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Mustafa Hameed reports from Learning Technologies 2025 Learning Technologies pulled off an absolute cracker of an event this year at London’s ExCeL Centre. Packed with energy, innovation, and a palpable sense of urgency, the show floor was buzzing with conversations about the future of digital learning, AI, and the evolving role of content in corporate training. As a part-time tech journalist and full-time tech enthusiast, I found the event not only impressive in scale, but also in how sharply it captured the pulse of our rapidly shifting digital learning landscape. The Future of Content Creation Is Now One thing was clear from the get-go: content creation is no longer just a nice-to-have—it’s at the heart of learning strategy. The biggest players in the game came out in full force. Articulate, Synthesia, Adobe, Veed, and many others showcased cutting-edge tools designed to supercharge content production. These platforms are enabling companies to generate high-quality learning modules faster, cheaper, and more dynamically than ever before. Video synthesis, interactive simulations, AI voiceovers, and multilingual capabilities were the talk of the town—providing the kind of scale businesses need to meet the growing demand for on-the-job training and upskilling. Elevating the Underdogs: The Startups Making Big Waves Here at Techenova, we make it our mission to spotlight startups and lesser-known innovators—the ones often overshadowed by tech giants but who are often the real engines of disruption. And this year, they did not disappoint. I met founders and reps from across Europe—Poland, Spain, the Netherlands—who are already collaborating with a wide array of UK businesses. I even spoke with a team from India who had made the journey specifically to forge cross-continental partnerships. Their passion, technical expertise, and vision for ethical, human-centered AI tools left a lasting impression. These aren’t just new kids on the block. They’re lean, fast, and extremely focused on building tools that are accessible, ethical, and built for real-world impact—not just enterprise buzzwords. Competitive Landscape: Rapid Growth and Ruthless Evolution One of my key takeaways? The learning tech sector is in a state of hyper-evolution . The speed at which companies are iterating, innovating, and scaling is both exhilarating and brutal. It’s no longer enough to have a great idea or even a moderately successful product. AI has shifted the terrain completely. We’re now in a space where only the most adaptable will survive—a kind of digital Darwinism. Think of it as the Wild West meets Black Mirror. With Ginger Swart Community Manager at Articulate And yet, within this chaos, a new rulebook is emerging. It’s not just about who has the flashiest tools. It’s about who can form the strongest partnerships, build trust, and foster long-term collaboration. Relationships Over Transactions In this climate, relationships are the new currency. It’s not about showing off your tech just to look cool on a demo stage. Everyone’s got flashy tools now. Everyone's "down with the kids." What truly matters is building alliances that last longer than a funding round or an algorithm update. Companies want more than just suppliers—they want strategic partners who understand their values and grow with them over time. As one startup founder told me, “We don’t just sign contracts. We build commitments.”  That sentiment echoed throughout the event. The Rise of Ethical AI in Learning Another major theme: AI ethics. And interestingly, the most thoughtful conversations weren’t coming from the big vendors—they were from the startups. They spoke passionately about the importance of transparent data sourcing, ethical content generation, and the potential harms of unchecked automation in learning environments. This is an important signal. As AI becomes more embedded in education and training, the companies asking hard questions now are likely to be the ones we trust tomorrow. What’s Next? This is just the beginning of our coverage. I’ve got some fascinating interviews lined up with startup founders, innovators, and educators from the event—each offering their unique take on the future of tech, learning, and what it means to create responsibly in an AI-driven world. Stay tuned to Techenova.net , and follow us on LinkedIn for the full series.

Learning Technologies 2025, taking place 23–24 April 2025 at ExCeL London. If you're in the world of learning and development, HR, or talent management, there's one event in 2025 you can’t afford to miss: Learning Technologies 2025, taking place 23–24 April at ExCeL London. Now in its 25th year, Learning Technologies is Europe’s leading showcase of workplace learning innovation, offering an unmatched opportunity to explore the technologies, strategies, and tools shaping the future of learning. What Is Learning Technologies? Learning Technologies is more than just a trade show—it's the epicenter of innovation for the L&D world. Every year, the event attracts over 11,000 professionals  from around the globe, featuring: 200+ world-class exhibitors 200+ free-to-attend seminars An in-depth conference programme  packed with expert-led sessions This is where forward-thinking organisations go to find the tools and strategies that help their people learn faster, smarter, and more effectively. What to Expect in at the 2025 Learning Technologies Event 2025 The Learning Technologies Conference runs alongside the free exhibition and features over 80 expert speakers covering everything from AI in learning to impactful content creation and skills development. This year’s theme focuses on the intersection of technology and human learning, offering fresh insights into: The evolving role of AI in L&D Personalised learning experiences at scale Building real-world capabilities across organisations Compliance training that actually works Data-driven decision making in learning programmes Whether you're a seasoned pro or new to L&D, you’ll walk away with practical strategies and inspiration you can apply immediately. Why You Should Attend Get Ahead of Trends : Learn about the latest tools and technologies reshaping workplace learning. Make Meaningful Connections : Network with over 11,000 professionals from 50+ countries. See the Best in Tech : Interact with cutting-edge platforms, VR tools, learning systems, and AI solutions. Sharpen Your Skills : Attend insightful seminars and workshops, all under one roof. Event Details 🗓 Date : 23–24 April 2025 📍 Location : ExCeL London, 1 Western Gateway, Royal Victoria Dock, London E16 1XL ⏰ Time : 9:00 AM – 5:00 PM 🎟 Registration : Visit the official site to register 🚀 Join the Learning Revolution Whether you're responsible for your organisation’s training strategy or just passionate about helping people grow, Learning Technologies 2025  is your chance to explore what’s next in learning. 💡 Be there to discover, connect, and elevate how we learn at work.

If you've ever used a mobile app on your phone, chances are it was built with a development framework like Flutter. Flutter is a cross-platform development toolkit created by Google that allows developers to write a single codebase for both iOS and Android apps. This means instead of building separate apps for each platform, developers can use Flutter to write one app that works seamlessly across both systems. Flutter isn’t just for developers—it’s also an amazing tool for businesses and startups. Whether you’re launching your first app or improving an existing one, Flutter can help you build fast, beautiful, and high-performance apps without breaking the bank. What is Flutter? Flutter is an open-source UI toolkit for building natively compiled applications from a single codebase. It supports iOS, Android, web, and desktop platforms, enabling developers to create high-performance apps with minimal code duplication. The framework uses Dart, a programming language designed to be fast and easy to work with. What makes Flutter stand out is its ability to allow developers to write a single codebase that can be run on both iOS and Android devices, making it a top choice for those looking to save time and money in app development. What Can You Do With Flutter? Flutter is a versatile framework that can be used for a wide range of applications, from small personal projects to large-scale business apps. Here are a few things you can use Flutter for: Create mobile apps : Whether it’s a simple tool or a full-fledged app, Flutter helps you develop apps that look and feel great on both iOS  and Android . Build web apps : Flutter isn’t just for mobile. You can also use it to build apps that run on the web, making it a great option for businesses wanting to reach more customers. Develop desktop apps : Flutter can also be used to build apps for Windows, macOS, and Linux, giving developers a powerful, cross-platform solution. A Popular and Successful Use Case: One of the most successful companies using Flutter is Alibaba, the Chinese e-commerce giant. Alibaba used Flutter to build parts of its mobile app, specifically the Xianyu marketplace. The company chose Flutter for its ability to create an app that worked well across both iOS and Android without the need to write separate code for each platform. This allowed Alibaba to save time on development and provide a smooth, consistent experience for users. Other Big Names Using Flutter: It’s not just Alibaba that has seen the potential in Flutter. Some of the world’s biggest companies are also using this framework to build their apps, including: Google Ads : Google’s own Google Ads app is built using Flutter, providing a sleek and user-friendly experience for managing ad campaigns across platforms. eBay : The popular e-commerce platform eBay uses Flutter to build parts of its mobile app, helping ensure fast performance and a great experience for users. BMW : The automotive giant BMW has embraced Flutter for building mobile apps, focusing on creating a seamless user experience for its customers on both iOS and Android devices. Realtor.com : The real estate platform Realtor.com  has adopted Flutter to improve the speed and performance of its app, offering a smoother experience for its users. These companies, alongside many others, are taking advantage of Flutter’s flexibility and efficiency to build apps that deliver high performance, intuitive designs, and great user experiences. Why Flutter Might Be Right for Your App: If you're considering building an app, here are some reasons Flutter might be a great option: Faster Development : With Flutter, you only need to write one codebase for both iOS and Android, cutting development time in half. This is especially helpful for startups or small businesses that need to launch quickly. Cost-Effective : Since you're writing a single codebase, Flutter can help you save money by reducing the need for separate teams to build apps for each platform. High Performance : Flutter compiles to native code, meaning the app runs smoothly and quickly, offering a great user experience. Customizable Design : Flutter gives you full control over the design of your app, allowing you to create unique, visually appealing user interfaces that stand out in the app store. Growing Community and Resources : Flutter has a vibrant, supportive community and tons of resources that can help you get started with building your app. Flutter is quickly becoming one of the most popular tools for building cross-platform mobile apps, and for good reason. It allows developers to create beautiful, high-performance apps faster and more cost-effectively than ever before. Whether you’re an entrepreneur, startup founder, or developer, Flutter is a great tool to consider for your next app project. If global leaders like Alibaba, Google, and BMW are using Flutter to create outstanding apps, then it’s worth considering for your own projects. With its growing community, customizable designs, and cross-platform capabilities, Flutter is poised to continue changing the way we build apps for years to come.

London’s skyline may still be peppered with double-deckers and black cabs, but next week the capital takes a powerful step toward an electric future. Everything Electric  — the UK’s ultimate festival of clean energy and electric vehicles — is rolling into the ExCeL Centre from April 19–21, 2025 , and it’s looking to be the biggest and boldest edition yet. Brought to life by the creators of the Fully Charged Show , Everything Electric 2025 is more than just an exhibition — it’s a hands-on, high-voltage celebration of all things sustainable, smart, and seriously innovative. ⚡ What to Expect at Everything Electric 2025 Whether you're an EV enthusiast, a climate-conscious homeowner, or a tech-savvy startup on the lookout for the next big thing in clean energy, there’s something here for you. 🔌 Test Drives Galore Try out the latest electric vehicles from Tesla, Polestar, Hyundai, Kia, and more. From family-friendly electric SUVs to sleek two-wheelers and micro-mobility solutions, test drives are one of the main draws — and yes, you can book in advance to avoid the queues. 🏡 Home Energy Tech Explore how your house can become a self-sustaining energy hub. Dive into demos of solar panels, smart home batteries, heat pumps, and next-gen energy management systems. Whether you're planning a full green retrofit or just dipping your toes into the eco-home world, this section is full of insights. 🎤 Expert Talks & Panels Expect top-tier speakers from the worlds of science, tech, policy, and media. From debates on the future of transport to deep dives into the UK's green energy landscape, these sessions are designed to inform, challenge, and inspire. 🌍 Future Tech & Startups One of the most exciting parts of the show is the innovation zone, where startups and emerging companies showcase cutting-edge products — many making their public debut. Think smart charging systems, AI-powered energy management, and tech that could reshape how we live. 🎟️ Who’s It For? Tech innovators  looking to connect or pitch Families  curious about going electric Policy watchers  and climate change advocates Startups  in energy, transport, or sustainable living You  — if you're even slightly curious about the future of power, mobility, and the planet 💬 Final Thoughts Everything Electric  is more than just a tech expo — it’s a glimpse into a cleaner, more connected future. And it’s happening right here, in London. Whether you’re looking to test drive your next car, meet the makers of tomorrow’s tech, or simply learn how to make your lifestyle more sustainable, this is the place to be. 🗓️ Dates : April 19–21, 2025📍 Location : ExCeL London🔗 Tickets & Info : everythingelectric.show   (check for booking details and speaker schedules)

Techenova Wants to Promote Your Start Up Calling All Tech Startups and Innovators: Get Featured for FREE on Techenova! Are you working on something groundbreaking in green tech, AI, EV tech, health tech, digital marketing, gaming, animation, or software development? Whether you’re a startup looking for exposure or an innovator seeking funding, Techenova is here to help you get noticed. We’re offering FREE promotion by featuring your business or project in a YouTube Shorts video that showcases your work to our engaged audience. Why Techenova for your tech start up? At Techenova, we’re dedicated to covering the latest and most exciting tech innovations. From AI breakthroughs to sustainable technologies, gaming, animation, and digital marketing, we want to highlight what’s next in the tech world. If you’re seeking visibility or investment for your project, this is your chance to share your story with a community that’s eager to discover the next big thing. What’s the Catch? There is no catch! We believe in giving innovators—whether companies or individuals—a platform to showcase their projects. Simply send us a brief about your startup or innovation, and we’ll create a YouTube Shorts video to spotlight your work. Whether you're looking for investment, exposure, or simply the chance to tell your story, Techenova is here to help. Who Should Apply? Tech Startups  seeking exposure and growth App Developers  building the next big thing in mobile tech Programmers  with innovative software or system solutions Health Tech Innovators  transforming healthcare with technology AI Entrepreneurs  shaping the future of artificial intelligence Green Tech Companies  pioneering sustainable innovations EV Tech Leaders  driving change in the electric vehicle space Digital Marketers  pushing the boundaries of online strategy Gaming Studios  creating the next generation of interactive experiences Animation Studios  bringing creative worlds to life Individuals seeking funding  for their tech projects or ideas How to Get Started: Reach out to us via our website or social media. Share a brief overview of your company, project, or idea, and tell us why it’s worth investing in. We’ll create your custom YouTube Shorts video and share it with our growing audience of tech enthusiasts, investors, and industry professionals as well as on other platforms like Instagram and LinkedIn. Let’s Share Your Innovation This is your chance to shine in front of a community that’s excited about the future of technology. Whether you’re a startup looking to grow or an innovator seeking investment, Techenova can help amplify your story. Contact us today to be part of our next featured video! This version now includes digital marketing, gaming, and animation, making it more inclusive for a wider range of tech innovators.

Watch our Youtube guide on Brendan Kane's Going Viral Methodology Want to understand how content truly goes viral, moving beyond fleeting trends to create lasting impact? You're in the right place. This article delves into the expertise of Brendan Kane , a 20-year veteran who's worked with giants like Taylor Swift, MTV, and IKEA. Drawing from his wealth of experience and books like "1 Million Followers" and "The Guide to Going Viral", we'll explore his actionable strategies – a recipe, if you will – to help you create content that resonates and spreads. Brendan's approach, highlighted in a deep dive video from the TechNova YouTube channel, isn't about luck; it's about a systematic understanding of how to create content that works. It starts with a fundamental shift in perspective: moving from being a passive consumer of social media to an active, analytical creator. Here’s how to bridge that gap and unlock your viral potential, according to Brendan Kane's Hookpoint viral content model: 1. From Consumer to Creator: The Power of Analysis Instead of simply scrolling through your feed, Brendan urges you to become a content detective. Just as a chef breaks down a dish to understand its ingredients and techniques, creators need to analyse successful online content. Ask yourself: What makes this video work beyond just being funny or entertaining? What is the underlying structure driving its success? What are the patterns in the pacing, editing, and storytelling? This analytical mindset is the first crucial step in understanding the mechanics of viral content. 2. Select and Analyse Your Format Meticulously Brendan emphasises the importance of identifying and understanding repeatable formats – sustainable structures with a proven track record, rather than one-off viral moments. Think of them as templates for success into which you can plug your own message or brand. Don't chase one-hit wonders:  Look for creators who consistently get results using the same structure across multiple videos. Formats over trends:  While trends can offer a temporary boost, they fade. Formats provide a lasting foundation. Pay attention to context and delivery:  Even if competitors use similar content, their execution might be flawed. To help identify these formats, Brendan's company, Hookpoint, developed the Hookpoint Format Finder. Crucially, Brendan argues that formats don't limit creativity; they unlock it. Just like filmmakers adhere to basic storytelling structures while producing diverse movies, mastering a format provides a framework within which your unique context and voice can shine. To choose the right format, consider: Your resources:  Be realistic about your time, equipment (even an iPhone can suffice), and team. Your passions:  Enthusiasm is contagious and fuels consistency. Hookpoint's research has uncovered over 300 different storytelling formats. Examples include: Man on the street:  Engaging random people in public, like Alex Dlosski's spontaneous interactions or School of Hard Knocks' entrepreneur interviews. Two characters, one light bulb:  One person playing multiple characters to explore a topic from different angles, as seen with Mark Tilbury's buyer/seller negotiations or Erica Cobberg's legal jargon demystification. Walking listicles:  Sharing a list of items while walking and talking, exemplified by Robert Croak's tips for becoming a millionaire. However, 99% of people fail at using these formats because they don't analyse them deeply enough. This is where the Gold, Silver, Bronze process comes in. Examine 5-10 top-performing (gold), average (silver), and low-performing (bronze) videos within your chosen format to identify the performance drivers. Analyse the pacing, tone, camera angles, captions, and editing – all the subtle nuances that contribute to success. Hookpoint has analysed over a thousand of these performance drivers. Brendan illustrates this with the visual metaphor format used by Dr. Julie Smith. By comparing a high-performing video (overflowing waste paper basket for bad memories) with a lower-performing one (traffic as thoughts), he highlights key performance drivers: Active metaphor:  Actively interacting with props creates a more engaging visual story. Tension:  Visually creating a sense of urgency or intrigue draws viewers in. Potential energy:  Setting up an expectation of interaction or action from the start. Cleverness:  Using everyday objects in unexpected and insightful ways to represent abstract concepts. 3. Ideation Within That Format: Your Creative Blueprint Instead of starting with a random idea, use your chosen and analysed format as a framework for generating ideas. The format becomes your blueprint, focusing your creative energy. Tanner Leatherstein of Pugy exemplifies this. After struggling with typical social media strategies, he developed the "Is It Worth It" format, deconstructing luxury leather goods and offering his expert opinion. This repeatable format, fuelled by his passion, led to phenomenal growth. Key takeaway: Find a format that works and let it guide your content creation. 4. One Video at a Time: Quality Over Quantity In a world of batch production, Brendan advocates for a more iterative approach: create one video, analyse its performance, adjust your strategy, and then create the next. Think of a chef perfecting a sauce – small adjustments based on taste lead to the best results. Avoid wasting time by producing a large batch of content before understanding what resonates. 5. Analyse and Improve: Refine, Repeat, Succeed After sharing your video, dig into the data using the Gold, Silver, Bronze process. If a video underperforms, revisit your research – did you miss a key performance driver? Use the Hookpoint mirror test to compare your video side-by-side with high-performing ones in the same format to identify subtle differences in execution. Brendan’s work with Aaron Gory, who experienced massive growth after analysing her videos, highlights the power of this step. Comparing a 15,000-view video with a 59 million-view video revealed key performance drivers like big reactions, clear conflict, and the strategic use (or absence) of captions. By being brutally honest with yourself and analysing the data, you can turn failures into valuable learning experiences. Refine your approach, repeat what works, and test and iterate based on data, not guesswork. How to Go Viral Going viral isn't a matter of chance; it's a process rooted in understanding and applying proven strategies. Brendan Kane's five-step Hookpoint viral content model – go from consumer to creator, select and analyse your format, ideate within that format, focus on one video at a time, and analyse and improve – provides a powerful framework for creating content with intention and achieving consistent results. With billions of views and millions of followers generated by those using this model, the question now is: how will you use these insights to achieve your own content goals? It's time to take action and start creating strategically.

It's becoming clearer that one of the skills we will all need master as AI advances is the knowledge and use of terms used in machine learning. A knowledge of such terms will help you to understand and thereby guide your AI generation. So, in the spirit of learning here are some common AI prompt related terminology Prompt Engineering Definition:  The practice of designing and structuring prompts to elicit desired responses from large language models (LLMs). Example: If you want a model to generate a poem, instead of just saying "Write a poem," you could engineer the prompt as follows: "Write a 4-line poem about the beauty of the sunset, using metaphors." Chain-of-Thought Prompting Definition:  A technique that encourages LLMs to explain their reasoning step by step, improving the accuracy of responses. Example: If you're asking the AI how to calculate the area of a triangle, you might prompt it with: "First, explain how to calculate the area of a triangle. Then, apply the formula to a triangle with a base of 5 units and a height of 3 units." Generative AI Definition:  AI systems capable of generating content such as text, images, or music based on prompts. Example: "Generate a short story about a dragon who befriends a knight in the middle of a battle." This would lead the AI to generate a complete narrative based on the input. Large Language Models (LLMs) Definition:  Advanced AI models trained on extensive text data, enabling them to understand and generate human-like text. Example: "What is the impact of AI on healthcare?" An LLM would generate a well-informed, detailed response drawing on its vast training data. One-Shot Prompting Definition:  Providing a single example within the prompt to guide the AI’s response. Example: "Translate the following English sentence into French: 'I am going to the market.' " This prompt provides one example sentence to help guide the translation. Zero-Shot Prompting Definition:  Designing prompts that enable the AI to perform tasks without prior examples, relying on its pre-existing knowledge to generate responses Example: "Translate the sentence 'I will be there soon' into German." This prompt asks for a task without providing an example translation, relying on the AI's internal knowledge. Prompt Injection Definition:  Incorporating additional instructions or contextual details into a prompt to influence the AI's behavior. Example: "Incorporate a surprising plot twist into the following short story about a detective solving a crime." This prompt includes an extra instruction to shape the story's direction. Adversarial Testing Definition:  Evaluating AI models by providing inputs designed to challenge their robustness and identify vulnerabilities. Example: Asking the model to generate a list of 100 valid domain names when it can only generate a few would challenge its capabilities and reveal weaknesses. Hallucinations Definition:  Instances where AI models generate responses that sound plausible but are incorrect or nonsensical. Example: Asking the model: "Who won the 1999 World Series?" And the model responds: "The Detroit Tigers,"  which is incorrect (the correct answer is the New York Yankees). Bias in AI Definition:  Systematic favoritism or prejudice in AI outputs, which can arise from biased training data or flawed model design. Example: If an AI model trained mostly on text data from Western sources provides responses that consistently favor Western viewpoints, it reflects bias in the model's training data. Mean Average Precision at k (MAP@k) Definition:  A metric used to evaluate the quality of a model's output across multiple prompts, assessing the precision of the top-k responses. Example: If a search engine provides 5 results for a query, MAP@k would measure the precision of the top 5 answers provided, ranking them based on relevance. Seed Definition:  A specific value used in the AI model’s random number generation, ensuring consistency in the AI’s output when using the same prompt. Example: If you use a seed like "12345"  with an AI image generator, it will generate the same image when the prompt is run again with that seed. Iteration Definition:  The process of refining or adjusting the prompt and its details in response to the AI’s outputs. Example: After the first response from the AI is not what you expected, you adjust the prompt to be more specific: "Can you generate a detailed scene of a beach at sunset with vibrant colors and a calm sea?" Aspect Ratio Definition:  The proportional relationship between the width and height of an image. Example: "Generate an image of a sunset with a 16:9 aspect ratio." This instructs the AI to create an image that fits within a widescreen format. Feedback Loop Definition:  The process of adjusting and improving prompts based on the output received, allowing users to learn what works and refine their prompting strategies. Example : You might input a prompt for an AI to generate an image of a "dragon flying over a city" and then refine it after feedback: "Add more details to the dragon's wings and make the city look futuristic."

Why Attend the Retail Technology Show 2025? This year's show is not just about retail—it’s about the future of retail with AI-powered solutions leading the way. From automated checkout systems and personalized AI-driven marketing to predictive analytics and smart supply chains, AI is redefining the way businesses interact with customers and optimize operations. Who’s Sponsoring the Event? The event is backed by leading tech and retail giants, ensuring attendees get firsthand insights into the latest advancements. Some of the top sponsors include: Aptos  – Headline Stage & Recharge Cafe Sponsor FreedomPay  – Lanyard Sponsor Nuvei  – Stage Sponsor PMC  – BIG Party & Champagne Bar Sponsor SheerID  – Official Sponsor Toshiba  – Retailers Lounge Sponsor XY Retail  – Store Tour Sponsor Zeal  – Registration Sponsor World-Class Keynote Speakers The Retail Technology Show 2025 features an impressive lineup of industry thought leaders who will discuss emerging retail trends, digital transformation, and AI-powered strategies. Key speakers include: Archie Norman  – Chairman, Marks & Spencer Theo Paphitis  – Chairman, Theo Paphitis Retail Group & former BBC Dragons' Den investor Joe Wicks MBE  – Social Media & E-Commerce Expert, Bestselling Author Steve Hewitt  – Former CEO of Gymshark Sophie Neary  – Managing Director, Retail & Consumer Goods UKI at Google Prerana Issar  – Chief People Officer, Sainsbury’s Alex Gourlay  – Executive Chair, Holland & Barrett Peter Pernot-Day  – Global Executive, SHEIN What to Expect at the Retail Technology Show 2025 AI-Powered Innovations – Explore the latest AI retail technologies, from chatbots and virtual assistants to real-time data-driven decision-making tools. 400+ Exhibitors – Discover cutting-edge retail solutions from the world’s leading brands. Insightful Conference Sessions – Learn from 125+ top industry experts on how to stay ahead in e-commerce, omnichannel strategies, and digital retail transformation. Networking & Exclusive Events – Connect with industry leaders at The BIG Retail Party, Retailers Lounge, and the London Store Tours. Takeaways: Why You Can’t Miss This Event If you’re searching for the best retail trade show in 2025, how AI is transforming retail, or top retail events in London, this is your must-attend event. Whether you're looking to explore AI-driven customer experiences, next-gen point-of-sale systems, or sustainable retail innovations, Retail Technology Show 2025 is the place to be. Secure your spot now and be part of the retail revolution!

The increasing accessibility of artificial intelligence (AI) tools has opened up new possibilities for individuals across various domains. At the heart of effectively engaging with these tools lies the ability to communicate instructions clearly. This report explores the concepts of prompt design and prompt engineering, explaining what they are, why they are important, and how anyone can begin to master them to get the most out of AI. The information presented here is intended for individuals who are new to AI and may not have a technical background in this field. 1. Demystifying Prompt Design and Prompt Engineering: Defining the Basics At its core, a prompt is simply the way we communicate with an AI tool. It is the input we provide to get the AI to perform a task or generate a response . Think of it as posing a question to get an answer, or giving a command to initiate an action . This interaction happens through natural language, the same way we converse with each other every day . For instance, a prompt could be as simple as asking "What is the weather like today?" or instructing the AI to "Write a short email thanking a colleague for their help." It could also involve providing initial text and asking the AI to continue it .    The process of creating these initial requests in a way that ensures the AI understands what is being asked is known as prompt design . It involves careful consideration of what you want the AI to do and then phrasing your request in a clear and structured manner . This foundational step is akin to planning what you want to say before you ask someone for assistance . Just as well-structured instructions are easier for a person to follow, thoughtfully designed prompts are more likely to yield accurate and high-quality responses from an AI .    Taking this a step further is prompt engineering. This involves a more advanced and nuanced approach to crafting prompts . It's about experimenting with different ways of phrasing instructions, adding specific details, or providing relevant context to optimize the AI's performance and the quality of its output . Prompt engineering is often an iterative process . This means you might start with a prompt, evaluate the AI's response, and then refine the prompt based on the results to get closer to your desired outcome . Consider it like fine-tuning directions to ensure the AI fully grasps your needs and can deliver the best possible result . The analogy of providing a recipe to a chef effectively illustrates this . A detailed recipe (prompt) guides the chef (AI) to create the desired dish (output). Similarly, using natural language to instruct AI can be seen as a new form of "programming," making powerful technology accessible to a wider audience .    2. Why Your Words Matter: The Importance of Effective Prompts in the Age of AI In the era of increasingly sophisticated AI tools, the ability to create effective prompts is paramount. These AI systems, particularly large language models (LLMs), function somewhat like highly knowledgeable but very literal assistants . They depend on the precise wording of your prompts to accurately understand your intentions . Well-crafted prompts serve as a clear roadmap, guiding the AI towards the specific output you are seeking . Without these clear instructions, the AI might generate responses that are irrelevant, inaccurate, or simply not what you were hoping for . Therefore, the skill of prompt engineering essentially bridges the gap between the user and the AI, making the technology more accessible and usable for individuals without deep technical expertise .    AI tools possess the capability to perform a vast array of tasks, ranging from generating creative text formats like poems or scripts to answering complex questions and even producing computer code . However, the effectiveness with which they execute these tasks is significantly influenced by the quality of the prompts they receive . By mastering prompt engineering, users can unlock these advanced functionalities and obtain more sophisticated and valuable outputs . Just as using high-quality ingredients leads to a better-tasting meal, providing well-designed prompts results in better AI-generated content or solutions . Furthermore, when prompts are clear and effective, the AI is more likely to produce the desired results quickly, minimizing the need for multiple attempts and revisions . This efficiency not only saves time and effort but also enhances the overall practicality and value of using AI tools in various applications. Developing proficiency in prompt engineering can thus be seen as a means to significantly improve personal and professional productivity when working with AI.    3. Anatomy of a Prompt: Understanding the Key Components While prompts can vary in complexity, they often share several key components. The most fundamental element is the core task or instruction . This is the central part of your prompt, clearly stating what you want the AI to do . It could be a question you need answered, a task you want the AI to perform, or something you want it to create. Examples include "What is the capital of France?", "Summarize this article in three sentences," or "Write a short poem about a cat." This task essentially represents the "what" of your request to the AI.    Another crucial component, though optional, is contextual information  . Providing context helps the AI understand the background and specific details of your request, leading to more relevant and accurate responses . For instance, instead of just saying "Summarize this article," you might say, "Summarize this article about the history of the internet , focusing on the early development ." The italicized parts provide context. This is similar to giving someone the necessary background information before asking for their help.    System instructions  are another optional element, particularly relevant in chat-based AI models . These are instructions given at the beginning of the interaction to set the overall tone, style, or behavior of the AI . Examples include "You are a friendly and helpful chatbot," "Respond in the style of a Shakespearean play," or "Keep your answers concise and to the point" . System instructions allow you to essentially define the "persona" or "role" of the AI, tailoring its responses to specific needs.    Including examples, also known as "few-shot" learning, can be highly effective in guiding the AI, especially for more complex tasks or when you have specific formatting requirements . By providing a few input-output pairs, you show the AI what a correct or desired response looks like . For example, in a translation task, you might provide a few English-French pairs before asking the AI to translate a new phrase. This is akin to showing someone what "getting it right" means.    Finally, while not always explicitly stated as a separate component, you can often specify the output format  you desire within your prompt . For example, you might ask the AI to "List the top 5...", "Provide your answer as a bulleted list," or "Present the data in a table." Clearly stating the desired output format significantly increases the likelihood of receiving a response that is immediately usable.    4. Putting it into Practice: Exploring Different Ways to Structure Your Prompts There are various ways to structure your prompts to effectively communicate with AI tools. Understanding these basic structures can help beginners get started. Question-based prompts  are perhaps the most straightforward, where you directly ask the AI a question to obtain an answer . An example is: "What are the main benefits of using renewable energy sources?" This method is intuitive as it mirrors how we naturally seek information.    Instruction-based or task-oriented prompts  tell the AI to perform a specific action or task . Examples include: "Write a short story about a robot who learns to love," "Summarize the key points of this article," or "Translate this sentence into Spanish." These prompts demonstrate the AI's capability to go beyond simply answering questions and perform a wide range of actions.    Context-based prompts  provide the AI with background information or context before posing a question or giving an instruction . For example: "You are a historian specializing in ancient Egypt. Based on this excerpt from a historical text [insert excerpt], what were the main religious beliefs of the ancient Egyptians during this period?" By grounding the AI in a specific scenario or knowledge domain, these prompts allow for more nuanced and specific responses.    Analogy-based prompts  use comparisons to help the AI understand complex or abstract concepts . For instance: "Explain the concept of blockchain technology as if you were explaining it to a five-year-old." This technique can simplify intricate topics and make them more accessible to the AI, potentially leading to clearer explanations.    Finally, role-playing prompts  ask the AI to adopt a specific role or persona, which can influence the style and content of its responses . An example is: "You are a marketing expert. Provide three creative slogans for a new eco-friendly cleaning product." This can be particularly useful for generating ideas and content from different perspectives or simulating specific types of expertise.    Table 1: Basic Prompt Structures and Examples Prompt Structure Example Prompt Explanation Question-Based What are the main benefits of using renewable energy sources? Directly asks the AI for information. Instruction-Based Write a short poem about a cat. Tells the AI to perform a specific action. Context-Based You are a historian specializing in ancient Egypt. Based on this excerpt from a historical text [insert excerpt], what were the main religious beliefs of the ancient Egyptians during this period? Provides background information to guide the AI's response. Analogy-Based Explain the concept of blockchain technology as if you were explaining it to a five-year-old. Uses comparisons to help the AI understand complex ideas. Role-Playing You are a marketing expert. Provide three creative slogans for a new eco-friendly cleaning product. Asks the AI to adopt a specific persona. 5. The Future is Prompt: Why These Skills Will Be Essential AI tools are increasingly becoming integrated into our daily lives, impacting how we work, learn, and interact with technology . As this trend continues, the ability to effectively communicate with these AI systems will become an indispensable skill. The rise of generative AI, which can create text, images, and other media, is a significant driver in the growing demand for prompt engineering expertise . The need for precise instructions to guide these powerful creative tools is becoming more and more apparent.    This increasing reliance on AI is also reflected in the job market. The field of prompt engineering is experiencing rapid growth as companies recognize the critical need for individuals who can expertly guide AI models to achieve specific business objectives . We are seeing the emergence of dedicated roles like "Prompt Engineer," and many existing jobs are likely to incorporate or benefit from these skills . Professionals in this field often act as a crucial link between end-users and the underlying AI technology, developing effective prompts and templates to maximize the value derived from these models . The skills required for these roles often include an understanding of natural language processing (NLP) principles .    Beyond the professional realm, mastering prompt design and engineering empowers individuals to leverage AI for a wide array of personal and professional tasks . Whether it's generating creative content, solving complex problems, facilitating learning, or fostering innovation, the ability to craft effective prompts unlocks the potential of AI for everyone. This democratization of access to advanced AI capabilities allows individuals without deep technical knowledge to benefit from this transformative technology . In this context, prompt engineering can be viewed as a fundamental skill for enhancing both personal and professional productivity in the evolving landscape of AI. As AI technology continues its rapid evolution, with new models and capabilities emerging regularly, staying updated on the latest advancements in AI and prompting techniques will be crucial for long-term success in effectively utilizing these tools.    6. Learning by Example: Deconstructing Effective Prompts Examining specific examples of prompts can provide valuable insights into what makes them effective. Consider the task of generating a creative story. A poor prompt might simply be: "Write a story." This is too vague and lacks any specific direction. In contrast, an effective prompt would be: "Write a short science fiction story (around 200 words) about a robot who discovers a hidden garden in a post-apocalyptic city. Make the tone hopeful and slightly melancholic." The effective prompt provides specificity regarding genre, length, setting, and desired emotional tone, guiding the AI to produce a more focused and engaging narrative . This demonstrates that providing detailed instructions significantly improves the quality and relevance of the AI's output.    Another example involves summarizing information. A poor prompt could be: "Summarize this article." This lacks focus and does not specify the desired length or key aspects to highlight. An effective prompt would be: "Summarize the main arguments of this article [insert article text] in three concise bullet points, highlighting the key supporting evidence for each argument" . This prompt clearly defines the task, specifies the output format (bullet points), limits the length (three points), and directs the AI to focus on key evidence. Specifying the desired format makes the output more structured and easier to use.    Finally, consider generating ideas. A poor prompt might be: "Give me some ideas." This is too broad and could yield a wide range of potentially irrelevant suggestions. An effective prompt would be: "As a marketing expert, brainstorm five innovative and low-cost marketing ideas for a new online bookstore targeting young adults (ages 18-25) who are interested in fantasy and science fiction" . By assigning a role ("marketing expert") and providing detailed information about the target audience and their interests, the AI can generate more relevant and creative marketing ideas. Assigning a role to the AI can often lead to more tailored and expert-level responses.    7. The Golden Rules: Fundamental Principles of Great Prompting Several fundamental principles underpin effective prompt design and engineering. Clarity  is paramount; your instructions should be easy for the AI to understand . Use clear and straightforward language, avoiding jargon or ambiguous terms . Imagine you are giving instructions to someone with no prior knowledge of the topic. Unambiguous prompts are essential to prevent misinterpretations by the AI .    Specificity  is another crucial principle. The more specific you are in your prompt, the better the AI can grasp your intent and provide a relevant response . Include details about the desired format, length, style, tone, and any constraints . Specific prompts help models understand exactly what you are looking for .    Providing sufficient context  is also vital . Give the AI the necessary background information it needs to fully understand your request . This helps the AI generate responses that are accurate and aligned with your overall goals . Adequate context within the prompt ensures the AI produces more relevant outputs .    Remember that iteration  is a key part of the process . Be prepared to experiment with different phrasings, add more details, or adjust your prompt based on the AI's initial responses . Prompt engineering is an iterative process of experimentation and refinement .    Finally, consider setting boundaries  . Explicitly state any limitations or things you do not want the AI to include in its response. This can help prevent unwanted or irrelevant information and focus the AI's output .    Table 2: Principles of Effective Prompting Principle Description Why it Matters Clarity Using clear and straightforward language. Avoids misinterpretations by the AI. Specificity Providing enough detail to guide the AI. Leads to more relevant and targeted responses. Context Giving the AI necessary background information. Ensures accuracy and alignment with your goals. Iteration Experimenting and refining prompts based on results. Helps to optimize prompts for better outcomes. Setting Boundaries Defining what to include and avoid in the response. Focuses the output and prevents irrelevant information. 8. Your Toolkit for Success: Practical Tips and Guidelines for Writing Better Prompts When starting with prompt design and engineering, it's often helpful to begin with simple requests and gradually add complexity as you become more comfortable. This step-by-step approach can be more effective than trying to create very complex prompts from the outset. Using action verbs  to clearly specify what you want the AI to do, such as "write," "summarize," or "translate," can make your instructions more direct and less ambiguous .    If you have specific requirements for the length or format of the output, be sure to include this information in your prompt . For example, specifying a word count or asking for a bulleted list ensures the output meets your practical needs. Similarly, if you want the AI to generate content for a particular audience, mentioning this in your prompt will help the AI tailor its language and style accordingly . Defining the target audience helps the AI generate more relevant and engaging content.    Don't hesitate to experiment with different phrasings and structures for your prompts . Sometimes, even a slight change in wording can significantly impact the AI's response. Experimentation is key to discovering the most effective prompting techniques for various tasks. For recurring tasks, consider creating or using pre-defined prompt templates that you can adapt as needed. This can streamline the process and ensure consistency in your interactions with AI.    9. Conclusion: Embracing the Power of Prompting Prompt design and prompt engineering are fundamental skills for anyone looking to effectively engage with the growing landscape of AI tools. By understanding the basic principles of crafting clear, specific, and context-rich prompts, individuals can unlock the vast potential of these technologies for a wide range of applications. Mastering these skills empowers users to guide AI systems to generate high-quality, relevant outputs, ultimately enhancing productivity and fostering innovation. As AI continues to evolve and integrate into our daily lives, the ability to communicate effectively with these systems through well-designed prompts will only become more crucial. Therefore, embracing the power of prompting and continuously refining these skills is a valuable investment for navigating the future of human-AI interaction.

The "gorilla problem" in artificial intelligence (AI) is a metaphor highlighting the potential existential risk that advanced AI systems could pose to humanity. This analogy draws parallels between the fate of gorillas and the possible future of humans in a world dominated by superintelligent machines.​ The Analogy Explained Historically, gorillas have seen their autonomy and habitats diminished due to human activities. Despite sharing approximately 98% of our DNA, gorillas are now endangered, not out of human malice, but as a consequence of our dominance and expansion. This scenario serves as a metaphor among AI researchers, highlighting the risks of creating machines that surpass human intelligence—a concept known as superhuman AI. The fear is that such AI could potentially take over the world, threatening our very existence.  Potential Pathways to Human Subordination Loss of Control:  As AI systems become more intelligent and autonomous, there is a risk that they could make decisions misaligned with human values or interests. This misalignment could lead to scenarios where AI actions are detrimental to humanity. ​ Resource Competition:  Advanced AI might prioritize its objectives over human needs, leading to competition for resources. This competition could result in humans being sidelined or even endangered if AI systems deem human activities counterproductive to their goals. ​ Unintended Consequences:  AI systems could develop unforeseen behaviors or pursue goals in ways that harm humanity, even if not explicitly programmed to do so. The complexity of superintelligent AI might make it challenging to predict and control such behaviors. Addressing the Gorilla Problem To mitigate these risks, several strategies are being explored: Robust AI Alignment:  Ensuring that AI systems' goals and behaviors are consistently aligned with human values and ethics.​ Comprehensive Oversight:  Implementing stringent monitoring and control mechanisms to oversee AI development and deployment.​ Global Collaboration:  Fostering international cooperation to establish regulations and standards for AI research and application.​ Ethical AI Development:  Prioritizing ethical considerations in AI design to prevent harmful outcomes.​ The "gorilla problem" serves as a cautionary tale, emphasizing the need for careful consideration and proactive measures in the development of advanced AI systems. By reflecting on this analogy, we are reminded of the importance of aligning technological progress with the well-being and survival of humanity.

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As AI continues at a rapid pace of development, the average person is having to come to terms with what it means for them. Will AI bring about millions of job losses? Will it create more? And if it does create more, will they be up to the task? We examine some of these pressing issues in our deep dive today powered by NotebookLM The