#llms

#llms

The 5th International Conference on Computing and Communication Networks (ICCCNet-2025) concluded on a high note at Manchester Metropolitan University, solidifying its reputation as a premier platform for global innovation. From August 1-3, 2025, the conference became a crucible for ideas, bringing together brilliant minds from academia, industry, and government to forge the future of technology. The prestigious best paper awards, announced at the close of the event, weren't just accolades; they were a roadmap to a more intelligent, sustainable, and equitable world.

"There are definitely some groups that are using AI to aid with the development of ransomware and malware modules, but as far as Recorded Future can tell, most aren't," says Allan Liska, an analyst for the security firm Recorded Future who specializes in ransomware. "Where we do see more AI being used widely is in initial access."

First things first, you're going to select your LLM. You can go with OpenAI. It's a pretty standard choice for your Hello World. You're going to go to the documentation and you'll see how to actually do a Hello World using OpenAI. Of course, you'll see Python over there. Python is always there. I'm going to count as a win because we're starting to see examples in Java as well.

Large language models (LLMs) are just another fancy compiler. Back in the 50s and 60s, everyone was working in Assembly, and then C showed up, and we didn't stop coding in Assembly because C was suddenly perfect. C isn't perfect, but we stopped doing it because C is good enough, and we're more productive coding in C. And to me, LLMs are a very similar trade-off. They're not perfect yet, but at some point they will be good enough to make us more productive.

The failure to utilize Huawei's chips forced DeepSeek to shift to Nvidia's H20 GPUs for the training of its next-gen LLMs due to instability and performance issues.

OpenAI has released two open weight LLMs, gpt-oss-120b and gpt-oss-20b, which can perform similarly to recent small language models on accessible hardware.

We’re essentially a technology digital team for any business... with particular agents that have particular functions. We just need general ideas on what to do.

The purpose of Meta's copying was to train its LLMs, which are innovative tools that can generate diverse text and perform numerous functions.

Code Feedback MCP Server provides AI with real-time feedback necessary to ensure that code meets quality standards before it is deployed.

The comparisons reveal that GPT-3.5 excels in bug detection with the highest rates on Defects4J and ConDefects, showcasing its powerful mutation generation capabilities.

In this study, we comprehensively assess the capabilities of various LLMs in generating code mutations, emphasizing their effectiveness, usability, and performance across distinct metrics.

In evaluating LLM-generated mutations, we designed metrics that encompass cost, usability, and behavior, recognizing that higher mutation scores don't guarantee higher quality.

LLMs (Large Language Models) have dramatically evolved, accomplishing previously thought impossible tasks. However, challenges remain, and insights from industry leaders are essential to navigate these complexities.

Building LLM-powered applications is comparable to developing modern cloud-native applications, requiring notable support for REST and RPC protocols, where Go excels.

Nowadays, LLMs are everywhere - and it's amazing to see how these models are being used in practical DevOps workflows.