Facial recognition software provider Clearview AI has revealed that its entire client list was stolen by someone who'gained unauthorized access' to company documents and data. According to a notice sent to its customers, Cleaview AI said that in addition to its client list, the intruder had gained access to the number of user accounts associated with each client, as well as the number of searches conducted through those accounts. The company didn't specify how the security breach had occurred nor who might have been responsible, and it claimed its servers and internal network hadn't been compromised. Facial recognition software company Clearview AI has revealed a security breach that exposed it's client list and number of searches those clients made'Unfortunately, data breaches are part of life in the 21st century,' Clearview attorney Tor Ekeland told The Daily Beast, who broke the story. 'Our servers were never accessed.
The exponential growth of data has had an inverse impact on the ability of businesses to gain value from their data through traditional rules-based programming. Machine Learning is viewed as an essential enabler that will allow applications to act on the collection of new data sets to improve their predictive capabilities. This white paper shows how Talend and AWS are bridging the gap between data scientists and data engineers to operationalize ML.
SalesChoice Inc., an award winning AI SaaS Sales Platform is expanding its USA market coverage as it enters its Scale Up Plans in the Guided Selling and Responsible AI Market place. This is the amazing story of what made a veteran Silicon Valley sales leader join SalesChoice. The global artificial intelligence software market is expected to experience massive growth in the coming years, with revenues increasing from around 9.5 billion U.S. dollars in 2018 to an expected 118.6 billion by 2025, according to the market research firm Tractica. "We wanted to ensure we recruit only talent that can see beyond where we are today in Sales Enablement and can help guide our customers to a more productive top line revenue growth realization. The reality is B2B Sales Productivity is rapidly declining and CRM systems, have in many cases been empty and unproductive vessels of incomplete or inaccurate data. Our software is uncannily simple where every move you make on opportunities or accounts, determines your odds, like in chess. AI gives Sales professionals an edge that we have never had before, by blending Science and Relationships into a stronger formula that no longer focusses only a segment of sales but on the entire journey. We wanted to go beyond just forecasting or predictions to enable sales teams end-to-end. Accordingly, we had to ensure that we recruited strong sales talent that were passionate about the changes with AI Enablement, and also have been in the trenches in both mid and large enterprises with robust CRM operational experiences and valued fact based leadership, something I deeply learned from my Xerox Leadership experience. We found these leadership skills in Steve Levy who recently joined our Sales and Marketing Leadership Team to advance our USA market coverage in the Silicon Valley," says Dr. Cindy Gordon, CEO and Founder, SalesChoice Inc. Steve Levy, Strategic Advisor and Silicon Valley Scale Up Leader, shares his story: The journey to SalesChoice for me started three decades ago in Redwood City, California.
Artificial intelligence and machine learning are increasingly embraced by U.S. carriers as they seek to remain competitive and modernize their operations, a new LexisNexis Risk Solutions study has found. Struggles remain, however, in terms of figuring out staffing and proper use of the technology to optimize its benefits. LexisNexis' look at how the top 100 U.S. carriers are using and benefiting from artificial intelligence and machine learning found a robust adoption of the technology and a strong belief in the benefits it will bring. Approximately 62 percent of respondents said they worked for insurance carriers that have already adopted artificial intelligence (AI) and machine learning (ML) initiatives. About 75 percent said they believe AI and ML can provide carriers with a competitive advantage through better decision-making.
At a technical level, artificial intelligence seems to be the future of software. AI is showing remarkable progress on a range of difficult computer science problems, and the job of software developers – who now work with data as much as source code – is changing fundamentally in the process. Many AI companies (and investors) are betting that this relationship will extend beyond just technology – that AI businesses will resemble traditional software companies as well. Based on our experience working with AI companies, we're not so sure. We are huge believers in the power of AI to transform business: We've put our money behind that thesis, and we will continue to invest heavily in both applied AI companies and AI infrastructure. However, we have noticed in many cases that AI companies simply don't have the same economic construction as software businesses. At times, they can even look more like traditional services companies. Anecdotally, we have seen a surprisingly consistent pattern in the financial data of AI companies, with gross margins often in the 50-60% range – well below the 60-80% benchmark for comparable SaaS businesses.
How well do Robinhood's financials stack up against incumbent online brokerages? While we wait for the seven-year-old company's long-planned IPO, Alex Wilhelm examined Morgan Stanley's big $13 billion purchase of E-Trade for fresh data comparison points. Robinhood has 10 million accounts -- twice what E-Trade has -- but it also appears to make much less money per user and has far fewer assets under management, as he covered for Extra Crunch. So while its fee-free approach has destroyed a key revenue stream for competitors, it still has to grow its own "order-flow" business into its private-market valuation. One solution is to make the platform stickier via social features.
At a technical level, artificial intelligence seems to be the future of software. AI is showing remarkable progress on a range of difficult computer science problems, and the job of software developers – who now work with data as much as source code – is changing fundamentally in the process. Many AI companies (and investors) are betting that this relationship will extend beyond just technology – that AI businesses will resemble traditional software companies as well. Based on our experience working with AI companies, we're not so sure. We are huge believers in the power of AI to transform business: We've put our money behind that thesis, and we will continue to invest heavily in both applied AI companies and AI infrastructure. However, we have noticed in many cases that AI companies simply don't have the same economic construction as software businesses. At times, they can even look more like traditional services companies.
The key concepts in Machine Learning How AI applications and their development are reshaping company's IT How enterprises are applying devops practices to their ML infrastructure and workflows How Canonical's AI / ML portfolio from Ubuntu to Charmed Kubernetes and and how to get started quickly with your project How AI applications and their development are reshaping company's IT How Canonical's AI / ML portfolio from Ubuntu to Charmed Kubernetes and and how to get started quickly with your project What is an AI model? How do you train it? How do you develop / improve it? How do you execute it? What is an AI model?
A few days ago, Andreessen Horowitz's Martin Casado and Matt Bornstein published an interesting piece digging into the world of artificial intelligence (AI) startups, and, more specifically, how those companies perform as businesses. Core to the argument presented is that while founders and investors are wagering "that AI businesses will resemble traditional software companies," the well-known venture firm is "not so sure." Given that TechCrunch cares a lot about startup business fundamentals, the notion that one oft-discussed and well-funded category of venture-backed startup might sport materially less attractive economics than we expected captured our attention. The Andreessen Horowitz (a16z) perspective is straightforward, arguing that AI-focused companies have lesser gross margins than software companies due to cloud compute and human-input costs, endure issues stemming from "edge-cases" and enjoy less product differentiation from competing companies when compared to software concerns. Today, we're drilling into the gross margin point, as it's something inherently numerical that we can get other, informed market participants to weigh in on.
Microsoft on Wednesday unveiled several new artificial intelligence capabilities across Dynamics 365 applications and a new solution to help project-centric services organizations transform their operations. The AI enhancements include first- and third-party data connections in Dynamics 365 Customer Insights, Microsoft's customer data platform (CDP). "The work in AI and CDP is new and a key part of Microsoft taking their products to an AI-driven approach," noted Ray Wang, principal analyst at Constellation Research. The company also unveiled new manual and predictive forecasting capabilities for Dynamics 365 Sales and Dynamic 365 Sales Insights. "Integration with the CDP is important, but more important will be the ability to automate transactions and apply AI to drive the next best action," Wang told CRM Buyer.