A new report from MIT and Deep Instinct seeks to dispel confusion in the cybersecurity market ... [ ] between artificial intelligence, machine learning, and deep learning. There are a lot of buzzwords in the world of cybersecurity marketing. When an emerging concept hits a certain viral tipping point, it seems like suddenly all vendors are using the same buzzword--which just makes everything more confusing. Artificial intelligence and machine learning are ubiquitous in cybersecurity marketing--and often confused with each other and with deep learning. A recent report from MIT clarifies the distinction between the three, and emphasizes the value of deep learning for more effective cybersecurity.

Froggett to support accelerating growth and continued international expansion. Froggett was formerly Head of Global Infrastructure Defense, CISO Cybersecurity Services at Citi. In his previous role, Carl was responsible for delivering integrated risk reduction capabilities and services aligned to the architectural, business, and CISO priorities across Citi's devices and networks in 100 countries. Since 1998, he has held various regional and global roles for Citi, covering all aspects of architecture, engineering, global operations, as well as running critical enterprise cyber services for Citi's cybersecurity functions. "Carl has a proven track record in building teams, systems architecture, large scale enterprise software implementation, as well as aligning processes and tools with business requirements and I believe he will play a key role in helping our company grow and scale," said Guy Caspi, CEO of Deep Instinct.

The following is the "100 most noteworthy artificial intelligence companies" compiled by the AI generation (tencentAI) (in alphabetical order by company name): Inspired by recent discoveries about the way the brain processes information, Cortical.io's Retina engine converts language into semantic fingerprints, and then compares the semantic relatedness of any two texts by comparing the degree of overlap of the fingerprints. CrowdFlower is a human intervention training platform for data science teams that helps clients generate high-quality custom training data. The CrowdFlower platform supports a range of use cases including self-driving cars, personal assistants, medical image tagging, content classification, social data analysis, CRM data improvement, product classification and search relevance, and more. Headquartered in San Francisco, CrowdFlower's clients include Fortune 500 and data-driven companies.

Deep Instinct applies deep learning to cybersecurity--going beyond what machine learning can ... [ ] accomplish with a neural network designed to emulate the human brain and learn as it goes. Cyber attacks are not a new issue by any stretch of the imagination--but they are a rapidly growing threat. As the volume and types of technologies businesses and consumers use continues to expand, the attack surface--the configuration errors, vulnerabilities, human errors, or other weaknesses that increase the potential for a successful cyber attack--increases exponentially. To keep pace with the threat landscape, organizations need to rethink their approach to security. According to AVTest, there are more than 18,000 new malware and/or potentially unwanted applications identified every hour.

Deep Instinct applies deep learning to cybersecurity--going beyond what machine learning can ... [ ] accomplish with a neural network designed to emulate the human brain and learn as it goes. Cyber attacks are not a new issue by any stretch of the imagination--but they are a rapidly growing threat. As the volume and types of technologies businesses and consumers use continues to expand, the attack surface--the configuration errors, vulnerabilities, human errors, or other weaknesses that increase the potential for a successful cyber attack--increases exponentially. To keep pace with the threat landscape, organizations need to rethink their approach to security. According to AVTest, there are more than 18,000 new malware and/or potentially unwanted applications identified every hour.

Trumpeting a message that he conceded might be different from peers, Stefan Golling, a member of Munich Re Board of Management, said that Munich Re remains bullish on the cyber insurance and reinsurance markets. In fact, "if insurers and reinsurers shy away from the cyber market, they will not survive," said Golling, Munich Re board member for Global Clients/North America, during a presentation the European reinsurer's virtual Rendez-Vous presentation. He noted media reports of a hardening cyber insurance market, reduced available capacity and narrower carrier and reinsurer appetites for cyber risk. Those shouldn't scare insurers and reinsurers away, Golling said. "If we want to remain relevant in this industry, relevant for our clients, then we need to find solutions for cyber. And we will," he said.

Thanks to the exponential growth of malware, traditional heuristics-based detection regimes have been overwhelmed, leaving computers at risk. Machine learning approaches can help, but the bottleneck presented by the feature engineering step is a potential dealbreaker. The best path forward at this point is deep learning, says the CEO of Deep Instinct, which claims to have taken an early lead in the emerging field. Ten years ago, the cybersecurity industry faced a dilemma. The volume of malware was exploding, with tens of thousands of new types discovered every day.

Where does your enterprise stand on the AI adoption curve? Take our AI survey to find out. Security operations teams have a data management problem: The volume of security alerts they have to process is so high they can miss signs of an attack. In the first Voice of SecOps report from security vendor Deep Instinct, 86% of respondents said tools driven by data science -- which includes artificial intelligence, machine learning, and deep learning -- would make a significant impact in preventing unknown threats and reducing false positives. Above: 90% of in the 2021 Voice of SecOps report said automation frees up teams to focus on high-value and more strategic tasks.

Nowadays, retail industry is in a constant state of transformation. The sector highly depends on data from its own operations and customer analysis as a whole to make crucial decisions. The retailers are attempting to survive the fierce competition on the market and fast-changing customer shopping habits using technology. Artificial intelligence in retail industry comes with several benefits such as predictive merchandising, programmatic advertising, market forecasting, in-store visual monitoring & surveillance, and location-based marketing. The implementation of technology has impacted constant changes in CRM and sales, manufacturing, logistics and customer service.

LONDON--(BUSINESS WIRE)--Deep Instinct, the first and only cybersecurity company to apply end-to-end deep learning to predict, identify, and prevent cyberattacks, is continuing its strategic expansion into EMEA, contracting with T-Systems (Poland), one of the region's largest IT services providers, to utilize and distribute Deep Instinct's protection to its customers. Deep Instinct also signed strategic partnership agreements with Cyber Monks and Spinnakar to distribute Deep Instinct's deep learning-based solution across the region. Leading Deep Instincts' EMEA expansion is Brooks Wallace, VP Sales EMEA, a veteran cybersecurity sales leader with over 20 years of experience in building sales teams. Wallace will oversee the newly opened sales and support office in the UK and forge additional strategic partnerships with MSSPs across the region. "Our expansion into EMEA comes at a critical time for the region, and contracting with T-Systems Poland attests to the unique value of our deep learning-based cyber-attack prevention solution," said Guy Caspi, CEO and Co-founder of Deep Instinct.