Blockchain technology and cryptocurrencies are poised to influence the rate and direction of innovation. By allowing firms to perform costless verification, blockchain lowers the cost of auditing transaction information and allows new marketplaces to emerge. Adding a distributed ledger to the mix allows marketplaces to be bootstrapped without the need for traditional intermediaries. How will this technology challenge existing revenue models? What impact will it have on the regulation, auction, and provision of public goods, software, identity, and reputation systems? With research grounded in economic theory, Catalini will discuss how blockchain is poised to upset the global market.
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Moderator: Margaret Childs Panels: Sinan Aral, Frank Schweitzer, Shermin Voshmgir We’re in a continuous struggle to combat falsity. It’s a Wild, Wild West with verification a moving target. New digital media platforms based on block chain can run applications exactly as programmed without the possibility of downtime, censorship, fraud, or third-party interference. Still, we do not know enough about the phenomenon of falsity and why it spreads so readily on digital media. But, we may be closer to answers—and interventions—since we now have data at scale and are on the brink of a revolution understanding how humans behave. The panel will discuss possible interventions to mitigate and hopefully prevent the spread of falsity including how new digital media platforms will algorithmically redefine confirmation, validation, and value. How could blockchain and tokenization of social media based on examples like provide a solution to these problem? What can we learn from early blockchain use cases like Steemit, Basic Attention Token (BAT), and Token Curated Registries (TCRs).
Video can be used as the input data for the real-time monitoring of machines, products, or processes to which sensors cannot be affixed. Industrial and scientific monitoring applications, compared to other video sources, such as those from surveillance, broadcast, mobile robotics, social media, or entertainment, can often be engineered and structured. Yet, applications of video-based instrumentation in industrial, manufacturing, and scientific experimentation environments are not extensively addressed by the computer vision community.
We discuss the needs, challenges, and recent success in deploying real-time, data-science enabled techniques to efficiently reduce the complexity and dimensionality of raw video data to extract actionable information for real-time feedback and process control, defect detection, and wear and degradation related for factories and the factory subsystem.