In a series of posts entitled Autonomous Everything, we are exploring automation in all its technological forms, including legacy working assumptions about the term itself. Autonomy is not just about the future of the automobile and personal mobility but includes a broad autonomous future in areas such as Security Automation, Automation and the Workforce, Automation – or Augmentation – of the Workforce, and Automation of AI/Machine Learning Training Models and Industry Standardization.  

Recently, we checked in with OODA Network Member Junaid Islam, a well-known cybersecurity expert, about “Automated Continuous Threat Testing”. We continue this conversation to discuss the increased cyber risks Enterprises face due to the current geo-political environment and actions they should take to mitigate cybersecurity and operational risk.

Open the Pod Bay Door – Resetting the Clock on Artificial Intelligence

Panel Description:  Artificial intelligence is like a great basketball head-fake. We look towards AI while we pass the ball to machine learning. But, that reality is quickly changing. This panel taps AI and machine learning experts to level-set our current capabilities in the field and define the roadmap over the next five years.

In Part 1 of this interview, we checked in with Mergeflow CEO and OODA Network Member Florian Wolf about all things machine learning and small data.

In Part 2, we continue the conversation with Florian spanning a wide range of topics, including the real-life lessons of machine learning innovation, the centrality of data, problem-solving over performance as the competitive advantage while developing ML systems, leading a team, what keeps him up at night, what he is tracking and what he is excited and hopeful about in the future.

On multiple occasions, OODA Network member Florian Wolf has presented to the OODA Network membership on the topic of small data.  An evangelist and subject matter expert on the topic, Wolf is the CEO of Mergeflow, a company he founded in 2007, where he is responsible for company strategy and product design.   Wolf has a Ph.D. in Cognitive Sciences from MIT and is a former research associate in Computer Science and Genetics at the University of Cambridge. Some of his work at MIT was funded by DARPA and he is a member of the Global Panel at MIT Technology Review.  Mergeflow initially developed analytics software for hedge fund investors. We recently checked in with Florian on all things machine learning and “small data”.

More than 24,000 registered attendees descended upon Detroit earlier this month to see the latest products and innovations around the world of robotics and automation at the Automate 2022 event and trade conference. Visitors spoke with more than 600 companies displaying new solutions in the automation space, or heard from

Applying machine learning techniques to its rule-based security code scanning capabilities, GitHub hopes to be able to extend them to less common vulnerability patterns by automatically inferring new rules from the existing ones. GitHub Code Scanning uses carefully defined CodeQL analysis rules to identify potential security vulnerabilities lurking in source

The cybersecurity landscape is evolving more rapidly than ever. Adversaries are becoming increasingly sophisticated, developing new tactics and tools to steal valuable data — and, at times, disrupt business operations and extort ransoms. Concurrently, researchers are advancing technologies for threat prediction, detection, prevention and mitigation with improved effectiveness and efficiency. Artificial

Artificial intelligence (AI) is gaining a lot of traction lately. Apparently, the majority of AI services and products will be in high demand for the next few years. According to Gartner, worldwide AI software revenue is forecast to total $62.5 billion in 2022, and one-third of organizations with AI technology

Closing the gap between their organization’s choice to invest in a data science and machine learning (DSML) strategy and the needs that business units have for results, will dominate data and analytics leaders’ priorities in 2022. Despite the growing enthusiasm for DSML’s core technologies, getting results from its strategies is

The e-commerce platform Shopify has successfully leveraged machine learning through a methodological, five-step strategy. Below we’ll examine each step and detail how it’s helped the company thrive. Shopify’s growth is unparalleled in the e-commerce industry. Collectively, the platform’s merchants make up the 7th largest company in the world in terms of