Panoptic is the novel Ethereum blockchain-based options trading protocol that is perpetual, oracle-free and offers instant-settlement. Panoptic aims to develop a trustless, permissionless, and composable options product, i.e., to do for decentralized options markets what x*y=k automated market maker protocols did for spot trading. This is made possible by allowing options trading to occur on top of any asset pool in the Uniswap v3 ecosystem without requiring special permissions. Panoptic revolutionizes DeFi options. Join our community: - https://twitter.com/Panoptic_xyz - https://discord.gg/7fE8SN9pRT

Panoptic

panoptic

A holy grail of computer vision is the complete understanding of visual scenes. Progress in perceptual tasks began with the task of identifying what’s in the image, for example, whether there’s a man or not. Next, if there’s a man, we want to know where it is in the image. can draw a bounding box around it or label every pixel, e.g., whether the pixel belongs to a man or not. These tasks are called image classification, object detection, and image segmentation. AI What else can we say about the image? Was the man talking to a friend or running with a ball? To answer this question, AI needs to understand the interactions and relationships between objects in an image. This task is called Scene Graph Generation (SGG). Let’s discover how relationships between objects can be described. Relationships connect two objects. These relationships can be actions (jumping over), spatial (is behind), verbs (wear), prepositions (with), comparative (taller than), or prepositional phrases (drive on). Combining the objects and relationships, we create a directed graph representation (figure below). Objects can be represented by bounding boxes, from object detection, or by masks from panoptic segmentation. But panoptic segmentation has advantages, such as it covers the full scene with background and has better accuracy compared to the coarse bounding boxes. So, gives us a deeper scene understanding. Panoptic Scene Graph Generation (PSG) Understanding scenes would enable important applications such as image search, question answering, and robotic interactions. Although It seems easy for us, there’s a big perception gap between robotic systems and humans. This technology will allow them to do more intellectual work. Now, let’s dive into how this AI looks under the hood. We expect a set of triplets as an output of our neural net. Every triplet consists of two objects and their relationship. Such an output raises a couple of challenges for our network architecture. For example, should we predict all triplets simultaneously or just one by one? Can we solve the task in two stages: first performing object detection, then pairwise relationship prediction between these predicted objects? Or is it better to use a one-stage end-to-end neural net? There are multiple ways to approach this task. Let’s look at a promising one using a Transformer. The transformer has established itself as a surprisingly versatile network. It fits us because by using an attention mechanism, it can understand the relationship between sequential elements that are far from each other. As shown in the figure above, the PSGTR model first extracts image features from a CNN backbone and then feeds the features along with trainable queries and position encoding into a transformer encoder-decoder. Here, we expect the queries to learn the representation of scene graph triplets so that for each triplet query, the object/relationship/object predictions can be extracted by three individual Feed Forward Networks (FFNs), and the segmentation task can be completed by two panoptic heads for both objects, respectively. To train, the model authors created a dataset consisting of object/relationship/object triplets. The model predicts all triplets at once and is trained end-to-end with a set loss function that performs bipartite matching between prediction and ground truth. This is one way an . You can check the paper and code linked below for better understanding. AI understands a scene Reference Yang, Jingkang and Ang, Yi Zhe and Guo, Zujin and Zhou, Kaiyang and Zhang, Wayne and Liu, Ziwei. Panoptic Scene Graph Generation. Code: https://github.com/Jingkang50/OpenPSG Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, Li Fei-Fei. Visual Genome.

How An AI Understands Scenes: Panoptic Scene Graph Generation.

Overview Digital fingerprinting is a technique used to identify users across different websites based on their unique device and browser characteristics. These characteristics - fingerprint parameters, can include various software, hardware (CPU, RAM, GPU, media devices - cameras, mics, speakers), location, time zone, IP, screen size/resolution, browser/OS languages, network, internet provider-related and other attributes. The combination of these parameters creates a unique identifier - fingerprint, that can be used to track a user's online activity. Fingerprints play a crucial role in online security, enabling services to identify and authenticate unique users. They also make it possible for users to trick such systems to stay anonymous online. However, if you can manipulate your fingerprints, you can run tens or hundreds or more different accounts to pretend that they are unique, authentic users. While this may sound cool, it has serious implications as it can make it possible to create an army of bots that can spread spam and fakes all over the internet, potentially resulting in fraudulent actions. Note: Obviously, I won’t discuss here how you can do "bad" things; you must always be careful, stay away from the “dark side,” and avoid committing illegal actions. This article is about the technology behind this, so use the information wisely. This is the first (and maybe not the last) article in this domain, so it will be more like an overview. The content offers an intro to the topic. There are dozens of tools and ways to detect, collect, and spoof fingerprints, and there are many different parameters and technologies that can reveal or hide your real identity or the fact that you're spoofing fingerprints (meaning you're not an authentic user). Parameters in Digital Fingerprints Let's consider some of them, some examples of obvious, simple, or well-known params, some that are rarer, less-know, and difficult to spoof. this string provides information about the user's browser, operating system, and device. User-Agent: it reveals the user's network and geo-location. Services use IP addresses for security and to prevent malicious activities. If you use one account from different IPs or many different accounts from the same IP, some services may view this activity (in combination with other params) as suspicious and use some level of bot protection against you. This can also be triggered if you use IPs that are already used or in some kind of banned list (proxies). IP: Information about installed plugins and extensions can be used to create a unique fingerprint - it helps in identifying users based on their browser's additional functionalities. Browser Plugins and Extensions: different users often have different display characteristics. Screen Resolution and Color Depth: they are important factors in fingerprinting - if you have random values, e.g., Japan timezone Norwegian language this is a bit unusual. Timezone and Language Settings: it involves rendering hidden graphics in the user's browser to gather information about the graphics hardware. Quite a tricky one because if you spoof your hardware info, then you can’t have the proper canvas value - you can’t render it on your different real hardware. Canvas: it exploits the unique capabilities and limitations of the user's graphics hardware in rendering 3D graphics - additional information about the user's device. WebGL Fingerprinting: the list of fonts installed on a user's system can be used as a fingerprinting parameter. This information is accessible through JavaScript. The list of fonts has to be realistic - so e.g. you can’t have Win fonts on macOS or you can’t have just 1 or 2 fonts, this is a very suspicious indicator. Fonts: it allows websites to determine the device's battery level and charging status, the combination of battery attributes can be used for fingerprinting. Battery status API: websites can use the web audio API to generate unique audio fingerprints by analyzing the audio processing characteristics of the device. Audio Fingerprinting: This information includes details about the software and hardware components of the device, such as the graphics card, network adapter, and operating system. This adds to the uniqueness of the fingerprint. Hardware Concurrency: This information includes details about the network connection, such as the IP address, ISP, and DNS server. Network Information: some users may use some software that listens to specific ports which also might be useful for some specific cases. Open and used ports: Navigating the Web incognito Digital fingerprint manipulation is a difficult task that demands a proactive approach to avoid detection. The are lots of strategies and tools to hide your identity (fingerprints) or pretend that you are someone else. Use privacy-focused browsers Opting for privacy-focused browsers, such as Brave, Ghostery, Tor, Octo Browser, or Vivaldi with enhanced privacy settings, provides a fundamental defense against common fingerprinting techniques. These browsers prioritize user privacy and incorporate features designed to hide your real fingerprints, making it harder to track your activities. For example, the Tor Browser, grounded in principles of anonymity, routes internet traffic through the Tor network. This strategic routing obscures the user's identity by bouncing connections through a series of volunteer-operated servers, enhancing overall online anonymity. Browser Extensions Privacy-centric browser extensions, including AdBlock, uBlock Origin, Privacy Badger, or CanvasBlocker, could be active defenses against tracking scripts, cookies, and fingerprinting attempts. These tools operate in the background, protecting and preserving user anonymity. VPN and Proxies The use of VPNs or proxy services adds an additional layer of protection by masking the user's real IPs (location, timezone, language, etc) and encrypting internet traffic. This is not only used to change your fingerprints but also to provide a more anonymous online presence and a higher security level. Motivations behind fingerprint spoofing Understanding the Whys Individuals concerned about personal privacy and the growing digital surveillance often spoof fingerprints to shield themselves from relentless online tracking. Privacy: Spoofing fingerprints prove useful for circumventing geo-restrictions, allowing users to access content restricted to specific regions. VPN and proxy services play a crucial role here by not only hiding the user's identity but also providing access to servers in different geographic locations. Geo-restriction: Avoiding targeted advertising and online profiling serves as a compelling motive for individuals to manipulate their digital fingerprints. Some tools can block 3rd-party tracking scripts and cookies, disrupting the profiling process. Ads: Web scraping, multi-accounting, e-commerce, bounty&airdrop, bonus-hunting, social networks bots, and affiliate marketing are often sources of income or bases for medium businesses. Digital agencies, individuals, and influencers engaged in these activities may require fingerprint spoofing to navigate through complicated bot detection systems. Avoiding detection becomes vital for some services, ensuring that legitimate activities are not mistakenly flagged or restricted (though quite often, such activities and accounts are not really legit but pretend to be so). Some of the most popular tools are Multilogin, X-Browser, Octo Browser, AdsPower, Incogniton, Scrapy, Surfsky, Web Scraper.io, ScrappingBee, etc. Strategic needs in the digital arena, bot detection, and protection systems: Collecting Users' Fingerprints Websites use JS (obviously) to harvest details about users to construct comprehensive digital portraits. This involves probing screen resolution, device orientation, mouse movements, keystroke dynamics, etc. Sophisticated fingerprinting scripts enumerate a wide range of browser and hardware attributes. JavaScript: Persistent cookies and data stored in local storage work to track users across sessions and platforms. Techniques include leveraging browser cookies and storing unique identifiers for user tracking. Depending on your purposes you need to know when you need an "empty" browser with unique fingerprints or when you need to trick a service showing that you have particular cookies and the same fingerprints. Cookies and local storage: The inclusion of 3rd-party scripts for analytics and advertising embeds invisible trackers often used to adjust systems behavior for a specific user based on collected fingerprints. You can use the aforementioned tools and approaches to selectively block or trick such scripts to get the needed behavior. 3rd-party scripts: Understanding Your Online Identity Panopticlick (EFF), Pixelscan, deviceinfo.me, and BrowserLeaks show your browser's fingerprint parameters such as User-Agent, canvas fingerprinting, fonts, etc. These checkers provide insights into the uniqueness and stability of your digital fingerprint across different browsing sessions. Online checkers: they allow users to inspect network requests, cookies, and other fingerprinting parameters, fostering a deeper understanding of their digital imprint and how websites detect bots and unique legit users and collect fingerprints. Examining the Network and Application tabs in browsers provides a real-time view of the data exchanged between the browser, websites, and servers. Browser developer tools: Here are some examples of how you can get some info about users' fingerprints in the browser. GEO: navigator.geolocation.getCurrentPosition(function(position) { var userLocation = position.coords; }); Microphone: navigator.mediaDevices.enumerateDevices() .then(function(devices) { var microphones = devices.filter(device => device.kind === 'audioinput'); }); Camera: navigator.mediaDevices.enumerateDevices() .then(function(devices) { var cameras = devices.filter(device => device.kind === 'videoinput'); }); Speakers: navigator.mediaDevices.enumerateDevices() .then(function(devices) { var speakers = devices.filter(device => device.kind === 'audiooutput'); }); Audio: var audioContext = new (window.AudioContext || window.webkitAudioContext)(); var oscillator = audioContext.createOscillator(); var analyser = audioContext.createAnalyser(); oscillator.connect(analyser); analyser.connect(audioContext.destination); GPU: var canvas = document.createElement('canvas'); var gl = canvas.getContext('webgl') || canvas.getContext('experimental-webgl'); var renderer = gl.getParameter(gl.RENDERER); console.log(renderer); Fonts: var fonts = []; var fontList = document.fonts.forEach(function(font) { fonts.push(font.family); }); console.log(fonts); Canvas (hashing): var canvas = document.createElement('canvas'); var context = canvas.getContext('2d'); var dataURL = canvas.toDataURL(); var canvasHash = MurmurHash3(dataURL); console.log(canvasHash); RAM and CPU: function getCPUInfo() { return navigator.hardwareConcurrency || 0; } function getDeviceMemory() { return navigator.deviceMemory || 0; } var cpuInfo = getCPUInfo(); var deviceMemory = getDeviceMemory(); console.log(`CPU Cores: ${cpuInfo}`); console.log(`Device Memory (GB): ${deviceMemory}`); Bot Detection Systems: Defending Against Automation A couple of examples of such systems: It is a global leader in bot detection and mitigation. It provides a proactive and precise way to verify that legitimate human users are accessing your website, mobile app, and APIs. Distil Networks uses a combination of techniques to detect bots. It studies a range of variables such as cursor movement, click patterns, and web browsing patterns across other websites. It uses , which checks all visitors against hundreds of different characteristics, focusing on their behavior. Distil Networks defends against web scraping, competitive data mining, account takeovers, transaction fraud, unauthorized vulnerability scans, spam, click fraud, denial of service, and API abuse. It can automatically block 99.9% of malicious traffic without impacting legitimate users. It also offers Distil Bot Defense for Web and API, which protect your website and API servers respectively. Distil Networks: Bot Detection: device fingerprints and Are You a Human technology It actively pulls additional data from the browser to identify devices with precision. When a browser request comes in, Distil interrogates the headers to see if the visitor is lying about their identity. This unique identifier can be used to fully or partially identify individual devices even when cookies cannot be read or stored in the browser, the client IP address is hidden, or one switches to another browser on the same device. It uses machine learning to detect biometric patterns in mouse activity and scrolling, as well as looking at browsers, devices, and other factors for clues. It can detect many simple or medium complexity bots that run JS from a web page. Resource Protection: It's a comprehensive cybersecurity platform that integrates fingerprint-based identification to discern legitimate users from potential threats. Utilizing advanced behavioral analysis and anomaly detection, Imperva builds profiles based on a combination of factors, including IP reputation, user-agent, different fingerprint params, and behavioral characteristics. This allows the system to detect suspicious activities indicative of bot traffic and mitigate potential threats effectively. Imperva: It's a prominent content delivery and cloud service provider that incorporates robust bot detection mechanisms within its security offerings. Leveraging a combination of fingerprint-based detection, behavior analysis, and machine learning, Akamai identifies and mitigates various bots. Akamai's global network allows for real-time threat intelligence, enabling proactive defense against evolving bot tactics. Akamai: It's a widely used content delivery network and security service that employs a multifaceted approach to bot detection. Cloudflare distinguishes between human users and bots by analyzing parameters such as IP reputation, user-agent characteristics, and behavioral patterns. The platform also utilizes threat intelligence and community-driven insights to stay ahead in the battle against emerging bot threats. Cloudflare uses to profile SSL/TLS clients and block potential bot requests. It also uses to apply rules and route traffic based on HTTP request information. is used to identify specific files and prevent data loss. These techniques help in detecting not real users. Cloudflare: JA3 Fingerprinting HTTP Filtering Data Fingerprinting Role of Bot Detection Systems: They play a pivotal role in enhancing bot detection capabilities. With servers strategically positioned around the globe, they can leverage geographical insights and real-time threat intelligence to identify and mitigate bot traffic effectively. The platform's WAF and bot managers contribute to a comprehensive defense against automated "users.” In this ongoing cat-and-mouse game, Bot Detection Systems continue to evolve, leveraging advanced technologies to stay ahead of fingerprint spoofing tech. The collaboration between security providers, businesses, and the wider online community remains crucial in defense against the tactics of automated threats but also, in a way, used against users' privacy, anonymity, and experience online, bringing intrusive ads and sophisticated user tracking tools that are only beneficial for businesses not for users. However, privacy protection, fingerprint hiding and spoofing, and ads and trackers blocking tools are also developing to evade even the most sophisticated user tracking systems. Websites' additional verification steps If a fingerprint appears suspicious, such as frequent changes or unusual combinations of data points, the website may trigger additional verification steps. Suspicious behavior: Websites may present users with captcha challenges to verify their identity. This involves solving puzzles or identifying distorted text, tasks that are difficult to perform for primitive bots. Captcha: Websites may request users to verify their mobile phone numbers to establish a stronger connection between a unique identity and a real-world entity. This can help prevent fraudulent activities. Mobile verification: the idea is the same as with mobile phones, but you need to submit your ID ID verification: Examples: Google doesn't require additional verification for new users with clear, consistent fingerprints. If a user's fingerprint changes frequently or resembles those used by known bots (or just already known for Google), Google may ask for a mobile phone number or ask to deal with a captcha. Financial websites often enforce stricter verification measures due to the sensitive nature of transactions. They may require users to provide additional personal information, verify their identity through secure channels, or pass more complex captcha challenges. Opinion: spoofing is better than hiding Hiding fingerprints can enhance privacy, security, and online anonymity, but spoofing them to appear as a unique, legitimate user offers even greater advantages. By blending in with the crowd and avoiding suspicion from systems that detect anti-detection tools, you can maintain credibility and trust. This approach allows you to enjoy the benefits of being perceived as a unique, legitimate user, minimizing the chance of facing additional protecting measures or obstacles. and, obviously, it helps in preventing leaking of your real data and identity. Also published . here

Intro to Digital Fingerprints: Understanding, Manipulating, and Defending Against Online Tracking

ডিজিটাল ফিঙ্গারপ্রিন্টের ভূমিকা: অনলাইন ট্র্যাকিংয়ের বিরুদ্ধে বোঝা, ম্যানিপুলেট এবং ডিফেন্ডিং

Einführung in digitale Fingerabdrücke: Online-Tracking verstehen, manipulieren und sich dagegen wehren

Introducción a las huellas digitales: comprensión, manipulación y defensa contra el seguimiento en línea

Introduction aux empreintes digitales : comprendre, manipuler et se défendre contre le suivi en ligne

डिजिटल फ़िंगरप्रिंट का परिचय: ऑनलाइन ट्रैकिंग को समझना, हेरफेर करना और उसके विरुद्ध बचाव करना

デジタル指紋の概要: オンライン追跡の理解、操作、および防御

디지털 지문 소개: 온라인 추적에 대한 이해, 조작 및 방어

Introdução às impressões digitais: compreensão, manipulação e defesa contra rastreamento on-line

Введение в цифровые отпечатки пальцев: понимание, манипулирование и защита от онлайн-слежения

Dijital Parmak İzlerine Giriş: Çevrimiçi Takibi Anlamak, Yönetmek ve Savunmak

Giới thiệu về Dấu vân tay kỹ thuật số: Hiểu, thao tác và bảo vệ chống lại việc theo dõi trực tuyến

数字指纹简介：理解、操纵和防御在线跟踪

Hi, all! Here is my weekly email discussing mental models, performance, business, and entrepreneurship. If you love this content (please share it), but also… Check out my , connect with me on / , and read my Podcast YouTube Twitter daily newsletter. What’s in today’s newsletter? We now enjoy the most health, freedom, and opportunities in human history - standing on the shoulders of inventors and pioneers who sacrificed to expand potential. But too many people waste this unprecedented access to tools for fulfillment by chasing distraction and pleasure while avoiding reality and responsibility. It's ironic how much progress surrounds us externally, yet how stagnant most individuals are in taking the initiative to actually seize it. Entitlement has bred widespread complacency. We must shake off victim mindsets full of excuses. Progress depends on personal accountability. Inheriting progress means accepting responsibility to compound it. Seize the generosity of past generations as fuel for your own creation. Transform excuses into action. Lift all rising tides through your differentiated efforts right now. The heaviest weight is unfulfilled potential despite an unprecedented opportunity explosion. Fortify resolve beyond comfortable circumstances handed to you. Don't take generational privilege for granted - use it as a foundation for your own progress. “We are living at the peak of human civilization.” I know that sounds hyperbolic. But consider this objectively. You stand now at the highest vantage point in the history of mankind when it comes to opportunity, technology, wisdom, and quality of life. In 75 years, we went from prop planes to commercial space flight. From news communicated by post to video calls on handheld devices transmitted by satellites in space. You can access virtually all cumulative knowledge known to humans in seconds from something in your pocket. Translate between languages instantly via AI. Map travel to remote villages Google hasn’t even photographed yet. But here’s the shocking part most haven’t realized... Despite all this exponential progress around us, most individuals fail to hold themselves to the standards such advancements make possible when it comes to actualizing our potential. We life spanned through a renaissance period that unlocked orders of magnitude more opportunity, tools, and information to enhance performance, well-being, and success... Yet, most trade this inheritance for distraction and limitation. Why Do We Squander Our Potential Despite Having Every Advantage? Make no mistake, you stand at the mountaintop when it comes to opportunity. But most come nowhere near achieving what is newly possible in their lifetime when it comes to fulfillment, human performance, and leaving a legacy. There is an alarming chasm between the acceleration of external potential... And lack of internal initiation to seize it. We’re living through discoveries and technological leaps our ancestors couldn’t even conceptualize. Yet, most use these for distraction and entertainment versus deliberate enhancement. For example, learning mastery was always a privilege of the well-connected or exceptionally motivated self-starter. To be a for most pursuits required intense commitment bordering on obsession. “student of the game” Now, you can access Ivy League-level curriculum from home on nutrition, fitness, finances, starting a business, languages, and more for free or extremely affordable. Yet, how many leverage this privileged panopticon of education handed to them? The mere abundance of opportunity actually has the inverse effect. It creates anxiety. The paradox of choice kicks in. They feel overwhelmed by open doors and unsure which path aligns with innate talents or burns with authentic passion and zeal. We know exponentially more about performance, psychology, wellbeing, and success than prior generations too. But we rarely apply this diligently to transcend the excuses that are holding us back. The pioneer heart still lies dormant within despite overwhelmingly favorable conditions for bold new frontiers. The perfect analogy: you’re standing in a forest, amongst massive Redwoods. You can’t help but be memorized by their grandeur, but you can’t bring yourself to plant a seed yourself. So Why This Tragic Gap Between Peak Potential and Performance? In one word? Entitlement. Entitlement manifests when we inherit reward without risk. Have privileges dropped in our lap without paying dues. Act entitled to outcomes without earned merit. The hallmark of entitled mindsets is desiring results now without requisite work beforehand. A gross sense of entitlement stems from the unusual situation we find ourselves in... We’re thrust into an environment drastically different than what our recent ancestors faced. Like time travelers, we skipped hundreds of incremental steps. We opened our eyes to a life wildly transformed by technology and innovation created before we were even born. Handed gadgets, tools, and abundances like magic. Yet, without direct experience progressively earned through each rung ourselves from the bottom up. We didn’t slowly acclimate across generations to appreciate or have a reference for how good we have it. We just stepped into this future now and accepted it as normal. Numbing ourselves to the heights we stand atop. When you don’t earn through your own blood, sweat, and tears — forced to find opportunity where little exists — you don’t fully respect the competitive advantage and possibilities at your fingertips today. Like trust fund kids aimlessly drifting through privilege not grounded by reality. Without scarcity as a sharp contrast, we lose sight of how overwhelmingly abundant life is now for those taking initiative. We gaze into the infinite realm of potential yet focus only on what remains out of reach still versus claiming all within grasp already. Innovation Alone Doesn’t Elevate Individually Make no mistake, access alone means little without action. Books on the shelf don’t transform until read and applied diligently. Courses mean nothing if never finished. Accountability partners lose their leverage when you stop showing up. As Morpheus reminded... “There is a difference between knowing the path, and walking the path.” Don’t pat yourself on the back simply for discovering life-changing wisdom not utilized. It remains inert potential energy at best. Only through courageous initiation do we embody new standards what expanded possibility now allows for. Step fully through the doorway from old limitations into frontiers before off-limits. Otherwise, we cash our inheritance early for distraction instead of investing and compounding gains. We celebrate progress but don’t individually push progress. Squandering our unprecedented opportunity ultimately just increases disempowerment and entitlement. Until we regress despite external progress lifting most boats. As Viktor Frankl said... “Ultimately man should not ask what the meaning of his life is, but rather realize it is he who is asked. In a word, each man is questioned by life; and he can only answer to life by answering for his own life; to life he can only respond by being responsible.” The path is paved, and tools are available to actualize your best life. But it demands responsibility. Owning our personal progression versus making excuses. Amor Fati — loving your fate — regardless of where you start. Seizing opportunity despite disadvantage. Forging your capability despite circumstance. Excuses or Action. Constraint or Creation. You choose daily. Mindset Determines Outcomes Over Environment Here’s an uncomfortable truth most deny... Your external conditions don’t determine outcomes nearly as much as initiative, mindset, psychology, and choices. Environment influences but doesn’t override individual responsibility. Regardless of noise that’s not within control, own what is, with extreme prejudice. This is called displacement theory — where we overfactor context and underappreciate personal accountability. Consider two examples that illustrate the immense leverage of mindset over environment: Immigrants frequently outperform their native peers in academics, income, and home ownership. Despite less access to resources, networks, or cultural familiarity when they start over, many immigrants radically thrive through bottom-up hustle. Conversely, lottery winners ending up worse financially years later is a documented phenomenon. Through entitlement without maturity, they squander windfalls despite luck removing obstacles for them. Or another example... Children of wealthy parents earning trust funds underperform self-made peers substantially, despite infinite safety nets allowing risk and failure. They substitute privilege for individual will and work ethic. Yet, those climbing from nothing showcase immense ambition regardless of environmental factors trying to limit belief in potential outcomes. The Championship Mindset In An Era Of Participation Awards Maybe these realities make you uncomfortable. Good. They are. We want to believe factors out of our control determine destinies. It absolves responsibility to take inventory of decisions and habits within influence that drive outcomes. Blaming society, injustice, or circumstance is easier than reflecting on the dicey notion “If I transformed my psychology and made better choices, I could radically change my results.” But let’s pause here. The goal isn’t condemnation over what have been done or guilt for past approaches. “should” The purpose is illumination, so we pivot forward empowered by truth. Awareness spurs change, not judgment. Transform excuses into energy toward your next phase of actualized potential. Forge opportunity by expanding the possibility of what you believe can be done despite constraints trying to convince you otherwise. Musashi called this having a “championship mindset.” Winners in any domain — sports, art, business, spirituality, relationships — build identity narratives that cut through obstacles in their heads first before ever seeing them manifest physically. Mental fortitude precedes external manifestation. Jelly insides show up as weak results regardless of your potential. Champions hold an almost delusional-level conviction in what they can accomplish if they strategically apply themselves over enough time. They embody the identity of excellence, domination, and impact so completely that it etches their physiology. Confidence is their baseline, not an aspirational boost needing external validation. This unstoppable mindset fuels consistent action towards audacious goals despite hurdles or timelines seeming unreasonable to rest. Great ones know external wins start within long before visible to the outside world. Cultivating sheer efficacy and willpower to turn dreams into plans and then plans into progress. They hold themselves to higher standards constantly. Making incremental improvement daily until the plateau of potential reached elevates baseline. Knowing marginal gains compound over time. This mentality separates those who squander natural talents that the rest wish they had...from those with championship vision who maximize every drop of human potential possessed. Who will you become? Identity drives reality. Claim Your Modern Birthright Manifesting potential starts by taking complete ownership of precious opportunity within your grasp right now. Birthright means an inheritance you’re entitled to by birth. Financial security, status, and assets family members pass down. I challenge you to view the situation you were born into more expansively. Your ancestor just two generations ago likely: Performed backbreaking labor from sunrise to sundown Had health issues we resolve easily today Had way less economic opportunity without global mobility and the internet Access to maybe a few books their whole life in rural areas Die by 60 years old from now preventable causes Just since 1990... Automation replaced 50% of tedious and dangerous jobs Healthcare innovation increased life expectancy over a decade The Internet created millions of economic opportunities Education went from privilege of few to accessible for all Extreme global poverty dropped by 50% The point is you won the cosmic lottery simply by being born in this time and place in history. So before complaining about limitations, perhaps compassionately reflect on how much circumstance-defying potential surrounds you here and now... Then courageously claim it. Sacrifice excuses for initiative. Accept abundance over entitlement. Double down on excellence and accountability. Living through these rare times is a modern birthright. But Destiny's true inheritance must be claimed with both hands despite endless distractions tempting complacency. Compounding This Windfall Part of maturity means realizing you don’t deserve anything simply because you exist. Universal energy rewards those taking responsibility. Actualizing your full potential involves stewarding ALL inheritances — money, knowledge, tools, relationships, inspiration — handed down to responsibly create MORE value as you climb the hierarchy of goals. Think back to stories like the Jesus told. A master going on a journey entrusts servants with bags of gold. In return, two invested and compounded the money. But one simply preserved the original inheritance, digging a hole to hide it without attempting to increase it. “Parable of the Talents” The message is clear: To those faithfully stewarding opportunity: “Well done! You have been trustworthy with small things, I will now give you much more.” But to the servant burying their potential: “You wicked and lazy servant! Take the gold from him and give it to the man enterprising increase.” So think back… Who worked diligently starting with little versus who squandered opportunity? Who multiplied gains versus who generated entitlement? Who owned the identity of excellence versus excuses? Compare where you started to possibilities before you now thanks to external progress. Have you compounded personal capability at an equal rate? Or stagnated in complacent entitlement enjoyed as a birthright? Awaken The Modern Pioneer Spirit Beyond holding yourself to higher standards, adopt the heart and spirit of past pioneers who settled frontiers. The pioneer journeys not for glory itself but so their grandchildren may have opportunities they never dreamed of. Sacrifice in the short term to build foundations for the betterment of future generations. Plant trees under whose shade you may never sit. But know they allow the fruits of your labor to be enjoyed for decades beyond your short, fleeting lifespan. This pioneer spirit is precisely what built the privileged conditions we enjoy but take for granted today. We forget the backs broken with labor and risk so we could have comfort and safety to unlock our creativity. Standing on the shoulders of giants, how will we lift the next wave still higher? The Modern Pioneer Rises What frontiers — physical, spiritual, scientific, personal — will you charge courageously into despite unknowns and fears holding most peers paralyzed? How can we hold ourselves to elevated expectations equal to the abundant privileges we inherited? Where can you multiply opportunity before passing the baton to youth who will one day stand exactly where you stand now? Progress depends on pioneers scraping trails where none exist yet. To blaze so others may follow. To settle where most only daydream of. To actualize imaginary places into inhabitable spaces. You now have guides, tools, and abundance allowing manifestation beyond the wildest dreams of ancestors just decades ago. Much gifted to start farther than they ever imagined. But the modern pioneer can’t rest on generational privilege alone. They must charge forward to meet the future. Create so their young may build upon foundations in place. Ignite sparks today so flames illuminate unforeseen horizons tomorrow. The Bravest Act of Our Times Perhaps this whole discussion seems irrelevant. But I assure you, truly embracing even a fraction of the exponential change swirling around us requires courage and foresight seen only at pivotal transitions in human history. Our complacency and distraction are simply conditioned comfort against risking the unknown frontier. Preference for slow deaths of boredom and limitation over daring greatly into undiscovered possibility. But you can’t selectively inherit the privilege of progress without also accepting responsibility to steward this momentum. Enjoying luxury without risking further elevation is not honorable. Progress depends on pioneers in every generation putting their shoulders to the wheel. To push exponential technology, innovation, and thought even higher. Standing on shoulders while lifting still taller. The bravest act in our times is acknowledging frankly the heights we now stand atop... legacy capital accumulated... gifts and knowledge solemnly passed down to us. Then courageously planting flags further. For not even the sky need be the limit anymore. The Summit Still Beckons Perhaps this brings more questions than concrete steps. It would make sense to feel overwhelmed realizing the progress civilization has made. Opportunities now exist beyond anything known for thousands of generations before. You may also feel anxious realizing you haven’t taken full advantage of what currently surrounds you. Instead, you’ve taken for granted the progress and inventions created by past generations who made this moment possible. That’s completely understandable. The first step is to gain perspective - to accurately see where we are thanks to those who came before us. Consider feeling grateful for the progress made by ancestors you now benefit from. Appreciation carries no judgment, only responsibility. We honor past generations by continuing the march of progress. Their innovations enable us; now, we must execute ourselves and pave the way for those to come. If you enjoyed this article, I’d love to hear from you. Email me at scott@scottdclary.com or at me and I’ll do my best to get back to everyone! tweet , @ScottDClary Also published here

We're Living in the Greatest Time in History (Yet Most Squander It)

আমরা ইতিহাসের সর্বশ্রেষ্ঠ সময়ে বাস করছি (তবুও এটি সবচেয়ে বেশি নষ্ট করে)

Wir leben in der großartigsten Zeit der Geschichte (und doch verschwenden die meisten sie)

Estamos viviendo el mejor momento de la historia (aunque la mayoría lo desperdicia)

Nous vivons la plus grande époque de l’histoire (et pourtant, la plupart la gaspillent)

हम इतिहास के सबसे महानतम समय में रह रहे हैं (फिर भी सबसे अधिक इसे बर्बाद कर रहे हैं)

私たちは歴史上最も素晴らしい時代に生きています（しかし、最も多くの人がそれを浪費しています）

우리는 역사상 가장 위대한 시대에 살고 있습니다(그러나 대부분은 그것을 낭비하고 있습니다)

Estamos vivendo o melhor momento da história (ainda que a maioria o desperdice)

Мы живем в величайшее время в истории (однако большинство его растрачивают)

Tarihin En Harika Zamanını Yaşıyoruz (Fakat Çoğu Kişi Bunu İsraf Ediyor)

Chúng ta đang sống trong thời đại vĩ đại nhất trong lịch sử (Tuy nhiên, hầu hết đều lãng phí nó)

我们生活在历史上最伟大的时代（但也是最浪费的时代）

Craig Wright And The Bitcoin Supercomputer Fraud

Let's learn about via these 33 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Smart Cities /Learn Repo 1. How Smart are our Homes Getting? Smart spaces will become an essential part of our lives, he says. Smart homes are changing our lives in the same way as wearable devices. 2. Micro Electric Vehicles and their Massive Advantages Over Standard EVs Companies around the world are developing smaller, more efficient electric cars that provide solutions to growing concerns within the standard EV market. 3. Smart Trains: A Long Journey to Transportation Revolution Smart cars might be the future, but what about high-speed smart trains? 4. 5 Reasons Our Cities Are Not Full of Autonomously Flying Drones (Yet!) We are slowly but surely moving towards a world where autonomous drones will play a major role. In this article, I will show you what stopes them today. 5. Building a Smart City with Smart Transportation Systems To achieve the smart cities of the future, government officials need to develop smart infrastructure to increase road and passenger safety. 6. 5 Intriguing Applications of Computer Vision in Smart Cities Computer vision will radically change smart technology. Here are five ways it's already impacting smart cities. 7. How Technology Can Help Make Sustainable Cities As the global population continues to grow exponentially, the number of people living in urban areas is growing the fastest. With over 50% of the world’s population currently living in major cities, and an anticipated 2.4 billion more over the next 30 years, the term ‘megacity’ has been created to describe the urban metropolises of the future. 8. We Will Soon Enter the 5G Revolution Since 2009, 4G has been an essential technology in our hyperconnected world, enabling our handsets to consume and produce multimedia, browse the majority of internet web sites, and run awesome apps. But these features have been evolving towards more and more data consumption rates, because hardware resources like CPU, memory and screens allowed them to process large amounts of data. 9. Smart Cities Raise Data Privacy Concerns Should you be excited about smart cities or concerned about your privacy and data? I go through three of the ten privacy principles (PIPEDA) and their effects. 10. Using IoT to Solve Housing Problems and Improve Safety IoT can help manage air quality and emissions at industrial sites, improve control over electricity, water, and heat meters, and more. 11. What AI Advancements Will Mean for Our Daily Lives in 2021 AI arguably dates to the 1950s when Alan Turning invented the Turing Test. This was essentially a machine that could think for itself. Fast forward 70 years and if sci-fi thrillers made throughout the years are anything to go by, the world is overrun by robots and human beings are now servants to the machined man. 12. Are Smart Cities a Threat to Data Privacy? For smart cities to function, they must collect data. But is that good for citizens? Is true data privacy achievable for smart cities? 13. The Automotive Industry Continues to Widen its Connectivity The Future Is Now 14. AI-enabled Smart Cities: What to Get Right Data is the foundation of smart cities. However, to deliver the right solutions, planners must establish sustainable data and AI technology policies. 15. How Are Smart Cities Made 'Smart': Top 6 Enabling Technologies The ultimate goal of smart cities is to improve citizens’ quality of life, reduce the cost of living and attain a sustainable environment through technology. 16. Eco-Big Data Applications in the City: Cleaning Up with IoT and ML Digitalization is possible not only in enterprises. Digital transformation is catching up even with cities to make them more convenient for residents and less harmful to the planet. How to quickly monitor garbage cans, the state of forest parks, cycling and air purity with the help of big data, machine learning and the Internet of things? 17. The 23rd Century: Enter the Smart City While it is easy to visualize a smartphone, a smart TV, or even a smart car — the quintessential 23rd Century smart city might largely elicit confusion from the public. 18. How to Determine the Relative Smartness Level of a City To determine the relative smartness level of a city, there are several indicators that have been defined to arrive as such a number. These indicators, among many others, are: 19. Is "Society 5.0" Supplementing AI as Technology's Latest and Greatest Snake Oil? Photo Credit, Jeremy Weate 20. How Local Governments are Future-Proofing their Urban Centres with Blockchain Technology Nearly two thirds of the global population are city-dwellers. Urbanization, whilst generally associated with increased standards of living, better job opportunities, and access to critical services like healthcare, is intertwined with rapid industrialization, which puts tremendous pressure on environmental resources. 21. How IoT Technology Helps Cities to Focus on People As cities are concentrating the largest part of the world’s population, they face challenges that have never existed before. Evolution of smart cities from basic infrastructure elements to a comfortable urban ecosystem supports citizens throughout their lives and raises new concerns. 22. Is AI the Best Solution for Crowd Management? We increasingly use technology for a broad variety of purposes. One new purpose has been to manage crowds in crowded events to streamline the experience. 23. The Birth of a New Niche — Smart Cities By 2050, 66% of the world’s inhabitants will live in cities. Rapid urbanization entails global challenges, such as air pollution, power shortages, clean drinking water, and overpopulation. The demand from cities for technological solutions to these problems now makes up a global market of $1.5 trillion in value. 24. Understanding Usage Control in Smart Cities: Smart Health Use Case Usage control provides fine grained access to data and resources through restricting access to smart health resources. 25. Life in Smart Cities: Your Walk in the Park isn't Private Anymore Access control ensures authorized access to the city's municipalities, which is critical for ensuring the security of smart cities. 26. How Swarm Intelligence-Powered Vehicles and Smart Cities can Help Streamline Traffic Given the advent of autonomous cars and their growing penetration in the transportation market, it is empirical that companies consider using Swarm Intelligence to tackle traffic and make the daily commute a lot more pleasant for billions around the world. 27. Building Robots for Smarter Cities: How the Manufacturing Process is Everything Hardware is seeing a resurgence and exponential innovation similar to the software boom a decade ago. And as a robotic delivery company founded in 2017, we have been navigating the manufacturing world and hardware revolution, picking up product design and smart tips along the way. [28. Edge Computing Is So Fun - Part 2: The Future  Begins with The Road Side Unit](https://hackernoon.com/edge-computing-is-so-fun-part-2-the-future-begins-with-the-road-side-unit-4ls3wrp) This is the second in a series of articles on edge computing, delving into the infrastructure of outdoor edge computing, the emergence of the Roadside Unit as a common building block, a real-life example of the Roadside Unit, and the way forward. 29. Digital Dystopia as a Panopticon Model of Society Much has been written about the mechanisms of social control that have appeared in China since 2010. And especially many publications are devoted to the emerging system of social credit, which will allow monitoring and regulate the behavior of citizens, which later transforms into a system of social rating. 30. Understanding Data Usage Control in a Smart City Learn how data usage can be controlled in smart cities? 31. Art + Science + Scripture = Bible Math This science/scripture/art article known as Bible Math came about in a most-riveting, creative, and spiritual way. For over two decades, I have been leading weekly Bible Discussion Groups and studying the Bible with people on an individual mentoring level. In the course of these spiritual adventures, as part of the City of Angels International Christian Church, I am typically delighted to share the gospel with all who are willing to listen and put the word of God into practice. Such delight is especially true of the following mathematics-focused Bible study. [32. Edge Computing Is So Fun Part 3: Help Save The Planet With Smart Cities](https://hackernoon.com/edge-computing-is-so-fun-part-3-help-save-the-planet-with-smart-cities-n5143e85) Figure 1. Singapore was ranked №1 on the Institute for Management Development’s 2020 Smart City Index Report. Credit: International Case Studies of Smart Cities 33. Why SigFox is Not a Good Option for Connected Street-Lighting SigFox has notable data size limitations; while it can be good for several IoT applications, it limits the smart street lighting E2E capabilities. Thank you for checking out the 33 most read stories about Smart Cities on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

33 Stories To Learn About Smart Cities

76 Stories To Learn About China

206 Stories To Learn About Digital Transformation

Let's learn about via these 79 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Youtubers /Learn Repo 1. The State of AI in 2022: An End-of-Year Recap of the Machine Learning Industry An 8-minute AI rewind with results and limitations of all the hottest AI models shared in 2022! 2. An Interview with Quadruple Kaggle Grandmaster Chris Deotte from NVIDIA In this episode, I interview Chris Deotte, one of the very few Kaggle quadruple grandmasters. 3. How to Enable Autocomplete (and AI) in your Terminal Here's how I enhance my terminal with autocomplete and Artificial Intelligence 4. GPT-4 Explained: ChatGPT's Big Brother is Here to Disrupt Everything If you thought ChatGPT was good, just wait until you try GPT-4. 5. 5 Docker Desktop Alternatives For Windows and macOS users, Docker Desktop has been the main way to use Docker containers for many years. But how about now? 6. #FoundersConnect: Interview with Hanu Agbodje, the Founder and the CEO of Patricia In this episode, Peace Itimi interviews Hanu Agbodje, CEO of Patricia, on his journey as a tech entrepreneur and 7. Making the Case for Why React Native is Garbage Ex-Google/ex-Facebook TechLead presents the case against the React Native cross-platform mobile app framework.  Join my interview training prep here http://techinterviewpro.com/ 8. 8 BEST Crypto Wallets for Beginners If there’s one thing that every crypto investor needs to have, it’s a crypto wallet. There are all kinds of different crypto wallets you can use. 9. The New AI Model Lets You Generate Music via Text Prompt We recently covered a model able to imitate someone’s voice called VALL-E. Let’s jump a step further in the creative direction with this new AI called MusicLM. MusicLM allows you to generate music from a text description. 10. 6 Common Monetization Problems for Creators on YouTube If you are a video creator looking for ways to make your videos work hard, you are not wrong in worrying about Youtube monetization issues. Read on to know the how-tos and what-nots of monetizing your videos. 11. Top 10 Computer Vision Papers of 2020 This is a video of the 10 most interesting research papers on computer vision in 2020. 12. Google's PaLM-E (AI Robot) Can See and Understand Language Google's latest publication, PaLM-E, is an embodied multimodal language model. 13. OBS for Dummies : How to Record Your Screen Wait... OBS..I have heard it somewhere. 14. Top 8 Machine Learning Content Creators on YouTube Here are the top Machine Learning content creators on YouTube to follow for tutorials, deep learning, and more. 15. 'Why I don't eat out at restaurants, even as a millionaire' - TechLead Ex-Google Tech Lead reveals the secret to why he doesn't enjoy eating out at restaurants, even as a multi-millionaire. 16. How to Get Started Streaming on Twitch Twitch is a great place to learn in public. I'll cover tools, tips, and workflows to help you get started with streaming. 17. How to Turn Mockups Into Videos Instantly with This New AI Model GEN-1 is able to take a video and apply a completely different style onto it, just like that… 18. 5 Gaming YouTubers That are Worth a Sub There are far too many people sharing their opinions about gaming on the internet but not all of them are for us. These are some people who we enjoy the most. 19. Even Disney is Investing in AI: A Look at Face Re-Aging for Visual Effects Whether it be for fun in a Snapchat filter, for a movie, or even to remove a few riddles, we all have a utility in mind for being able to change our age in a picture. 20. 6 Vlogging Tips For Business Success in 2020 Vlogging has taken the world by storm in recent years. It's just a way of blogging, using videos instead of text to reach out, create an audience, and share information. 21. 5 Gaming YouTubers That are Worth a Sub There are far too many people sharing their opinions about gaming on the internet but not all of them are for us. These are some people who we enjoy the most. 22. Youtube Deletes Video About Bitcoin: Is This a Common Trend? You would think that Youtube would at least wait till the holidays are over to hit its creators with this news but apparently, bitcoin and all cryptocurrency talk is now concrete himself and a danger to society. A lot of YouTube creators woke up to find many of their crypto-related videos taken down because youtube sees them as violating their guidelines. 23. How to Use GitHub Copilot with Your Voice “Hey, GitHub” comes in the form of a VSCode extension and has many more capabilities accessible with your voice. 24. How to Ace ML Interviews: Get Your Foot in the AI Door An interview with the Director of Perception at Zoox, Ruijie (RJ) He, with the goal of demystifying what is a good profile to get an ML engineer job and perform 25. 3D Articulated Shape Reconstruction from Videos With LASR, you can generate 3D models of humans or animals moving using only a short video as input. 26. How to Set Up Aleph.im Virtual Machines Nearing the end of 2021, most blockchain dApps still have large parts of their stack that are centralized. With Aleph VMs, you can decentralize the rest. 27. Let’s Play Ethermore: Part 1 – Exploring The Ruins of Nio Cegod Ethermore's first-ever let’s play video is being used to showcase a possible new feature: AI-generated synthetic audio narration. 28. 5 Ways to Get More Likes on Your YouTube Videos Business owners and marketers around the globe know that YouTube is one of the best places to connect with their target audience. 29. The Facebook TransCoder Explained: Converting Coding Languages with AI This new model converts code from a programming language to another without any supervision! 30. The Best AI Articles of October 2022 Support vector machines, decision trees, and AI-generated content are some of the topics in the best AI articles of October. 31. ChatGPT Explained in 5 Minutes ChatGPT has taken over Twitter and pretty much the whole internet, thanks to its power and the meme potential it provides. 32. 5 Strategies To Grow Your YouTube Channel YouTube is the most popular online video platform as of now. Over hundreds of hours of content is uploaded every minute on this platform, and on average, the viewership crosses billions of hours every day. 33. YouTube Fake Crypto Giveaways Explained - Behind The Account Hacks Maybe you have noticed that there is a lot of fake Binance, Ethereum, Ripple and Bitcoin Cash streams on Youtube lately. The crazy part is that those live streams are on a big accounts with thousands of subscribers. 34. 8 Tools Every Data Scientists Should Use The most useful tools I use daily as a research scientist for finding and reading AI research papers 35. OpenAI's New Code Generator: GitHub Copilot (and Codex) You’ve probably heard of the recent Copilot tool by GitHub, which generates code for you. Find out how OpenAI's AI generates code from words 36. Introducing DALL·E: Inspired by GPT-3 and Image-GPT from OpenAI DALL-E from Open AI can generate images from text captions. It is very similar to GPT-3 and Image GPT and produces amazing results. 37. How to Optimize a YouTube Channel: 15 Effective Tips Competing on YouTube isn’t an easy task. Here are 15 effective ways to optimize your channel. Follow these ways to optimize now. 38. PSG is a New Task for AIs Requiring Higher Levels of Understanding Panoptic scene graph generation, or PSG, is a new problem task aiming to generate a more comprehensive graph representation of an image or scene based on panoptic segmentation rather than bounding boxes. It can be used to understand images and generate sentences describing what's happening. This may be the most challenging task for an AI! Learn more in the video... 39. Will Transformers Replace CNNs in Computer Vision? This video explains how transformer architecture can be applied to computer vision with a new paper called the Swin Transformer. 40. Galactica is an AI Model Trained on 120 Billion Parameters On November 15th, MetaAI and Papers with Code announced the release of Galactica, a game-changer, open-source large language model trained on scientific knowledge with 120 billion parameters. 41. DALL·E 2 Pre-Training Mitigations You’ve all seen amazing-looking images like these, entirely generated by an artificial intelligence model. I covered multiple approaches on my channel, like Craiyon, Imagen, and the most well-known, Dall-e 2.Most people want to try them and generate images from random prompts, but the majority of these models aren’t open-source, which means we, regular people like us, cannot use them freely. Why? This is what we will dive into in this video... 42. This AI Can Separate Speech, Music and Sound Effects from Movie Soundtracks Have you ever tuned in to a video or a TV show and the actors were completely inaudible, or the music was way too loud? Well, this problem, also called the cocktail party problem, may never happen again. Mitsubishi and Indiana University just published a new model as well as a new dataset tackling this task of identifying the right soundtrack. For example, if we take the same audio clip we just ran with the music way too loud, you can simply turn up or down the audio track you want to give more importance to the speech than the music. 43. Meta's Groundbreaking AI Film Maker: Make-A-Scene Meta AI’s new model make-a-video is out and in a single sentence: it generates videos from text. It’s not only able to generate videos, but it’s also the new state-of-the-art method, producing higher quality and more coherent videos than ever before! 44. How YouTubers Can Improve Their Marketing Strategies in 2021 2020 with its lockdown affected both video creation and consumption, and that resulted in new rules in video marketing. 45. How to Spot a DeepFake in 2021 How to Spot a Deep Fake in 2021. Breakthrough US Army technology using artificial intelligence to find deepfakes. 46. What is the InfiniteNature-Zero AI Model? This AI generates infinite new frames as if you would be flying into your image! 47. Efficient NeRFs for Real-Time Portrait Synthesis (RAD-NeRF) We’ve heard of deepfakes, we’ve heard of NeRFs, and we’ve seen these kinds of applications allowing you to recreate someone’s face and pretty much make him say whatever you want. 48. DeOldify can Colorize your Black & White Photos with Full Photorealistic Renders DeOldify is a technique to colorize and restore old black and white images or even film footage. It was developed by Jason Antic. 49. OpenAI’s DALL·E: Text-to-Image Generation Explained OpenAI just released the paper explaining how DALL-E works! It is called "Zero-Shot Text-to-Image Generation". 50. How to Talk to ChatGPT: An Intro to Prompt Engineering Prompting is pretty much the only skill you now require to be a master of these new large and powerful generative models such as ChatGPT. 51. This AI Prevents Bad Hair Days This AI can transfer your hair to see how it would look like before committing to the change. 52. VOGUE by Google, MIT, and UW: The AI-Powered Online Fitting Room Google used a modified StyleGAN2 architecture to create an online fitting room where you can automatically try-on any pants or shirts you want using only an ima 53. How Uber Uses AI to Improve Deliveries How can Uber deliver food and always arrive on time or a few minutes before? How do they match riders to drivers so that you can find a Uber? All that while also managing all the drivers?! always 54. How to Create Realistic Slow Motion Videos With AI TimeLens can understand the movement of the particles in-between the frames of a video to reconstruct what really happened at a speed even our eyes cannot see. 55. Text Embedding Explained: How AI Understands Words Large language models are a specific type of machine learning-based algorithm that understand and can generate language 56. How to Create Realistic Slow Motion Videos With AI TimeLens can understand the movement of the particles in-between the frames of a video to reconstruct what really happened at a speed even our eyes cannot see. 57. How Apple Recognizes People in Private Photos via Machine Learning Apple uses machine learning to directly recognize people in private photos on your iPhones and iPad, without having access to your images for training. 58. Is Subjective Beauty Something We Can Model with AI? This AI reads your brain to generate personally attractive faces. It generates images containing optimal values for personal attractive features. 59. Using AI to Detect and Count Plastic Waste in the Ocean A deep-learning-based algorithm that is able to detect and quantify floating garbage from aerial images of the ocean. 60. Imagic: AI Image Editing from Text Commands This week’s paper may just be your next favorite model to date. 61. Google Brain's New Model Imagen is Even More Impressive than Dall-E 2 If you thought Dall-e 2 had great results, wait until you see what this new model from Google Brain can do. Dalle-e is amazing but often lacks realism, and this is what the team attacked with this new model called Imagen. They share a lot of results on their project page as well as a benchmark, which they introduced for comparing text-to-image models, where they clearly outperform Dall-E 2, and previous image generation approaches. Learn more in the video... 62. Combining CNNs, GANs, and Transformers to Outperform Image-GPT Researchers combined the efficiency of GANs and convolutional approaches with the expressivity of transformers to outperform Open AI's Image-GPT 63. Introducing Total Relighting by Google In a new paper titled Total Relighting, a research team at Google presents a novel per-pixel lighting representation in a deep learning framework. 64. What is Data Science like at NVIDIA? What is it like to work in big companies like NVIDIA, and how to get there? 65. How to Create Realistic Slow Motion Videos With AI TimeLens can understand the movement of the particles in-between the frames of a video to reconstruct what really happened at a speed even our eyes cannot see. 66. What is OpenAI's Whisper Model? Have you ever dreamed of a good transcription tool that would accurately understand what you say and write it down? Not like the automatic YouTube translation tools… I mean, they are good but far from perfect. Just try it out and turn the feature on for the video, and you’ll see what I’m talking about. 67. An Intro to eDiffi: NVIDIA's New SOTA Image Synthesis Model eDiffi, NVIDIA's most recent model, generates better-looking and more accurate images than all previous approaches like DALLE 2 or Stable Diffusion. 68. How Waymo Combines Lidar and Cameras for 3D Object Detection Let us talk about how autonomous vehicles 'see' the world. 69. NVIDIA and Tel Aviv University's Approach to Conditioning Text-to-Image Models Text-to-Image models like DALLE or stable diffusion are really cool and allow us to generate fantastic pictures with a simple text input. But would it be even cooler to give them a picture of you and ask it to turn it into a painting? Imagine being able to send any picture of an object, person, or even your cat, and ask the model to transform it into another style like turning yourself into a cyborg of into your preferred artistic style or adding it to a new scene. 70. New SOTA Image Captioning: ClipCap We’ve seen AI generate images from other images using GANs. Then, there were models able to generate questionable images using text. In early 2021, DALL-E was published, beating all previous attempts to generate images from text input using CLIP, a model that links images with text as a guide. A very similar task called image captioning may sound really simple but is, in fact, just as complex. It is the ability of a machine to generate a natural description of an image. 71. Secrets to Grow a Small Business Without Spending Money Ex-Google Tech Lead shares his experience in growing a business from 0 to millions of users fast, and his top tips for you to get going too. 72. What is General Video Recognition? We’ve seen AI generate text, then generate images and most recently even generate short videos 73. Would You Swipe Right for an AI Profile? Most of us are convinced that we can dissociate humans from machines, but is it really the case?  Would you swipe right for an AI-generated profile? 74. Convolutional Neural Networks (CNNs) Explained What is a convolutional neural network and explanation of one of the best and most used state-of-the-art CNN architecture in 2020: DenseNet. 75. How to Make $40K Per Month in Your 20's: Building a Side-Business Ex-Google Tech Lead talks about building a side-hustle and making $40K/month in your 20's. 76. Top 5 AI Articles of February 2022 Every Data Scientist Should Read Here are the five best articles related to artificial intelligence in February, hoping they will make you want to learn more and visit their website. 77. How to Get Started With AI in 2021 and Keep Up with Latest Innovations in ML How to start machine learning & Ways to keep up with the latest developments in Machine Learning. 78. How to Get Started With AI in 2021 and Keep Up with Latest Innovations in ML How to start machine learning & Ways to keep up with the latest developments in Machine Learning. 79. 'How I got a $500K job at Facebook (as a software engineer)' - TechLead Ex-Google TechLead explains the interview process at Facebook for staff software engineer.  (FYI, this video is a little more technical in nature.) Thank you for checking out the 79 most read stories about Youtubers on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

79 Stories To Learn About Youtubers

123 Stories To Learn About Youtube Transcripts

is a company co-founded by Sam Altman, the now-infamous CEO of OpenAI (of ChatGPT fame). The premise for the company’s flagship project, , is simple: Tools for Humanity WorldCoin Exponential improvements in Artificial Intelligence technology will one day lead to the creation of Artificial General Intelligence (AGI). When this happens, the global economy will be disrupted beyond recognition by job destruction, wealth concentration, etc. A post-AGI world will need something resembling a Universal Basic Income (UBI): money with no strings attached to par inequalities. AI improvements will make proving that someone online is a human very difficult. But, for UBI projects to work, you will need to verify that the people receiving it are real and are not cheating the system. So far, so good, right? It’s, however, all downhill from here. WorldCoin is the weirdest project happening in the tech world right now. How does WorldCoin “work”? To solve the issues mentioned above, WorldCoin has a two-step plan. . First, the company wants to scan your eyes This is being done using metallic spheres the size of bowling balls called . You Stare Into the Orb, and the Orb Stares Back at you. The device uses a thermal scanner to check people’s body temperature, a 3D camera to map out their faces, and high-resolution cameras to capture video and images of their bodies, faces, eyes, and irises. Orbs The irises are supposedly the important part. Since , it’s possible to create a code based on this specific biometric information. This unique crypto-graphic identifier is called a “World ID” or “IrisHash.” This code would supposedly replace IDs in an AI-dominated future. all irises are different unique If that feels like random techno-babble, trust your instincts. If this was it, this project would be creepy… but not nefarious. But no. Altman and his goons aren’t thinking about the future. They’re trying to peddle a cryptocurrency. Once your irises have been scanned, you download an app (there’s always an app). is yet another crypto wallet, which you can log onto by linking it to your IrisHash and proving you’re a human. At this point, you automatically receive some WorldCoins, which are supposed to be the basis for a new post-AGI, UBI-based economic order. This is your reward for selling out your biometrics. The World App , WorldCoins is not backed by any cash flows and are not tied to a fiat currency. Unlike other tokens, it doesn’t give , either. It is essentially worthless. Like most cryptos voting powers Congrats, you sold your eyes for something worth less than a Chuck e Cheese token (~17 cents). Like everything in crypto, this is a silly solution looking for a problem. Why is WorldCoin a Bad Idea? More than 2 million people have supposedly already had their eyes scanned by one of the 300+ Orbs in the world today, with the ominous spheres popping up in most major cities of the world. It must be noted, however, that most of that data was gathered , in what can only be referred to as . in the developing world while violating privacy laws crypto-colonialism : As the MIT Technology Review writes It’s just cheaper and easier to run this kind of data collection operation in places where people have little money and few legal protections. Ay, there’s the rub! If some form of Universal Basic Income was created in the future, it would exist to help the global poor. And so far, . At all. the global poor used as guinea pigs don’t feel helped The project’s leadership also fails to address the risks of the Orbs being hacked or how (which is how most crypto-scams come to be) could be used to derail their plans for a fair and transparent UBI system. And don’t expect transparency on this any time soon. social engineering As the reports: MIT Technology Review WorldCoin has promised to open source its code, including repeating to MIT Technology Review on multiple occasions that this would occur “within the next few weeks” — since we first contacted the company in February. Oh, the guy building a super-intelligent AI is compiling a permanent electronic identification database of all humans and refusing to explain how he’s using that data. That’s not an alarming science-fiction premise at all. Obviously, regulators will have something to say about the project if it gains traction because we have systems to distribute money to people in need. They are based on national identity and work fairly well. Sure, there is some fraud… but that fraud is usually committed like Sam Altman and his backers. UBI isn’t happening because we lack the technology; it’s happening because we lack the political will to do it. But that’s a story for another day. already by rich people Why does WorldCoin exist, really? WorldCoin is backed up by the usual crypto suspects: , , and (maybe?) are all investors. Coincidentally, these are all venture capitalists . Andreessen Horowitz Khosla Ventures Three Arrows Capital with massive crypto-related losses These people didn’t invest because they cared about the world’s poor or privacy. To them, this is a last-ditch effort to make fetch happen and recoup some of their losses. It didn’t work in the West, so they’re now . setting their sights on the global south Want UBI? Scared of AI? They will spin it however they can to get you onboard. They hope that using enough buzzwords like AI, , , and will make users forget about WorldCoin’s core concept. Which, again, . biometric data verification censorship-resistant transfer Sybil attacks is getting your eyeball scanned for free If the team in charge of WorldCoin was serious about UBI, they would be working on the political will to give money to people all over the world. But that’s . And that would make WorldCoin a tech company. It would make it a . And tech bros profits. The fact that makes that abundantly clear. difficult not non-profit love investors hold 10%+ of the WorldCoin supply I have no doubt that Sam Altman has good intentions. But that doesn’t really matter, does it? There is a reason the phrase “ ” exists. Actions speak louder than words, and right now, his actions point to him building a crypto- . the road to hell is paved with good intentions Panopticon The project launched “officially” in late July. The quicker it goes back to obscurity, the better. Good luck out there. Also published . here

The Strangest Tech Project Happening Right Now: Scan Your Eyeballs for Crypto

Object Detection Frameworks That Will Dominate 2023 and Beyond

Many enterprises that implement Kubernetes don’t realize how insecure it can truly be out of the box — and even when they do, they’re not sure what to do about it. And since Kubernetes is an extremely complex and flexible tool that in production can consist of hundreds, if not thousands, of moving parts — understanding the vulnerabilities of Kubernetes, potential solutions, and relevant regulations and trends can be a time-consuming and daunting task. For most any business, this makes it way too easy to introduce serious legal or security issues into their clusters and production applications. With KubeCon Europe 2023, I was impressed with (and happy to see) the number of security solutions entering the market. Continuing from 2022, the biggest theme from KubeCon Europe 2023 was software supply chain security — ensuring that you know what’s running in your cluster and that it’s vulnerability free. I was struck then, as I have been in recent years, by the importance of software supply chain security. With cloud-native apps, containerization, and Kubernetes, today’s software organizations are in an arms race with malicious attackers who seek to undermine and poison our software. So I was pleased to come across several additional projects at KubeCon Europe 2023 that are dedicated to tackling the challenge of Kubernetes security. In this article, I’ll give a whistle-stop tour of those projects. But let’s start with a quick overview of the conference and what I consider to be the most important aspects of k8s security. Breaking Down Kubernetes Security First, the conference. I was a little worried that the IT recession might mean the conference wouldn’t be as meaningful as in past years — but I’m happy to say that I had no need to worry! While I wasn’t able to attend in person, through remote and post-conference conversations with those that were there, the conference seemed to be as exciting as ever! While there weren’t any standout new trends at the conference, there was a ton of tooling and discussion around Kubernetes security. To keep everything straight in my mind, I categorize k8s security into three particular aspects: attestation, provenance, and SBOM: Attestation: Confirming your artifact’s origin and that it is what it claims to be. Attestation typically comes in the form of signing containers, packages, and so on, in a way that the receiving party can verify. Provenance: The audit trail of where the artifact came from and who had interactions with it. Often used in connection with attestation if something doesn’t look right. Software bill of materials (SBOM): What are the packages and dependencies inside the artifact? These are increasingly necessary for regulation and as a demonstration to customers. With that in mind, let’s walk through the solutions. OpenClarity consists of a suite of tools that aim to bring insights into different levels of the cloud-native stack, from security to observability. OpenClarity The two relevant components to this post are KubeClarity and VMClarity which create SBOMs and perform vulnerability analysis for Kubernetes clusters and virtual machines respectively. runs on any Kubernetes cluster and provides a UI and CLI for analyzing images and generating SBOMs. By default, KubeClarity doesn’t have its own SBOM generator or vulnerability scanner, but instead, supports third-party tools that you can enable in any combination, making it great for adding additional interfaces for existing toolchains. KubeClarity If you would rather not install each of the components yourself, then they’re commercially available as part of . Cisco Panoptica Support includes the following SBOM generators and vulnerability scanners: Syft CycloneDx-gomod Trivy Grype Dependency-Track We’ll cover some of these projects in more detail below. works similarly but within the context of VMs used by cloud services to host containers and clusters. Compared to containers, VMs may be as (or even more) vulnerable to threats and they typically need complex tools for analysis. VMClarity Following a similar pattern to KubeClarity, VMClarity supports aggregating multiple tools into one UI and CLI. in-toto is an open-source project that focuses on the attestation part of software supply chain security. You use it to define a “layout” for a project, i.e., how the different components should fit together. in-toto A project ships this definition with its code, and then another user of that software can compare what they have with the attached definition to see if it matches the structure and contents they expect. If it doesn’t, then this could point to external tampering or other issues. Trivy is a mature and comprehensive open-source tool from Aqua Security that supports scanning multiple sources, from file systems to containers and VMs. Trivy also looks beyond vulnerabilities, to scan licenses, secrets, infrastructure as code misconfiguration, and more. Trivy It supports different SBOM output formats, attestation using in-toto, as well as scanning the attestation for vulnerabilities. To tie all these features together, Trivy has an ecosystem support, complete with IDE plugins, CI/CD, and a Kubernetes operator. Slim.ai Historically, aimed to help you understand the contents of an image and how to “slim” it down to the essentials. The platform has now expanded its feature set to include vulnerability scanning. Slim.ai Slim.ai presents the data in a more user-friendly way than many of the other tools in this post. On top of its open-source for identifying the contents of an image, Slim.ai uses Trivy for vulnerability scanning. SlimToolkit You can then use the “harden” feature to create a new version of the image that’s removed any vulnerabilities and extraneous packages. The Update Framework A common reason behind insecure software is out-of-date package versions, but how do you trust that an update is what it says it is and won’t cause you more problems? Release signing—or attestation—was a hot topic at KubeCon among vendors, with many offering their own solutions. One in particular that stood out was CNCF’s recently graduated (TUF). The Update Framework Confusingly named, it’s not a framework, but a specification that developers can follow when implementing their update systems to help users know they can trust the updates they receive. There’s also a . Python reference implementation Syft is a popular open-source CLI tool created by for generating an SBOM from container images and filesystems. It’s designed to provide a catalog of dependencies for other tools to use as a data source. Syft Anchore It supports many popular programming languages, package managers, and container image formats. With its support for different SBOM file formats and custom templates for reports, Syft has become an ideal component for vulnerability scanning toolchains. Grype is another popular open-source tool from Anchore. Working with SBOM files, Grype scans container images and filesystems for vulnerabilities. Grype supports different output formats for vulnerabilities and custom templates for output. Grype sigstore is another suite of tools that focuses on attestation and provenance. Within the suite are two tools I heard mentioned a few times at KubeCon: and . sigstore Cosign Rekor Cosign is used for signing containers through a variety of different methods. It has strong integration with other open-source tools, such as . Kyverno Rekor is a tamper-resistant ledger for metadata generated by a software supply chain project. This means that parties can query the metadata to help them make decisions based on decisions previously made by others. It’s not a very well-known project, but it is growing in popularity. Kubescape is a comprehensive Kubernetes security platform and CNCF sandbox project. It can scan clusters, Helm charts, and YAML manifests to detect misconfigurations. It supports various frameworks, including , , and the . Kubescape NSA-CISA MITRE ATT&CK® CIS Benchmark Chainguard Taking a very definite enterprise approach, is impossible to try without first speaking with their sales department. But as far as I can tell, it consists of two main products. Chainguard Chainguard Images are specialized, hardened images that focus on a minimal footprint, promise no vulnerabilities, are as small as possible, and ship with SBOMs. Chainguard Enforce combines the creation of policies for your software supply chain with the enforcement of those policies. You write policies in YAML or by using a CLI tool to configure a Kubernetes agent that reports back to the service. You can view reports via the CLI or a GUI. Policies can include image signing, SBOM inclusion, and more. Chainguard also appears to have several . The most popular one is , used for building OCI images from APK packages. open-source projects apko Falco is a well-known open-source security solution originally created by Sysdig. It’s a CNCF incubating project and one of the few (as far as I can tell) options on this list that uses eBPF to scan for vulnerabilities. Falco This does mean it needs a few extra steps to install, and you can only test it on Linux systems. However, once you have Falco set up, it runs more performant than any container agent and can detect vulnerabilities at all system levels. The Future Is Complicated I hope you enjoyed this overview and found a few tools that will help you secure your enterprise. Most experts believe that cybersecurity will become more complex and challenging as more aspects of the world are dominated by software: IoT, smart cars, and drones—and now, we’ve added AI and LLMs to the mix. The arms race between attackers and defenders doesn't seem to favor the defenders. And deploying solutions is a complicated endeavor. Now is a good time to find the tools and workflows that suit you and your organization before you become the target. Have a really great day!

An Overview of Kubernetes Security Projects at KubeCon Europe 2023

Using AI to find out what's in an image with mask2former! There's a world of possibilities when it comes to image segmentation, and Mask2Former is here to help you unlock them. In this guide, I'll walk you through using this amazing AI model for universal image segmentation. I'll show you how to understand its inputs and outputs, and how to interact with it using code. The model is ranked highly on , and we'll also see how we can use this platform to find similar models and decide which one we like. Replicate Codex Let's begin. About the Mask2Former Model Mask2Former, developed by , is an AI model designed for universal image segmentation. It helps you segment images with great precision, and its applications range from object detection to image editing. Facebook Research Understanding the Inputs and Outputs of the Mask2Former Model Before we dive into using Mask2Former, let's take a moment to understand its inputs and outputs. Inputs Mask2Former requires only one input: : This is the input image for segmentation. The output will be the concatenation of Panoptic segmentation (top), instance segmentation (middle), and semantic segmentation (bottom). image file Outputs The output schema of the Mask2Former model is as follows: {
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "file": {
        "type": "string",
        "format": "uri",
        "x-order": 0
      },
      "text": {
        "type": "string",
        "x-order": 1
      }
    }
  },
  "x-cog-array-type": "iterator"
} Now that we have a better understanding of the inputs and outputs, let's move on to actually using the model. A Step-by-Step Guide to Using the Mask2Former Model Interact with the model's demo on Replicate If you're not up for coding, you can interact directly with the model's "demo" on Replicate via their UI. This is a nice way to play with the model's parameters and get some quick feedback and validation. If you do want to use coding, this guide will walk you through how to interact with the model's Replicate API. Step 1: Install the Node.js client First, you'll need to install the Node.js client: npm install replicate Step 2: Authenticate with your API token Next, copy your API token and authenticate by setting it as an environment variable: export REPLICATE_API_TOKEN=[token] Step 3: Run the model Now, you can run the model using the following code: import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

const output = await replicate.run(
  "facebookresearch/mask2former:97c0c2edeeb7c120c2859dca4fdee58d185131f79c857ba519e3a5cb7cdd7c66",
  {
    input: {
      image: "your_input_image_here"
    }
  }
); Step 4: Set up a webhook (optional) You can specify a webhook URL to be called when the prediction is complete. This can be useful if you want to receive updates asynchronously. Here's an example of how to set up a webhook: const prediction = await replicate.predictions.create({
  version: "97c0c2edeeb7c120c2859dca4fdee58d185131f79c857ba519e3a5cb7cdd7c66",
  input: {
    image: "your_input_image_here"
  },
  webhook: "https://example.com/your-webhook",
  webhook_events_filter: ["completed"]
}); For more information, take a look at the webhook docs on Replicate. Taking it Further - Finding Other Image Segmentation Models with Replicate Codex Replicate Codex is a fantastic resource for discovering AI models that cater to various creative needs, including image segmentation. It's a fully searchable, filterable, tagged database of all the models on Replicate, and also allows you to compare models and sort by price or explore by creator. It's free, and it also has a digest email that will alert you when new models come out so you can try them. If you're interested in finding similar models to Mask2Former... Step 1: Visit Replicate Codex Head over to to begin your search for similar models. Replicate Codex Step 2: Use the Search Bar Use the search bar at the top of the page to search for models with specific keywords, such as "image segmentation" or "object detection." This will show you a list of models related to your search query. Step 3: Filter the Results On the left side of the search results page, you'll find several filters that can help you narrow down the list of models. You can filter and sort by models by type (Image-to-Image, Text-to-Image, etc.), cost, popularity, or even specific creators. By applying these filters, you can find the models that best suit your specific needs and preferences. For example, if you're looking for an image segmentation model that's the most popular, you can just search and then sort by popularity. Conclusion In this guide, we explored the power of the Mask2Former model for universal image segmentation and how to interact with it using code. We also discussed how to leverage the search and filter features in Replicate Codex to find similar models and compare their outputs, allowing us to broaden our horizons in the world of AI-powered image segmentation. I hope this guide has inspired you to explore the creative possibilities of AI and bring your imagination to life. Don't forget to subscribe for more tutorials, updates on new and improved models, and a wealth of inspiration for your next creative project. AI You can also follow me on for more AI-related content. Twitter Also published here.

An Intro to Mask2Former and Universal Image Segmentation

Una introducción a Mask2Former y Universal Image Segmentation

Une introduction à Mask2Former et à la segmentation d'image universelle

Mask2Former और यूनिवर्सल इमेज सेगमेंटेशन का परिचय

Mask2Former とユニバーサル イメージ セグメンテーションの概要

Uma introdução ao Mask2Former e à segmentação universal de imagens

Giới thiệu về Mask2Former và Universal Image Segmentation

Mask2Former 和通用图像分割简介

You can from the WordPress Plugin Directory. download Smol Links About the LevelUp series: At The Markup, we’re committed to doing everything we can to protect our readers from digital harm, write about the processes we develop, and share our work. We’re constantly working on improving digital security, respecting reader privacy, creating ethical and responsible user experiences, and making sure our site and tools are accessible. The Markup in everything we do—including the links we use to share our journalism. respects our readers’ privacy We don’t use popular URL shorteners like Bitly, because the tracking that comes along for the ride poses more privacy risks—such as sharing our readers’ click traffic—than we are comfortable with. See our code here, and let us know if you find any bugs GitHub Instead, we found an existing privacy-minded URL shortener called , built a custom WordPress plugin on top of it called so our editors could easily generate short URLs themselves, and then hosted it all on server infrastructure we have full control over. Shlink Smol Links Our short links count aggregate clicks only, so our audience team can gauge trends in a way that fits within our privacy constraints. From day one, our entire organization, and especially our product team, has had a to avoid tracking technologies to the greatest extent possible—no third-party analytics, no sketchy ad tech, no monetizing visitor data. clear and public mandate This means we’re often doing on the services we rely on, and if we don’t find something that fits our privacy requirements, and host it ourselves. Here’s why and how we approached hosting our own URL shortener. extra due diligence we build our own tools or customize existing systems The Tracking That Comes with Existing Short Links A popular approach to sharing news links on Twitter—used by The New York Times, BBC News, Yahoo! News, and many others—employs multiple sequential redirects from short URLs. By chaining redirects, news outlets capture audience analytics in different tools, each tracking how many people clicked and who they are. Clicking on a Yahoo! News yhoo.it link posted to Twitter will take you to another short URL at yahoo.trib.al (hosted by analytics service SocialFlow), ultimately redirecting you to the story at news.yahoo.com. Twitter itself has its own URL shortener, t.co, that automatically tracks clicks to each URL published on its platform. One such click on a news article can be observed by Twitter, Bitly, SocialFlow, the news outlet, and any third-party affiliates those companies have partnered with. What happens between your clicking on a link and when the page loads? A link to a video example. Dan Phiffer SocialFlow that it has tracked more than 12 billion consumer clicks from more than two billion devices. Bitly similarly 10 billion clicks and scans monthly. advertises advertises The scale of accumulated traffic data is big, the exact amount of tracking that companies deploy isn’t transparent to the public, and the data and short URLs generated are all stored with the analytics or URL shortener company an organization uses. These are some of the reasons why we adopted an open source URL shortener and built Smol Links so it can all be hosted on server infrastructure we have full control over. The tracking from all those URL redirects also happens the page loads. Once you’ve actually loaded an article, websites that are willing to host ads will pile on even more tracking through ad trackers, third-party cookies, and canvas fingerprinting. before If you’re ever curious to know how websites you visit are tracking you, check out another tool we made: . Blacklight Not all news outlets rely on short URLs this way, but when links are shared on Twitter, they get automatically shortened using Twitter’s own t.co service, which can’t be turned off. In most cases we post full article URLs to Twitter, and clicks on those links are still tracked by the t.co redirect. There’s nothing we can do about that if we want to tweet our work; all we can do instead is make sure we don’t layer invasive tracking on top of that. Other news outlets like Newsweek and The Guardian also avoid using a short URL in their Twitter updates. The Markup does occasionally rely on our own short URLs in our Twitter posts, to measure traffic or for aesthetic reasons. We count the number of aggregate clicks on each short URL but do not track individual people or IP addresses. That lets us understand the various sources of our website traffic without invading anyone’s privacy. Finally, while the tracking that happens in URL redirects is almost imperceptible, like other ad tech that loads on the article page, each redirect slows down the article load time. By eliminating these redirects, we reduce privacy risks while marginally speeding things up. Building The Markup’s URL Shortener and “Smol Links,” Our WordPress Plugin We’re not interested in building things that already exist, so before writing our own link shortener, we tried to find out whether a privacy-minded tool already existed. So when we found , an URL shortener written by software developer , we decided to use it. Shlink open source Alejandro Celaya Shlink has functionality similar to Bitly’s but is designed to run on one’s own server. Our self-hosted Shlink server takes care of most of the heavy lifting—keeping track of our short URLs and redirecting them to the longer original article URLs. For example, when you click on , our Shlink server is what sends you to . mrkup.org/amazon-brands https://themarkup.org/amazons-advantage/2021/10/14/amazon-puts-its-own-brands-first-above-better-rated-products Shlink also includes a feature that avoids tracking our visitors by IP address. When we were testing out the software, that meant IP addresses were being tracked anyway and logged a request with Celaya to fix it. we discovered a bug We appreciated how seriously Celaya took the request, and he fixed the bug in a day. The software part that we’ve built on top of Shlink’s URL shortener is a WordPress plugin . The plugin lets our editors create and manage short URLs from our existing WordPress CMS, a user interface they are already familiar with. we’re releasing called Smol Links The plugin has an option to automatically generate new short URLs anytime a story gets published, which was an essential feature for sending out SMS announcements. The plugin uses WordPress to offer more customization possibilities—for example, to append query string arguments to each long URL. filter hooks Because mrkup.org is hosted on server infrastructure we have full control over, running code we can observe and modify, it means we have more confidence about what happens to our readers’ click data. It means we are not limited to choosing between the ad-tech panopticon and no traffic insights whatsoever. Smol Links lets us measure where our visitors come from in general without undermining the trust in our privacy promise that we’ve worked hard to earn. ↩︎ link Everything Started with SMS Last year, our audience team wanted to experiment with sending out SMS notifications, announcing via text message whenever we’d publish an article. We ran this experiment for five months and originally set up our own partially disemvoweled domain, mrkup.org, in order to fit article updates within the 160-character limit of a text message. Another essential feature for sending out SMS announcements was the ability to generate new short URLs anytime a story gets published. That’s what drove us to find Shlink and then build Smol Links on top of it. After looking at aggregate traffic numbers, we saw that SMS was not a popular way for our readers to get article updates, so we decided to end that experiment. But we continued to use the URL shortener on other social media platforms like Instagram, where hypertext links are not natively supported except as a sticker in Stories. Doing Our Work in Public Join us in building a better World Wide Web, starting with the modest short URL redirect. You can or download it . We look forward to reading your issues and pull requests. download Smol Links in the WordPress Plugin Directory from GitHub We intend to do more of that work in public, sharing what we know about maintaining privacy-respecting systems and releasing some of the software we’ve written. We hope this effort might encourage others to make a similar investment on behalf of their own website visitors and help us gather feedback about where we might have room for improvement. By Dan Phiffer Also published here Photo by on Daniel K Cheung Unsplash

How to Shorten URLs Without Tracking With The Markup's Smol Links

Panoptic scene graph generation, or PSG, is a new problem task aiming to generate a more comprehensive graph representation of an image or scene based on panoptic segmentation rather than bounding boxes. It can be used to understand images and generate sentences describing what's happening. This may be the most challenging task for an AI! Learn more in the video... References ►Read the full article: ►Yang, J., Ang, Y.Z., Guo, Z., Zhou, K., Zhang, W. and Liu, Z., 2022. Panoptic Scene Graph Generation. arXiv preprint arXiv:2207.11247. ►Code: ►Project page (PSG dataset): ►Try it: , ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/psg/ https://github.com/Jingkang50/OpenPSG https://psgdataset.org/ https://replicate.com/cjwbw/openpsg https://huggingface.co/spaces/ECCV2022/PSG https://www.louisbouchard.ai/newsletter/ Video Transcript 0:00 you can use ai to identify what's in an 0:02 image like finding out whether there's a 0:04 cat or not in this scene if there's one 0:07 you can use another ai to find where it 0:10 is in the image and you can find it very 0:12 precisely these tasks are called image 0:15 classification object detection and 0:17 finally instance segmentation then you 0:20 can build cool applications to extract 0:23 your cat from an image and put it into a 0:25 fun gift card or a meme but what if you 0:27 want an application that understands the 0:29 scene and image not only being able to 0:32 identify whether there's an object and 0:34 where it is but what's happening you 0:36 don't want to identify if there's a 0:38 customer or not in your shop but you 0:40 might want to identify if the customer 0:42 in question is stealing you whether 0:44 using such surveillance is ethically 0:46 correct or not is a whole other question 0:49 you also need to consider still suppose 0:51 we focus on finding out what's happening 0:53 in a scene or a particular image in that 0:56 case you'd want to use a task called 0:58 scene graph generation where objects are 1:01 directed using bounding boxes as shown 1:04 previously with object detection which 1:06 is then used to create a graph with each 1:09 object's relationship to each other 1:11 object it will basically try to 1:13 understand what's happening from all the 1:15 principal objects of the scene it works 1:17 quite well and finds out these main 1:19 characteristics of the image but there's 1:21 a big problem it relies on the bonding 1:23 box accuracies and completely disregards 1:26 the background which is often crucial in 1:28 understanding what's happening or at 1:30 least giving a more realistic summary 1:33 instead you might want to use this new 1:35 task called panoptic scene graph 1:38 generation or psg psg is a new problem 1:42 task aiming to generate a more 1:43 comprehensive graph representation of an 1:46 image or scene based on panoptic 1:49 segmentation rather than bonding boxes 1:52 something much more precise taking into 1:54 account all pixels of an image as we saw 1:57 and the creators of this task didn't 1:58 only invent it but they also created a 2:01 data set as well as a baseline model to 2:03 test your results against which is 2:05 really cool this task has a lot of 2:07 potential as understanding what is 2:09 happening in an image is incredibly 2:11 useful and complex for machines even 2:14 though humans do it automatically it 2:16 brings some sort of needed intelligence 2:18 to the machines making the difference 2:20 between being a cool funny app like 2:23 snapchat to a product you'd use to save 2:25 time or complete a need like 2:27 understanding when your cat wants to 2:29 play and using a robot to play with it 2:31 automatically so it isn't bored all the 2:33 time 2:34 understanding a scene is really cool but 2:36 how can a machine do that well you need 2:39 two things a data set and a powerful 2:42 model we know that we already have the 2:44 data sets since they built it for us now 2:47 the second thing how to learn from this 2:50 data set which means how to build this 2:52 ai model and what should it do there are 2:55 multiple ways to approach this problem 2:58 and i invite you to read their paper to 3:00 find out more but here's one way to do 3:02 it 3:03 before getting into it give me a few 3:05 seconds to be my own sponsor and talk 3:07 about our community since you are 3:09 watching this video i know you will love 3:11 it as it was basically created for you 3:13 of course we have the youtube community 3:15 which you should definitely join by 3:17 clicking the little subscribe button and 3:19 commenting below for instance i'd love 3:21 to know what you think about this task 3:23 and if it's interesting or not to the ai 3:25 community i also wanted to share our 3:28 discord community learn ai together it's 3:31 a place to connect with fellow ai 3:33 enthusiasts from any skill level find 3:35 people to learn with find people to work 3:37 with ask your questions or even find 3:40 interesting job offers we are organizing 3:42 a lot of very cool events and q as like 3:44 the one we are currently running with 3:46 the mine rl organizers from deepmind and 3:49 openai the link is in the description 3:51 below and i'd love to see you join an 3:53 exchange with us there 3:55 as we said the model needs to find the 3:57 class for each pixel of the image 3:59 meaning that it has to identify every 4:01 pixel of the image the first stage of 4:04 the model will be responsible for this 4:06 it will be a model called panoptic fpn 4:09 already trained to classify each pixel 4:12 such a model is already available online 4:14 and quite powerful it will take an image 4:17 and return what we call a mask with each 4:19 pixel matched to an existing object like 4:22 a ball human or grass in this case you 4:25 now have the segmentation and you know 4:28 what's in the image and where if you are 4:30 not familiar with how such a model works 4:32 i invite you to watch one of the videos 4:34 i made covering similar approaches like 4:36 this one the next step is to find out 4:38 what's happening with those objects 4:41 here you already know it's a man playing 4:43 soccer on the field but the machine 4:45 actually has no idea the only thing it 4:48 knows is that there is a man a ball and 4:50 a field with a lot of confidence but it 4:53 doesn't understand anything and cannot 4:55 connect the dots as we do with ease we 4:58 need a second model trained just to take 5:00 those objects and figure out why they 5:03 are in the same picture this is the 5:05 scene graph generation step where a 5:07 modal will learn how to match a 5:09 dictionary of words and concepts 5:12 covering multiple possible object 5:13 relations to objects in a scene using 5:16 the information extracted from the first 5:19 stage learning how to structure the 5:21 objects with each other object and voila 5:25 you end up with a clear graph that you 5:27 can use to build sentences covering 5:29 what's happening in your image you can 5:31 now use this approach in your next 5:32 application and give a few iq points to 5:35 your approach getting it closer to 5:37 something intelligent if you'd like to 5:39 learn more about this new task i 5:41 strongly invite you to read the paper 5:43 linked below thank you for watching 5:45 until the end and i will see you next week with another amazing paper

PSG is a New Task for AIs Requiring Higher Levels of Understanding

PSG es una nueva tarea para las IA que requiere niveles más altos de comprensión

Le PSG est une nouvelle tâche pour les IA nécessitant des niveaux de compréhension plus élevés

पीएसजी एआई के लिए एक नया कार्य है जिसके लिए उच्च स्तर की समझ की आवश्यकता होती है

PSG は、より高いレベルの理解を必要とする AI の新しいタスクです

PSG é uma nova tarefa para IAs que exigem níveis mais altos de compreensão

PSG là một nhiệm vụ mới cho những AI yêu cầu mức độ hiểu biết cao hơn

PSG 是需要更高理解水平的 AI 的一项新任务

70-Page Report on the COCO Dataset and Object Detection [Part 2]

Take a look at the to quickly find common resources and/or assets for a given dataset and a specific task, in this case dataset=COCO, task=object detection. We are building a dataset-first marketplace focusing on the end-to-end machine learning pipeline, one where data and assets can be shared and traded. The marketplace will contain all that the contains (and much more for a lot more datasets) report report I’m open to suggestions, questions, and criticism — let’s start a conversation. I have broken up the report into the following blogs: Part 1 (this one): COCO Summary Card. Each link will take you to the longer report where you can learn more. The next 3 parts represent a specific section in the report. Part 2: This part is about COCO and examples and tutorials of tools and platforms used to work with COCO (or object detection tasks). Part 3: Process: This part is about the tools and platforms that can be used for different phases of data preparate or data processing involved in vision, object detection, and specifically COCO-related tasks. It will also discuss synthetic data and data quality. Part 4: Models: This part is about a quick introduction to some pre-trained models and some corresponding readings. COCO Summary Card (Common Objects in Context) COCO COCO is a large-scale object detection, segmentation, and captioning dataset. The dataset classes include 80 pre-trained objects. Website: https://cocodataset.org/ Github: GitHub — cocodataset/cocodataset.github.io Paper: Microsoft COCO: Common Objects in Context dataset with evaluation metric Average Precision (AP) Benchmark : Object Detection, Panoptic Semantic Segmentation, Keypoint Detection, DensePose Tasks Tools and platforms used to work with COCO (or object detection tasks) : Explore with tutorials FiftyOne, DataTorch, Know Your Data (KYD), OpenCV, OpenVINO, CVAT, Roboflow, SuperAnnotate, OpenMMLab, Coral, Amazon, Facebook, Google, Microsoft, NVIDIA, Weights and Biases. Open-source tools and Paid platforms to perform the following steps. : Processing Data collection : CVAT, LabelImg, Label Studio, Makesense.AI, OpenLabeling, Dataloop, Hive Data, Labelbox, Scale AI, SuperAnnotate, V7, Ximilar Data labeling and annotation Data cleaning : Albumentations, AugLy, Augmentor, autoalbument, DALI, Data Augmentation for Object Detection, Imgaug, Kornia, MXNet, Tensorflow, Transforms (PyTorch) Data transformations Data visualization : Cvedia, Neurolabs, Synthesis AI, Unity, UnrealROX Synthetic data Data quality To answer what objects are in image X and where are they? (You’ll find a brief summary and readings.) : Models RCNN SPPNet Fast RCNN and Faster RCNN Pyramid Networks / FPN Mask RCNN YOLOv1 SSD RetinaNet YOLOv3 YOLOv4 YOLOv5 DINO (and DETR) Swin Transformer V2 Vision Transformer Adapter YOLOR If you have feedback please review this link ( ) and email me at samin@reasonets.com. Looking forward to starting a conversation. Marketplace — Coming Soon | ReasoNets Next, Part 2

70-Page Report on the COCO Dataset and Object Detection [Part 1]

If you’re in crypto, you know that Proof of Work or ‘PoW’ powers consensus on Bitcoin’s legendary blockchain. You probably know Proof of Stake (PoS) systems, too. Between the two, they power nearly all the major players in the world of blockchains today. So WTF is Proof of Transfer (PoX)? The short answer: It’s a mining mechanism that provides a new take on consensus, allowing for a Proof of Work chain (in Stacks' case, Bitcoin) to be leveraged and extended in important new ways. But, that doesn’t really tell you all that much does it? In this post, I’ll break down what PoX really is and more importantly, why it’s needed. To understand the need for PoX, it helps to understand a little about the tragic state of the internet today and the broken surveillance capitalism business models that power it. Even a quick scan of the news shows you just how parasitic business models, highly concentrated wealth and power, and a complete lack of digital rights have distorted and destroyed the open internet. There’s nothing open about it anymore.  We wanted an internet for people, of people, and by people, but what we got was a Panopticon tracking our every move in order to sell us stuff we don’t need. - Tech Talks The internet is broken—and so’s the rest of the tech industry - WSJ Google Sued Over Abuse of Search Power, Opening Path for More Claims - Fast Company Here are the data brokers quietly buying and selling your personal information - New York Times Tech’s Frightful Five: They’ve Got Us - New York Times Facebook Security Breach Exposes Accounts of 50 Million Users - NPR How 5 Tech Giants Have Become More Like Governments Than Companies - Tech Talks/World Economic Forum Will these tech companies eventually become the uncontested rulers of our planet? - Slate The Evil List: Which tech companies are really doing the most harm? Here are the 30 most dangerous, ranked by the people who know. Facebook and Google make billions of dollars to the most valuable commodity in the world: You - selling access Inc.com The key to pushing past these broken business models and imbalance of power is true digital ownership. Right now you don’t own anything about your digital life; Facebook, Instagram and TikTok own it. If you connect with 10,000 people on Twitter, you don’t own those connections. Twitter owns them. If you build a big discussion group on Facebook with 25,000 people and you all share stories and ideas, Facebook owns those stories. If you want to leave Facebook you leave all that content you created behind. It’s locked in a digital citadel. You leave the laughter and debates between you and all your friends.  Every back and forth, every comment is gone. The things you don’t own, end up owning you. But what if it were different? What if you owned your connections, your comments, all of the banter between you and your friends. It’s like going into a bar with three of your best pals.  You own the jokes and discussions between you, not the bar.  If the bar isn’t a good place, you leave and go to another bar and take your friends with you. PoX helps us deliver that in the digital world.  You own the relationships, not the bar or platforms you’re a prisoner of right now. With digital ownership comes freedom. When we take back our digital freedom the old pillars that prop up the current system start to crumble. Network lock-in disappears.  People can pick up and leave without losing their life’s work or their community. When people own their data and they can choose where it goes and what companies can do with it, ad-based models will get ripped up, replaced or re-balanced.  It will force companies to compete for your business. Today, companies grow to a certain point and they don’t have to care about you anymore; they achieve a network effect and they’re done. They can stop innovating and they can stop serving your best interests because they have you locked in. When you own your data, that dynamic gets flipped on its head. It puts people back in charge and makes it so that companies have to work hard to keep you and serve your interests. Obviously, we’re not there yet. That’s where Bitcoin and Proof of Transfer come into the picture. Call it a user-owned internet, call it Web 3.0, call it whatever buzzword you want, but what we’re really talking about here is returning power to the people.  We’re moving to an internet where people matter again and you’re the center of the story, not companies. With Stacks, PoX is the foundation of that story. In the most basic sense, PoX is a way to extend the power of Bitcoin beyond the silo of the Bitcoin network. It brings the properties that make true digital ownership possible to wherever developers need it. Before Bitcoin, the notion of owning any digital asset, even something as basic as money, was a pipe dream. The entire architecture of the Bitcoin network, including the P2P nature, elimination of middlemen, and overall transparency, is centered around the notion of digital ownership. PoX helps us unlock this power and push it beyond Bitcoin to reshape our digital lives. Without PoX, building new features on Bitcoin is a paradox. Bitcoin is secure because it’s stable and resistant to change. It’s secure because it has a very limited scripting language with a small attack surface, among other properties. Introducing new features to the Bitcoin core protocol is hard and not desirable as these features add complexity. PoX solves exactly this. It is designed so that builders can benefit from Bitcoin’s properties without modifying Bitcoin itself. It also means builders can tap into the immense value stored on the Bitcoin network, activating cases for DeFi, NFTs, and more for all holders of BTC. PoX is broken down much more deeply in , but basically, the PoX consensus mechanism allows a new project to create a new network with its own unique features that has the security of an existing Proof of Work blockchain from the beginning without the need to modify that existing chain. In the case of Stacks, core developers chose Bitcoin because it lets us leverage the security of the world’s most secure and most widely used blockchain, while delivering full support for token creation, smart contracts, light clients, unique funding mechanisms, and more. the whitepaper So how does Proof of Transfer actually work? To understand Stacks' Proof of Transfer implementation, you need to understand the two core mechanisms that power it: Mining & Stacking. STX Mining If we’ve converted electricity to mine a token already (PoW to mine Bitcoin, in this case), we can leverage that to secure a new chain rather than waste more electricity. This is the core insight that led to the idea of Proof of Transfer. Like other blockchains, the network is secured by miners who commit resources in order to compete to mine a Stacks block, and receive an STX reward. In the case of Stacks, it is Bitcoin, not electricity/computing power, that is input by miners for a chance to win new Stacks blocks. A nice added feature of this is that Stacks mining doesn’t require any special hardware or high upfront costs; anyone who wants to mine a block simply sends Bitcoin to the address provided by the protocol. The protocol uses the amount of Bitcoin sent by each miner as an input, and combines it with a verifiable random function (VRF) in order to run the leader election and select a winning miner. The more Bitcoin a miner commits, the higher their chances of winning the leader election. Once a winning miner is selected, they are able to broadcast the new block they’ve created across the network, and the protocol rewards their effort by sending them a reward of 500 STX tokens. But what happens to the Bitcoin that the miners have sent to the protocol? That’s where Stacking comes in. Stacking Essentially, Stacking is when STX token holders lock up their STX tokens on the network. This completes the economic cycle of Proof of Transfer as these 'Stackers are sent BTC from miners. Stacking adds value to the network in 3 ways: (1) signaling support for a chain tip requires getting information that is commonly provided by running a node and thus encourages further decentralization of the network, and (2) signaling support for a specific chain tip adds an extra incentive for STX Miners to be honest with how they mine (3) locking up STX adds value directly to the network, as more and more token holders are incentivized to put further skin in the game. In exchange, the Proof of Transfer mechanism sends the Bitcoin committed by STX Miners each block to users who are Stacking. This is where the word “Transfer” comes from. The protocol takes the Bitcoin sent by miners in order to secure the network, and transfers it to users who are providing value to the network. Stacking runs in cycles lasting roughly 14 days, meaning every 14 days there is a new opportunity to participate in Stacking and earn BTC. The below diagram gives a high-level representation of Proof of Transfer. The end result of all this is that people are incentivized to hold the tokens so long as the service / network resource given back is worth it. If that changes, they can leave with their creations and connections intact. This model of digital ownership, freed from the silo of Bitcoin, is what will fix our broken internet and become the standard. It finally rewards power and value to the people that are responsible for making it what it is in the first place. So WTF is PoX? Well, you could say it’s an abstraction of Proof of Work, or a mining mechanism on the Stacks blockchain, or an extension of Bitcoin, or even a way to enable true digital ownership in any application or service, and you’d be right. But more than that, PoX is the pen that is helping us write a new story for the Internet, one written in Bitcoin’s gold ink with you as the hero. A reality where you’re a decision-maker, have freedom and rights, and are a participant in the value you create. A reality in which you, not big companies, own your digital identity and life. PoX makes you the owner of tomorrow’s internet. Mitchell is the Head of Growth at the Stacks Foundation.

WTF is Proof of Transfer (and Why Should Anyone Care)?

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