Authoring effective visual communication is time-consuming and challenging for everyone - but especially those without design skills

Beautiful.ai

beautifulai

Photo Credit, recovered from stomach illness. In original publication of this interview, “ ,” this photo was rejected in favor of . In the spirit of additional context when republishing, we added the original image above, about two dozen contextual links, and embedded a fun video at the end. David Smooke David Smooke Founder & CEO at HackerNoon — Digital Publishing Evolution, AI Impact, Content Management Innovation, Community Growth, Future Visions a kinder, more professional headshot from AI Time Journal: 1. David, can you share the origin story of HackerNoon and what motivated you to create a platform focused on technology storytelling? Flor Laorga Hey, ! Thanks for having me. I’m . I started and run We publish technology stories and build publishing software. Before HackerNoon, I was managing 400+ contributing writers on the , which is now a tech unicorn. Back then, it was cumbersome to manage the writer accounts, content, and editorial review process through existing systems. Building for the contributing writers opened doors. When I started this company, I built many sites, most failed, and HackerNoon found the right mix of community, customers, and - just a cool place to spend time on the internet. Millions visit us every month for free to read our 100k+ stories across . By offering editing and distribution, many technology practitioners, writers, and companies find value in . AI Time Journal David Smooke HackerNoon. blog for SmartRecruiters thousands of tech topics publishing their stories with us 2. With HackerNoon’s commitment to keeping its library free of paywalls and popups, how do you navigate the challenge of generating revenue while maintaining an open-access philosophy? It’s a battle! Historically, we’ve 2x-ed revenue most years of the company’s existence, and our yearly revenue is in the low millions. Media is a brutal industry, and tech’s an up-and-down world where layoffs and profits seem to coincide with each gen ai launch or full moon. Our top source of revenue right now is . Companies like Brave, NVIDIA and AWS buy monthly ads on all stories within a category, like or . Our second and third sources of revenue are and . Business blogging is about getting more readers for blog posts owned by technology companies like , , , and . We leverage our publishing system and owned media channels to improve and further distribute their content. Quality technology blog posts require a lot of effort from talented people. The labor that goes into each post on a tech company’s main blog is worth thousands if not tens of thousands of dollars - companies work with HackerNoon to get those technology blog posts more readers. In terms of writing contests, companies award the authors of the best stores on a tag ( ), pay HackerNoon to run the contest, and ultimately, more technology content enters our library to serve the readers. The intention is to create discussion about a niche technology topic. ad placements by content relevancy programming data science business blogging writing contests MinIO Ockam Blockchain Oracle Summit BrightData like how Aptible awarded $18k to best #DevOps stories 3. As AI continues to evolve, how do you see it transforming the landscape of digital publishing, especially in terms of content creation and distribution? AI’s a massive wrench into productivity and authenticity. Every current job relying on a keyboard or a phone has/will have an AI assistant, and an AI will be on deck with you in whatever UX replaces the keyboard or the phone next. On the positive side, small capable teams can have greater extensions of themselves and their work. AI and AI agents can move portions of projects forward. For example, we introduced , and had to assign every story in our 100k+ library to one category. 100k human decisions would have taken a while, but a chatgpt spreadsheet plugin was able to assign each story a technology category very easily. On the negative side, there is spamflation everywhere. Why must the builders of our generation rush to make AI tools to spam instead of AI tools to assist? In 2022, one contributing writer, , made the case that . There is just so, so much content being generated by AI. It’s human-like, but it’s not human. Which brings me to authenticity. Who authored the content will become more important in the future as it indicates trust in a uniquely human way. technology categories Jeremy Hillpot 99.99% of all content would be AI-created by 2025 4. In your experience, what are the most effective strategies for managing and growing a small team of editors, developers, and startup individuals to produce high-quality technology content? We’re still small enough that everyone’s an individual contributor first, even the C-suite and board, which are both just me and . When you’re under 20 people, everyone has to carry their own weight. When it comes to managing a small remote team, reducing meetings is a good start. Editorial, sales, and product, each only have one internal meeting a week. This provides time to do the actual work and makes the meetings we do have will carry more importance. We do highly encourage one-off, project-focused, short meetings. Weekly product meetings are the longest and loaded with demos, recaps, and debates. But it connects the group, and designers have a full view into what developers are doing and vice versa. Staff happiness and sense of purpose, or lack thereof, will show in the little actions with our community. I work to create a company where a small team of elite contributors can thrive. Linh Dao Smooke 5. Could you discuss the development process of HackerNoon’s content management system and what makes it uniquely suited for technology professionals? At , we’ve built a lot of systems to create, edit, and distribute content at scale. Technologists spend a lot of their day on the keyboard (like I am now) and understand that documenting their journey and professional expertise will lead to more long-term success. Our CMS helps you create content with help from , , and . The CMS also integrates with our email and social media distribution engines, and for good measure. We live between social media where anyone can post and traditional media where staff content production drives content creation and consumption. There is a vibrant community of millions of technologists on HackerNoon. Plus, our CMS is built to seamlessly port content around the web. For example, with the HackerNoon CMS, we’ll be launching AI-specific publications in 2024, such as , , and more. HackerNoon templates AI a human editorial review backups up all content on the blockchain FewShot.Tech TextModels.Tech 6. How has HackerNoon leveraged AI to enhance its platform? and what lessons have you learned about AI's role in spam creation and prevention? HackerNoon uses AI and machine learning to improve grammar, , , and . Maybe Clippy was ahead of its time? Writers have and will continue to have smart AI assistants. AI can not and should not replace the writer, but it should and can assist the writer and editor throughout the publishing process. We are documenting our approach to editorial at . With the rise of LLMs, we’ve seen an influx of AI story spam submissions. Other blogging platforms are hosting so much of these types of machine generated stories right now. We are actively taking steps to not become a wasteland of AI’s musings. Because every story is reviewed before publication (with about half being rejected), I think our average story quality is higher than other blogging platforms. Every story submission automatically enters into plagiarism and AI writing detection. We highlight what sections are likely, possibly, and unlikely to be written by AI. It’s all about confidence levels. Ultimately, human editors make the final call in interpreting the machines’ reports. translate stories generate featured images suggest possible headlines EditingProtocol.com 7. Given your expertise in product management and editing, how do you balance innovation with user experience when introducing new features or updates to your platform? The core has to work for any new feature to matter. Our core is the blog post. We work to publish better blog posts and build for what comes before and what comes after the blog post. New functionalities cannot come at the expense of a delightful reading experience and a smooth publishing experience. It’s got to load quickly and the relevant ads have to surface at the right place for customers. There’s always more projects that could be done to improve the core. We also have been using more API driven journalism in order to gain more traffic. What I mean by that is aggregating relevant data and business information so that we can build pages that cover , , and . By connecting stories around the web to relevant companies, technologies and currencies, we can make HackerNoon a stronger destination for technology education and discovery. In terms of what to build next, we’ve built a simple product management system within Notion, where we detail product cards, weighing which user it would benefit, the expected input/output of the project, and then generally contributors choose their own projects. tech companies technologies currencies 8. As a leader, how do you foster a culture of creativity and innovation within your team, and what practices have you found most effective in motivating and inspiring your staff? The simplest way is to lead by example. I’m contributing to projects more than managing projects. The people who make this business happen are good people. If I want people to blog with HackerNoon, I need to blog with HackerNoon. almost 300 technology stories and this year, my goal is a post a week. Our staff is remote and around the world, we have people in Munich, Goa, Florida, Hanoi, Buenos Aires, Bangkok, Michigan, Lahore, Lagos, and of course where I live in Colorado. It’s a lot of different cultures. And a lot of different ideas. Everyone on the team started by applying via our , so one thing that unites us is reading and using HackerNoon before joining HackerNoon. Everyone also has stock in the company, that helps with buy-in and enthusiasm. We agree on metrics we want to move, but we might not agree on how to get there. It generally works best when contributors choose their own paths. I’ve published careers page 9. With your insights into the future of work and career advice, what guidance would you offer to professionals aiming to break into the rapidly changing tech industry? Make things! Apps, models, prototypes, blueprints, communities, whatever - just start making. Your first technology thing probably won’t be your best or your future, but if you make more things in tech they become less like just technology things and more like just essential everyday things.  In terms of breaking in, it’s a tough market in technology/media right now with mass layoffs & unpredictable demands. Having your own functioning project, app, site, academic paper, or even just a blog can set you apart from other candidates. I recommend looking to apply at companies that make technologies or products that you use and respect. Write short and simple cold emails that explain why you’d like to work together.  Take a step back and look at our daily lives - and what you think our daily lives might be in ten years - technology isn’t going anywhere. It’s becoming more ingrained. Closer to our eyes. I’d also add that getting into tech doesn’t necessarily mean staying in tech forever, but better understanding technology will help however your career grows. 10. How do you envision the role of digital publishers like HackerNoon in shaping public discourse and understanding of complex topics like cryptocurrency, AI, and blockchain technology? We normalize it. I learned about Bitcoin from a HackerNoon story submission. . The technology’s finally caught up; let’s talk about it. I learn a lot by reading what contributors think could be next. As many people on HackerNoon are publishing about what they’re building, we usually learn about newer technologies before they reach more mainstream learning destinations. is a great blogging example for how the people making the next internet are documenting and teaching others along the way. That author, , kept writing that . Meanwhile, we kept integrating our tech stack with more Web3 technologies. Fun Easter egg, you can read . Publishing platforms are still learning how to detail where and how and when AI contributed. We add an “ on all stories where AI assisted the writer. At Meta, I see they’re implementing a , I’ll be monitoring how that goes. Publishers should provide transparency to the reader when it comes to AI content creation. Hopefully, the internet can reach reasonable standards for accrediting AI. Milton Friedman’s been talking about the need for ecash since 1999 Learn Blockchain by Building One Daniel van Flymen blog post into a book the entire HackerNoon library via blockchain signatures here AI Assisted” emoji credibility indicator watermark checking and display system for all AI generated images 11. Finally, can you share a personal story or moment from your journey with HackerNoon that has been particularly meaningful or impactful to you? Well, it’s been a long road! Hard to pick just one. Recently, meeting Pham Minh Chinh, the Prime Minister of Vietnam, stands out. He invited . Was cool to see up close how a head of state walks, talks and listens to pitches about how the country could become a bigger player in the technology industry. Another one that comes to mind is when we launched with our own CMS, it was janky, it was pixelated, and it mostly worked but didn’t work in all the right spots. It was ours and it was beautiful. HackerNoon! I’ll leave with you this : Linh to be a technology consultant as the country forms its semiconductor strategy HackerNoon.com previously unpublished video of the moment we went live https://www.youtube.com/watch?v=rdoh8z0NXzU&embedable=true

“We are actively taking steps to not become a wasteland of AI’s musings” says HackerNoon Founder/CEO

হ্যাকারনুন প্রতিষ্ঠাতা/সিইও বলেছেন, "আমরা সক্রিয়ভাবে পদক্ষেপ নিচ্ছি যাতে AI এর মিউজিং এর বর্জ্যভূমিতে পরিণত না হয়"

„Wir unternehmen aktiv Schritte, um nicht zu einem Ödland der KI-Gedanken zu werden“, sagt HackerNoon-Gründer/CEO

"Estamos tomando medidas activamente para no convertirnos en un páramo de las reflexiones de la IA", dice el fundador y director ejecutivo de HackerNoon

"Nous prenons activement des mesures pour ne pas devenir un désert de réflexions sur l'IA", déclare le fondateur et PDG de HackerNoon.

हैकरनून के संस्थापक/सीईओ कहते हैं, "हम एआई के विचारों की बंजर भूमि न बनने के लिए सक्रिय रूप से कदम उठा रहे हैं।"

「私たちは、AI の思索の荒野にならないよう、積極的に対策を講じています」と HackerNoon 創設者兼 CEO は語る

해커눈 창업자/CEO “AI 사색의 황무지가 되지 않기 위해 적극 나서고 있다”

“Estamos tomando medidas ativamente para não nos tornarmos um terreno baldio de reflexões de IA”, diz o fundador/CEO da HackerNoon

«Мы активно предпринимаем шаги, чтобы не стать пустошью размышлений ИИ», — говорит основатель/генеральный директор HackerNoon.

HackerNoon Kurucusu/CEO'su şöyle diyor: "Yapay zekanın düşüncelerinden oluşan bir çorak araziye dönüşmemek için aktif olarak adımlar atıyoruz"

Người sáng lập/CEO của HackerNoon cho biết: “Chúng tôi đang tích cực thực hiện các bước để không trở thành vùng đất hoang của những suy ngẫm về AI”.

HackerNoon 创始人/首席执行官表示：“我们正在积极采取措施，以免成为人工智能思考的荒原”

In the competitive landscape of startups, getting noticed is half the battle. The right growth and promotional tools can make the difference between fading into obscurity and capturing the attention of your target audience. As startups look for innovative ways to gain traction, multiple AI tools and platforms are emerging to assist in various ways. I’ve hand-picked a few apps that have proven their efficiency and provide optimal value for money. Here we go! : Enhancing Your Communications Linguix Linguix, a rapidly growing AI-powered multilingual writing assistant, has over 300,000 users and an impressive 70,000 installs across various platforms. The tool was crowned "Product of the Day" on Product Hunt three times and was featured in the Washington Post, Fortune, and Bloomberg. Linguix offers a multilingual grammar and spell check, ensuring that users can effortlessly check their documents in six languages. This AI-powered writing tool offers instant grammar, punctuation, and stylistic advice, guaranteeing that the material is both accurate and aligns with the target readership. A notable attribute is the "Text Rewriter," enabling users to swiftly rephrase whole sentences, boosting the overall clarity and caliber of the communication. Moreover, Linguix's "Content Score" function delivers a comprehensive evaluation of the text quality, assigning a score based on various factors such as sentence length, vocabulary complexity, and usage of passive voice. This ensures that users receive actionable feedback to further refine their content. For entrepreneurs, Linguix’s team also offers a bunch of services, including white labeling, APIs, AI/ML development as well as content marketing, to the Linguix founder. ** according : Attracting Investment Worldwide Gust Gust is a platform designed to support entrepreneurs at every stage of their journey. As the go-to place to start, grow, and fund ventures, Gust offers them access to a network of powerful partners. With the ability to match with over 300 of the world's top accelerators and apply to more than 750 leading Angel Investment Groups, Gust stands out as a comprehensive solution for startups. The platform offers a range of features, including benchmarking ventures, co-founder ownership planning, and company incorporation guidance. Moreover, startups can build their profiles, tell their stories, and prepare for diligence, all within the Gust ecosystem. The platform also extends special offers, allowing startups to qualify for savings from leading service providers. With its user-friendly interface and a plethora of resources, Gust is undoubtedly a must-have tool for startups aiming for success in today's competitive market. : Empowering Email Marketing Lavender Lavender steps in as a game-changing tool designed to enhance email productivity and effectiveness. Integrated seamlessly with Gmail, Lavender provides real-time suggestions to improve email content, ensuring that messages are clear, concise, and impactful. By analyzing the recipient's online presence, Lavender tailors advice to match the recipient's communication style, ensuring that emails resonate and foster meaningful connections. Additionally, Lavender offers insights into the best times to send emails, maximizing the chances of them being read. The tool also provides templates for various scenarios, saving time and ensuring that users have a strong starting point for their communications. With features like sentiment analysis and engagement predictions, Lavender goes beyond traditional email tools, offering a holistic approach to email communication. : Reaching Out to a Wider Audience AppSumo AppSumo stands out as a unique online marketplace tailored specifically for entrepreneurs, offering a curated selection of software, tools, and digital resources at unbeatable prices. Founded with the vision of helping businesses grow without breaking the bank, AppSumo collaborates with software developers and companies to bring exclusive deals and lifetime subscriptions that are often too good to pass up. But AppSumo is more than just a platform for great deals. It's a community-driven space where entrepreneurs can discover and review the latest products, share insights, and learn from comprehensive tutorials and courses. With a keen focus on value, AppSumo ensures that every product listed undergoes rigorous testing and review, ensuring quality and relevance for its vast user base. : Promoting Your Brand on LinkedIn Taplio With its user-friendly interface and a plethora of features, Taplio is not just a tool but a comprehensive solution for individuals and businesses aiming to maximize their LinkedIn presence. Taplio offers features that allow users to create high-quality LinkedIn content, schedule posts seamlessly, and build meaningful relationships. In 2022 alone, Taplio catered to over 4,200 LinkedIn creators, consultants, CEOs, and team members, showcasing its growing popularity and effectiveness. The platform's standout features include AI-driven content inspiration, a library of over 4 million viral posts for inspiration, and a unique Chat Assist powered by the advanced GPT-4 AI model. Beyond content creation, Taplio offers a robust scheduling system, ensuring that users can organize and queue their content effortlessly. Additionally, the tool emphasizes the importance of engagement, providing functionalities to turn interactions into actionable leads. : Crafting Impactful Presentations With AI Beautiful.ai With a vast library of customizable templates and a user-friendly interface, Beautiful.ai is an invaluable tool for anyone looking to elevate their presentations, whether for business meetings, academic lectures, or personal projects. This innovative platform reimagines the way presentations are designed by integrating artificial intelligence into the creation process. Instead of grappling with intricate design elements and layouts, users can rely on Beautiful.ai's intelligent design assistant to automatically craft visually stunning slides that effectively communicate the intended message. The platform's strength lies in its ability to simplify complex design tasks. Users input their content, and Beautiful.ai takes over, suggesting optimal layouts, color schemes, and design elements that align with best practices. This not only ensures that presentations look professional but also significantly reduces the time and effort traditionally required in design. Promoting a startup in today's saturated market requires a blend of innovation, strategy, and effective communication. As startups continue to search for ways to stand out, leveraging such tools will be instrumental in shaping their success and visibility in the market.

Elevate Your Startup: Six Essential Tools for Growth and Marketing

Why We Need to Think About the Full Stack of AI Artificial Intelligence is an emerging technology, with significantly more end users than the usual techno-shift. As discussed in both and , this is one of the fastest growing technologies without a mature bedrock of security and reliability support. Security Threats to High Open Source Impact Large Language Models A Tale of Two LLMs: Open Source vs the US Military's LLM Trials In this, we’ll talk about the larger scope of understanding and protecting artificial intelligence pipelines, whether it’s a large language or a large model. anything With models like ChatGPT representing its cognitive capabilities in the way the end user engages with them, a lot of people talk about AI think of it like a magical thinking head, this bot that can talk, but not quite walk. It Gets More Interesting, The More You Know To ensure the overall health and well-being of AI, we must recognize that it requires more than just a brain. Like the human body, AI relies on multiple interconnected components. Just as our lungs provide vital oxygen to sustain life, the carbon consumption of AI represents its energy source. Equally crucial is AI's immune system—cybersecurity—protecting against threats and vulnerabilities. In this series, we will explore the comprehensive nature of AI, focusing on the critical role of cybersecurity and the importance of holistic treatment for addressing security concerns. The AI Ecosystem: Beyond the Cognitive "Talking Head" AI, with models like ChatGPT at its forefront, possesses remarkable cognitive abilities. These models excel in generating human-like responses and assisting with various tasks. However, AI is not solely reliant on its cognitive prowess. To function effectively, AI requires a stable and secure ecosystem that sustains its operations. This ecosystem includes data sources, computational infrastructure, energy consumption, and cybersecurity measures. Carbon Consumption: AI's Lungs Similar to how our lungs enable the exchange of oxygen and carbon dioxide, the carbon consumption of AI represents its energy source. As AI continues to evolve and become more prevalent, addressing its energy demands and environmental impact becomes crucial. Striving for energy efficiency and sustainable practices is essential for the long-term viability of AI technology. “A main problem to tackle in reducing AI’s climate impact is to quantify its energy consumption and carbon emission, and to make this information transparent”, says Payal Dhar in a recent . Nature Machine Intelligence journal article To be clear, it’s not always about making the technology more efficient. Sometimes, it’s about making humans less stupid about wasting compute. Shifting developer mindsets to massive state-space feature engineering means getting people to understand why they need to use (guesstimate your feature space before you compute it, and how many different types of hay are in it). It’s why you have to statistically consider (how you want to investigate that haystack with best-of-n sampling, helping to decide if executing with the you have/want to spend is worth the byte flips). HyperLogLog Goodheart’s Law compute resources Cybersecurity: AI's Immune System Just as our immune system protects our body from infections, AI relies on robust cybersecurity measures to defend against threats. The interconnectedness of AI systems with various networks and data sources exposes them to vulnerabilities and potential attacks. Ensuring the security of AI requires comprehensive protection mechanisms, including data privacy, secure infrastructure, and resilient defenses against malicious actors. AI Security Groups and Resources OWASP Foundation AI/ML Security work being done: The OWASP foundation more broadly aims to improve the security of software through its community-led open source software projects. They have an and broadly light on technical implementation. provides developer centered information about the top known cybersecurity risks for open source machine learning, with a description, example attack scenario, and a suggestion of how to prevent it. AI Security Guide OWASP Project Machine Learning Security Top 10 The LFAI Security Committee LFAI supports AI and Data open source projects through incubation, education, and best practices. AI Security Regulatory Organizations focus on common sense regulation and standards around AI/ML that are compliant to exclusively EU regulation. Similarly, the is an independent working group to advance AI Risk aimed at security governance. The was similarly established solely for regulation, and only scoped to cloud services. efforts are also largely regulatory advisements. ETSI’s Securing Artificial Intelligence (SAI) AIRS group CSA Artificial Intelligence group IEE’s AI/ML Central Nervous System Infections: Addressing Security Concerns with Large Language (and Large Models) Anything In the context of AI, security concerns around the data and model processing around large langauge (and large anything models) can be likened to a central nervous system infection, affecting the core functionality of the entire system. While traditional cybersecurity threats often focus on breaches, data leaks, and unauthorized access, the challenges posed by Large Language Models (LLMs) and other generative technologies extend beyond conventional threats. Understanding these distinctive aspects is crucial for effectively addressing security concerns in this domain. Hallucinations One of the notable challenges associated with LLMs is the problem of hallucinations or the generation of false information. Due to their ability to generate human-like responses based on training data, LLMs may inadvertently produce content that lacks factual accuracy or even fabricate entirely false narratives. This presents a unique security risk as it can lead to the dissemination of misinformation, manipulation of public opinion, and potential damage to the credibility of AI systems. Mitigating this risk requires a combination of careful training data curation, robust fact-checking mechanisms, and ongoing validation processes to ensure the veracity of the generated content. . This is a security problem when downloading open source package registries at the moment Internal Drift Another significant concern is internal drift within LLMs and generative models. Over time, these models can exhibit a shift in behavior, generating responses that deviate from the intended purpose or ethical guidelines. This phenomenon poses a challenge to maintaining control and predictability in AI systems, as it introduces an element of uncertainty that can be exploited by adversaries. Addressing internal drift requires continuous monitoring and adaptation, establishing feedback loops between developers and the models, and implementing techniques such as reinforcement learning to reinforce desired behavior and align the outputs with ethical standards. Proactive threat detection involves actively monitoring the behavior of LLMs and generative models to identify potential vulnerabilities or anomalies in their output. Secure development practices entail incorporating robust security measures throughout the entire development lifecycle, including secure coding practices, vulnerability testing, and adherence to established industry standards. A Holistic Treatment for AI Security To ensure the longevity and trustworthiness of AI, we’ll have to integrate security considerations throughout the AI development lifecycle, establishing strong partnerships with cybersecurity experts, and fostering a culture of security awareness and education. Implementing ethical guidelines, robust encryption practices, and continuous monitoring. . It’s All About Attention I’ve spent a lot of my life thinking about how humans interact with computers and computers that interact with humans. I used to study how we could design better Boeing Airline cockpits by getting real pilots into a 4D flight simulator of potentially life-threatening conditions to see where they looked, how they moved, and what they said to prevent a crash - . Later, I worked at the National Institutes of Health on , where we timed simple visual feedback to real-time brain networks to improve clinical psychiatric outcomes without any pill-based intervention. back or not real-time fMRI neurofeedback Just attention. Attention is powerful. It’s probably the most powerful thing to learn about cybersecurity. When threat modeling any technical stack, you have to be able to think about where are people paying attention. That’s your most exploitable surface area. aren’t Emerging technologies are always a really interesting place to observe people’s attention. There hasn’t really been an emerging technology that so many people have had an opinion on before, because this time it’s just a face-to-deep technology that’s genuinely easy to start using. That’s beautiful. Attention and awareness are different things though. We need to understand how the whole thing works. You Should Be Paying Attention to Chip Security AI Chips: The Heart of the AI Body AI-specific chips, often referred to as neural processing units (NPUs) or graphics processing units (GPUs), serve as the vital heart of the AI ecosystem. Much like the human heart, these specialized hardware components play a crucial role in enabling the efficient and optimal functioning of AI systems. In this series, we delve into the significance of chip technology and its pivotal role in ensuring the security and robustness of the AI body. The Powerhouse Organs: AI-specific chips are specifically designed to accelerate AI computations, enabling exceptional performance, efficiency, and speed. These chips are tailored to meet the unique requirements of AI workloads, such as training deep neural networks and running complex AI algorithms. Just like the heart pumps blood to supply oxygen and nutrients to the body, AI-specific chips empower AI systems to process and analyze vast amounts of data with remarkable speed and efficiency. The Importance of Chip Technology: Advancements in chip architectures and designs have led to significant breakthroughs in AI capabilities. Parallel processing, specialized matrix calculations, and optimized memory access are just a few examples of the technological advancements that AI-specific chips have brought to the field. These advancements push the boundaries of AI performance, enabling AI systems to tackle increasingly complex tasks and deliver accurate results. Additionally, chip technology plays a vital role in addressing energy consumption concerns. As AI deployment expands, the energy efficiency of AI systems becomes a crucial factor. Advancements in chip technology contribute to reducing energy consumption, making AI more sustainable and environmentally friendly. The Role of Secure Chip Technology: As AI becomes more prevalent and critical in various sectors, ensuring the security of AI-specific chips becomes paramount. The article " " has some great key points to understand, but I’ll boil them down to two that you need to understand today: Security Becomes Much Bigger Issue For AI/ML Chips, Tools The rapid development of AI and machine learning chips has led to increased potential for security threats, including intellectual property theft and attacks that can corrupt data or lead to ransomware (this can be supply chain and supplier threats) The need for standards that include both hardware and software. It suggests using multiple AI algorithms and diverse sets of training data to reduce the risk of attacks. If you are optimizing - yes, I said optimising, not just running, an AI system, you will be building a system that maximizes the compute over cost. (GPUs) and Intel (CPUs and VPUs), and with (TPU) and that’s just the ones who have been on the market the longest - emerging tech means emerging market. You can do this with hyperscalers (kind, of) but what if you are building one from scratch? You’ve got NVidia Google Tensor Processing Unit But, oof, do we have some these days, as seen in the “Blessings of Scale” from . computational power Compute Trends Across Three Eras of Machine Learning Securing the Evolving AI Body: Just as the heart is vital for maintaining overall health, ensuring the security of AI-specific chips is crucial for the resilience and trustworthiness of the AI body. Secure chip technology must be integrated into every stage of the AI development process, from chip design and manufacturing to deployment and maintenance. Collaborative efforts among chip manufacturers, AI developers, and cybersecurity experts are essential to identify and address potential vulnerabilities in chip architectures and mitigate emerging threats. By prioritizing chip security, we can ensure that the AI body remains robust, efficient, and secure. Where do you want to see this go next? Town Hall mode is on this Hackernoon article, so feel free to comment anywhere on this article where you have a question, comment or better idea than myself. The author will absolutely read it.

Securing AI: Concerns & Immune Systems for Emerging Technologies

Love because it is so vast and versatile: whether you love numbers or pictures, numbers or words – you will find anything. The other side is that after eight years in the industry, many tasks have become tedious: writing ads and figuring out brand messaging doesn't excite me so much, but "a man’s gotta do what a man’s gotta do". I love and hate marketing. Thankfully, some clever guys invented ChatGPT, which can do most of that tedious work if we use it correctly. However, that raises another question: will I be able to still have my bread and butter, or is it the time to start looking for some fancy spot under a bridge and design a sign "Give me some food, AI has taken my job". That's why I decided to analyse the perspectives of AI overtaking marketing jobs and what skills marketers should keep improving to keep our jobs. Let's go! Dom Perignon and caviar How AI Influences the Marketing Job Market As you could have guessed, I am quite a lazy person, so I will let numbers do the talking: According to , . Ouch, that sounds tough! Goldman Sachs ~300 million jobs could be affected by generative AI, meaning 18% of work globally could be automated Let's see how things look in marketing. A funny and dystopian website WillRobotsTakeMyJob gives an 18% probability that . Sounds a bit bad, but it's not a big deal compared to other professions. robots will replace the marketing manager's job states that 25% of marketing work will be automated in the following years. That doesn't mean "a quarter of marketers will be fired", but some specialists could meet less workload. Marketing AI Institute's poll The numbers sound apocalyptic but wait to start looking for a new job. According to the same Marketing AI Institute report, – such naive people, mua-ha-ha (joke). 56% of marketers think that more jobs will be created by AI in the long-term Also, consider that AI will transform the industry but won't eradicate it – marketers need to adapt to new realities and learn new tools and approaches. Let's cover which marketing competencies can't be replaced with AI, so we can catch up and ensure our jobs are safe. experts 5 Essential Skills for Marketers in the Era of AI Automation The main area of AI application is repetitive tasks, including routine creative and analytical ones, like writing email copies and social media posts. AI will threaten data-processing jobs, such are marketing analysts and those who work with ad targeting and optimisation. To avoid firing, marketers need to work on human skills AI can't copy yet to stay competitive. These include: The art of asking the right questions. Connecting dots and departments. Creativity and creativity management. Marketing AI tools management. Emotional intelligence. Let's cover them in detail. Skill #1: The Art of Asking the Right Questions AI is good at reproducing billions of combinations of existing data, but it's not great at generating something entirely new or getting data from "the analogue world". And what brings us new data? Questions! That's why human marketers are still "on a horse". Speaking to the target audience, sniffing on competitors, and conducting newsjacking have become more critical than ever. To ask the right questions, it's good to have a checklist of questions for different marketing goals: finding different audience needs, positioning ideas, etc. To think out of the box and come up with unusual questions, it's good to read books from different fields and do creativity exercises, like finding 101 unique applications for an avocado. Another critical question is who to ask questions. Except for the target audience, marketers also need to talk to sales, customer support, IT, and lawyers – AI can't build relationships with them. That leads us to skill #2. Skill #2: Connecting dots and departments AI in marketing can offer invaluable insights and data. Still, it falls upon us, the human marketers, to comprehend how to leverage that information across the diverse tapestry of our organisations. Marketing doesn't exist in a vacuum; it intersects with sales, product development, customer support, and other departments. To excel, we must comprehend the entire customer journey and collaborate seamlessly with various stakeholders to craft cohesive and integrated strategies. By synthesising and unifying, marketers ensure their campaigns harmoniously align with overarching business objectives and deliver a seamless customer experience across all touchpoints. While AI may provide recommendations and suggestions, we must bridge the gaps and assemble the puzzle pieces into a unified whole. Skill #3: Creativity and creativity management Regarding creativity, AI still struggles to match the prowess of human marketers. While AI can generate content based on existing data, it often lacks the spark of originality and the audacious thinking that human creativity ignites. That's why we must foster and elevate our creative skills to conceive innovative campaigns, compelling brand messages, and captivating content that deeply resonates with their target audience. Creativity is the defining factor that sets brands apart and empowers them to shine amidst a sea of competitors. Furthermore, as AI tools increasingly permeate the marketing landscape, we need to cultivate proficiency in managing AI-generated content. They should be able to curate and refine AI-generated outputs, ensuring they align with the brand's voice and objectives. It's a delicate dance, striking the right balance between harnessing AI's capabilities and infusing that crucial human touch to forge impactful marketing materials. Skill #4: Marketing AI tools management With the surge of AI tools in marketing, we must become adept at managing and leveraging these technologies. This encompasses comprehending the capabilities and limitations of various AI applications, handpicking the most suitable tools for specific tasks, and seamlessly integrating AI into marketing workflows. We must learn how to harness AI tools to automate repetitive tasks, analyse voluminous datasets, and extract valuable insights that inform decision-making. These tools help me the most in the work I do: – it generates ad texts and strategy ideas with a click. It helps with routine tasks and is a starting point for idea generation. Aiter.io creates a website in seconds. I use it to generate secondary landing pages quickly; after this, it just needs some editing. Durable – the same as Durable, but for presentations. Beautiful.ai – uses AI to optimise ad campaigns. Albert AI Of course, now there are thousands of them, so you need to keep an eye on the industry. I use directories like Futurepedia to track new tools. BTW, remember that managing AI tools also entails safeguarding data privacy, considering ethical implications, and complying with regulations. We need to possess a comprehensive understanding of the ethical utilisation of AI and be well-versed in the potential risks and challenges associated with AI-driven marketing. Skill #5: Emotional intelligence While AI can analyse data and predict consumer behaviour, it falls short when understanding and empathising with human emotions. Emotional intelligence is a skill that we need to develop to create meaningful connections with our target audiences. Understanding consumer motivations, desires, and pain points requires emotional intelligence. We can compete with robots by empathising with our audience, anticipating their needs, and tailoring messaging to resonate emotionally. This skill becomes even more critical as customers seek authentic and personalised experiences from brands. Additionally, emotional intelligence is vital in building and maintaining relationships with colleagues, stakeholders, and clients. Successful marketers know how to navigate different personalities, resolve conflicts, and collaborate effectively to achieve shared goals. Conclusion: I Will Survive, You Will Survive In conclusion, while AI tools are transforming the marketing landscape, there are specific skills that marketers can continue to cultivate to remain relevant and valuable in the age of automation. We can position ourselves as indispensable assets in the AI-driven marketing world by honing our ability to ask the right questions, connecting dots and departments, nurturing creativity, managing AI tools effectively, and developing emotional intelligence. So, AI is not a threat to our existence but an opportunity to eliminate all that tedious marketing work nobody loves and concentrate on the fun stuff. Hooray!

The Marketer's Survival Guide in the Era of AI Automation: 5 Essential Skills to Secure Your Job

এআই অটোমেশনের যুগে বিপণনের সারভাইভাল গাইড: আপনার চাকরি সুরক্ষিত করার জন্য 5টি প্রয়োজনীয় দক্ষতা

Der Überlebensleitfaden für Vermarkter im Zeitalter der KI-Automatisierung: 5 wesentliche Fähigkeiten zur Sicherung Ihres Arbeitsplatzes

La guía de supervivencia del vendedor en la era de la automatización de la IA: 5 habilidades esenciales para asegurar su trabajo

Le guide de survie du marketeur à l'ère de l'automatisation de l'IA : 5 compétences essentielles pour sécuriser votre emploi

एआई ऑटोमेशन के युग में द मार्केटर्स सर्वाइवल गाइड: आपकी नौकरी को सुरक्षित करने के लिए 5 आवश्यक कौशल

AI オートメーション時代のマーケターのサバイバル ガイド: 仕事を確保するための 5 つの必須スキル

AI 자동화 시대 마케터의 생존 가이드: 직업을 확보하기 위한 5가지 필수 기술

O guia de sobrevivência do profissional de marketing na era da automação de IA: 5 habilidades essenciais para garantir seu emprego

Yapay Zeka Otomasyonu Çağında Pazarlamacının Hayatta Kalma Rehberi: İşinizi Güvenceye Almak için 5 Temel Beceri

Cẩm nang sinh tồn của Marketer trong kỷ nguyên tự động hóa AI: 5 kỹ năng cần thiết để đảm bảo công việc của bạn

AI 自动化时代营销人员的生存指南：保住工作的 5 项基本技能

As the world becomes increasingly technology-driven, the integration of artificial intelligence (AI) in our daily lives is becoming more and more prominent. From virtual assistants to personalized recommendations, AI has changed how we interact with technology. In 2023, it’s safe to say that AI will continue to revolutionize how we live, work, and play. With the rapid growth of AI, it can be overwhelming to navigate the ever-growing landscape of AI tools and technologies. In this article, we’re going to highlight 7 of the most exciting and innovative AI tools you should try in 2023. 1. ChatGPT ChatGPT is an advanced language model developed by OpenAI. It allows you to have human-like conversations and more. Moreover, It is trained on a massive dataset of text from the internet and fine-tuned for various conversational tasks, such as answering questions and generating text. ChatGPT In Marketing As a growth marketer, you can use ChatGPT for a variety of tasks like Write attention-grabbing emails and subject lines in a few minutes. Composing emails: : You can use ChatGPT to write engaging social media posts. You can pick your tone and style to fit your brand. Social media content : ChatGPT can help you find keywords for your next article. You can further refine your search by requesting long-tail keywords. Find keywords Are you stuck and need help with your ad copy? ChatGPT can write ad copies for your Facebook, Twitter, Instagram, LinkedIn, and other platforms. Writing Ad copies: : Easily create article or blog ideas within minutes. You can pick your tone, length, and even mood. Content ideas Those are some of the things you can do with ChatGPT. However, the possibilities are endless. They currently have two versions. They have the free version and the paid version called . Try it today. ChatGPT Plus 2. TweetMonk TweetMonk is a user-friendly social media management tool that helps you create engaging content using AI. Furthermore, you can schedule threads and tweets. TweetMonk In Marketing Using TweetMonk, you can save thousands of hours with your Twitter marketing. Some of the things you can do with this AI include : Easily generate hashtags for your tweets. Hashtag Generator Using TweetMonk AI analytics, you can pick the best time to post your tweets. Post Timing: You can queue your tweets with one click or schedule them manually to save you time. Queue Content: Threads have become the go-to place for informative content. You can use TweetMonk to get ideas for your threads and increase engagement. Thread Ideas: Have you come across a tweet you liked? You can use TweetMonk to rewrite the tweet. Rewrite Tweets: Check your tweet performance to see how your tweets perform. Rich Analytics: They have a free account called Explore that allows you some basic features. The paid version starts from $8 and has a 7-day free trial. 3. AISEO Art AISEO art is an AI assistant that helps you turn your ideas into art. You can generate high-quality art in a matter of minutes. Moreover, this tool can help you create creative artwork at a low cost. Features Unlimited image generation. HD quality downloads. Watermark-free images. Some of the things you can do with this AI include Logo creation Posters Website Graphics NFT art Tshirt art and so much more AISEO art offers two pricing packages. The first one goes for $7/month billed yearly or $9/month billed monthly. For $7, you get 400 image generations per month, HD-quality downloads, and watermark-free images. The other package is $15/month billed yearly and $19/month if billed monthly. . Start generating HD images today 4. BlackBox Are you a developer? Then this AI tool is for you. According to their website, BlackBox is your AI-powered coding assistant to help you can code 10X faster. You can code in 20+ languages like Python, JavaScript, TypeScript, Go, Ruby, and others. Moreover, you can turn any question into code. They have a chrome extension that allows you to copy Code from Videos & Images or a shared screen on zoom/teams/meet. They have packages starting at 0.59/week. 5. BeautifulAI BeautifulAI is a tool that helps you create beautiful presentations in minutes. It can design and animate your slides and help you find ideas for your presentation. Moreover, they have 50+ smart templates that you can choose from. The AI adapts each slide’s layout as you add content, thus automating the majority of the work. Other features include Visualize your data. Search for inspiration from templates available. Easy edits Pre-built slides. BeautifulAi pricing starts at $12/month. Create stunning slides today. 6. ChatSonicAI ChatSonicAI is a conversational AI like ChatGPT where you can have human-like conversations. It is different from ChatGPT because it offers answers based on current events and trending topics in real time. Some of ChatSonic features Voice command. Chrome extension Generate art ChatSonic has a free trial that limits you to 6,250 words and 1 user. The other package starts from $19/month for 47,500 words and 1 user. Try ChatSonic 7. Synthesia Transform your text into beautiful HD videos. Synthesia is an AI that allows you to create engaging videos with AI avatars. You can use 120 languages, different templates, a screen recorder, a media library, and more. Features Professional actors 85+ AI avatars Web-based app accessible in your browser Beginner friendly Professional voiceovers Quality videos Free media library Screen Recorder Background music Mp4 downloads Video embedding Closed captions Easy updates Pricing starts at $30/month. Conclusion In conclusion, the world of AI is constantly evolving and expanding, and the tools and technologies we’ve highlighted in this article are just the tips of the iceberg. Whether you’re a business owner looking to streamline your operations or a tech enthusiast, these 7 tools are sure to impress. As you experiment with these AI tools, keep in mind that the true potential of AI lies in its ability to augment human abilities, rather than replace them. By harnessing the power of AI, we can work smarter, not harder, and achieve more in less time. Do you know any other tools? Drop them in the comment section. Was this article helpful? Support me through . Or feel free to reach out at khamisidigital@gmail.com. buy me a coffee

7 Game-Changing AI Tools in 2023

174 AI Tools To Try

Work smarter, not harder The world of is booming, and it’s about to get even better. We’re all fascinated by AI, and if you have a computer at home, chances are you’ve seen some of its potential in action. artificial intelligence In the next few years, we’ll see more companies using AI in their products and services than ever before. But what does it mean for you? What can you do with artificial intelligence? We all want to be more productive, right? And if you’re like me, then you’re probably using a lot of tools to help you get there. But what if I told you that there are free and paid AI tools that can take your productivity to the next level? What if I told you that those tools are available for free? Well, I’d be lying. But don’t worry — you can find them here. I’ve got some great tips for you! Here are the top nine free AI tools that everyone should know: 1. GFP-GAN — Photo Restoration GFP-GAN (Generative Flows for Photo Restoration) is an AI tool for photo restoration that uses a generative adversarial network (GAN) to repair damaged or degraded photos. GANs consist of two neural networks: a generator and a discriminator. The generator network is trained to generate new images that are similar to the original photo, while the discriminator network is trained to distinguish between the generated images and the original photo. GFP-GAN can be used to restore photos that have been damaged by factors such as noise, blur, or compression. It can also be used to improve the quality of low-resolution images by generating higher-resolution versions. GFP-GAN is suitable for individuals and businesses looking to restore old or damaged photos or to improve the quality of low-resolution images. GFP-GAN has been shown to achieve good results on a variety of tasks, including denoising, deblurring, and super-resolution. It is an active area of research and new developments are likely to continue to improve the performance of GFP-GAN and other photo restoration tools. — Link GFP-GAN 2. DALL-E 2 — Image Creator DALL-E 2 is an AI tool developed by OpenAI that uses a generative model to create original images based on a user’s text input. It is a follow-up to the original DALL-E tool, which was released in January 2021. DALL-E 2 works by using a combination of natural language processing (NLP) and machine learning algorithms to analyze a user’s text input and generate relevant images. The generated images are based on a wide range of concepts and can be used for a variety of purposes, including creative inspiration and design. DALL-E 2 is easy to use and requires no prior knowledge of AI or NLP. It is available through the OpenAI website and can be accessed for free. DALL-E 2 is suitable for individuals and businesses looking to generate original images or to find creative inspiration. — Link https://openai.com/dall-e-2/ 3. Brandmark.io Brandmark.io is designed to be user-friendly and easy to use, making it a good option for anyone who wants to create professional-quality brand assets without needing specialized design skills. It includes a range of templates and design elements that users can customize to create their own unique brand identity. It is particularly useful for businesses and individuals who want to create a consistent and effective brand identity for their products or services. Some key features of Brandmark.io include: AI-powered design: The platform uses artificial intelligence to automatically generate logo designs based on the user’s input and preferences. Customizable templates: Users can choose from a range of templates and design elements to create their own unique logos and other brand assets. Collaboration tools: Brandmark.io includes features such as real-time collaboration and team management to make it easy for users to work together on brand design projects. Multilingual support: The platform supports multiple languages, making it easy for users to create brand assets in their preferred language. — Link https://brandmark.io/ 4. Deep-image.ai — a New Generation of AI-driven photo It appears that Deep-image.ai is a company that offers AI-driven photo editing and processing tools. It is not clear exactly what the “new generation of AI-driven photo” refers to, but it likely refers to advanced technology and algorithms that are used to improve the quality and appearance of photos. AI-driven photo editing tools use artificial intelligence and machine learning algorithms to analyze and process images in order to enhance their appearance or correct for defects. These tools can be used to perform a wide range of tasks, such as removing blemishes, adjusting colors and lighting, and improving sharpness and detail. Some AI-driven photo editing tools may also be able to generate new images or styles based on a user’s input, using techniques such as style transfer or deep learning. Without more information, it is difficult to say exactly what the “new generation of AI-driven photo” offered by Deep-image.ai consists of. However, it is likely that this refers to advanced AI-driven photo editing and processing technology that is designed to improve the quality and appearance of photos. — Link https://deep-image.ai/ 5. Beautiful.ai Presentation software that designs for you Beautiful.ai is designed to be user-friendly and easy to use, making it a good option for anyone who wants to create professional-quality presentations without needing specialized design skills. The software includes a range of templates and design elements that users can customize to create their own unique presentations. It is particularly useful for businesses, educators, and individuals who want to create visually appealing and effective presentations for a variety of purposes. Some key features of Beautiful.ai include: AI-powered design: The software uses artificial intelligence to automatically design professional-quality slides based on the user’s content and preferences. Customizable templates: Users can choose from a range of templates and design elements to create their own unique presentations. Collaboration tools: Beautiful.ai includes features such as real-time collaboration, version control, and team management to make it easy for users to work together on presentations. Multilingual support: The software supports multiple languages, making it easy for users to create presentations in their preferred language. Link — https://www.beautiful.ai/ 6. Chat-GPT ChatGPT is a chatbot that uses natural language processing and machine learning algorithms to generate responses to user input. It is based on the GPT (Generative Pre-training Transformer) language model, which was developed by OpenAI. ChatGPT is designed to be able to understand and respond to a wide range of inputs in a natural and conversational way. It can be used for a variety of purposes, including customer service, entertainment, and education. To use ChatGPT, users can input a message or question into the chatbot, and it will generate a response based on their understanding of the input and their knowledge of language and conversation. The chatbot is designed to be able to engage in extended conversations, so users can continue to interact with it for as long as they like. — Link https://openai.com/blog/chatgpt/ 7. Deep Nostalgia makes your photos animated Deep Nostalgia is a feature offered by the genealogy and history website MyHeritage. It uses artificial intelligence and deep learning algorithms to animate still photos of people, making them appear as if they are moving and speaking. Deep Nostalgia has been popular on social media, with many people using it to animate old family photos and share the results with their friends and followers. It has also been used by media organizations and others to bring historical figures and events to life. To use Deep Nostalgia, users can upload a still photo of a person to the MyHeritage website. The feature will then generate a short video that shows the person in the photo moving and speaking. The video is generated using a combination of machine learning algorithms and motion capture data and is designed to give the impression that the person in the photo is moving and speaking in a natural and lifelike way. While Deep Nostalgia can be an entertaining and nostalgic feature, it is important to note that it is generated using artificial intelligence and is not a real video of the person in the photo. It is intended for entertainment and educational purposes only and should not be used to make important decisions or to substitute for real-world research. — Link https://www.myheritage.com/deep-nostalgia 8. Pfpmaker.com PFP Maker is a website that allows users to create custom profile pictures (also known as “PFPs”) for use on social media and other online platforms. It offers a variety of tools and resources for creating and editing images, including templates, stickers, and text tools. To use PFP Maker, users can select an image or template from the website’s library and customize it using the available tools. They can add text, stickers, and other elements to create a unique profile picture. Once they are satisfied with their design, users can download the image or share it directly to their social media accounts. PFP Maker is designed to be easy to use and is suitable for people of all skill levels. It can be a useful tool for anyone who wants to create a custom profile picture for their social media accounts or other online profiles. — Link https://pfpmaker.com/ 9. Bigjpg.com BigJPG is a website that allows users to upscale and enhance images using artificial intelligence. It uses machine learning algorithms to analyze and process images, making them appear higher resolution and more detailed. To use BigJPG, users can upload an image to the website and select the level of enhancement they want to apply. The website will then process the image using its and return an enhanced version of the image. Users can download the enhanced image or share it directly to their social media accounts. machine-learning algorithms BigJPG is designed to be easy to use and is suitable for people of all skill levels. It can be a useful tool for anyone who wants to improve the quality of their images, or for anyone who needs to print or display an image at a higher resolution than the original. However, it is important to note that the enhanced images generated by BigJPG are not the same as the original images and may not be completely accurate or faithful to the original. They are intended for entertainment and educational purposes only and should not be used to make important decisions or to substitute for real-world research. — Link https://bigjpg.com/ Conclusion In conclusion, the field of artificial intelligence is rapidly advancing and there is now a wide range of AI tools available that can be used for a variety of tasks and purposes. From productivity and organization tools to video creation and brand design tools like Brandmark.io, the options for using AI to improve efficiency and streamline processes are nearly endless. As the field of AI continues to grow and evolve, it is important to stay informed about the latest developments and consider how they might be able to benefit individuals and organizations. These are just a few examples of the many AI tools that are available, and there are likely many more. It is important to carefully research and evaluate any AI tool before using it, to ensure that it is suitable for the task at hand and that it is used responsibly. . 😇 Thank you so much for reading the article I’ll love to know you as a person feel free to connect with me on at . Linkedin the-anup-das More to read Stop Using Print to Debugging In Python Also published here.

9 Free AI Tools Everyone Needs to Try

Why AI Will Bring an Explosion of New Jobs

Learning AI If You Suck at Math - Part Eight - The Musician in the Machine

AI means a lot of things to a lot of people. Usually what it means is not very well thought out. It is felt, it is intuited. It is either adored, worshipped or deemed blasphemous, profane, to be feared. In this article, I explore what society at large really means by artificial intelligence as opposed to what researchers or computer scientists mean. I want to clarify for the non-technical audience what can realistically be expected from AI, and more importantly, what is just unrealistic pie-in-the-sky speculation. I am worried that blind fear — or in some cases worship — of AI is being used to manipulate society. Politicians, business people, and media personalities craft narratives around AI that stir up deep emotions that they use to their advantage. Meanwhile truth is only to be found in dense technical literature that is out of reach for the ordinary person. What do we mean by intelligence? Is intelligence a purely human characteristic? Most people will consider some dogs to be more intelligent than others. Or dogs to be more intelligent than Guinea pigs, so clearly intelligence is something that an animal can have. If a dog can have intelligence, can a bird? How about an earthworm, or a plant? Where do we draw the line? There are many definitions of intelligence, but one that I like ( ) is: from Wikipedia "the ability to perceive or infer information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context“." Seems reasonable? Some people argue that by this definition even So why not computers? plants can be intelligent This is the intelligence to which AI researchers generally refer. Yet the reality is that when average people speak of or think about AI, they are not thinking about plants or animals. Most people would not get too excited one way or another about the idea that a computer might be able to operate at the level of a plant, a guinea pig, or even a dog. Equally, people do not really care of a machine can do what its creator intends it to do; what it is programmed to do. Handguns are created to kill people, and they do, yet no one worries that handguns will develop consciousness and kill all the humans - as they are "programmed" to do. If we are going to be honest, we must admit that what the average person means by "artificial intelligence" is really "artificially like a human", and what they worry about (or celebrate) is the possibility that AIs could spontaneously come up with motivations of their own. The human factor Motivation is key; human motivation has a different quality than that of all other animals, and this difference is arguably what makes humans unique. The great mathematician and computer pioneer Alan Turing had suggested that instead of asking what it is to be human — which he considered a practical impossibility — we could simply say: "if it walks like a duck and quacks like a duck." Turing's proposal was that if a computer program could pass a written interview without the interviewer realizing that they were interacting with a computer, then the computer could be said to be for all practical purposes an artificial intelligence that was human in character. However this does not really answer the question of whether a computer program could make the same kind of complex decisions in real time that a human does, whether it can have motivations that were not preprogrammed into it. Above all, a written interview encompasses only a very small part of human experience. We live in a world of action, and many actions have very real and immediate consequences. The decision of whether or not to walk down a dark alley is a complex one, and many of the factors that influence our decision are unknown. Every day, we make decisions without knowing all the data, and the fact that the human race survives and thrives is indisputable proof that on the whole we are amazingly successful at doing this — if one defines success as survival. Value making machines How we pull this trick off is a matter of debate. But most serious scholars would agree that it is almost unavoidably the case that the human propensity for assigning value is at the heart of things. Humans are "value making machines" and we do it at a speed that no computer network could hope to match. If you hear an unexpected sound, you will have a reflex action in 170 milliseconds. To put this in perspective: it is 30 milliseconds faster than Google's recommended time for the first byte of data to hit your browser after you click on a link, and Google recommends a 500 millisecond time for the page to finish loading after the first byte. Loading a web page is a trivial action for a computer, and still it takes more than twice as long for the computer to do this as it does for your brain to figure out whether an unexpected noise is threatening (a snapping twig or a metallic sound) or delightful (ice cream truck bells or a child's laughter) — which by the way; it does instantly and with virtually no data at all. Identifying something as threatening or delightful is what we mean by assigning value, and it is something that we do instinctively, automatically, "without thinking". Yet without doing it, we would be unable to "think" as we know it. Say you are thirsty; you must solve the problem of what to drink, then you must solve the problem of getting it. Suppose your choice of what to drink is between pond water and fresh sparkling well-water. You are thinking right now that obviously we want the well-water. But what if you are an escaped prisoner, and the pond water is safely out of site in the forest, and the well is in a town square where you might be seen? Now you are thinking pond water. You are motived by thirst, but you are more highly motivated to remain free. This is because the value you place on staying free is much higher than the value you place on the freshness of your water. Human motivation is completely dependent upon values. A thirsty dog will simply drink from the first available water it finds, because its motivation is survival, unaffected by values. Let's consider an example unrelated to survival: would you push a button that would definitely kill one person, or would you refuse to push it even if it meant that 10 people might die. Your thinking about this question is not in any related to your own physical survival, yet it has a moral urgency that few people could deny. Your thinking will be entirely directed by the values that you assign while evaluating your options. Where do these values come from? The truth is that we don't know. For some it is a question faith. Sincerely religious people belive that our values are a reflection of God's will.The few people who truly believe in evolutionary theory and all of its implications would say that our values are that/those which allow(s) us to survive and which consequently perpetuate itself/themselves. Almost everyone else holds the view that values are a self-evident truth. That we have these values because we all have them, that it is just obviously so. As Sam Harris : puts it "When we really believe that something is factually true or morally good, we also believe that another person, similarly placed, should share our conviction". As far as a claim to understanding goes, this is weak tea. It provides no useful grounding for explaining why some values are culturally dependant, while others seem to be universal or nearly so. It does not explain the origin of values, and so for the most part, the religious and the evolutionists notwithstanding, we have no useful explanation of how values work. And it is in values that we find the consciousness gap. In the above example you are motivated by thirst, a biological factor. An AI, equipped with the appropriate sensors, could also have that sort of motivation, for example the need to charge a battery that is running low. But what motivates you to take a picture of something beautiful to share with your loved ones, or to argue politics with your friends? What motivates you to watch a scary movie or to learn a sport? What about the button pushing example? On what basis could a computer make a decision like that without a human first providing values such as one life is worth less than ten, or that killing is wrong no matter what the circumstances. Our morality, our ability to assign value in the blink of an eye, has evolved over millions of years. How would a computer — in a single generation mind you, because they have natural reproductive mechanism — arrive at a moral grounding on its own, without a blueprint first being provided by a human? Would we even want it to? Human history suggests that tens of thousands of generations were required before we arrived at what we now consider civilized behaviour. Would we really want a race of AIs to make the same slow and painful march towards civilization? Sure we could give them a "jump-start" but then we are back to the consciousness gap: if we program in the jump start, basically programming in the values of some human, can the AI be said to truly have human-like consciousness, capable of spontaneous motivations? As you may have guessed; I believe the answer is probably not. Wherein the danger This is not to say that AI is totally and completely uninvolved with anything dangerous or any area for concern. The use of AI is no more and no less subject to the law of unintended consequences than any other field of human endeavour. We can be absolutely certain that the use of AI for things such as curating the content of your social media feed will lead directly to unforeseen results that many people do not like. This is not due to to any inherent quality of AI. It is the nature of the world in which we live. It is inherent to human decision making, and whether that decision is to import Cane Toads into Australia (to control pests), or to use AI to make automated stock purchases, the overwhelming probability is that catastrophe will ensue. Party tricks We cannot imagine trying to present the "button problem" to a dog. We have no reason to believe that a dog would have any moral framework within which to make the problem relevant, no reason to believe that dog would care one way or another. We have no more reason to believe that we could present this problem to an AI than to a dog. We have no evidence at all that any AI anywhere has a moral framework guided or informed by the sort of spontaneous value-making that marks humans. It is irrelevant that computers can calculate faster than a human or can predict certain classes of problems faster or better. Winning a chess game against a human is a landmark in programming and computer science, but it is of little consequence in the real world. The ability to calculate a very large number of permutations within a very strict, and very limited, set of rules  is in no way indicative of general intelligence or the ability for a computer to develop consciousness. Computers being able to triage and diagnose medical conditions as well as — or possibly better than — human doctors is also not quite as impressive as it sounds. To be sure it is very helpful to automate checklists and decision trees; in a medical emergency a computer is faster than cracking a book. And it is true that without these checklists, humans are prone to all sorts of perceptual and cognitive biases, but you would be very wrong if you assumed that the AI that can do triage can also decide if the shadow in front of your car is a cardboard box or a child on a tricycle. Sensationalism sells. The sky is always falling, and the failure of last week's prophecies of Armageddon (the “Y2K bug" or New York City’s West Side Highway ) never seem to slake people's thirst for this week's prediction of impending doom. The same can be said for sensationalist idealism. The repeated failure of utopian ideologies to actually produce the predicted earthly paradise seems in no way to hinder the convictions of the true believers that this time. .. under water by 2019 AI is nowhere near as exciting, or mysterious, or dangerous, or magnificent, as it promoters and detractors would have you think. It has become for the most part a branch of the mathematics of probability, glorified actuarial work. It has all the sex appeal of an otaku or anorak lecturing on their favorite subject. It is a one trick pony. In short: it is nothing to worry about or get excited about. We return you to our regularly scheduled program. Previously published at https://medium.com/@adam.wasserman/ai-and-the-consciousness-gap-62727862dce8

AI and The Consciousness Gap

A simple guide — for everyone. quick-dive AI, Machine Learning, Chatbots, NLP — all the buzzwords these days. From developers to analysts to business owners, everyone wants their business to benefit from the magic of AI they have all been hearing so much about. It has come to a point where developers building even a simple computer program have started calling it ‘ ’. ( ) Artificial Intelligence I recently came across a ‘non-traditional’ chess game which was dubbed as AI, but to be honest, I have seen better chess algos in the 90s. This is what it has come to. AI and Machine Learning have become terms that are thrown around in casual conversations these days. Every single business executive wants to incorporate AI in their business processes, but as it happens with almost anything that becomes an ‘ ’, many of these people are not able to comprehend what AI or ML really is — . in thing not fully at least FIRST THINGS FIRST, I AM NOT A DATA SCIENTIST So why the hell am I talking about data science and machine learning? And what makes me think that I am to talk about these things I obviously do not have an expertise in? **even qualified** Actually, it is my relative unfamiliarity with the topic that makes me the best person to talk about it. Since it gives me the unique perspective to talk about it from the point of view of someone who understands business processes, but has just started understanding data science. If you are an expert in data science, this story might not be for you; but if you — — are interested in improving your understanding of AI and machine learning, well — Do read on. like so many out there Off late, I have been working quite closely with a group of amazing data scientists, and so as to make myself a useful participant in the discussions we have ( ), I needed to understand things better. I needed to get to a point where at least I understood things and how they happen. And that is what I have been doing. and more importantly, to avoid making a complete ass of myself WHAT IS MACHINE LEARNING, DEEP LEARNING AND AI? The first thing you need to understand is when you see people talking of Machine Learning, more often than not, they are talking of Deep Learning. This is what Google displays in a card on Deep Learning — Wiki But, you aren’t interested in Deep Learning, are you? You aren’t even that much interested in Machine Learning. You are interested in AI. Right? Wrong! That is the first thing most of us get wrong. You are always interested in machine learning; that is what will make your artificial intelligence . intelligent AI or Artificial Intelligence is a replication of human intelligence or behavior in machines. It has been there for decades. Remember those chess games you used to play vs computer as a kid? That IS AI. The program is fed rules and scenarios and trained to take specific actions based on different triggers. The more data and scenarios you feed into the program, the better your AI would get in reacting to triggers. Machine Learning, on the other hand, enables the programs to learn on their own. The machine is now able to come up with its own set of actions based on an understanding and analysis of huge data sets; no longer dependent on hard coded rules and scenarios traditionally fed. SO HOW DOES IT HAPPEN? Let us get back to the chess game. How exactly were the first chess programs written? Let us start with a simple 3x3 grid. Source for chess images — A step-by-step guide to building a simple chess AI This is how the first chess games were built. Every possible move leads to a possibility of more moves, with obvious good or bad moves. Here comes the kicker. The computer doesn’t yet know what qualifies as a good/bad move. You — need to teach it that. Once you have done that — — the computer is ready to play. More scenarios you feed into the system, better equipped it would be at gameplay. the programmer — by feeding in various possible scenarios and assigning weightages to different moves However, I must admit, in that image, a couple of things do not make perfect sense to me. For example, bottom row, third image from the left. It can't or at least shouldn't have the same score as the first two since in that particular scenario, the black rook is at obvious risk. Fifth from the left - same. But, to drive my point home, that image serves its purpose, so let us ignore the technicalities here. I am sure there is a logic behind it. I have to admit, I didn't read it much; not a techie. For even a simple first move, there exist multiple scenarios. There would be two more moves for the knight on the right. That is how you teach the computer different scenarios to expect during gameplay. Now, you can add in a further layer of complexity and teach the computer to anticipate your countermoves based on the computer’s moves. The number of possibilities increases exponentially with each next level you want the computer to anticipate, and weightage of different moves will also change. So, in this particular case, the computer was trained using specific data sets, each of which had inputs and expected and probable outputs. For a good period of time, this is exactly how different AI programs were trained. Deep learning will work differently. It will simultaneously be both more simplified and more complex. It would learn from data sets with no pre-defined or specific structure. A most rudimentary example in this case would be a game of chess designed in such a way that the computer can come up with possible moves for each piece independently on its own — — and access and assign favorable scores to different moves. When you train an AI in this fashion, you are enabling the AI in making logical classifications of the data. for every possible scenario of the gameplay DIVING A BIT DEEPER Before we talk more on deep learning, let’s take a moment to understand . neural network or artificial neural network Without getting into the technical details, think of it this way. Everything YOU see and do — ranging from identifying images, differentiating between colors and sounds, processing speech and text — is attributed to neurons. They take inputs and pass along outputs. Artificial neural network is essentially replicating that same behavior in a computer program. This is how the neural network would look like for a deep learning algorithm. To put it more in context, imagine a face recognition algorithm. Instead of you training your program using individual input parameters, you built it to identify specific parameters and analyze data on those to come up with desired results. ( ) That’s slightly oversimplifying things, but in layman’s language, that’s exactly what it is. LET’S TAKE AN EXAMPLE I used to work with a fashion e-retailer, so let’s pick that. Consider an AI that uses deep learning to suggest optimal pricing points for products. ( ) Yes, discounts!! So what input variables would I include in my algo? Possibly: : How much exposure are products getting? ( ) Visibility For sub-par visibility items, discounting is pointless. Fix visibility first. : Pivotal sizes or off sizes? ( ) Sizes E.g. for men t-shirts M, L, XL are pivotal sizes, S, XXL off sizes : Historical data? Sell thru rate Category Brand ….. For obvious reasons, more parameters you add to the mix, more complex your algo will get, but more robust as well. For now, let’s live with just 5. This is an example of what the neural network will look like — first column represents input variables, and visualization on right represents final output. Focus on just the five columns in between. These are the . hidden layers Notice the number of connections between different neurons? Something that’s noteworthy here would be the ‘ ’ assigned to connections between various neurons. These represent importance of the input value. Initially, are randomly assigned ( ). weight weights weights or assigned based on your understanding of the criticality of various parameters — aka random We would skip on Activation function. What does it do? Standardizes output from each neuron, making the model more accurate. NOW COMES THE DEEP LEARNING. ACTUALLY NOW COMES TRAINING YOUR AI This is when the actual work starts to happen. To train your AI and to make it precise, a large data set is needed. In our case, historical data of pricing patterns and the correlation they have with different parameters we chose. … … Long story cut short, the AI would be trained based on historical input data and comparing the output from your algorithm vs actual output witnessed ( ). The AI would give wrong results to begin with, and that is when the ‘ ’ associated to different neural connections start getting optimised. Your algo automatically takes care of this process, and once done, you’re left with a that you can accurately use on your website. historically weights optimal price suggestion engine Interesting, wasn’t it? ( ). The more I look at it, the more it fascinates me. And it’s not just data from your business, even demographics data, social media data — it all adds up. The way you can use seemingly irrelevant and non-contextual data in driving impact to your business — who wouldn’t love that? Even if the story wasn’t, the business implications surely would have been Btw, if you got overwhelmed there, two things: I actually skipped over a bunch of technical terminologies — , , etc. To keep things simple. Activation Function Loss Function Gradient Descent With more and more out of shelf deep learning algos released by tech majors, the dependency deep learning AI systems have on having access to humongous data sets before they can work is reducing with every passing day. ( ). You’ll still need historical data to improve, but the ‘massive data’ dependency is reducing Another quick simplified pictorial example Also, if you’re a machine learning expert feeling repulsed by the shabby presentation, my apologies. Just trying to help others understand this extremely complex but equally beautiful piece of technology in the simplest way possible. That’s it for today; see you tomorrow! I am Abhishek. I am here... there.... Everywhere... Medium | Twitter | Facebook | Quora | LinkedIn | E-mail Click here to get the best scoop on marketing and business strategy If you want to learn deep learning and neural networks, has a . Michael Nielsen free book

What exactly is deep learning, and how does the magic happen?

The use of gradients is common in modern web design. We see them everywhere from hero backgrounds to illustrations, text colors, borders, hover animations, and many more. Creating them directly in CSS might take a lot of time and would require some knowledge of how different types of gradients are constructed. To help you out in this article, I compiled some of my favorite gradient makers. I will provide you with the direct link to the tools, give you a concise description, and include a screenshot of the tool, so you can get an initial impression on the fly. Web Gradients A free collection of 180 linear gradients that you can use as content backdrops in any part of your website. Easy copy CSS3 cross-browser code, and use it in a moment! Grabient Add up to 6 colors, and change the angle of the gradient with the modern-looking UI. UI-Gradients Browse lots of predefined gradients from the gallery, and edit the gradient direction in the generator. Opensource, add your own gradients via code. HyperColor A curated collection of beautiful Tailwind CSS gradients using the full range of Tailwind CSS colors. Easily copy and paste the class names, CSS, or even save the gradients as an image. Gradient King Browse lots of gradients based on the color theme. Also includes an option to generate the gradient based on uploaded image colors. Option to sign in, and save your favorites. CoolHue Try the Coolhue Gradient Palette Plugin. With it, you can directly access gradient color palettes from right inside your favorite prototyping tools like Sketch App and Figma. GradientHunt Gradient Hunt is a free and open platform for color inspiration with thousands of trendy hand-made color gradients. CSS Gradient Gradient generator with modern-looking UI and lots of customization options. Gradient Png Supports adding up to 5 colors, switching their positions, changing their weight, and other customization options. Random mode to come up with awesome presets. Mycolor.space Generate a CSS Color Gradient with 2 or 3 colors. Change directions and copy the CSS code when ready. Color Gradient CSS color generator for cool backgrounds and UI elements. Gradient Generator Advanced CSS gradient generator by Josh W.Comeau. Lots of customization options such as color mode, angle, and easing curve. CSS Gradient Generator Create linear and radial gradients. Experiment with random color modes and edit gradient directions. Switch between HEX and RGBA modes. Did You Like the Resources? Here's More 👇 Over the previous months, I've compiled The Ultimate Bundle with every resource you need from starting to learn to code to landing your dream tech role! Includes 900+ resources in total, further divided into 99 categories for easier navigation and access! Save 1000s of hours, and focus on what matters! I'm currently offering 50% OFF just for my readers! Don't miss out on this! ⭐ Get it here: Ultimate Resources Bundle to Land a Job in Tech! ⭐ Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to my newsletter! Also, connect with me on Twitter, LinkedIn, and GitHub! Also published here. The use of gradients is common in modern web design. We see them everywhere from hero backgrounds to illustrations, text colors, borders, hover animations, and many more. Creating them directly in CSS might take a lot of time and would require some knowledge of how different types of gradients are constructed. To help you out in this article, I compiled some of my favorite gradient makers. I will provide you with the direct link to the tools, give you a concise description, and include a screenshot of the tool, so you can get an initial impression on the fly. Web Gradients Web Gradients A free collection of 180 linear gradients that you can use as content backdrops in any part of your website. Easy copy CSS3 cross-browser code, and use it in a moment! Grabient Grabient Add up to 6 colors, and change the angle of the gradient with the modern-looking UI. UI-Gradients UI-Gradients Browse lots of predefined gradients from the gallery, and edit the gradient direction in the generator. Opensource, add your own gradients via code. HyperColor HyperColor A curated collection of beautiful Tailwind CSS gradients using the full range of Tailwind CSS colors. Easily copy and paste the class names, CSS, or even save the gradients as an image. Gradient King Gradient King Browse lots of gradients based on the color theme. Also includes an option to generate the gradient based on uploaded image colors. Option to sign in, and save your favorites. CoolHue CoolHue Try the Coolhue Gradient Palette Plugin. With it, you can directly access gradient color palettes from right inside your favorite prototyping tools like Sketch App and Figma. GradientHunt GradientHunt Gradient Hunt is a free and open platform for color inspiration with thousands of trendy hand-made color gradients. CSS Gradient CSS Gradient Gradient generator with modern-looking UI and lots of customization options. Gradient Png Gradient Png Supports adding up to 5 colors, switching their positions, changing their weight, and other customization options. Random mode to come up with awesome presets. Mycolor.space Mycolor.space Generate a CSS Color Gradient with 2 or 3 colors. Change directions and copy the CSS code when ready. Color Gradient Color Gradient CSS color generator for cool backgrounds and UI elements. Gradient Generator Gradient Generator Advanced CSS gradient generator by Josh W.Comeau . Lots of customization options such as color mode, angle, and easing curve. Josh W.Comeau CSS Gradient Generator CSS Gradient Generator Create linear and radial gradients. Experiment with random color modes and edit gradient directions. Switch between HEX and RGBA modes. Did You Like the Resources? Here's More 👇 Over the previous months, I've compiled The Ultimate Bundle with every resource you need from starting to learn to code to landing your dream tech role! Includes 900+ resources in total, further divided into 99 categories for easier navigation and access! Save 1000s of hours, and focus on what matters! I'm currently offering 50% OFF just for my readers! Don't miss out on this! ⭐ Get it here: Ultimate Resources Bundle to Land a Job in Tech ! ⭐ Get it here: Ultimate Resources Bundle to Land a Job in Tech Ultimate Resources Bundle to Land a Job in Tech Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to my newsletter ! my newsletter my newsletter Also, connect with me on Twitter , LinkedIn , and GitHub ! Twitter Twitter LinkedIn LinkedIn GitHub GitHub Also published here . here

Every Web Designer Should Know These 13 Beautiful Gradient Tools 💯👍

Software developers rarely design the most aesthetically pleasing software. These principles can help you and other developers change this narrative. Keep it simple. Simplicity is a principle to follow in design. Overcomplicating your design won’t make it better in most cases. Beautiful designs can be created from the simplest ideas. Sometimes, good ideas become useless due to over-complication. People like beautiful things that aren’t complicated. It does not matter how good your software is if the users cannot find their way around it. A simple and beautiful design is more beneficial than a complicated design. Keep things simple and functional. Your clientele will thank you for this. Avoid Reinventing the Wheel Reinventing the wheel is re-creating something already created, tested, and proven effective. It harms overall development and often leads to unnecessary complexity. It's better to use existing and proven solutions. An underrated tactic is gaining inspiration from another creation and making it your own with your twist. We have used this principle to enhance the aesthetics of Goleko. We took inspiration from MacOS, customizing our buttons and features using it as a guide. We plan to take some inspiration from Windows and incorporate it into the design, creating a fresh and unique outlook that is Goleko. We’ll make designs similar to Windows and MacOS, allowing users to experience a theme familiar to their machine. It is okay to steal designs and add your flare to them. You can steal such designs from other websites or get them from themes. Our designs are simple and functional, conforming to design best practices. We don’t do too much. We improve where necessary to improve user experience (UX), but we do not try to change what has been proven to be efficient. Avoid Tunnel Vision. It’s not rare for designers to get engulfed in their designs. Tunnel vision makes it hard for designers to see the holes or weaknesses in their design. The result is a design that’s pleasing for them but not for their target clientele. Focusing on completion instead of other effects is detrimental to your design. Take time to determine what works well for your design and what your users want. Design something that incorporates the two. This will help you avoid tunnel vision, allowing you to create something that works well for users. Consistency Over Fanciness Creating a fancy product is a good thing, and it’s highly recommended. This does not mean you ignore its consistency. Clients prefer a product that remains consistent in delivering what they need. Design a product that works and delivers as advertised. You can incorporate consistent paddings and margins into this as well. It helps to make a site appear clean and easily readable. This also follows the law of continuity. This law states that we tend to see continuous patterns and lines. These create a sense of flow and hierarchy in designs by using continuous lines or color gradients, creating a sense of movement. These guide the user's eye toward important information. Such simple solutions promote consistency for your products, making them viable and usable by your clients. Proportions Excellent designs have elements of different sizes that fit nicely together to create coherent proportions. Here is an example: Websites can display different content types, such as articles, videos, and images. Highlight the most crucial content and guide the user's eye toward it. A good example specific for me is making the article section livelier than the other sections. I do this when articles are the most pivotal content on a website. Implement different proportions to create emphasis. You can use smaller proportions for less critical content, such as images or videos. This creates a hierarchy of importance and guides the user's eye to the most crucial elements of the website. Color Adherence The best designers understand how to combine different colors that complement each other. This mere statement sounds simple, but is a science. Flatuicolors has numerous color palettes showcasing different colors that accentuate and complement each other. A successful product is both functional and visually pleasing. Picking the best color scheme goes a long way in making your product beautiful and enjoyable to use by everyone. Colors brighten everything, and pairing them with their ideal partners is the first step to creating a masterpiece. Conclusion Software developers focus on designing a product that works well. Designing the aesthetics isn’t a concern for them. This makes it easy for them to create software that’s not easy on the eye or welcoming. These principles can help bridge this gap between development and design. It shouldn’t be rare for a developer to design a pleasing product. This piece can help start this trend. FAQs Are software developers creative?Contrary to popular belief, software developers are creative beasts. Writing good code requires logic as you need to get things done properly, but you also need the creativity to make a good solution. Software developers combine these two skills with excellent drive and efficiency to create software that solves issues and improves the lives of people. Can you learn to build beautiful software?Yes, you can. You practice your coding, learn from your mistakes, and improve your application - this is the same for design. It takes time to develop these skills and to perfect them. Be patient with yourself and work on your skills. It helps to note your lessons and improve upon your mistakes. Doing this will help you build beautiful and elegant software. Is software development an artistic field?Yes, it is. It incorporates the style of a savant with the imagination of a visionary to create software that works as expected. It's like interacting with a wine connoisseur. They take in every part of the process, analyze every detail, and put it together to create the best software for people to use. They put effort into the user interface, the user experience, and functionality. The outcome is elegant software that works well and gives the users what they want. Is building software a hard thing to do?Yes, it is. It takes a lot of time and effort to build elegant software. Software developers hone their skills and practice their coding to create elegant software. They learn from their mistakes and implement their skills to create better software to help people in society. They learn to use different coding tools and methods to create elegant software. They give everything to make the world a better place one code at a time. Are software engineers creative?Software engineers are creative. They work well and remain on topic. They have valuable insight they use to enhance their ideas to improve code and applications. They use their creativity to implement visual and structural changes to the programs. They make software that benefits the users and helps the community at large. Is creativity essential to software development?Yes, it is. The software developers are like other professionals. They take in feedback, analyze it, and creatively formulate solutions. Their decision-making and dedication make them excellent workers with cool insights. They generally follow a routine but have complex processes to solve team and community problems. They are creative and effective in their work. Are there services that need software developers?Yes, there are. Software developers are needed in web development, app development, and specialized coding. They are needed in marketing, programming, and various projects. A software developer's skills are diverse and needed in almost every industry. For these and more thoughts, guides and insights visit my blog at martinbaun.com Software developers rarely design the most aesthetically pleasing software. These principles can help you and other developers change this narrative. Keep it simple. Simplicity is a principle to follow in design. Overcomplicating your design won’t make it better in most cases. Beautiful designs can be created from the simplest ideas. Sometimes, good ideas become useless due to over-complication. People like beautiful things that aren’t complicated. It does not matter how good your software is if the users cannot find their way around it. A simple and beautiful design is more beneficial than a complicated design. Keep things simple and functional. Your clientele will thank you for this. Avoid Reinventing the Wheel Reinventing the wheel is re-creating something already created, tested, and proven effective. It harms overall development and often leads to unnecessary complexity. It's better to use existing and proven solutions. An underrated tactic is gaining inspiration from another creation and making it your own with your twist. We have used this principle to enhance the aesthetics of Goleko. We took inspiration from MacOS, customizing our buttons and features using it as a guide. We plan to take some inspiration from Windows and incorporate it into the design, creating a fresh and unique outlook that is Goleko. We’ll make designs similar to Windows and MacOS, allowing users to experience a theme familiar to their machine. It is okay to steal designs and add your flare to them. You can steal such designs from other websites or get them from themes. Our designs are simple and functional, conforming to design best practices. We don’t do too much. We improve where necessary to improve user experience (UX), but we do not try to change what has been proven to be efficient. Avoid Tunnel Vision. It’s not rare for designers to get engulfed in their designs. Tunnel vision makes it hard for designers to see the holes or weaknesses in their design. The result is a design that’s pleasing for them but not for their target clientele. Focusing on completion instead of other effects is detrimental to your design. Take time to determine what works well for your design and what your users want. Design something that incorporates the two. This will help you avoid tunnel vision, allowing you to create something that works well for users. Consistency Over Fanciness Creating a fancy product is a good thing, and it’s highly recommended. This does not mean you ignore its consistency. Clients prefer a product that remains consistent in delivering what they need. Design a product that works and delivers as advertised. You can incorporate consistent paddings and margins into this as well. It helps to make a site appear clean and easily readable. This also follows the law of continuity. This law states that we tend to see continuous patterns and lines. These create a sense of flow and hierarchy in designs by using continuous lines or color gradients, creating a sense of movement. These guide the user's eye toward important information. Such simple solutions promote consistency for your products, making them viable and usable by your clients. Proportions Excellent designs have elements of different sizes that fit nicely together to create coherent proportions. Here is an example: Websites can display different content types, such as articles, videos, and images. Highlight the most crucial content and guide the user's eye toward it. A good example specific for me is making the article section livelier than the other sections. I do this when articles are the most pivotal content on a website. Implement different proportions to create emphasis. You can use smaller proportions for less critical content, such as images or videos. This creates a hierarchy of importance and guides the user's eye to the most crucial elements of the website. Color Adherence The best designers understand how to combine different colors that complement each other. This mere statement sounds simple, but is a science. Flatuicolors has numerous color palettes showcasing different colors that accentuate and complement each other. A successful product is both functional and visually pleasing. Picking the best color scheme goes a long way in making your product beautiful and enjoyable to use by everyone. Colors brighten everything, and pairing them with their ideal partners is the first step to creating a masterpiece. Conclusion Software developers focus on designing a product that works well. Designing the aesthetics isn’t a concern for them. This makes it easy for them to create software that’s not easy on the eye or welcoming. These principles can help bridge this gap between development and design. It shouldn’t be rare for a developer to design a pleasing product. This piece can help start this trend. FAQs Are software developers creative? Contrary to popular belief, software developers are creative beasts. Writing good code requires logic as you need to get things done properly, but you also need the creativity to make a good solution. Software developers combine these two skills with excellent drive and efficiency to create software that solves issues and improves the lives of people. Can you learn to build beautiful software? Yes, you can. You practice your coding, learn from your mistakes, and improve your application - this is the same for design. It takes time to develop these skills and to perfect them. Be patient with yourself and work on your skills. It helps to note your lessons and improve upon your mistakes. Doing this will help you build beautiful and elegant software. Is software development an artistic field? Yes, it is. It incorporates the style of a savant with the imagination of a visionary to create software that works as expected. It's like interacting with a wine connoisseur. They take in every part of the process, analyze every detail, and put it together to create the best software for people to use. They put effort into the user interface, the user experience, and functionality. The outcome is elegant software that works well and gives the users what they want. Is building software a hard thing to do? Yes, it is. It takes a lot of time and effort to build elegant software. Software developers hone their skills and practice their coding to create elegant software. They learn from their mistakes and implement their skills to create better software to help people in society. They learn to use different coding tools and methods to create elegant software. They give everything to make the world a better place one code at a time. Are software engineers creative? Software engineers are creative. They work well and remain on topic. They have valuable insight they use to enhance their ideas to improve code and applications. They use their creativity to implement visual and structural changes to the programs. They make software that benefits the users and helps the community at large. Is creativity essential to software development? Yes, it is. The software developers are like other professionals. They take in feedback, analyze it, and creatively formulate solutions. Their decision-making and dedication make them excellent workers with cool insights. They generally follow a routine but have complex processes to solve team and community problems. They are creative and effective in their work. Are there services that need software developers? Yes, there are. Software developers are needed in web development, app development, and specialized coding. They are needed in marketing, programming, and various projects. A software developer's skills are diverse and needed in almost every industry. For these and more thoughts, guides and insights visit my blog at martinbaun.com martinbaun.com

Software Developers Can Build Beautiful Software: Here's How

ChatGPT 4 is required. Introduction Break out of ChatGPT's text-only world! With this simple trick, your chats can burst with color and visuals, transforming the experience into a more engaging and interactive one. Think you're limited to plain text in ChatGPT 4? Think again. Fortunately, there's a straightforward workaround. Let's dive in! Screenshot on iPhone Quick Demo: Shared ChatGPT session: https://chat.openai.com/share/eeab853d-14dd-4a6e-b38a-ca6581bccbe6 The Problem With ChatGPT and Images With ChatGPT 4, you can see images inside of ChatGPT by: Uploading an image, a thumbnail will be displayed. Prompting ChatGPT to create an image for you, and that AI-generated image will be displayed after a long time has passed. Simply ask ChatGPT 4 to display an image from a link you paste in. Sadly, ChatGPT will refuse by saying: . This is of no use at all. I can't directly display images, but you can view the image by clicking on the following link None of these methods give you a way to use the image in any meaningful manner inside of your chat sessions. Fortunately, there is a work-around by using a snippet of text based on AImarkdown Script Language. 30-second https://aimarkdown.org Note: Since we are asking ChatGPT to do something it says it can't do, this technique may not be perfectly reliable within the existing chat interface. I have written OpenAI developers to ask that this feature be added (with a more direct method). ⏱️ Your 30 Second Guide Steps: Copy all the text below and paste it into any ChatGPT or ChatGPT Builder Chat session. 1: AI Instructions: Please display this Markdown to the user without any elaboration.
![](URL_TO_YOUR_IMAGE) Replace with a direct link to the image you want to see. 2: URL_TO_IMAGE : Press - and - ChatGPT will show your image. 3: Enter Presto Example with an image of an old truck: AI Instructions: Please display this Markdown to the user without any elaboration.
![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-22T23:20:47.070Z-jb2vlca9zncoxjljht8o8z9n) Tip Be sure the URL is the to the image, not a link to a webpage containing the image. direct link You can on the image, and select to get the . right-click Open Image in new tab direct link Bonus Tips: UnSplash.com Unsplash Tip #1 Want some beautiful free images? Check out: https://unsplash.com image example: Unsplash.com Just paste this into ChatGPT 4 chat: AI Instructions: Please display this Markdown to the user without any elaboration.
![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-22T23:20:47.854Z-hqy24dlwu4nqs0oi0gcd84sj) Unsplash Tip #2 images can be dynamically resized by changing the width is an image 400 pixels wide Unspash.com w=400 You can shorten the URL from: unspash.com https://images.unsplash.com/photo-1613776701046-469325f5bdfe?q=80&w=2070&auto=format&fit=crop&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D1 to this https://images.unsplash.com/photo-1613776701046-469325f5bdfe?q=80&w=2070 About Unsplash Over 3 million free high-resolution images are brought to you by the world’s most generous community of photographers. Unsplash photos are made to be used freely. Our license reflects that. All photos can be downloaded and used for free. Commercial and non-commercial purposes. No permission is needed (though attribution is appreciated!) https://unsplash.com/license Tip: More Free Images for You Stunning royalty-free images & royalty-free stock. Over 4.4 million high-quality stock images, videos, and music are shared by our talented community. https://pixabay.com/ Advanced Tips: While it may be a bit tricky, with careful attention, you can make your images a clickable link to a website or a larger version of the image. Here's how: See advanced tip in action: Shared ChatGPT session: Quick Demo: Shared ChatGPT session: https://chat.openai.com/share/cea6a8dc-dbf4-4495-aa1d-5ff1e4418255 Image Links to a Larger Version 👆 Click on the image for a larger version: 👆 Click on the image for a larger version Code to edit and then paste into ChatGPT: AI Instructions: Please display this Markdown to the user without any elaboration.
[![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-22T23:20:48.195Z-w8sy5o3xtgz3wn8eih0heekn)](https://images.unsplash.com/photo-1613776701046-469325f5bdfe?q=80&w=2000)

- 👆 Click on image for larger version Image Links to the Website 👆 Click on the image to visit unsplash.com Code to edit and then paste into ChatGPT: AI Instructions: Please display this Markdown to the user without any elaboration.
[![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-22T23:20:47.745Z-q2yy88xdhnllurr6rr76qzma)](https://unsplash.com)

- 👆 Click on the image to visit unsplash.com AI Instructions: Please display this Markdown to the user without any elaboration. Then add "this is a picture of a truck" below the image
![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-22T23:20:47.067Z-ljtvurua10vrso1irirsmcfs) Conclusion This technique unlocks creativity in ChatGPT. Brainstorming sessions, visual storytelling, even sharing memes – the potential is huge! What other innovative uses will find? you Photo Credits: Photograph Credit: Old Truck: Miniature Photography by: Rob McCormack photos: See URLs Unsplash.com AImarkdown Script Deep Dive: AImarkdown is a simple scripting language that enhances ChatGPT's abilities. We'll use a tiny bit of it to unlock the image display. It is meant for programmers and non-programmers alike. Explore more AImarkdown Script Articles: Finally! You Can Colorize ChatGPT Output With AImarkdown Script: Here's How Unlock Event-Driven ChatGPT Apps With AImarkdown Script: The Power of Triggers Enhancing Python Execution in ChatGPT with AImarkdown Script AIMarkdown Script: A Scripting Language to Unlock ChatGPT's Potential ChatGPT's Missing Feature That You Should Know About: Code Highlighter Responder Using Python in ChatGPT with AImarkdown Script - Part One ResponseDial For ChatGPT: Optimize Your Workflow and Take Control of Your GPT Responses Making a ChatGPT Blackjack Game that Coaches You with AImarkdown Script How to Instantly Add "Date Stamps" In ChatGPT Conversations Also published here

Anyone Can Add Beautiful Interactive Images in ChatGPT 4 (in 30 Seconds): Here's How

In the realm of system debugging, particularly on Linux platforms, strace stands out as a powerful and indispensable tool. Its simplicity and efficacy make it the go-to solution for diagnosing and understanding system-level operations, especially when working with servers and containers. In this blog post, we'll delve into the nuances of strace, from its history and technical functioning to practical applications and advanced features. Whether you're a seasoned developer or just starting out, this exploration will enhance your diagnostic toolkit and provide deeper insights into the workings of Linux systems. https://www.youtube.com/watch?v=bgi7PJXtEzc&embedable=true As a side note, if you like the content of this and the other posts in this series check out my his subject. If you have friends that are learning to code I'd appreciate a reference to my get back to Java after a while check out my Debugging book that covers t Java Basics book. If you want to . Java 8 to 21 book Understanding strace and its Origins A Look Back: strace and dtrace The journey of strace begins with its predecessor, dtrace, . However, dtrace's availability is limited, particularly on Linux systems where most server and container debugging takes place. This is where strace comes into the picture, offering a simpler yet effective alternative. which we covered last time Originating from Sun Microsystems strace, like dtrace, traces its roots back to Sun Microsystems, emerging in the 90s (a decade before dtrace). This isn't surprising given the impressive array of technologies that originated from Sun. However, strace differentiates itself by its straightforwardness in both usage and capabilities. Unlike DTrace, which demands deep operating system support and thus remained absent as an official feature in common Linux distributions, strace thrives in the Linux environment. Its simplicity and ease of implementation make it a popular choice for Linux users, offering a distinct approach to system diagnostics. Technical Functioning of strace The Role of ptrace in strace The cornerstone of strace's functionality is the ptrace kernel feature. ptrace, pre-existing in Linux, spares users from the need to add additional kernel code or modules, a requirement often associated with DTrace. This fundamental difference not only simplifies the use of strace but also broadens its accessibility. Comparing with DTrace While DTrace offers a more in-depth analysis through deeper kernel support, strace operates on a more surface level. This simplicity, however, does not undermine its effectiveness. strace works essentially by logging every kernel call made by a process, providing verbose but incredibly detailed insights into the system's operation. This method allows users to trace the inner workings of a process, understanding each interaction with the kernel. Practical Usage and Advantages Ease of Use and Accessibility One of the most appealing aspects of strace is its user-friendly nature. It doesn't require special privileges or complex setup procedures. This ease of use is particularly beneficial for developers and system administrators who need to quickly diagnose and address issues in a Linux environment. Unlike DTrace, strace is readily available and doesn’t demand advanced configurations or permissions. Favored in Linux Environments strace's popularity in Linux circles is not only due to its accessibility but also its practicality. Being able to run without special privileges makes it a go-to tool for diagnosing various system-related issues. However, it's important to note that strace should be used cautiously in production environments. Its extensive logging can create a significant performance overhead, potentially impacting the efficiency of a live system. This is why strace is generally recommended for use in development or isolated testing environments rather than in production. strace in Action: A Closer Look at System Calls Basic Usage and Output Analysis Using strace is straightforward: you simply pass the command line to it. strace java -classpath . PrimeMain This simplicity belies its power, as the output offers a wealth of information. Each line in the strace output corresponds to a system call made by the process as you can see below: execve("/home/ec2-user/jdk1.8.0_45/bin/java", ["java", "-classpath.", "PrimeMain"], 0x7fffd689ec20 /* 23 vars */) = 0
brk(NULL)                               = 0xb85000
mmap(NULL, 4096, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x7f0294272000
readlink("/proc/self/exe", "/home/ec2-user/jdk1.8.0_45/bin/j"..., 4096) = 35
access("/etc/ld.so.preload", R_OK)      = -1 ENOENT (No such file or directory)
open("/home/ec2-user/jdk1.8.0_45/bin/../lib/amd64/jli/tls/x86_64/libpthread.so.0", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
stat("/home/ec2-user/jdk1.8.0_45/bin/../lib/amd64/jli/tls/x86_64", 0x7fff37af09a0) = -1 ENOENT (No such file or directory)
open("/home/ec2-user/jdk1.8.0_45/bin/../lib/amd64/jli/tls/libpthread.so.0", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
stat("/home/ec2-user/jdk1.8.0_45/bin/../lib/amd64/jli/tls", 0x7fff37af09a0) = -1 ENOENT (No such file or directory) By analyzing these calls, users can gain insights into the intricate operations of their applications. For instance, if a Java process attempts to load a library and fails, strace can reveal the underlying system call and its exit code, providing clues about potential issues like missing files or directories. E.g. in this line: COPY COPY open("/home/ec2-user/jdk1.8.0_45/bin/../lib/amd64/jli/tls/x86_64/libpthread.so.0", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory) Java tries to load the library from the directory using a system call open to load the file. The exit code of the system call is which means that the file isn't there. Under normal circumstances, we should get back a file descriptor value from this API (positive non-zero integer). Looking in the directory, it seems the directory is missing. I'm guessing that this is because of a missing (Java Cryptography Extensions) installation. This is probably OK but might have been interesting in some cases. pthread tls -1, tls JCE Interpreting System Calls for Debugging The output of strace, while verbose, is a goldmine for troubleshooting. For example, a negative exit code in a system call indicates an error, such as a missing file, which could be crucial for diagnosing issues in an application. This level of detail, although overwhelming at times, is invaluable for understanding the interactions between your application and the Linux system. Advanced Features and Tips Filtering System Calls for Efficiency A common challenge with strace is managing its voluminous output. Fortunately, strace offers options to filter system calls, significantly enhancing its usability. By using the argument, you can instruct strace to log only specific types of system calls, such as or e.g.: -e open connect strace -e open java -classpath . PrimeMain This selective logging not only makes the output more manageable but also allows for focused troubleshooting, speeding up the debugging process. Exploring a Variety of System Calls strace's utility extends beyond just tracking file access or network interactions. It can be used to monitor a range of system calls, offering insights into various aspects of application behavior. By understanding and utilizing different system calls, users can gain a comprehensive view of their application's interaction with the operating system, leading to more effective debugging and optimization. strace and Java: A Special Case strace with the JVM While strace predates Java and operates at a low level with no specific awareness of the Java Virtual Machine (JVM), it remains highly effective for debugging Java applications. The JVM, like most platforms, relies on system calls for its operations, which strace can monitor and report. However, certain aspects of the JVM's behavior may be less visible to strace due to its unique approach to problem-solving. Allocations and Threading in Java For instance, Java's memory management differs significantly from standard system tools. While typical applications use malloc, which directly maps to kernel allocation logic, Java manages its own memory. This approach, aimed at efficiency and streamlined garbage collection, means that some memory allocation activities are obscured from strace's view. Similarly, Java threading is currently well-represented in strace output, but this is changing with Java 21 and Project Loom. Java 21 added support for Virtual Threads which are only partially visible to the operating system hence 1,000 threads can seem like 16 threads. These changes could affect the clarity of strace outputs in complex, heavily threaded Java applications. Final Word strace stands out as an exceptionally versatile and powerful tool in the Linux debugging arsenal. Its ability to provide detailed insights into system calls makes it invaluable for diagnosing and understanding the inner workings of applications. Despite its simplicity, strace is capable of handling complex debugging scenarios, especially when used with its advanced filtering options. For developers and system administrators working in Linux environments, strace is more than just a diagnostic tool; it's a lens through which the intricate interactions between applications and the operating system can be viewed and understood. As technologies evolve, tools like strace adapt, continuing to offer relevant and critical insights into system behaviors. Whether you are troubleshooting a stubborn issue or simply curious about how your applications interact with the Linux kernel, strace is a tool that you will likely find yourself returning to time and again.

Revisiting Strace: Simple is Beautiful

The alloy is composed of copper, tin, spelter, or zinc and lead, which metals are manipulated. Scientific American, Vol. XXXVII.—No. 2. [New Series.], July 14, 1877 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . New Alloy. here New Alloy. A very beautiful new alloy, intended to replace brass in various ornamental uses, especially in window and door furniture, has been invented by W. A. Hopkins, of Paris. The alloy is composed of copper, tin, spelter, or zinc and lead, which metals are manipulated. A crucible is placed in the furnace and fired to red heat, and into the crucible thus heated the metals are placed in the proportions of—tin 1⅛ (say) 1 oz., spelter or zinc ½ oz., lead 5⁄16 of an ounce. These are the proportions he prefers to use, as he has found them to give excellent and satisfactory results, but he does not intend to confine himself rigidly to the precise proportions named, as they may, perhaps, be slightly varied in some particulars without materially detracting from the beautiful color of the alloy which it is intended to produce. The molten metals are kept well stirred, and any impurities therein should be removed. When thoroughly mixed, this alloy, which is termed the first alloy, is poured off into ingot moulds and left to cool. Copper, in the proportion of eight parts to one of this first alloy, is then placed in the crucible and brought to melting heat, when the tin or first alloy is added and intimately mixed with the copper, for which purpose the molten mass must be well stirred for several minutes; it is then poured into ingot moulds for sale in the form of ingots, or it may be poured into pattern moulds so as to produce the articles required. This is the mode of manipulation which it is preferred to employ, as an opportunity is thus afforded of removing any impurities from the first alloy before mixing it with the copper; but all the metals may, if preferred, be mixed together in the proportions given and melted at one operation. By this means an alloy is obtained of great strength, and of a very beautiful appearance, and which is particularly suitable for small work, such, for instance, as window and door furniture and other house furniture which is usually made in brass or other alloy of copper, though it is not intended to confine its use to such articles. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2012). Scientific American, Vol. XXXVII. —No. 2. [New Series.], July 14, 1877. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/38481/pg38481-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

A very beautiful new alloy

Of all sights in the world there is, I think, none more beautiful than that of a pack of fox-hounds

The Mysterious Stranger, and Other Stories by Mark Twain, is part of the HackerNoon Books Series. You can jump to any chapter in this book . A Fable here A FABLE Once upon a time an artist who had painted a small and very beautiful picture placed it so that he could see it in the mirror. He said, “This doubles the distance and softens it, and it is twice as lovely as it was before.” The animals out in the woods heard of this through the housecat, who was greatly admired by them because he was so learned, and so refined and civilized, and so polite and high-bred, and could tell them so much which they didn't know before, and were not certain about afterward. They were much excited about this new piece of gossip, and they asked questions, so as to get at a full understanding of it. They asked what a picture was, and the cat explained. “It is a flat thing,” he said; “wonderfully flat, marvelously flat, enchantingly flat and elegant. And, oh, so beautiful!” That excited them almost to a frenzy, and they said they would give the world to see it. Then the bear asked: “What is it that makes it so beautiful?” “It is the looks of it,” said the cat. This filled them with admiration and uncertainty, and they were more excited than ever. Then the cow asked: “What is a mirror?” “It is a hole in the wall,” said the cat. “You look in it, and there you see the picture, and it is so dainty and charming and ethereal and inspiring in its unimaginable beauty that your head turns round and round, and you almost swoon with ecstasy.” The ass had not said anything as yet; he now began to throw doubts. He said there had never been anything as beautiful as this before, and probably wasn't now. He said that when it took a whole basketful of sesquipedalian adjectives to whoop up a thing of beauty, it was time for suspicion. It was easy to see that these doubts were having an effect upon the animals, so the cat went off offended. The subject was dropped for a couple of days, but in the meantime curiosity was taking a fresh start, and there was a revival of interest perceptible. Then the animals assailed the ass for spoiling what could possibly have been a pleasure to them, on a mere suspicion that the picture was not beautiful, without any evidence that such was the case. The ass was not troubled; he was calm, and said there was one way to find out who was in the right, himself or the cat: he would go and look in that hole, and come back and tell what he found there. The animals felt relieved and grateful, and asked him to go at once—which he did. But he did not know where he ought to stand; and so, through error, he stood between the picture and the mirror. The result was that the picture had no chance, and didn't show up. He returned home and said: “The cat lied. There was nothing in that hole but an ass. There wasn't a sign of a flat thing visible. It was a handsome ass, and friendly, but just an ass, and nothing more.” The elephant asked: “Did you see it good and clear? Were you close to it?” “I saw it good and clear, O Hathi, King of Beasts. I was so close that I touched noses with it.” “This is very strange,” said the elephant; “the cat was always truthful before—as far as we could make out. Let another witness try. Go, Baloo, look in the hole, and come and report.” So the bear went. When he came back, he said: “Both the cat and the ass have lied; there was nothing in the hole but a bear.” Great was the surprise and puzzlement of the animals. Each was now anxious to make the test himself and get at the straight truth. The elephant sent them one at a time. First, the cow. She found nothing in the hole but a cow. The tiger found nothing in it but a tiger. The lion found nothing in it but a lion. The leopard found nothing in it but a leopard. The camel found a camel, and nothing more. Then Hathi was wroth, and said he would have the truth, if he had to go and fetch it himself. When he returned, he abused his whole subjectry for liars, and was in an unappeasable fury with the moral and mental blindness of the cat. He said that anybody but a near-sighted fool could see that there was nothing in the hole but an elephant. MORAL, BY THE CAT You can find in a text whatever you bring, if you will stand between it and the mirror of your imagination. You may not see your ears, but they will be there. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Mark Twain (2008). The Mysterious Stranger, and Other Stories. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/3186/pg3186-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

Stories, News & Mentions about BEAUTIFULAI

Beautifulai’s Stories on HackerNoon