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Synergies raises $12M to give factory managers an AI analytics assistant – TechCrunch

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There's no lack of startups around the world trying to make industrial activities more efficient with artificial intelligence. Some invent robots to assist or replace manual labor, while others use machine learning to help businesses discover insights. Synergies Intelligent Systems falls into the second category. Michael Chang founded Synergies in 2016 in Boston to provide easy-to-use AI-powered analytics tools to medium-sized manufacturers. Having worked at Foxconn in Shenzhen in the late 2000s helping the Apple supplier improve yield rate, or reduce the percentage of defective products, using data analysis, Chang realized that not every factory has the financial prowess to spend tens of thousands of dollars on digitization.


Top 10 Synthetic Data StartupsMaking a Mark in the Tech Sphere

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Designing good data-driven models hugely depends on the quality of data. Well, data is a set of numbers, and shouldn't bother the developers much. As they say, the devil lies in the details, real data comes with a set of issues like imbalanced classes, inherent biases, unstructured values, etc. On the other hand, synthetic data provides the developers with the flexibility of scalability of data and freedom from biases, opening a whole lot of possibilities for creating a model that doesn't exist in the real world. In addition, synthetic data holds the benefits of protecting user data privacy all while giving the freedom to experiment with.


Artificial Intelligence and Automated Systems Legal Update (1Q22)

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Secretary shall support a program of fundamental research, development, and demonstration of energy efficient computing and data center technologies relevant to advanced computing applications, including high performance computing, artificial intelligence, and scientific machine learning.").


Real-time Analytics News for Week Ending April 30 - RTInsights

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In this week's real-time analytics news: HPE launched HPE Swarm Learning, a privacy-preserving, decentralized machine learning framework for the edge. Keeping pace with news and developments in the real-time analytics market can be a daunting task. We want to help by providing a summary of some of the important news items our staff came across this week. Hewlett Packard Enterprise (HPE) announced the launch of HPE Swarm Learning, an AI solution to accelerate insights at the edge, from diagnosing diseases to detecting credit card fraud, by sharing and unifying AI model learnings without compromising data privacy. HPE Swarm Learning is a privacy-preserving, decentralized machine learning framework for the edge or distributed sites.


Two Paths for Digital Disability Law

Communications of the ACM

People with disabilities often cannot count on modern digital devices, software, and services to be accessible. Will streaming video platforms include closed captions for viewers who are deaf or hard of hearing? How will virtual assistants work for users with speech disabilities? Can websites be read aloud by text-to-speech engines for readers who are blind or visually impaired? How will smartphones be accessed by people with physical and mobility disabilities?


Senior Data Analyst, Field Analytics

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It's no surprise that 6sense is named a top workplace year after year -- we have industry-leading technology developed and taken to market by a world-class team. Our CEO Jason Zintak was recognized as the #1 CEO in the small & medium business category by Glassdoor's 2021 Top CEO Employees Choice Awards. The 6sense Account-Based Orchestration Platform helps B2B revenue teams better compete and win by putting the power of AI, big data and machine learning behind every member of the B2B revenue team, empowering them to uncover anonymous buying behavior, prioritize fragmented data to focus on accounts in market, and engage resistant buying teams with personalized, multi-channel, multi-touch campaigns. Come join us and see what all the fuss is about. What you'll bring to this role: We move fast and innovate.


The best way to regulate artificial intelligence? The EU's AI Act

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With the Artificial Intelligence Act (AI Act), we have – again – crossed the Rubicon. The die has been cast, there is no way back. We are setting standards for another industry that until now has been left mostly on its own, that has important social functions, and that is of central importance in the global tech rivalry. The European electorate was and still is quite united in demanding rules for digital players while maintaining easy digital access and a competitiveness for all things digital. With the AI Act and other legislation currently under way in such fields as cybersecurity, data, crypto and chips, the European Union is finalizing what it began with the General Data Privacy Regulation (GDPR), the Digital Services Act (DSA) and the Digital Markets Act (DMA). It will surely not be the last time digital policy is undertaken in Brussels, and updates to these regulations are partly already necessary.


AI in the Canadian Financial Services Industry

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In recent years, players within Canada's financial services industry, from banks to Fintech startups, have shown early and innovative adoption of artificial intelligence ("AI") and machine learning ("ML") within their organizations and services. With the ability to review and analyze vast amounts of data, AI algorithms and ML help financial services organizations improve operations, safeguard against financial crime, sharpen their competitive edge and better personalize their services. As the industry continues to implement more AI and build upon its existing applications, it should ensure that such systems are used responsibly and designed to account for any unintended consequences. Below we provide a brief overview of current considerations, as well as anticipated future shifts, in respect of the use of AI in Canada's financial services industry. At a high level, Canadian banks and many bank-specific activities are matters of federal jurisdiction.


What Stanford's recent AI conference reveals about the state of AI accountability

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We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. As AI adoption continues to ramp up exponentially, so is the discussion around -- and concern for -- accountable AI. While tech leaders and field researchers understand the importance of developing AI that is ethical, safe and inclusive, they still grapple with issues around regulatory frameworks and concepts of "ethics washing" or "ethics shirking" that diminish accountability. Perhaps most importantly, the concept is not yet clearly defined. While many sets of suggested guidelines and tools exist -- from the U.S. National Institute of Standards and Technology's Artificial Intelligence Risk Management Framework to the European Commission's Expert Group on AI, for example -- they are not cohesive and are very often vague and overly complex.


AI can now kill those annoying cookie pop-ups

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The EU may have brought freedoms, peace, and wealth to millions of people, but all those benefits have been nullified by one horrendous drawback: cookie pop-ups. The consent banners enforced by the bloc's privacy regulations are among the internet's most irritating features. The lawmakers behind them may have had good intentions, but they've merely trained us to blindly click through every notification. After years of suffering this digital torture, a new AI tool has finally offered hope of an escape. Named CookieEnforcer, the system was created by researchers from Google and the University of Wisconsin-Madison. The system was created to stop cookies from manipulating people into making website-friendly choices which put their privacy at risk.