1_r/devopsish

In this post, we will describe how we built an eBPF-powered agent to monitor networking traffic within our Kubernetes clusters.

Apple is developing a large array of features that use generative AI, including a new version Siri, that could launch next year, according to...

We've just updated Camtasia 2023 with an incredibly powerful new, AI-assisted workflow, that takes you from recording to layout (and almost to done), before you even get into the editor. In this video Andy walks you through the incredibly powerful, yet simple-to-use Camtasia Rev. With the Camtasia Rev workflow, anyone can take a new recording and in just a few clicks have a completed video in a variety of sizes and layouts ready to be shared to their preferred platforms. Camtasia is easy enough for beginners, but powerful and versatile enough to be your video editing solution for life Learn more about Rev here: https://bit.ly/3Qh6mvl 0:00 - Welcome 0:15 - Start a New Recording with Camtasia Rev 1:02 - Record Your Camera & Screen Recording As Always 1:15 - Introducing Camtasia Rev 1:26 - Size: Widescreen, Vertical, Square (Aspect Ratio) 1:47 - Layout: Picture-in-Picture & Screen Recording Layout Options 2:14 - Background: Animated Gradient or Dynamic Animations (Customizable) 2:41 - Effects: Background Removal, Border, Corner Rounding, Cursor Options, Reflection 3:54 - Filters: Add Color Grading Options to your Camera Footage from Rev 4:25 - Preview Your Video Inside of Rev 4:40 - Edit in Camtasia (Make Any Changes & Edits This Way) 4:50 - Fill the timeline 5:05 - Nothing is burned in, or flattened - your video is customizable 5:52 - Camtasia Rev is Easy and FREE for Camtaia 2023 users (& future)! Just Check for Updates!

Taking things personally at work is not a sign of weakness, but a reflection of your passion, commitment, and deep sense of responsibility. But what if your professional role has become too intertwined with your sense of self. While equating your value as a person with your performance at work is common, it’s also possible to break free from the pattern. In this article, the author offers five strategies for how to approach situations with more objectivity so that you can navigate your professional journey with greater clarity, balance, and effectiveness.

Platforms like GitHub are helping non techies write software, boosting productivity at companies and at home.

The $4.5 billion startup is used by software developers to collaborate on machine learning projects.

False claims about the latest Israel-Hamas war are flooding social media, making it difficult for onlookers to sort fact from fiction. Here are the facts: The Israeli military didn't say in a Facebook post that it bombed a hospital in Gaza, the account was a fake.

Federal authorities say that thousands of information technology workers contracting with U.S. companies secretly sent millions of dollars of their wages to North Korea for use in its ballistic missile program.

'Beatings will continue until morale improves'

Fast stable diffusion CPU. Contribute to rupeshs/fastsdcpu development by creating an account on GitHub.

With the newest AMD Ryzen 7040 series laptops there is 'Ryzen AI' as a dedicated AI engine based on Xilinx IP to help accelerate machine learning with the likes of PyTorch and TensorFlow

CRIL analyzes a malware campaign targeting users downloading Windows VPN applications with the goal of delivering BbyStealer malware. CLick here to know more!

No word on motivation but pair face up to 5 years in the cooler

Selling original or quirky products is often an uphill battle. But research that involved an analysis of quirky products sold by some 7,000 craft entrepreneurs on Etsy suggests that effective storytelling that helps people relate to such offerings can turn them into successes. This article shares three storytelling techniques that work.

Cybersecurity firm Okta said an unidentified hacker had accessed the company's support system and viewed client files.

IBM’s NorthPole processor sidesteps need to access external memory, boosting computing power and saving energy.

A primer on GPU architecture and computing

News organizations are scrambling to adjust to the latest rift in the long-fractious relationship between publishers and tech platforms.

Take a tour of Radius by getting started with your first app

Mr. Stewart and Apple are parting ways because of creative differences over “The Problem,” people with knowledge of the decision said.

September was a busy month with participation in 3 different events, regular work on security reports, and discussions around creating an SBOM for Node.js. In September, we responded to 9...

Iran-linked attackers compromised multiple computers and servers over the course of eight months.

Google has announced an additional $2 million investment in two HBCUs as part of an ongoing collaboration with the UNCF

Arson case produces a very tricky precedent for anyone who values digital privacy

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a promising approach to address some of the challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications is contingent upon their efficient execution on the underlying hardware infrastructure. Specialized AI accelerator hardware systems have recently become available for accelerating AI applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT- 2 model, and (iii) an LLM-driven science use case, GenSLM. We present our findings and analyses of the models' performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, sparsity, and sensitivity to gradient accumulation steps.

Aims to lower costs and broaden appeal of system popular with devs