Machine Learning Spam in Google

searchenginejournal.com | January 21, 2020

Spammers are taking advantage of Google Rich Results algorithms in order to place content at the top of Google search. Spammers are taking advantage of machine learning technologies to automatically create video content from web pages and vice versa. The same technology can be used to create text content from podcasts and  podcast content from web pages.This isn’t theory, it’s currently live on Google.  Can Google keep up with machine learning spam? I first noticed the text to video spam when I searched on a news headline.I won’t name the YouTube channel nor the news sites that are having their content “re-purposed” however. The point is to describe a spam technique that currently is live on Google. Who the spammers are is besides the point.

Spotlight

Today, modern computing techniques are capable of easily storing, processing and analyzing large amounts of and a variety of data. These techniques could correlate diverse datasets in order to create individual’s profiles, to gain insights, and to offer new digital services. Among others, three technologies that could play a major role in gaining these capabilities are Cloud computing, Internet of Things (IoT) and Big data. Although developed independently, the integration of these three technologies (referred to as Smart ICT) has accelerated the growth of data-driven applications and has unleashed numerous opportunities for businesses, individuals and the society at large [1].

Spotlight

Today, modern computing techniques are capable of easily storing, processing and analyzing large amounts of and a variety of data. These techniques could correlate diverse datasets in order to create individual’s profiles, to gain insights, and to offer new digital services. Among others, three technologies that could play a major role in gaining these capabilities are Cloud computing, Internet of Things (IoT) and Big data. Although developed independently, the integration of these three technologies (referred to as Smart ICT) has accelerated the growth of data-driven applications and has unleashed numerous opportunities for businesses, individuals and the society at large [1].

Related News

BUSINESS INTELLIGENCE

Cube Dev Announces Universal BI Support

Cube Dev | June 01, 2022

Cube Dev, the open source startup behind the Cube headless BI platform, launched today an improved API that makes its uniform data definitions available to users of all major business intelligence applications. Thousands of businesses, ranging from startups to Fortune 500 corporations, have created data stacks that include cloud data warehouses for data storage, Cube for accessing this data and developing data models, and open source front-end tools for data visualization. This stack has facilitated the development of an ecosystem of bespoke data applications and analytics tools incorporated into mobile and desktop apps. However, a considerably higher proportion of firms employ business intelligence apps and dashboard tools to summarize and store data, with the worldwide market for these applications expected to approach $25 billion USD by 2022. “It has always been our ambition to make Cube’s power accessible to a great diversity of data consumers. Data needs to be consistent and performant not just for developers but also for analysts and general business users. This requires bringing Cube into the tools where these users already work.” Artyom Keydunov, Cube Dev’s Chief Executive Officer and co-founder With the addition of a PostgreSQL interface to the Cube platform today, BI applications like Tableau, Superset, and Microsoft Power BI can query Cube as a data source. That is, these tools consume the same concepts and data as bespoke apps and embedded analytics features that leverage Cube's GraphQL and REST APIs.

Read More

DATA SCIENCE

Wejo Launches Wejo Labs

Wejo Group Limited | June 24, 2022

Wejo Group Limited, a global leader in Smart Mobility cloud and software solutions for interconnected, electrified, and self-driving car data, announced the establishment of Wejo Labs today. Wejo Labs is a cloud-based platform that enables researchers and data scientists from universities, research organizations, and civil and traffic engineering consultancies to conduct large-scale traffic and mobility studies using accurate Connected Vehicle Data (CVD) from tens of millions of connected vehicles in the United States and Europe. Wejo Labs can conduct traffic and mobility research by configuring CVD on vehicle events. In order to promote safety improvements, queries on this data can lead to a better understanding of how road conditions impact driving behaviors, confirm weather conditions with hyper-local data points, assess parking patterns, and recognize routes where hazardous driving happens most frequently. Users can also utilize the CVD to analyze vehicle movements for perspectives into routes and trips, improving origin-destination studies, congestion management, event planning, and high traffic locations. “Part of our smart mobility for good mission at Wejo is to democratize access to the power of connected vehicle data. With Wejo Labs, users can easily experiment with one of the most innovative data sources in the world to create proof of concepts using innovative technology that keeps their research and data analysis ahead of the curve to help shape the future of traffic and road safety. With this platform, researchers’ leverage billions of data points to design future-proof traffic systems and drive the future of smart mobility,” Richard Barlow, Founder and CEO of Wejo. Wejo Labs customers can also explore, query, and analyze CVD using their choice of programming language. Data outputs can then be presented in a variety of ways, such as bar graphs, heat maps, and map layers, to interactively and visually examine data over a specific time period. The platform streamlines the process for users by importing the data for them, geofencing it depending on location and time zone, and then giving them all of the required tools for analysis, with additional help from Wejo's in-house data analytics team.

Read More

BIG DATA MANAGEMENT

CloudFabrix Announces Robotic Data Automation Fabric Availability

CloudFabrix | June 13, 2022

CloudFabrix, the developer of the Robotic Data Automation Fabric (RDAF), which unifies Observability, AIOps, and Automation, has announced its launch on self-service cfxCloud, an AWS-hosted SaaS platform. RDAF's patent-pending method uses Bots and a low-code approach to simplify and automate AIOps and Observability processes. Enterprises have struggled to communicate effectively around their data, limiting their capacity to adapt and thrive with Digital Transformation, gain meaningful insights, and innovate. There is a growing recognition that every AI challenge begins with a data problem. This is causing what Accenture refers to as the "Data Value Gap," in which 80% of effort is spent on data preparation. According to Forrester, 60-70% of gathered data is useless owing to data quality, and 55 percent employ a manual technique, with a skill gap of 50%. Data is siloed, and just 16% report having agile data supply chains. These difficulties are addressed front on by Robotic Data Automation Fabric. Gartner as the No. 1 trend for I/O leaders in 2022 and the No. 3 trend has highlighted data Fabric in 2021. Data Integration and Data Automation address the problem of data preparation and data quality by transforming, enriching, and contextualizing data. Low code 1000+ data and AI Bots Marketplace are used to fill skill gaps. Customers and partners can create new Bots and pipelines or leverage existing pipelines. Low latency, streams-based Data Fabric, capable of ingesting billions of real-time events and messages, addresses data silos at the edge, data center, and multi-cloud. As a result, RDAF provides integrated and enhanced real-time data to operational and analytical workloads and use cases. The RDAF platform provides several real-time data management use cases across sectors, including OSS / BSS for Telcos, MSPs, BFSI, and Healthcare Enterprises. Customer 360, machine data/IoT/Industrial IoT management, operational intelligence to accurately predict customer churn, detect fraud, and deliver customized service, multi-tenant data privacy management, test data management, unifying observability, AIOps, and automation across business and IT systems are a few examples. The RDAF platform used in the form of cfxCloud and cfxEdge, which operate as microservices in AWS cloud or hybrid data centers. The Log Intelligence service, which increases TCO and productivity by 50% and MTTR by 60% for Splunk and SIEM customers, is one of the latest services released utilizing RDAF. Log Intelligence service performs log reduction and correlation while routing full fidelity copies and persisting to either an S3 bucket with timestamps or SnowFlake, enriches log with CVE, MITRE feeds, or geo IP looks-up using Infoblox, performs log replay to your preferred stream, and facilitates EdgeAI and anomaly detection. For end users and consulting channel partners, the Log Intelligence service is accessible on AWS Marketplace as a consumption and contract listing.

Read More