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Infiniti Vision Qe Previews a Coming EV

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Callisto is in "Fallen Angel" and "Seeds of Faith". In "Fallen Angel," Callisto is in hell until Xena gives up her place in heaven, then we see the Callisto that would have been had Xena not killed her family. In "Seeds of Faith," Callisto is the angel ...

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So, here's the tease: In the first chapter of Mortal Kombat 1 — when you play as Kung Lao — there is a brief moment where Lao grabs a weapon off the wall and throws it at one of his enemies. Now, this may not seem like much to you, but to a huge nerd and fan of Xena Warrior Princess like me, this was a pretty exciting moment.

Is Mortal Kombat 1 teasing a Xena Warrior Princess crossover on PS5?

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XENA VISION

xenavision

HackerNoon Reporter: Please tell us briefly about your background. I have lots of titles as an entrepreneur. I am a technical solo female founder. This is how the ecosystem defines me. I define myself as a passionate one. I want to save human life. This is all about my startup spirit. What's your startup called? And in a sentence or two, what does it do? It is called Xena Vision. We are a computer vision-focused deep tech startup. We employ tech to save human lives in the case of an emergency. The system acts as an independent warrior who fights to save you by detecting your situation and asking for help by alarming. Our focus is violence detection, heart attack, fall, car accident detection, and prevention by real-time video analytics. What is the origin story? The story began in France, Nice, on the 14th of Jun 2016. I was a master's student in Nice Univesity in Theoretical Computer Science and working in Inria as a research intern on video activity recognition. At the same time, I attended a 15 days Entrepreneurship Bootcamp called EIA. Students from Berkeley, Nice, and all around the world, we were about to conclude great MVPs. That day a terrible terrorist attack happened in Nice, and 83 people lost their lives; and 3 of them were our friends of Bootcamp. I was broken into pieces, and afterward, I wanted nothing more than to save people. I am a computer engineer with expertise in Activity Recognition. So that I have the power to convert any camera to an intelligent one to capture emergencies, this is how the story begins. In 2018 I launched my startup dedicated to this project with national R&D Institution Funding by being selected into 140 out of 4500. What do you love about your team, and why are you the ones to solve this problem? We are great together! So young, so energetic, so impatient! We are sensitive and care for each other. We have no fixed hours on the team. No pressure and no intolerance. First, we care for each other in the team. By performing this each day, we develop a product that cares for human life, safety and security. We learn a lot! We are bright enough to believe that the world can become a much better place, so that we work by heart to make it happen. We dedicate our most important asset to this project. It is our time and dedication at a young age. If you weren’t building your startup, what would you be doing? I have professional experience in sports volunteer management. I lead 2 times international workcamps of 20 people for almost a month. Probably I could be preparing to launch my own startup and practicing voluntary management along with my profession as a full-time worker. At the moment, how do you measure success? What are your core metrics? Our primary metric is our customer satisfaction.(Saving Lives). The secondary one is traction. The third one could be the number of customers obtained for the period. Of course, customer persistence. What’s most exciting about your traction to date? Hearing Wows from executives. They are motivated to support and suggest the product. We work with our biggest enterprises locally. What technologies are you currently most excited about and most worried about? And why? We develop our own activity recognition algorithms and models. The most exciting part is the involvement and interest in AI. There is a great growing audience. The most challenging part for us was to show our customers that our system is not like an ordinary system for people identity tracking. We are fully focused on events and unwanted happenings. We collect data in an anonymous way. We are not interested in personalized information. All we want is to create every corner of a city secure by detecting abnormal events in a real-time manner. This is so new that we applied the patent for our system. Changing their perception to be watched is challenging even though we won’t. What drew you to get published on HackerNoon? What do you like most about our platform? Great place to be in as the audience is technologists. What advice would you give to the 21-year-old version of yourself? It’s all worth it. What is something surprising you've learned this year that your contemporaries would benefit from knowing? Being an idealist, desiring to change the world and never stop creating innovation, if these are all about your personality, there is nothing that fits you best other than being an entrepreneur. Do not wait and don’t think twice! We are born to die and live to change. Let’s shape the team, build the game and go for it! Vote for us! I promise we will help you on this journey on the same road. Vote for XENA VISION as ! Ankara’s startup of the year

I Chose Emergency Healthcare After Losing My Friends in a Terrorist Attack: CEO Xena Vision

214 Stories To Learn About Computer Vision

95 Stories To Learn About Startup Founders

Heyo Hackers! I'm pretty sure that you are familiar with . In case you aren't, here is tl;dr: startups of the year by Hackernoon It's the BIGGEST and GREENEST celebration of startups around the world. Startups of the Year honors the best startups among 4,500+ cities with over 100,000 population. Why Startups of the Year? HackerNoon understands the struggle and pain involved in running a startup. I mean, we are also ONE OF YOU! And being a community-driven tech publishing company, tech startups are a big part of us. Here is an excerpt from our COO : Linh Smooke's interview We’re publishing mostly tech stories, as well as really, really deep dive technical stuff on JavaScript, software development programming, as well as blockchain content. but we do believe that tech infiltrates all aspects of life. So we also have stories about startups and building your own businesses With the startup of the year awards, we are celebrating those who not only survived but thrived through 2021. Shoutout to all the startups! For us YOU ALL ARE WINNERS! Why do Startups choose HackerNoon? Yup, feelings are mutual. HackerNoon is the FAV publishing platform of startups around the globe. Recently, we've started a with our nominations. In this series, more than 200 startups have shared their stories, work culture, and thoughts about the latest tech. startup of the year interview series We also asked them: What drew you to get published on HackerNoon? What do you like most about our platform? We received a variety of interesting responses. Just sharing a few with y'all here. Let's see why startups from around the globe want to publish with HackerNoon: 1. Range and Variety Matters Jason Eisen, CEO of UTU, is one of our oldest readers, and of the content published on HackerNoon: he loves the range and diversity I've been reading Hacker Noon for many years now, and I admire how it went from being a developer-focused blog to a massive, wide-ranging tech publication. The content ranges from developer tutorials to life-improvement stories all focused on tech. It's truly a unique reading experience, and we would be honored to be published on Hacker Noon. Andrew Cross, CEO GooseChase, shares the : same sentiments I am technical, and I do code, but I'm also a product person at heart. HackerNoon does a great job at treating the spectrum of engineering and product, and isn't afraid to dive deep on the topics they cover regardless of how technical or niche they may be: from talking about the latest programming libraries, to HIPAA compliance, to running a product team... the content is always relevant and hits the sweet spot between product and engineering. It's a resource everyone on the team benefits from. So yes - there is something for everyone to read! 2. Accessibility! Here is an excerpt from : the startup interview with AIR Cofounders HackerNoon offers a very open, accessible platform for people to learn and share knowledge, with accessible tools everyone can use from anywhere; in that sense, it aligns pretty well with how we think about what the future of AI should be :) Talking about accessibility, we have great news for everyone! HackerNoon has just launched a new feature - You can now listen to top HackerNoon stories too! LISTENING TO STORIES IS ALWAYS FUN! Simply scroll down to any recent story, pick your AI voice, and experience HackerNoon stories like you have never before! 3. The GROOVE As Avijeet Kumar Singh, : Cofounder of Prakshep, said The fact that you publish " ". unfettered stories and opinions Adam Gordon Bell from Earthly : endorses the groove I like the aesthetics of HackerNoon and the mischievous and whimsical tone of some of the articles. 4. FREE Content Forever We all agree: . All tech content on Hacker Noon will always be free for the readers. Johnpaul Nwobodo, CEO of Elesaro . Paywalls suck loves HackerNoon for that Real-life solutions for founders to implement in their startups are always dished out here for free. 5. Tech Viewership: Now, this is a very pragmatic response we received from : CEO, Xena Vision Great place to be in as the audience is technologists. This is one of the top reasons HackerNoon is loved by . With our dedicated readership and strong domain authority, we're a reliable partner to get the good word out and grow your presence across the interwebs. We showcase your story on our website to a monthly + tech audience! tech brands 3M 6. What's in a Name? This response by the : Head Of Hackers at Intigriti is quite amusing It probably won't surprise you that I'm in love with the name. The positive usage of the word 'hacker' is something we need to encourage - the hacker community is the greatest, most welcoming family you can imagine. On this note, let's wrap up this story. We thank you for all the love. Do check out the and vote for your favorite startup. Also, do check out ! startups of the year page Startup Specials - HackerNoon's limited-time, startup-friendly packages This article was originally published as on . 6 Reasons Why Startups Publish With HackerNoon HackerNoon Sponsors Blog

Why Startups Publish With HackerNoon 

After a marathon of interviews, tests, code challenges, and awkward small talk with people you’ll likely never see again, you finally land the job. You’re excited, ready to dive in and make an impact. But then reality hits: onboarding feels like an afterthought. It’s like dating someone who showers you with attention—right up until you move in. Suddenly, they’re on the couch eating chips, and you’re left wondering, “Where do I put my stuff? Is this really what I signed up for?” In tech, onboarding is often rushed—a box to check before new hires start coding. But poor onboarding isn’t just frustrating; it’s a silent productivity killer. It slows down the whole team, disrupts development cycles, and drives up turnover costs. The bigger the team, the bigger this problem becomes Longer ramp-up times
Higher turnover
Reduced team productivity
Knowledge silos …And the list goes on. With so much at stake, isn’t it time to treat onboarding as a critical driver of team success and product momentum? The Problem For many developers, onboarding is like being thrown into a maze with a half-finished map and hoping they’ll figure it out. You’re handed a laptop, access to a few tools, and maybe a “buddy” to show you around. But without clear guidelines, expectations, or structure, it quickly becomes chaotic—especially in larger organizations. Instead of hitting the ground running, you’re left navigating a minefield of confusion and bottlenecks. One of the biggest myths? That simply assigning a buddy solves everything. Sure, having a go-to person can help, but without clear goals and structure, this approach leaves gaps. Why the Traditional Checklist Isn’t Enough Many companies still treat onboarding as a checklist: grant tool access, set up emails, assign a few tasks, and call it a day. But this “transactional” approach misses the mark. Checklists are great for covering the basics—the “how” of a role—but rarely address the “why.” New developers need more than a tour of tools; they need a clear understanding of the mission, purpose, and impact of their work. Without that, engagement suffers, and new hires quickly feel like just another cog in the machine. My take is that we need to approach onboarding with the same care and thoughtfulness we put into hiring. Rather than rushing through orientation and tool setup, onboarding should gradually integrate new developers through role-specific workflows and clear milestones that help them see both the technical and strategic context of their work. A checklist is where passion goes to die. Onboarding needs to be dynamic, intentional, and empowering, giving developers a clear path to early wins and a strong sense of purpose from day one! Breaking Down Knowledge Silos One of the biggest onboarding headaches is knowledge silos. Developers constantly need info that’s scattered across teams, tools, and documents. Chasing down these details every week isn’t just a productivity drain; it’s frustrating. Imagine flipping the process so it’s not just up to the stakeholder creating the onboarding journey to attach relevant knowledge. Instead, the system could actively surface the right information for new developers at the right time, reducing back-and-forth. This is the direction I envision—starting with building a structured journey, integrating essential apps, attaching relevant knowledge, and automating its delivery. I also think community-generated templates are a great idea—a library that evolves and improves with real-world input. There’s a lot more to explore here, and it’s an exciting road ahead! I asked Killian Dunne, CTO of Telepathic, "How do you think templates could support onboarding efficiency and consistency across teams?" His response: It’s a huge hassle to keep making resources and then going through the same onboarding process every time with technical hires. If you're able to significantly cut down that setup and training time then that’d be huge! Onboarding and Retention: Two Sides of the Same Coin Onboarding and retention are intrinsically linked. A positive onboarding experience makes developers feel valued and supported, which is key to long-term satisfaction and engagement. Poor onboarding, by contrast, can be a red flag, signaling that the company lacks organization, which will lead developers to look for opportunities elsewhere. I see time and again that an investment in onboarding is an investment in retention. Developer onboarding isn’t just a step in the hiring process; it’s a long-term investment in your team. Thank you so much for reading my first HackerNoon article! 😊 I'm Rasmus Stjernström, co-founder of Silo Team. Together with my sister and our small, passionate team, we're on a mission to make onboarding truly seamless. Why? Because when developers can hit the ground running, they ship products faster—and everyone benefits. If you're interested in exchanging ideas or trying out our beta, feel free to reach out! After a marathon of interviews, tests, code challenges, and awkward small talk with people you’ll likely never see again, you finally land the job. You’re excited, ready to dive in and make an impact. But then reality hits: onboarding feels like an afterthought. It’s like dating someone who showers you with attention—right up until you move in. Suddenly, they’re on the couch eating chips, and you’re left wondering, “Where do I put my stuff? Is this really what I signed up for?” In tech, onboarding is often rushed—a box to check before new hires start coding. But poor onboarding isn’t just frustrating; it’s a silent productivity killer. It slows down the whole team, disrupts development cycles, and drives up turnover costs. The bigger the team, the bigger this problem becomes Longer ramp-up times Higher turnover Reduced team productivity Knowledge silos Longer ramp-up times Higher turnover Reduced team productivity Knowledge silos …And the list goes on. With so much at stake, isn’t it time to treat onboarding as a critical driver of team success and product momentum? The Problem For many developers, onboarding is like being thrown into a maze with a half-finished map and hoping they’ll figure it out. You’re handed a laptop, access to a few tools, and maybe a “buddy” to show you around. But without clear guidelines, expectations, or structure, it quickly becomes chaotic—especially in larger organizations. Instead of hitting the ground running, you’re left navigating a minefield of confusion and bottlenecks. One of the biggest myths? That simply assigning a buddy solves everything. Sure, having a go-to person can help, but without clear goals and structure, this approach leaves gaps. One of the biggest myths? That simply assigning a buddy solves everything. Sure, having a go-to person can help, but without clear goals and structure, this approach leaves gaps. Why the Traditional Checklist Isn’t Enough Many companies still treat onboarding as a checklist: grant tool access, set up emails, assign a few tasks, and call it a day. But this “transactional” approach misses the mark. Checklists are great for covering the basics—the “how” of a role—but rarely address the “why.” New developers need more than a tour of tools; they need a clear understanding of the mission, purpose, and impact of their work. Without that, engagement suffers, and new hires quickly feel like just another cog in the machine. My take is that we need to approach onboarding with the same care and thoughtfulness we put into hiring. Rather than rushing through orientation and tool setup, onboarding should gradually integrate new developers through role-specific workflows and clear milestones that help them see both the technical and strategic context of their work. A checklist is where passion goes to die. Onboarding needs to be dynamic, intentional, and empowering, giving developers a clear path to early wins and a strong sense of purpose from day one! Breaking Down Knowledge Silos One of the biggest onboarding headaches is knowledge silos. Developers constantly need info that’s scattered across teams, tools, and documents. Chasing down these details every week isn’t just a productivity drain; it’s frustrating. it’s frustrating. Imagine flipping the process so it’s not just up to the stakeholder creating the onboarding journey to attach relevant knowledge. Instead, the system could actively surface the right information for new developers at the right time, reducing back-and-forth. This is the direction I envision—starting with building a structured journey, integrating essential apps, attaching relevant knowledge, and automating its delivery. I also think community-generated templates are a great idea—a library that evolves and improves with real-world input. There’s a lot more to explore here, and it’s an exciting road ahead! I asked Killian Dunne , CTO of Telepathic, "How do you think templates could support onboarding efficiency and consistency across teams?" His response: Killian Dunne It’s a huge hassle to keep making resources and then going through the same onboarding process every time with technical hires. If you're able to significantly cut down that setup and training time then that’d be huge! It’s a huge hassle to keep making resources and then going through the same onboarding process every time with technical hires. If you're able to significantly cut down that setup and training time then that’d be huge! Onboarding and Retention: Two Sides of the Same Coin Onboarding and retention are intrinsically linked. A positive onboarding experience makes developers feel valued and supported, which is key to long-term satisfaction and engagement. Poor onboarding, by contrast, can be a red flag, signaling that the company lacks organization, which will lead developers to look for opportunities elsewhere. I see time and again that an investment in onboarding is an investment in retention. Developer onboarding isn’t just a step in the hiring process; it’s a long-term investment in your team. Developer onboarding isn’t just a step in the hiring process; it’s a long-term investment in your team. Thank you so much for reading my first HackerNoon article! 😊 I'm Rasmus Stjernström , co-founder of Silo Team . Together with my sister and our small, passionate team, we're on a mission to make onboarding truly seamless. Why? Because when developers can hit the ground running, they ship products faster—and everyone benefits. If you're interested in exchanging ideas or trying out our beta, feel free to reach out! Thank you so much for reading my first HackerNoon article! 😊 Rasmus Stjernström Silo Team

Why Developer Onboarding is Broken—and What Needs to Change

At HackerNoon, we value stories about building groundbreaking tech. These questions aren’t just about AI mechanics—they’re about the innovation, challenges, and creativity of bringing cutting-edge tools to life, a perfect fit for our community of tech leaders, builders, and future-minded readers. Would you like to take a stab at answering some of these questions? The link for the template is HERE. Interested in reading the content from all of our writing prompts? Click HERE. What’s the main problem your AI product is designed to solve, and what is effective about your approach to solving it? What criteria did you use to select the specific AI models for this product, and how does your company make decisions like this? How do you ensure your product delivers accurate and unbiased results to users? What is your day in the life like as a product manager? What’s the next big breakthrough in AI that everyone should be watching for? What’s been the biggest challenge you’ve faced in bringing this AI product to market, from concept to launch? How do you envision AI evolving to better understand and respond to human emotions, and what challenges or opportunities do you see in that area? What performance metrics or KPIs do you track to gauge the success of this AI product? How do you approach designing a product experience that’s not only functional but also engaging and memorable for users? In the long-term, how do you think AI will help the individual reach one’s full potential? Where do you see the product evolving in the next few years, and what features are you most excited to add? What’s your perspective on AI’s impact on jobs, and how do you address those concerns in your product strategy? What user feedback surprised you and led to changes in your roadmap, strategy or product experience? Would you like to take a stab at answering some of these questions? The link for the template is HERE. Interested in reading the content from all of our writing prompts? Click HERE. Learn more about AI on HackerNoon. At HackerNoon, we value stories about building groundbreaking tech. These questions aren’t just about AI mechanics—they’re about the innovation, challenges, and creativity of bringing cutting-edge tools to life, a perfect fit for our community of tech leaders, builders, and future-minded readers. At HackerNoon, we value stories about building groundbreaking tech. These questions aren’t just about AI mechanics—they’re about the innovation, challenges, and creativity of bringing cutting-edge tools to life, a perfect fit for our community of tech leaders, builders, and future-minded readers. Would you like to take a stab at answering some of these questions? The link for the template is HERE. Interested in reading the content from all of our writing prompts? Click HERE. Would you like to take a stab at answering some of these questions? The link for the template is HERE . Interested in reading the content from all of our writing prompts? Click HERE . The link for the template is HERE HERE . HERE HERE . What’s the main problem your AI product is designed to solve, and what is effective about your approach to solving it? What’s the main problem your AI product is designed to solve, and what is effective about your approach to solving it? What criteria did you use to select the specific AI models for this product, and how does your company make decisions like this? What criteria did you use to select the specific AI models for this product, and how does your company make decisions like this? How do you ensure your product delivers accurate and unbiased results to users? How do you ensure your product delivers accurate and unbiased results to users? What is your day in the life like as a product manager? What is your day in the life like as a product manager? What’s the next big breakthrough in AI that everyone should be watching for? What’s the next big breakthrough in AI that everyone should be watching for? What’s been the biggest challenge you’ve faced in bringing this AI product to market, from concept to launch? What’s been the biggest challenge you’ve faced in bringing this AI product to market, from concept to launch? How do you envision AI evolving to better understand and respond to human emotions, and what challenges or opportunities do you see in that area? How do you envision AI evolving to better understand and respond to human emotions, and what challenges or opportunities do you see in that area? What performance metrics or KPIs do you track to gauge the success of this AI product? What performance metrics or KPIs do you track to gauge the success of this AI product? How do you approach designing a product experience that’s not only functional but also engaging and memorable for users? How do you approach designing a product experience that’s not only functional but also engaging and memorable for users? In the long-term, how do you think AI will help the individual reach one’s full potential? In the long-term, how do you think AI will help the individual reach one’s full potential? Where do you see the product evolving in the next few years, and what features are you most excited to add? Where do you see the product evolving in the next few years, and what features are you most excited to add? What’s your perspective on AI’s impact on jobs, and how do you address those concerns in your product strategy? What’s your perspective on AI’s impact on jobs, and how do you address those concerns in your product strategy? What user feedback surprised you and led to changes in your roadmap, strategy or product experience? What user feedback surprised you and led to changes in your roadmap, strategy or product experience? Would you like to take a stab at answering some of these questions? The link for the template is HERE. Interested in reading the content from all of our writing prompts? Click HERE. Would you like to take a stab at answering some of these questions? The link for the template is HERE . Interested in reading the content from all of our writing prompts? Click HERE . The link for the template is HERE HERE . HERE HERE . Learn more about AI on HackerNoon. Learn more about AI on HackerNoon . Learn more about AI on HackerNoon

Baker's Dozen AI: 13 Questions with a Product Manager Who Makes an AI Product 

How to Build a Sustainable Web3 Ecosystem

Kunjamas mä Ecosistema Web3 Sostenible luraña

Cómo construir un ecosistema Web3 sostenible

Comment construire un écosystème Web3 durable

Como construír un ecosistema Web3 sostible

Kako izgraditi održivi Web3 ekosustav

持続可能なWeb3エコシステムを構築する方法

지속 가능한 Web3 생태계를 구축하는 방법

Cara Membina Ekosistem Web3 yang Mampan

තිරසාර Web3 පරිසර පද්ධතියක් ගොඩනගන්නේ කෙසේද?

Maitiro Ekuvaka Yakasimba Web3 Ecosystem

Làm thế nào để xây dựng một hệ sinh thái Web3 bền vững

如何构建可持续的 Web3 生态系统

When people think about Artificial Intelligence (AI), they often envision a world filled with complicated algorithms, impenetrable code, and teams of expert mathematicians working with massive servers. For years, this intimidating image has kept non-technical people at bay, making AI seem like a realm accessible only to those with deep technological expertise. Yet, in 2024, many of these assumptions no longer hold true and are, quite frankly, absurd. Here’s a look at the myths that need debunking and the unexpected truths that may surprise you. You Need to Be in IT or Know Programming to Use AI The idea that AI is solely for IT professionals or those who can code is a relic of the past. Today, tools like ChatGPT, Midjourney, and other AI platforms have simplified user interfaces and accessible functionalities that cater to everyone, from writers and marketers to students and retirees. These platforms enable users to benefit from AI with just a few clicks, dragging and dropping content or engaging in natural language conversations. ICYMI: You can actually use AI to write code even if you’re not a programmer. Platforms like ChatGPT can generate snippets of code in Python, JavaScript, or even obscure languages like COBOL—all based on simple prompts. This means non-technical users can dabble in coding projects, troubleshoot errors, or automate mundane tasks without ever opening a coding textbook. You Need to Be a Mathematician or Statistician to Use AI It’s true that AI was built on complex mathematical principles and algorithms, but that’s where its association with math should end for most users. The AI systems we interact with today are designed to hide this complexity, providing users with straightforward, intuitive interfaces. You don’t need to understand calculus or linear algebra to appreciate the benefits of AI any more than you need to know how an internal combustion engine works to drive a car. ICYMI: Math was used to build these models, but math is arguably the worst place to use them. In fact, LLMs occasionally get math problems wrong. AI excels in creating dynamic conversations, generating creative content, and solving problems where human intuition would typically trump formulas. The irony is that for most business use cases, attempting to use AI purely for mathematical functions undermines its true potential. You Need a High-End Laptop, Servers, or Cloud Subscriptions to Use AI It’s natural to assume that cutting-edge technology requires cutting-edge equipment. However, with cloud-based services and AI applications that run on browsers, almost anyone with an internet connection can access the most powerful AI models in the world using a basic laptop, tablet, or even a smartphone. Free or low-cost subscription plans on platforms like Google Colab or OpenAI’s ChatGPT make experimentation affordable and accessible. You Need Clean, Curated, Warehoused Data to Use AI A common misconception is that AI systems need pristine, perfectly formatted datasets stored in high-end data warehouses to function. This was true for traditional machine learning models. Today’s generative AI models can work with natural language inputs, making them vastly more adaptable and flexible. You can input unstructured information like casual text, incomplete data, or even ideas you’re still developing, and AI will still deliver usable outputs. AI Hallucinates AI hallucinations—where the system generates plausible but false or nonsensical information—are a real concern, but they are often misunderstood. People blame the AI itself, but hallucinations occur mostly because of poorly framed prompts or insufficient context. When properly guided through techniques like prompt engineering, hallucinations can be minimized, making the AI’s outputs significantly more accurate. ICYMI: Hallucinations occur more often if you do not use prompt engineering. Understanding how to communicate with the AI, how to set constraints, and how to refine prompts leads to more reliable outputs and reduces the risk of confusing or incorrect information. Prompt Engineering is Useless The role of prompt engineering is often dismissed by skeptics who see it as trivial or unimportant. Yet, this skill—knowing how to communicate effectively with AI models—can make a significant difference in the quality of the AI’s outputs. Prompt engineering is akin to knowing how to ask the right questions in a search engine; it’s not a superfluous task but a critical competency. In fact, industries are beginning to see prompt engineers as an essential part of AI project teams, guiding the models to produce business-ready results. Final Thoughts: The Democratization of AI What we’re witnessing today is the democratization of AI—an era where AI isn’t just for techies or mathematicians. People from all walks of life are embracing AI to write books, create art, develop recipes, and even enhance personal productivity. The absurdity lies not in these widespread applications but in the stubborn myths that prevent more people from exploring AI’s potential. As AI continues to become more accessible and versatile, it’s time to lay these misconceptions to rest. Whether you’re a business owner looking to streamline operations or a teacher seeking new ways to engage students, AI has something to offer. Embrace it, experiment with it, and discover its real value—no technical degree is required. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com When people think about Artificial Intelligence (AI), they often envision a world filled with complicated algorithms, impenetrable code, and teams of expert mathematicians working with massive servers. For years, this intimidating image has kept non-technical people at bay, making AI seem like a realm accessible only to those with deep technological expertise. Yet, in 2024, many of these assumptions no longer hold true and are, quite frankly, absurd. Here’s a look at the myths that need debunking and the unexpected truths that may surprise you. You Need to Be in IT or Know Programming to Use AI The idea that AI is solely for IT professionals or those who can code is a relic of the past. Today, tools like ChatGPT, Midjourney, and other AI platforms have simplified user interfaces and accessible functionalities that cater to everyone, from writers and marketers to students and retirees. These platforms enable users to benefit from AI with just a few clicks, dragging and dropping content or engaging in natural language conversations. ICYMI : You can actually use AI to write code even if you’re not a programmer. Platforms like ChatGPT can generate snippets of code in Python, JavaScript, or even obscure languages like COBOL—all based on simple prompts. This means non-technical users can dabble in coding projects, troubleshoot errors, or automate mundane tasks without ever opening a coding textbook. ICYMI You Need to Be a Mathematician or Statistician to Use AI It’s true that AI was built on complex mathematical principles and algorithms, but that’s where its association with math should end for most users. The AI systems we interact with today are designed to hide this complexity, providing users with straightforward, intuitive interfaces. You don’t need to understand calculus or linear algebra to appreciate the benefits of AI any more than you need to know how an internal combustion engine works to drive a car. ICYMI : Math was used to build these models, but math is arguably the worst place to use them. In fact, LLMs occasionally get math problems wrong. AI excels in creating dynamic conversations, generating creative content, and solving problems where human intuition would typically trump formulas. The irony is that for most business use cases, attempting to use AI purely for mathematical functions undermines its true potential. ICYMI You Need a High-End Laptop, Servers, or Cloud Subscriptions to Use AI It’s natural to assume that cutting-edge technology requires cutting-edge equipment. However, with cloud-based services and AI applications that run on browsers, almost anyone with an internet connection can access the most powerful AI models in the world using a basic laptop, tablet, or even a smartphone. Free or low-cost subscription plans on platforms like Google Colab or OpenAI’s ChatGPT make experimentation affordable and accessible. You Need Clean, Curated, Warehoused Data to Use AI A common misconception is that AI systems need pristine, perfectly formatted datasets stored in high-end data warehouses to function. This was true for traditional machine learning models. Today’s generative AI models can work with natural language inputs, making them vastly more adaptable and flexible. You can input unstructured information like casual text, incomplete data, or even ideas you’re still developing, and AI will still deliver usable outputs. AI Hallucinates AI hallucinations—where the system generates plausible but false or nonsensical information—are a real concern, but they are often misunderstood. People blame the AI itself, but hallucinations occur mostly because of poorly framed prompts or insufficient context. When properly guided through techniques like prompt engineering, hallucinations can be minimized, making the AI’s outputs significantly more accurate. ICYMI : Hallucinations occur more often if you do not use prompt engineering. Understanding how to communicate with the AI, how to set constraints, and how to refine prompts leads to more reliable outputs and reduces the risk of confusing or incorrect information. ICYMI Prompt Engineering is Useless The role of prompt engineering is often dismissed by skeptics who see it as trivial or unimportant. Yet, this skill—knowing how to communicate effectively with AI models—can make a significant difference in the quality of the AI’s outputs. Prompt engineering is akin to knowing how to ask the right questions in a search engine; it’s not a superfluous task but a critical competency. In fact, industries are beginning to see prompt engineers as an essential part of AI project teams, guiding the models to produce business-ready results. Final Thoughts: The Democratization of AI What we’re witnessing today is the democratization of AI—an era where AI isn’t just for techies or mathematicians. People from all walks of life are embracing AI to write books, create art, develop recipes, and even enhance personal productivity. The absurdity lies not in these widespread applications but in the stubborn myths that prevent more people from exploring AI’s potential. As AI continues to become more accessible and versatile, it’s time to lay these misconceptions to rest. Whether you’re a business owner looking to streamline operations or a teacher seeking new ways to engage students, AI has something to offer. Embrace it, experiment with it, and discover its real value—no technical degree is required. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com

AI: It's Not What You Think

How Build Your Own AI Confessional: How to Add a Voice to the LLM

কীভাবে আপনার নিজের এআই স্বীকারোক্তিমূলক তৈরি করুন: কীভাবে এলএলএম-এ একটি ভয়েস যুক্ত করবেন

So bauen Sie Ihren eigenen KI-Beichtstuhl: So fügen Sie dem LLM eine Stimme hinzu

Cómo construir su propio confesionario de IA: cómo agregar una voz al LLM

Comment créer votre propre confessionnal d'IA : comment ajouter une voix au LLM

अपना खुद का AI कन्फेशनल कैसे बनाएं: LLM में आवाज़ कैसे जोड़ें

独自の AI を構築する方法 告白: LLM に声を加える方法

자신만의 AI 고백을 구축하는 방법: LLM에 음성을 추가하는 방법

Como construir seu próprio confessionário de IA: como adicionar uma voz ao LLM

Как создать свою собственную исповедь искусственного интеллекта: как добавить голос к LLM

Kendi Yapay Zeka İtirafınızı Nasıl Oluşturabilirsiniz: Yüksek Lisans'a Ses Nasıl Eklenir?

Cách xây dựng chuyên gia AI của riêng bạn: Cách thêm tiếng nói vào LLM

如何构建自己的 AI 忏悔室：如何为法学硕士 (LLM) 添加声音

At Hummus Said in Acre, Israel, I always order hummus with Foul, don’t think much about it, just add a bit of salt and digg in with the onion. At Hummus Said, a legendary restaurant in Akko, Israel, I savor their signature dish: creamy hummus with a side of Foul. The taste is always perfect, but on one visit, I brought a giant container, joking, "Can bulk hummus match this experience?" Said, the owner and hummus maestro, chuckled, "The flavor might be the same, but the experience suffers.” Just as the bulk hummus misses the essence of Hummus Said, many leaders get lost in the sheer volume of data.  They dream of overflowing databases, perfect metrics for drag-and-drop dashboards, and magically solved problems.- Lior Barak Forget the data dreamland, leaders! You envision overflowing databases, perfect metrics for drag-and-drop dashboards, and magically solved problems. Think again. Simple KPIs like sessions and revenue are just appetizers, not the full course to success. The harsh reality? Most companies choke on their data because they focus on the wrong ingredients. Data strategy isn't a gourmet buffet; it's a clear, actionable recipe. Time to ditch the data daydream and start cooking! Set Clear KPIs! Many leaders envision a data strategy as a readily available buffet - a vast collection of metrics that can be easily assembled into insights. This approach, however, overlooks a critical first step: defining clear and actionable Key Performance Indicators (KPIs). Just as a chef wouldn't haphazardly throw ingredients together and expect a culinary masterpiece, a data strategy requires a well-defined recipe. Your recipe, in this case, consists of the 3-5 key performance indicators (KPIs) that truly capture the essence of your company's success. These KPIs serve as the foundation for your data strategy, guiding all stakeholders towards the metrics that matter most. Think of KPIs as the flavor profile of your data. In my book, "Data is Like a Plate of Hummus" I promote a funnel methodology for defining KPIs: Identify key questions: What are the most critical questions you need answered about your business? For example: What are the revenues from ad-free subscriptions?
How many users bought more than one item in the same basket? Refine your questions: Focus on the most essential ones. Understand which questions are critical for your company goals and strategy, and which answers will help you evaluate the company's health. Define KPIs: Which metrics can effectively provide answers to those refined questions? Understand the KPIs that will give you these answers following the five W's principles: Who is the controller of the KPI? Who owns the data that will be used for the KPI, and who is responsible for ensuring its accuracy and stability?
What action will it drive me to take? If I see a positive or negative change in the KPI.
How well will it give me answers for the company’s health? What else am I missing?
Where is the issue? Can I receive an answer about which company section the issue is?
When do I need to see it? How frequently are these measurements needed? (For example, a weekly "time-on-site" KPI might be sufficient to gauge the effectiveness of UX changes, not requiring daily monitoring.) Building Scalable and Iterative Infrastructure Now that you know what flavors you need, let's talk kitchen setup. Think fast, efficient deployment. Forget a one-size-fits-all approach. Start with a basic setup that can be easily enhanced. Treat it like a recipe collection, evolving with each new dish. Each iteration focuses on either enhancing the kitchen tools or optimizing costs. As a chef, you care if your kitchen equipment is top-of-the-line or basic, but you will know how to work with both. What matters is delivering a delicious, well-presented dish. Your team needs to think about how to maximize the buy/build approach for the first iteration because they will learn all the time about what enhances the flavors and what doesn't, and where the issues lie. The main purpose of picking kitchen tools should be to enhance the Secret Ingredients you selected and allow for further experimentation by the chefs. It needs to be something that will be easy to switch or optimize. But for me, the more important part of the setup is to launch something I can taste-test with the diners and learn how it complements the dish, whether they notice enhancements or not. So, don’t deploy and forget until it breaks. The data chefs need to go around and collect feedback, understand the flavor profiles of diners, and prioritize them in the recipe book. Building trust is essential. Inconsistent flavors in a dish quickly erode a diner's trust in the chef. Similarly, unreliable or inconsistent data undermine the credibility of your data-driven insights. Establish clear data governance guidelines – outlining data availability timelines, ownership, and issue resolution protocols – to ensure data quality and consistency. Imagine the wasted effort required to validate data if its reliability is questionable constantly! Embrace the Journey, Share the Feast Data strategy is about crafting flavorful dishes for a successful restaurant. By focusing on clear recipes (KPIs), strong governance, and a scalable kitchen setup (infrastructure), you can create your culinary oasis – one that delights your diners (customers) and fuels your restaurant's (company's) growth. Ready to take a bite out of your data woes? Read my book, "Data is Like a Plate of Hummus” Buy My Book On Amazon Dive deeper into the five Ws of effective KPIs, explore data governance best practices, and guide you through building a scalable data infrastructure. Learn how to transform your data into a strategic advantage and unlock the full flavor of your company's success! At Hummus Said in Acre, Israel, I always order hummus with Foul, don’t think much about it, just add a bit of salt and digg in with the onion. At Hummus Said, a legendary restaurant in Akko, Israel, I savor their signature dish: creamy hummus with a side of Foul. The taste is always perfect, but on one visit, I brought a giant container, joking, "Can bulk hummus match this experience?" Said, the owner and hummus maestro, chuckled, "The flavor might be the same, but the experience suffers.” Just as the bulk hummus misses the essence of Hummus Said, many leaders get lost in the sheer volume of data.  They dream of overflowing databases, perfect metrics for drag-and-drop dashboards, and magically solved problems.- Lior Barak Just as the bulk hummus misses the essence of Hummus Said, many leaders get lost in the sheer volume of data.  They dream of overflowing databases, perfect metrics for drag-and-drop dashboards, and magically solved problems. - Lior Barak Forget the data dreamland, leaders! You envision overflowing databases, perfect metrics for drag-and-drop dashboards, and magically solved problems. Think again. Simple KPIs like sessions and revenue are just appetizers, not the full course to success. Forget the data dreamland, leaders! Think again. The harsh reality? Most companies choke on their data because they focus on the wrong ingredients. Data strategy isn't a gourmet buffet; it's a clear, actionable recipe. Time to ditch the data daydream and start cooking! The harsh reality? Time to ditch the data daydream and start cooking! Set Clear KPIs! Set Clear KPIs! Many leaders envision a data strategy as a readily available buffet - a vast collection of metrics that can be easily assembled into insights. This approach, however, overlooks a critical first step: defining clear and actionable Key Performance Indicators (KPIs). Just as a chef wouldn't haphazardly throw ingredients together and expect a culinary masterpiece, a data strategy requires a well-defined recipe. Your recipe, in this case, consists of the 3-5 key performance indicators (KPIs) that truly capture the essence of your company's success. These KPIs serve as the foundation for your data strategy, guiding all stakeholders towards the metrics that matter most. key performance indicators (KPIs) Think of KPIs as the flavor profile of your data. In my book, " Data is Like a Plate of Hummus " I promote a funnel methodology for defining KPIs: flavor profile Data is Like a Plate of Hummus funnel methodology Identify key questions: What are the most critical questions you need answered about your business? For example: What are the revenues from ad-free subscriptions? How many users bought more than one item in the same basket? What are the revenues from ad-free subscriptions? How many users bought more than one item in the same basket? Refine your questions: Focus on the most essential ones. Understand which questions are critical for your company goals and strategy, and which answers will help you evaluate the company's health. Define KPIs: Which metrics can effectively provide answers to those refined questions? Understand the KPIs that will give you these answers following the five W's principles: Who is the controller of the KPI? Who owns the data that will be used for the KPI, and who is responsible for ensuring its accuracy and stability? What action will it drive me to take? If I see a positive or negative change in the KPI. How well will it give me answers for the company’s health? What else am I missing? Where is the issue? Can I receive an answer about which company section the issue is? When do I need to see it? How frequently are these measurements needed? (For example, a weekly "time-on-site" KPI might be sufficient to gauge the effectiveness of UX changes, not requiring daily monitoring.) Who is the controller of the KPI? Who owns the data that will be used for the KPI, and who is responsible for ensuring its accuracy and stability? Who is the controller of the KPI? What action will it drive me to take? If I see a positive or negative change in the KPI. What action will it drive me to take? How well will it give me answers for the company’s health? What else am I missing? How well will it give me answers for the company’s health? Where is the issue? Can I receive an answer about which company section the issue is? Where is the issue? When do I need to see it? How frequently are these measurements needed? (For example, a weekly "time-on-site" KPI might be sufficient to gauge the effectiveness of UX changes, not requiring daily monitoring.) When do I need to see it? Building Scalable and Iterative Infrastructure Building Scalable and Iterative Infrastructure Now that you know what flavors you need, let's talk kitchen setup. Think fast, efficient deployment. Forget a one-size-fits-all approach. Start with a basic setup that can be easily enhanced. Treat it like a recipe collection, evolving with each new dish. Each iteration focuses on either enhancing the kitchen tools or optimizing costs. As a chef, you care if your kitchen equipment is top-of-the-line or basic, but you will know how to work with both. What matters is delivering a delicious, well-presented dish. Your team needs to think about how to maximize the buy/build approach for the first iteration because they will learn all the time about what enhances the flavors and what doesn't, and where the issues lie. The main purpose of picking kitchen tools should be to enhance the Secret Ingredients you selected and allow for further experimentation by the chefs. It needs to be something that will be easy to switch or optimize. But for me, the more important part of the setup is to launch something I can taste-test with the diners and learn how it complements the dish, whether they notice enhancements or not. So, don’t deploy and forget until it breaks. The data chefs need to go around and collect feedback, understand the flavor profiles of diners, and prioritize them in the recipe book. Building trust is essential. Inconsistent flavors in a dish quickly erode a diner's trust in the chef. Similarly, unreliable or inconsistent data undermine the credibility of your data-driven insights. Establish clear data governance guidelines – outlining data availability timelines, ownership, and issue resolution protocols – to ensure data quality and consistency. Imagine the wasted effort required to validate data if its reliability is questionable constantly! Building trust is essential. Embrace the Journey, Share the Feast Embrace the Journey, Share the Feast Data strategy is about crafting flavorful dishes for a successful restaurant. By focusing on clear recipes (KPIs), strong governance, and a scalable kitchen setup (infrastructure), you can create your culinary oasis – one that delights your diners (customers) and fuels your restaurant's (company's) growth. Ready to take a bite out of your data woes? Read my book, "Data is Like a Plate of Hummus” Ready to take a bite out of your data woes? Buy My Book On Amazon Buy My Book On Amazon Dive deeper into the five Ws of effective KPIs, explore data governance best practices, and guide you through building a scalable data infrastructure. Learn how to transform your data into a strategic advantage and unlock the full flavor of your company's success!

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