Page 32 – Advance Aii

PR Agencies in the Age of...

Grok 3 In an AI-powered world, PR agencies must adapt to remain relevant by leveraging technology while maintaining the human touch that defines effective communication. Below, we outline how agencies should adjust staffing, training, and skills profiles, evolve their services portfolio, and address the strongest impacts of AI on public relations, particularly in social media automation, AI-generated content, and creativity enhanced by generative AI. Staffing, Training, and Skills Profiles To stay competitive, PR agencies need a blend of traditional communication expertise and AI-driven capabilities: Training Focus Workshops on AI tools (e.g., analytics platforms, content generators). Data interpretation and basic coding for better collaboration with AI systems. Ethical AI use and governance to address emerging concerns.

What is this Every Thursday, I will share a dev diary about what we’ve been working on over the past few weeks. I’ll focus on the interesting challenges and solutions that I encountered. I won’t be able to cover everything, but I’ll share what caught my interest. Why am I doing it I want to bring our community along on this journey, and I simply love writing about things I’m passionate about! This is my unfiltered dev journal, so please keep in mind that what I write here are my thoughts and will be outdated by the time you read this, as so many things change quickly. Any plans I mention aren’t set in stone and everything is subject to change. Also, if you don’t like spoilers, then don’t read this. Space Engineers 2 VS 1.2 will be releasing in a few days, on Monday April 14 In survival, players will build in projection mode (so first as a projection, and then weld it). We need a particle effect for it, so here’s one prototype. The new IK is great, but when you walk up stairs or ramp, in first person mode, the camera goes up and down, and what...

This article is a cutout of my forthcoming book that you can sign up for here: https://www.danrose.ai/book. Synthetic data in AI is probably the subject I think the most about currently, to be honest. It has enormous potential to improve privacy, lower bias and improve model accuracy simultaneously in a giant technological leap in the coming years. Gartner even stated, “By 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated.“. That is a game-changer considering that many people working with AI today haven’t even started to adopt this technology. Synthetic data is data but not actual observations of the world. It is fake data either created by humans or algorithms. It is created artificially or synthetically, but the goal is the same as real data – To represent the world in which the AI is supposed to function. The idea that data for training AI models should accurately represent the world is still a means to the end. Ultimately, the goal of building AI is models that accurately predict to provide a good user experience. Types of synthetic data Depending on the data type, text, images and tabular data, there are different approaches and use...

Forbes reports that “most AI projects fail”; Techrepublic puts the number at 85%. How do we reconcile this reality with claims of AI as representing an “existential threat” such as those from Elon Musk and futurism.com? Often called AGI (Artificial General Intelligence), the idea is a general-purpose, human-like intelligence like Hal from 2001 or the Terminator. Here’s what’s going on. First, all new technology by its nature is disruptive, and AI today is no exception. The cotton gin, the telephone, and certainly the internet and personal computers all created massive shifts in employment and commerce. Wise governments adapt and retrain to try to minimize impact on workers. Sometimes this goes well, sometimes not so much, but that’s not what most are talking about with AGI, which goes to the next level. Second, unique to AGI is its ability to capture the imagination, as great fodder for Hollywood and more: driving an entire post-apocalyptic genre. AGI stories have become so powerful that some claim they have reached the level of global propaganda. We never saw blockbuster “disruptive telephony” Hollywood hits; AGI stories are unique in this regard. Third, AI has been genuinely successful in recent years. When combined with our ability...

The surge in GPT’s popularity (and, by extension, AI’s) is reshaping the digital landscape. In this competitive era, companies are vying to innovate their digital products with GPT-based features, even spearheading entire projects centered around this technology. Keen on staying ahead in the race and seeking inspiration? In our article, you will find a variety of inspiring business use cases of GPT implementation, from tech giants to local enterprises. Ready to explore? Let’s embark on this journey! GPT’s Surging Popularity: A Swift Journey to 100 Million Users Before delving into business uses cases of GPT, we shouldn’t overlook the impact ChatGPT has had on the market. Its emergence catalyzed a surge of company investment into large language models like GPT, the foundational technology behind this revolutionary application from OpenAI. ChatGPT has undeniably transformed the tech landscape in the past year, a transformation we’ve witnessed firsthand at DLabs.AI. It has proved its worth across an array of applications, from content creation and coding to managing daily tasks such as planning shopping lists, writing poetry, or crafting formal letters. The breadth of its utility and impact is profound. Turning our attention to the above chart, it’s clear that ChatGPT has set a...

The conference features a range of events designed to enrich attendees’ understanding of the chatbot industry: Expert Keynotes: Get insights from industry leaders at the forefront of AI innovation. Workshops: These certified workshops provide hands-on experience, helping participants design and deploy their own AI agents. Whether you’re looking to master AI automation or enhance chatbot designs, these workshops are crafted to guide you through each step. Panels and Discussions: Interactive panels allow you to learn directly from pioneers in the field, addressing topics like AI ethics, automation, and cognitive frameworks. If you’re eager to stay ahead of the curve, the Chatbot Conference offers a unique opportunity to: Learn from the Best: Access cutting-edge knowledge from top AI developers and researchers. Network with Peers: Engage with a vibrant community of innovators, entrepreneurs, and AI professionals. Discover the Future of AI: From exploring AI multi-agent systems to gaining insight into practical implementations of chatbots in business, the event provides a glimpse into the next wave of conversational technology. With upcoming events already lined up, now is the time to get involved. Whether you’re looking to deepen your technical skills or understand how AI can revolutionize your business, the Chatbot Conference offers a...

About six weeks ago, I sent an email to Satya Nadella complaining about the monolithic winner-takes-all architecture that Silicon Valley seems to envision for AI, contrasting it with “the architecture of participation” that had driven previous technology revolutions, most notably the internet and open source software. I suspected that Satya might be sympathetic because of past conversations we’d had when his book Hit Refresh was published in 2017. I made the case that we need an architecture for the AI industry that enables cooperating AIs, that isn’t a winner-takes-all market, and that doesn’t make existing companies in every industry simply the colonial domains of extractive AI conquerors, which seems to be the Silicon Valley vision. Little did I know that Microsoft already had something in the works that is a demonstration of what I am hoping for. It’s called NLWeb (Natural Language Web), and it’s being announced today. Satya offered O’Reilly the chance to be part of the rollout, and we jumped at it. Embracing the Early Stage of Innovation My ideas are rooted in a notion about how technology markets evolve. We have lived through three eras in computing. Each began with distributed innovation, went through a period of...

Midjourney has unveiled its long-awaited V7 image generation model – its first major upgrade in over a year. Now available in public alpha, V7 introduces significant enhancements in both visual quality and user functionality, signaling a bold new phase for one of the most widely-used AI image tools on the web. V7 features a completely rebuilt architecture, delivering much sharper results with vastly improved detail, texture realism, and object coherence. One of the most noticeable improvements is how well it renders complex body parts like hands and fingers – long-time challenges for AI image generators. Materials like fabric, skin, and ceramics also appear more realistic, offering creators better tools for artistic expression. A standout feature of V7 is Draft Mode, which allows users to rapidly iterate on visual concepts. Draft Mode renders images 10 times faster and at half the cost of standard jobs, making it ideal for creative brainstorming. While images in Draft Mode are lower quality, they can be easily enhanced to full resolution with a click. Another major addition is personalization by default. Upon starting with V7, users are asked to rate around 200 images to build a custom aesthetic profile. This enables the model to better...

Recently, we’ve discussed why embracing content agility is key and explained that the road towards it is rather agile in itself. But what to do once you’ve gone down this road? What is the publisher’s next step after digitalisation? Automation tooling: what’s out there? Even though publishers use an increasing number of digital tools (such as content management systems), few have implemented automation — which we believe is a missed opportunity, as it’s a logical, beneficial next step. So, let’s have a closer look at this form of technological innovation. If you run a spellchecker to make sure a document is flawless, that would be a nice example of an automation tool. Modern spellcheckers use AI models in the background to analyse the grammar and structure of a text. As a publisher, you’re probably familiar with several spellchecker examples, and everyone will agree that this type of automation has been beneficial to publishing. But you might not realise Artificial Intelligence (AI) is used to automate many other content-related processes, too. Examples include metadata tagging and text classification — relatively unknown ways to eliminate laborious manual tasks. Integrated and easy to use Moreover, text classifiers and metadata are just as easy...

Apache Airflow has become the de facto library for pipeline orchestration in the Python ecosystem. It has gained popularity, contary to similar solutions, due to its simplicity and extensibility. In this article, I will attempt to outline its main concepts and give you a clear understanding of when and how to use it. Why and when should I consider Airflow? Imagine that you want to build a machine learning pipeline that consists of several steps such as: Read an image dataset from a cloud-based storage Process the images Train a deep learning model with the downloaded images Upload the trained model in the cloud Deploy the model How would you schedule and automate this workflow? Cron jobs are a simple solution but they come with many problems. Most importantly, they won’t allow you to scale effectively. On the other hand, Airflow offers the ability to schedule and scale complex pipelines easily. It also enables you to automatically re-run them after failure, manage their dependencies and monitor them using logs and dashboards. Before we build the aforementioned pipeline, let’s understand the basic concepts of Apache Airflow. What is Airflow? Apache Airflow is a tool for authoring, scheduling, and monitoring pipelines. As...