Announcements
- Once considered an afterthought, application security risk management is now an integral aspect of application development. The rise of cloud-native adoption and proliferation of microservices has enlarged the attack surface, requiring elevated security measures. Service mesh technologies and API gateways emerge as pivotal solutions, streamlining communication, enhancing reliability, and fortifying security. Join the Advancing Application Security Practices Summit to discover how to bolster your security posture, exploring ways to mitigate security vulnerabilities, manage risks, and fortify against cyberattacks.
- Zero trust adoption has surged in recent years, driven by two main factors: 1). A wave of high-profile data breaches that highlighted the need for enhanced cybersecurity strategies and 2). The COVID-19 pandemic created the need for remote access technologies beyond VPN. While the zero trust model can be highly beneficial, it does have some challenges. That’s why making zero trust cybersecurity as effective as possible starts by understanding its challenges. In the upcoming The Zero Trust Journey: From Concept to Implementation summit, industry leaders, experts and practitioners provide resources and recommendations to help you build a zero trust framework.
Top Stories
- Cybersecurity practices and AI deployments
April 30, 2024
by Dan Wilson
For our 4th episode of the AI Think Tank Podcast, we explored cybersecurity and artificial intelligence with the insights of Tim Rohrbaugh, an expert whose career has traversed the Navy to the forefront of commercial cybersecurity. The discussion focused on the strategic deployment of AI in cybersecurity, highlighting the use of open-source models and the benefits of local deployment to secure data effectively. - Why is AI different? It Can Guide Our Societal Aspirations
April 29, 2024
by Bill Schmarzo
Traditional analytics optimize based on existing data, reflecting past realities, limitations, and biases. In contrast, AI focuses on future aspirations, identifying the learning needed to achieve aspirational outcomes and guiding your evolution toward these outcomes. When I talk to my students, the question I keep getting is, “Is AI really different from traditional analytics?” - Losing control of your company’s data? You’re not alone
April 24, 2024
by Alan Morrison
Losing control of your company’s data? You’re not alone To survive and thrive, data likes to be richly and logically connected across a single, virtually contiguous, N-dimensionally extensible space. In this sense, data is ecosystemic and highly interdependent, just as the elements of the natural world are.
In-Depth
- How long does it take to master data engineering?
April 30, 2024
by Aileen Scott
Data engineers are professionals who specialize in designing, implementing, and managing the systems and processes that transform raw data into usable and trusted information. They play a crucial role in ensuring data integrity and accessibility for downstream analytics and machine learning applications. - Data fitness and its impact potential on enterprise agility
April 30, 2024
by Alan Morrison
I had the opportunity to attend Enterprise Agility University’s prompt engineering course in April. The course provided a helpful agility lens through which to view efforts on how to make large language models useful. An LLM in this current enterprise context is like a herd of unruly sheep—you need plenty of herding dogs and fencing to manage the herd. - Understanding GraphRAG – 1: The challenges of RAG
April 26, 2024
by Ajit Jaokar
Retrieval Augmented Generation(RAG) is an approach for enhancing existing LLMs with external knowledge sources, to provide more relevant and contextual answers. In a RAG, the retrieval component fetches additional information that grounds the response to specific sources and the information is then fed to the LLM prompt to ground the response from the LLM(the augmentation phase). - Optimizing model training: Strategies and challenges in artificial intelligence
April 25, 2024
by Pritesh Patel
When you do model training, you send data through the network multiple times. Think of it like wanting to become the best basketball player. You aim to improve your shooting, passing, and positioning to minimize errors. Similarly, machines use repeated exposure to data to recognize patterns. - Top AI Influencers to Follow in 2024
April 25, 2024
by Vincent Granville
There are many ways to define “top influencer”. You may just ask OpenAI to get a list: see results in Figure 1. However, it states that the data is not recent (2022 and earlier), and there is no link to the individual profiles. Here I focus on leaders very active on LinkedIn, with at least 100k followers, and popping up regularly on my feed. Emphasis is on GenAI and LLM, which are today among the hottest topics in AI. It is also what I am working on. - DSC Weekly 23 April 2024
April 23, 2024
by Scott Thompson
Read more of the top articles from the Data Science Central community.
