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Automating Data Collection For AI At Morningstar

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One of the biggest challenges in making AI projects a success is dealing with the requirements for data needed by machine learning systems. Machine learning systems work by generalizing learnings from data, so if that data is insufficient in quantity or poor in quality, then the machine learning project will fail. Nothing is more true for artificial intelligence than the tech adage, "garbage in is garbage out". Shariq Ahmad, head of technology in the data collection group at financial services data firm Morningstar knows this very well. As part of his role at Morningstar, he is responsible for building a pipeline and methodology for dealing with large quantities of data in a wide variety of formats, qualities, and levels of completeness and accuracy to support big data projects, including those that support their machine learning efforts.


New AI 'Deep Nostalgia' brings old photos, including very old ones, to life

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An AI-powered service called Deep Nostalgia that animates still photos has become the main character on Twitter this fine Sunday, as people try to create the creepiest fake "video" possible, apparently. The Deep Nostalgia service, offered by online genealogy company MyHeritage, uses AI licensed from D-ID to create the effect that a still photo is moving. It's kinda like the iOS Live Photos feature, which adds a few seconds of video to help smartphone photographers find the best shot. But Deep Nostalgia can take photos from any camera and bring them to "life." The program uses pre-recorded driver videos of facial movements and applies the one that works best for the still photo in question.


MyHeritage now lets you animate old family photos using deepfakery – TechCrunch

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AI-enabled synthetic media is being used as a tool for manipulating real emotions and capturing user data by genealogy service MyHeritage, which has just launched a new feature -- called "deep nostalgia" -- that lets users upload a photo of a person (or several people) to see individual faces animated by algorithm. The Black Mirror-style pull of seeing long-lost relatives -- or famous people from another era -- brought to a synthetic approximation of life, eyes swivelling, faces tilting as if they're wondering why they're stuck inside this useless digital photo frame, has led to an inexorable stream of social shares since it was unveiled yesterday at a family history conference… This is my great-grandmother, Kathleen. I've always felt so close to her even though she died when I was 2 years old. This #DeepNostalgia video brought tears to my eyes to see her move, almost like seeing her as she was posing for this photo. MyHeritage's AI-powered viral marketing playbook with this deepfakery isn't a complicated one: They're going straight for tugging on your heart strings to grab data that can be used to drive sign-ups for their other (paid) services.


Progress Toward the Intelligent Enterprise

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If achieving the intelligent enterprise were easy, everyone would have done it by now. The road to creating, or re-creating, a business optimized by AI to take advantage of machine-assisted decision-making at all levels of the organization is a long one. Two key questions are, how far along are we on the path toward achieving this vision of future productivity, and are there ways organizations can improve their odds of success? Companies are now directing billions of dollars globally each year toward AI development, yet more often than not, they're frustrated by the lack of progress. In fact, only 1 in 10 managers who responded to a recent global survey conducted by MIT SMR and BCG could point to tangible returns.


Amazon AI patent could spell the end for voiceover actors

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A new plan by Amazon to use artificial intelligence (AI) to dub films could spell the end for voiceover actors. The technology giant has patented a system that would see computers learn the voices of Hollywood stars such as Tom Cruise by studying their films. Amazon's computer systems could then automatically generate foreign language versions without any need for voiceover actors to dub the audio. The company used the example of "The Last Samurai" as an example use of the technology in its patent filing. By analysing how Cruise sounds in other films such as "Mission Impossible" and "Rain Man," Amazon could recreate his lines from "The Last Samurai" in French or Polish while still sounding recognisable.


2021-2026 Enterprise Artificial Intelligence Market: Analysis by Business Growth, Development Factors, Applications, and Future Prospects – The Bisouv Network

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Global "Enterprise Artificial Intelligence Market" report provides qualitative and quantitative information covering market size breakdown, revenue, and growth rate by important segments. The Enterprise Artificial Intelligence market report provides a competitive landscape of major players with the current industry scenario, market concentration status. The report study explores the information on production, consumption, export, and import of Enterprise Artificial Intelligence market in each region. The Enterprise Artificial Intelligence Market is fairly fragmented. The Enterprise Artificial Intelligence Market report profiles some of the key market players while reviewing significant market developments and strategies adopted by them.


Rethinking The Artificial Intelligence Race - Analysis - Eurasia Review

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Artificial intelligence (AI) has become a buzzword in technology in both civilian and military contexts. With interest comes a radical increase in extravagant promises, wild speculation, and over-the-top fantasies, coupled with funding to attempt to make them all possible. In spite of this fervor, AI technology must overcome several hurdles: it is costly, susceptible to data poisoning and bad design, difficult for humans to understand, and tailored for specific problems. No amount of money has eradicated these challenges, yet companies and governments have plunged headlong into developing and adopting AI wherever possible. This has bred a desire to determine who is "ahead" in the AI "race," often by examining who is deploying or planning to deploy an AI system.


An introduction to Explainable Artificial Intelligence or xAI

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A few years ago, when I was still working for IBM, I managed an AI project for a bank. During the final phase, my team and I went to the steering committee to present the results. Proud as the project leader, I have shown that the model has achieved 98 percent accuracy in detecting fraudulent transactions. In my manager's eyes, I could see a general panic when I explained that we used an artificial neural network, that it worked with a synapse system and weight adjustments. Although very efficient, there was no way to understand its logic objectively. Even if it was based on real facts, this raw explanation conditioned the project's continuity at that time, unless we could provide a full explanation that the senior executive could understand and trust.


How Tata Steel Uses AI: A Case Study

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Tata Steel is one of the prominent names in the steel-making industry boasting over three decades of manufacturing expertise. The company is currently the world's second-most geographically-diversified steel producer, with fully integrated operations -- from mining to the manufacturing and marketing of finished products. To sustain its leadership position in a volatile market, Tata Steel needed to fortify its supply chain. Poor visibility of in-plant operations was causing delays in loading trucks. This, in turn, triggered a series of inefficiencies like traffic congestions, parking problems, and forced route diversions for inbound/outbound vehicles.