Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Responsible AI Licenses (RAIL) are a class of licenses created with the intention of preventing harmful or unethical uses of artificial intelligence while also allowing for the free and open sharing of models between those who intend to use and improve them for authorized purposes. Anyone can make their own version of RAIL for their model, and in doing so can create more or less restrictions than those detailed in the template licenses.

Artificial Intelligence is becoming an integral part of our work. It helps us be more productive by automating tasks, analyzing, and boosting the speed of our work. Due to the desire to accelerate work and make it more efficient, SaaS providers integrate AI into their software. For example, Atlassian in 2023 announced Atlassian Intelligence, a combination of state-of-art OpenAI models and the power and data within the Atlassian platform.

Development teams of all sizes are embracing the excitement and possibility of using AI tools to build software. Coding assistants like Google Gemini and Github Copilot have the potential to accelerate development like never before, and developers are adopting these tools — whether or not leadership has officially approved them. As your team considers the best ways to adopt this new technology, this transition might feel like déjà vu.

In the rapidly changing cybersecurity landscape, Identity and Access Management (IAM) is a critical pillar, safeguarding organizational data and access across different enterprise systems and platforms. As the head of CyberArk’s Artificial Intelligence Center of Excellence (AI CoE), I’m witnessing firsthand the transformative impact of artificial intelligence (AI) in this domain.

RSA Conference, held annually in San Francisco in the spring, defines itself as an information security event that connects industry leaders and highly relevant information. 50,000 people attended in 2024, and of course, the Sumo Logic team was there to offer insights and to learn from others at the conference. During a LinkedIn Live from the show, Sumo Logic VP of Product Marketing Michael Cucchi talked about the show floor being noisy and repetitive.

AI is everywhere—but how can you be sure that your data isn’t being used to train the AI models that power your favorite SaaS apps like Slack? This topic reached a fever pitch on Hacker News last week, when a flurry of Slack users vented their frustrations about the messaging app’s obtuse privacy policy. The main issue?

The content of this post is solely the responsibility of the author. LevelBlue does not adopt or endorse any of the views, positions, or information provided by the author in this article.

Since ChatGPT launched in November 2022, generative AI has emerged as one of the fastest-adopted technologies in the workplace ever. But, as seen in past paradigm shifts like cloud computing, the productivity benefits of this new technology are balanced with new risks.

Artificial intelligence (AI) has a long and storied history. Ancient Greeks, for example, told stories of Talos, an enormous automaton that stood guard over Crete’s shores. In the 17th century, Gottfried Leibniz, Thomas Hobbes, and René Descartes explored the possibility that all rational thought could be as systematic as algebra or geometry.