When things go wrong and fingers are pointed, who should go down? Should it be managers, executives or IT people? I think it should be all of the above. Recent research from IDC and Zerto (via BusinessWire) identifies a "perception gap" between senior-level IT and C-level executives when it comes to data availability and protection. Based on my own conversations as the CEO of a multicloud data management company, the problem may be even worse than reports like these suggest.

We are pleased to announce an exclusive agreement with Infinnium, a software company delivering innovative solutions to transform information governance and corporate decision-making using artificial intelligence for forensic accounting and related consulting services in the EU. The agreement creates a powerful combination between FRA's global expertise in forensic accounting and consulting expertise with Infinnium's 4iG platform, the innovative suite of technologies empowering modern data governance and privacy law compliance needs of the enterprise. Both FRA and Infinnium have extensive and global cross-border and cross-sector litigation and investigations experience and working together will offer a distinct competitive advantage in the marketplace. Exponential increase of data volume and types across the ever-growing multitude of siloed applications have combined to exceed organizations' ability to manage data conventionally. Organizations face challenges to identify and organize their data, comply with regulatory requirements, apply policy or process, or optimize its value.

Legalist, a San Francisco-based litigation finance company started by two Harvard University dropouts and advised by retired 7th U.S. Circuit Court of Appeals Judge Richard Posner, has just raised $100 million, which it will use to fund plaintiffs in 100-200 commercial cases over the next two years. Legalist scrapes federal and state court records and then uses algorithms to predict case outcomes and determine the best cases in which to invest. It invests exclusively in mid-market cases that require less than $1 million in funding. "Legalist leads the new wave of technologists using artificial intelligence and machine learning to streamline and underwrite litigation investments," says the company's website. "Our proprietary technology has been recognized by leading publications as revolutionizing the way plaintiffs interact with the justice system."

Likewise, banks can be alerted when suspicious activity is flagged up by the data. On their own, financial institutions struggle to identify and disrupt trafficking-related transactions because their data models cannot distinguish money-laundering transactions from trafficking ones. Fortunately, together with data sharing, this all becomes possible. Financial data can be combined with existing NGO and open-source data to identify specific signs of trafficking and the risk level of particular transactions and accounts. With these results, banks can now validate and improve their machine-learning models and educate staff to better identify trafficking-related transactions.

Social media platforms like Facebook use a combination of artificial intelligence and human moderators to scout out and eliminate hate speech. But now researchers have developed a new AI tool that wouldn't just scrub hate speech but would actually craft responses to it, like: "The language used is highly offensive. All ethnicities and social groups deserve tolerance." "And this type of intervention response can hopefully short-circuit the hate cycles that we often get in these types of forums." The idea, she says, is to fight hate speech with more speech--an approach advocated by the ACLU and the U.N. High Commissioner for Human Rights.

AI and its immense potential, spanning a range of areas, can address some of the major issues in Live Streaming. FREMONT, CA: Streaming constitutes a considerable share of all the data moving around. Video forecast is expected to account for 82 percent of internet traffic by 2022. Artificial intelligence (AI) will play a key role in the streaming industry. With AI's capability to impact a range of industry aspects, leaders are trying to utilize the technology to enhance the streaming space as well.

Figure 4 (left) shows that the probability of being a hit paper increases gradually with career and team novelty, but expedition novelty rises much more quickly as the strongest predictor. Papers involving the most unexpected publication events or conversations are 3.5 times more likely than random to be hit papers. Figure 4 (left) also shows that career and team novelties are highly correlated, suggesting that successful teams not only have members from multiple disciplines, but also members with diverse backgrounds who "glue" interdisciplinary teams together (also see Figure S3). Successful knowledge expeditions, however, are the most likely path associated with breakthrough discovery. When regressing content and context novelties of a paper separately on the three background novelty measures, we find that expedition novelty has by far the largest effect on context novelty (), but team novelty has the marginal top effect on . 2 3, p 0 0 1 β 2 .

Machine learning technology is poised to be huge thing in financial services. In fact, two-thirds of UK-based firms are already using it. That is according to two of the UK's top financial regulators. The Financial Conduct Authority (FCA) and the Bank of England have taken a deep dive into how the financial services industry in the country is using machine learning. The research is based on a survey sent out to 300 firms, including banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms.

With over 600,000 bridges across the United States, nearly 8% of which are deemed structurally deficient, monitoring and maintaining our country's infrastructure is critical to ensuring the safety of American motorists. Dynamic Infrastructure, a New York- and Tel Aviv-based startup, is currently implementing an innovative artificial intelligence system that allows infrastructure operators to observe condition changes in real time. The system provides live, cloud-based, 3-dimensional images of the bridge or tunnel, while detecting and alerting the operators to any observed change before it results in a collapse. "The world faces an infrastructure crisis," said Saar Dickman, co-founder and CEO of Dynamic Infrastructure. "Specifically, deficient bridges and tunnels represent a severe infrastructure challenge in the U.S. and worldwide and their poor condition leads to life losses and millions in unplanned expenditures."

Artificial intelligence (AI) algorithms are complex packets of code that strive to learn on given training data. But when this training data is flawed, not well-rounded, or biased, the algorithm quickly spirals into discrimination too. For women and minorities, these systemic AI issues can quickly become harmful. Bias in AI algorithms doesn't only occur because of problems in training data. When you dig deeper, it becomes readily apparent that bias often comes from how an AI developer frames a scenario or problem.