personalization to display curated content based on user preferences and history; 2) Ad targeting and filtering to tailor advertisements to audiences; 3) Content clustering and metadata building to add descriptive tags to content; 4) Voice-assisted content search and playback enabled by voice assistants; 5) Network optimization to balance video quality and bandwidth.
This White Paper outlines dramatic advances in content discovery, search and recommendation that will improve the business prospects for service providers, broadcasters and other content owners. It explains the revolution in metadata technology and processes that underpin these advances. It demonstrates clearly how an advanced content metadata system improves the user experience and helps to drive loyalty, differentiation and revenues for both broadcast and digital services.
This White Paper outlines dramatic advances in content discovery, search and recommendation that will improve the business prospects for service providers, broadcasters and other content owners. It explains the revolution in metadata technology and processes that underpin these advances. It demonstrates clearly how an advanced content metadata system improves the user experience and helps to drive loyalty, differentiation and revenues for both broadcast and digital services.
Building Smart Natural Language Applications with Data Ninja Services Data Ninja API
Text Analysis-This presentation was given at New Frontiers in Computing (NFIC) in connection with IEEE. Our mission is to enable companies of all sizes to build smart services with content intelligence without having in-house advanced data science and machine learning teams.
Vision: Image-processing algorithms to smartly identify, caption and moderate your pictures
Computer vision: Distill actionable information from images
Content Moderator: Automatically moderate potentially offensive images, text and videos
Customer Vision Service: Train a web service to recognize specific content in images
Face: Identify human faces and emotions in images
Video indexer: Easily extract insights from your videos to enrich your applications
Speech: Convert spoken audio into text, use voice for verification, or add speaker recognition to your app
Bing Speech: Convert speech to text and text to speech
Speaker Recognition: Use speech to identify and authenticate individual speakers
Custom Speech Service: Overcome speech recognition barriers like speaking style, background noise, and vocabulary
Translator Speech: Easily conduct real-time speech translation on your app
Language: Enable your apps to process natural language with pre-built scripts, evaluate sentiment and learn how to recognize what users want
Bing Spell Check: Add spell checking functionality to your app
Language Understanding (LUIS): Add language understanding intelligence to your apps with minimal effort
Linguistic Analysis: Easily parse complex text with language analysis
Text Analytics: Easily evaluate sentiment, language, and key phrases to understand what users want
Translator Text: Easily conduct machine translation for 60+ languages
Knowledge: Map complex information and data in order to solve tasks such as intelligent recommendations and semantic search
Knowledge Exploration Service: Enable interactive search experiences over structured data via natural language inputs
Entity Linking Service: Power your app's data links with named entity recognition and disambiguation
Academic Knowledge: Tap into the wealth of academic content in the Microsoft Academic Graph using the Academic Knowledge API
QnA Maker: Distill information into an easy-to-navigate FAQ for bot services
Customer Decision Service: Create custom experiences with adaptive, contextual decision-making
Search: Add Bing Search APIs to your apps and harness the ability to comb billions of webpages, images, videos, and news with a single API call
Bing Autosuggest: Give your app intelligent autosuggest options for searches
Bing News Search: Search for news and get comprehensive results
Bing Web Search: Get enhanced search details from billions of web documents
Bing Entity Search: Enrich your experiences by identifying and augmenting entity information from the web
Bing Image Search: Search for images and get comprehensive results
Bing Video Search: Search for videos and get comprehensive results
Bing Custom Search: Create tailored site search or vertical search experiences for topics you care about
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This case study was done as a part of my class assignment for Introduction of Analytics. It explains how Netflix uses Big Data and why is so successful.
Why I chose Netflix
Netflix: Stepping into Streaming
CLV used in Netflix
How Netflix uses Big Data and Analytics
Latest Relevant News!!
Conclusion
Overview of Data and Analytics Essentials and FoundationsNUS-ISS
As companies increasingly integrate data across functions, the boundaries between marketing, sales and operations have been blurring. This allows them to find new opportunities that arise by aligning and integrating the activities of supply and demand to improve commercial effectiveness. Instead of conducting post-hoc analyses that allow them to correct future actions, companies generate and analyze data in near real-time and adjust their operations processes dynamically. Transitioning from static analytics outputs to more dynamic contextualized insights means analytics can be delivered with increased relevance closer to the point of decision.
This talk will cover the analytics journey from descriptive, predictive and prescriptive analytics to derive actionable and timely insights to improve customer experience to drive marketing, salesforce and operations excellence.
Semantic video analysis & content search ( SVACS) uses machine learning and natural language processing (NLP) to make media clips easy to query, discover and retrieve. It can also extract and classify relevant information from within videos themselves.
Understanding Semantic Search and AI Content to Drive Growth in 2023 March 2023TysonStockton1
Exploring modern search engines, semantic search, and AI technology to better understand how we can integrate into SEO strategy and content initiatives.
With the rise of ChatGPT there has been a lot of discussion around if SEO content is good or bad. To best determine how to leverage this technology in SEO workflows we must revisit how a modern search engine works and where we are at with AI technology.
In this presentation, we describe how a text analytics command center can help you create a strategy for analyzing & integrating both social & private data.
As more and more enterprises look at leveraging the capabilities of public clouds, they face an array of important decisions. for example, they must decide which cloud(s) and what technologies they should use, how they operate and manage resources, and how they deploy applications.
Building Smart Natural Language Applications with Data Ninja Services Data Ninja API
Text Analysis-This presentation was given at New Frontiers in Computing (NFIC) in connection with IEEE. Our mission is to enable companies of all sizes to build smart services with content intelligence without having in-house advanced data science and machine learning teams.
Vision: Image-processing algorithms to smartly identify, caption and moderate your pictures
Computer vision: Distill actionable information from images
Content Moderator: Automatically moderate potentially offensive images, text and videos
Customer Vision Service: Train a web service to recognize specific content in images
Face: Identify human faces and emotions in images
Video indexer: Easily extract insights from your videos to enrich your applications
Speech: Convert spoken audio into text, use voice for verification, or add speaker recognition to your app
Bing Speech: Convert speech to text and text to speech
Speaker Recognition: Use speech to identify and authenticate individual speakers
Custom Speech Service: Overcome speech recognition barriers like speaking style, background noise, and vocabulary
Translator Speech: Easily conduct real-time speech translation on your app
Language: Enable your apps to process natural language with pre-built scripts, evaluate sentiment and learn how to recognize what users want
Bing Spell Check: Add spell checking functionality to your app
Language Understanding (LUIS): Add language understanding intelligence to your apps with minimal effort
Linguistic Analysis: Easily parse complex text with language analysis
Text Analytics: Easily evaluate sentiment, language, and key phrases to understand what users want
Translator Text: Easily conduct machine translation for 60+ languages
Knowledge: Map complex information and data in order to solve tasks such as intelligent recommendations and semantic search
Knowledge Exploration Service: Enable interactive search experiences over structured data via natural language inputs
Entity Linking Service: Power your app's data links with named entity recognition and disambiguation
Academic Knowledge: Tap into the wealth of academic content in the Microsoft Academic Graph using the Academic Knowledge API
QnA Maker: Distill information into an easy-to-navigate FAQ for bot services
Customer Decision Service: Create custom experiences with adaptive, contextual decision-making
Search: Add Bing Search APIs to your apps and harness the ability to comb billions of webpages, images, videos, and news with a single API call
Bing Autosuggest: Give your app intelligent autosuggest options for searches
Bing News Search: Search for news and get comprehensive results
Bing Web Search: Get enhanced search details from billions of web documents
Bing Entity Search: Enrich your experiences by identifying and augmenting entity information from the web
Bing Image Search: Search for images and get comprehensive results
Bing Video Search: Search for videos and get comprehensive results
Bing Custom Search: Create tailored site search or vertical search experiences for topics you care about
Crunching Popcorn Numbers : How Data Science Shapes Film Franchisesdijalvincent1
Data science plays a crucial role in the success and sustainability of film franchises by providing valuable insights that inform strategic decision-making. Through the analysis of audience behavior, preferences, and demographic data, data scientists help film studios optimize marketing efforts, tailor content to specific target audiences, and predict trends.
Digital-Marketing-Trends-and-Future-Predictions.pptxBiswadeep Das
Digital Marketing Trends and Future Predictions encompass the dynamic landscape of strategies and technologies shaping the way businesses engage with their audiences. With the rapid evolution of technology, these trends highlight the direction that marketing strategies are taking to stay relevant and effective. From the integration of artificial intelligence and chatbots for personalized customer interactions, to the rise of voice search optimization and video content dominance, these trends reflect the changing consumer behaviors and preferences. Additionally, as data privacy concerns grow, marketers are challenged to find innovative ways to gather insights while respecting user privacy. As we look ahead, the future of digital marketing holds exciting possibilities, such as the integration of augmented reality for immersive brand experiences, the utilization of blockchain for transparent and secure transactions, and the ongoing fusion of data analytics and creative storytelling for more impactful campaigns. By staying attuned to these trends and predictions, businesses can stay ahead of the curve and effectively connect with their target audiences in the ever-evolving digital landscape.
This case study was done as a part of my class assignment for Introduction of Analytics. It explains how Netflix uses Big Data and why is so successful.
Why I chose Netflix
Netflix: Stepping into Streaming
CLV used in Netflix
How Netflix uses Big Data and Analytics
Latest Relevant News!!
Conclusion
Overview of Data and Analytics Essentials and FoundationsNUS-ISS
As companies increasingly integrate data across functions, the boundaries between marketing, sales and operations have been blurring. This allows them to find new opportunities that arise by aligning and integrating the activities of supply and demand to improve commercial effectiveness. Instead of conducting post-hoc analyses that allow them to correct future actions, companies generate and analyze data in near real-time and adjust their operations processes dynamically. Transitioning from static analytics outputs to more dynamic contextualized insights means analytics can be delivered with increased relevance closer to the point of decision.
This talk will cover the analytics journey from descriptive, predictive and prescriptive analytics to derive actionable and timely insights to improve customer experience to drive marketing, salesforce and operations excellence.
Semantic video analysis & content search ( SVACS) uses machine learning and natural language processing (NLP) to make media clips easy to query, discover and retrieve. It can also extract and classify relevant information from within videos themselves.
Understanding Semantic Search and AI Content to Drive Growth in 2023 March 2023TysonStockton1
Exploring modern search engines, semantic search, and AI technology to better understand how we can integrate into SEO strategy and content initiatives.
With the rise of ChatGPT there has been a lot of discussion around if SEO content is good or bad. To best determine how to leverage this technology in SEO workflows we must revisit how a modern search engine works and where we are at with AI technology.
In this presentation, we describe how a text analytics command center can help you create a strategy for analyzing & integrating both social & private data.
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Global Interconnection Group Joint Venture[960] (1).pdf
5 current and near-future use cases of ai in broadcast and media.
1. 5 Current and Near-Future
Use Cases of AI in
Broadcast and Media.
PRESENTED BY TYRONE SYSTEMS
2. The aim is to deliver personalized and
targeted experiences to multiscreen
audiences to keep them coming back.
Whether done through big data analysis or
in combination with machine learning
methods, the underlying objective is the
same - that is to display curated content
based on user information, preferences,
watch history, and context.
Content Discovery and
Personalization:
3. To ad targeting, advertisements
can also be tailored to the
audience - based on their
demographics or preferences.
Ad Targeting and Filtering:
4. On content, recognizing images from live or
recorded videos can lead to metadata tags or
descriptive information of a movie or a program
beyond its usual essential attributes (genre,
language, actors, etc.). Such additional
metadata information can then be used to
cluster content by context or also as a basis for
content search and selection.
Content Clustering and
Metadata Building
5. With growing prevalence of voice-assistants
like Amazon's Alexa, and Google Assistant,
pretty soon, you'll just be voicing out context-
sensitive commands to play a particular
movie title, or search for movies released
within a specific time frame, with your
favorite actor in a starring role, and much
more.
Voice-assisted Content Search
& Playback
6. Analyzing available bandwidth and delivering
the best balance between video quality and
streaming bandwidth. Network optimization
can include real-time optimization of codecs,
network paths and data transfers, all to
minimize the amount of data and time to
reach a viewer while ensuring optimum video
quality.
Network Optimization