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Anodot

Top 10 AI & Data Podcasts You Should Be Listening To

With the speed of change in artificial intelligence (AI) and big data, podcasts are an excellent way to stay up-to-date on recent developments, new innovations, and gain exposure to experts’ personal opinions, regardless if they can be proven scientifically. Great examples of the thought-provoking topics that are perfect for a podcast’s longer-form, conversational format include the road to AGI, AI ethics and safety, and the technology’s overall impact on society.

Outlier Detection: The Different Types of Outliers

Time series anomaly detection is a tool that detects unusual behavior, whether it's hurtful or advantageous for the business. In either case, quick outlier detection and outlier analysis can enable you to adjust your course quickly, before you lose customers, revenue, or an opportunity. The first step is knowing what types of outliers you’re up against. Chief Data Scientist Ira Cohen, co-founder of Autonomous Business Monitoring platform Anodot, covers the three main categories of outliers and how you'll see them arise in a business context.

Data World Highlights: T-Mobile Netherlands, Anodot Discuss the Future of Network Monitoring

During the Data World event, Erwin Halmans, Project Manager of Data-Driven Network Operations & Assurance at T-Mobile Netherlands, Shounit Lax-Swisa, CEO of Company Booster, and Anodot Chief Data Scientist and Co-Founder Ira Cohen got together to discuss the future of network monitoring.

Anodot the business monitoring platform

Business metrics are notoriously hard to monitor because of their unique context and volatile nature. Anodot’s Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time alerts and forecasts in their context. This is machine learning packaged in a turn-key solution – no data science experience needed.

Alicorn Invests $3M in Anodot, Bringing Total Funding to $65.5M

Alicorn Global Ventures has completed an investment of $3 million in Anodot. Recently included in Forbes’ Top 20 Machine Learning Startups to Watch and a leading vendor in the fast-expanding AI analytics space, Anodot is helping companies such as Vimeo, Xandr, Atlassian and T-Mobile to leverage artificial intelligence to surface business incidents much faster and prevent loss.

How Xandr, AT&T's Adtech Company, Prevents Revenue Loss with Autonomous Business Monitoring

Anodot CEO and Co-Founder David Drai joined Amazon Web Services and Xandr to discuss the shift to machine learning-based anomaly detection in business monitoring. Xandr Chief Technology Officer Ben John shared how their advertising marketplace is using Anodot platform to cut detection from “up to a week to less than a day”. You can watch the webinar at the link above or read on for the highlights of that talk.

Anomaly detection 101

What is anomaly detection? Anomaly detection (aka outlier analysis) is a step in data mining that identifies data points, events, and/or observations that deviate from a dataset’s normal behavior. Anomalous data can indicate critical incidents, such as a technical glitch, or potential opportunities, for instance a change in consumer behavior. Machine learning is progressively being used to automate anomaly detection.