Operations | Monitoring | ITSM | DevOps | Cloud

Technology

The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!

Challenges & limitations of LLM fine-tuning

Large Language Models (LLMs) like GPT-3 have revolutionized the field of artificial intelligence, offering unprecedented capabilities in natural language processing. Fine-tuning these models to specific tasks or datasets can enhance their performance. However, this process presents unique challenges and limitations that must be addressed. This article explores the intricacies of LLM fine-tuning, shedding light on the obstacles and constraints faced in this advanced AI domain.

The Role of Electronic Evidence in Modern Criminal Defense: A Comprehensive Guide

In the digital age, electronic evidence has increasingly become an important part of criminal defense. In this era of technology, electronic evidence has taken on a central role in the legal world. In this guide, we will explain the role and significance of electronic evidence in modern criminal defense.

Does Step Function's new TestState API make end-to-end tests obsolete?

Step Function added support for testing individual states . Which lets you execute individual states with the following: And returns the following: With the TestState API, you can thoroughly test every state and achieve close to 100% coverage of a state machine. So, does this eliminate the need for Step Functions Local ? Can we do away with end-to-end tests as well? If not, where should this new API fit into your workflow, and how should you use it?

Emerging AI use cases in ITSM Knowledge management, chatbots and self-service

AI experts Louis Columbus and Susan Fung explore AI use cases in IT service management, highlighting how a symbiotic relationship between AI and human intelligence amplifies knowledge management capabilities and enhances user experiences by providing direct answers that synthesize complex information.

Navigating AI in SOC

With notable advancements in Artificial Intelligence (AI) within cybersecurity, the prospect of a fully automated Security Operations Center (SOC) driven by AI is no longer a distant notion. This paradigm shift not only promises accelerated incident response times and a limited blast radius but also transforms the perception of cybersecurity from a deterrent to that of an innovation enabler.

What's in store for AI in 2024 with Patrick Debois

In this episode, Rob is joined by Patrick Debois, a seasoned industry expert and DevOps pioneer. Patrick shares his personal odyssey within the realm of DevOps, reflecting on the current state of the industry compared to his initial expectations. The conversation delves into the convergence of business analytics and technical analytics, exploring innovative approaches developers are adopting to integrate generative AI into their products.

Prompt engineering: A guide to improving LLM performance

Prompt engineering is the practice of crafting input queries or instructions to elicit more accurate and desirable outputs from large language models (LLMs). It is a crucial skill for working with artificial intelligence (AI) applications, helping developers achieve better results from language models. Prompt engineering involves strategically shaping input prompts, exploring the nuances of language, and experimenting with diverse prompts to fine-tune model output and address potential biases.

Now's The Time For Delayed Open Source

Sentry was born and bred in the Open Source community, and we very much think of ourselves as part of it today. One thing we’ve learned together over the years is that an over-emphasis on user freedom can come at the cost of developer sustainability, to the point that we are now in an Open Source sustainability crisis.

IoT Monitoring Challenges

With the increasing prevalence of IoT devices, which are being used in a wide range of applications, from smart homes and cities to industrial and agricultural systems, monitoring thei performance and health is extremely important. However, it’s essential to remember that monitoring IoT devices involves more than just tracking device-level data. In addition, monitoring data from the IoT platform or application layer is equally important.