Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AT&T Cybersecurity featured a dynamic cyber mashup panel with Akamai, Palo Alto Networks, SentinelOne, and the Cloud Security Alliance. We discussed some provocative topics around Artificial Intelligence (AI) and Machine Learning (ML) including responsible AI and securing AI. There were some good examples of best practices shared in an emerging AI world like implementing Zero Trust architecture and anonymization of sensitive data. Many thanks to our panelists for sharing their insights.

Artificial Intelligence is a game-changer technology that has created a buzz in today’s market, which we believe you can agree on. How has AI become a game changer in such a short span of time? Well, the hype is real, and it is because of the revolutionary tools and technologies that come into the market. That’s the one side of the coin! What about the other side? Yes, with these modern AI technologies, there is a fear which we overlooked and that’s security.

In recent years almost every company has been utilizing technological solutions like artificial intelligence which has given rise to the importance of Compliance automation. It is a practice to protect the sensitive information of the companies. Hence, Compliance automation software keeps track of the company’s internal systems. Businesses process automation to achieve the main goals of the organizations effectively with the least amount of monitoring.

The realm of artificial intelligence (AI) unfolds like a captivating story, constantly introducing groundbreaking tools and methods that redefine possibilities. Retrieval-augmented generation (RAG), a technology that empowers applications to glean relevant information from vast datasets and utilize it for various tasks, is a prime example of this advancement.

In the realm of AI collaboration, Hugging Face reigns supreme. But could it be the target of model-based attacks? Recent JFrog findings suggest a concerning possibility, prompting a closer look at the platform’s security and signaling a new era of caution in AI research. The discussion on AI Machine Language (ML) models security is still not widespread enough, and this blog post aims to broaden the conversation around the topic.

Artificial intelligence (AI) is now present in almost every aspect of our lives. However, its influence is particularly relevant in the field of cybersecurity, where it impacts both defense and attack. While it has become a great tool to protect an organization's digital assets, it has also been weaponized by cybercriminals to spread and execute increasingly sophisticated and difficult to detect cyberattacks.

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LlamaIndex announces the release of version 0.10.0, a significant step towards enhancing the capabilities of its Python package. This update marks the most substantial overhaul, positioning LlamaIndex as a cutting-edge, production-ready data framework for large language models (LLMs) applications.