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The Wheels of Chance by H. G. Wells, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . OF THE ARTIFICIAL IN MAN, AND OF THE ZEITGEIST OF THE ARTIFICIAL IN MAN, AND OF THE ZEITGEIST You have seen these two young people—Bechamel, by-the-bye, is the man's name, and the girl's is Jessie Milton—from the outside; you have heard them talking; they ride now side by side (but not too close together, and in an uneasy silence) towards Haslemere; and this chapter will concern itself with those curious little council chambers inside their skulls, where their motives are in session and their acts are considered and passed. But first a word concerning wigs and false teeth. Some jester, enlarging upon the increase of bald heads and purblind people, has deduced a wonderful future for the children of men. Man, he said, was nowadays a hairless creature by forty or fifty, and for hair we gave him a wig; shrivelled, and we padded him; toothless, and lo! false teeth set in gold. Did he lose a limb, and a fine, new, artificial one was at his disposal; get indigestion, and to hand was artificial digestive fluid or bile or pancreatine, as the case might be. Complexions, too, were replaceable, spectacles superseded an inefficient eye-lens, and imperceptible false diaphragms were thrust into the failing ear. So he went over our anatomies, until, at last, he had conjured up a weird thing of shreds and patches, a simulacrum, an artificial body of a man, with but a doubtful germ of living flesh lurking somewhere in his recesses. To that, he held, we were coming. How far such odd substitution for the body is possible need not concern us now. But the devil, speaking by the lips of Mr. Rudyard Kipling, hath it that in the case of one Tomlinson, the thing, so far as the soul is concerned, has already been accomplished. Time was when men had simple souls, desires as natural as their eyes, a little reasonable philanthropy, a little reasonable philoprogenitiveness, hunger, and a taste for good living, a decent, personal vanity, a healthy, satisfying pugnacity, and so forth. But now we are taught and disciplined for years and years, and thereafter we read and read for all the time some strenuous, nerve-destroying business permits. Pedagogic hypnotists, pulpit and platform hypnotists, book-writing hypnotists, newspaper-writing hypnotists, are at us all. This sugar you are eating, they tell us, is ink, and forthwith we reject it with infinite disgust. This black draught of unrequited toil is True Happiness, and down it goes with every symptom of pleasure. This Ibsen, they say, is dull past believing, and we yawn and stretch beyond endurance. Pardon! they interrupt, but this Ibsen is deep and delightful, and we vie with one another in an excess of entertainment. And when we open the heads of these two young people, we find, not a straightforward motive on the surface anywhere; we find, indeed, not a soul so much as an oversoul, a zeitgeist, a congestion of acquired ideas, a highway's feast of fine, confused thinking. The girl is resolute to Live Her Own Life, a phrase you may have heard before, and the man has a pretty perverted ambition to be a cynical artistic person of the very calmest description. He is hoping for the awakening of Passion in her, among other things. He knows Passion ought to awaken, from the text-books he has studied. He knows she admires his genius, but he is unaware that she does not admire his head. He is quite a distinguished art critic in London, and he met her at that celebrated lady novelist's, her stepmother, and here you have them well embarked upon the Adventure. Both are in the first stage of repentance, which consists, as you have probably found for yourself, in setting your teeth hard and saying' “I WILL go on.” Things, you see, have jarred a little, and they ride on their way together with a certain aloofness of manner that promises ill for the orthodox development of the Adventure. He perceives he was too precipitate. But he feels his honour is involved, and meditates the development of a new attack. And the girl? She is unawakened. Her motives are bookish, written by a haphazard syndicate of authors, novelists, and biographers, on her white inexperience. An artificial oversoul she is, that may presently break down and reveal a human being beneath it. She is still in that schoolgirl phase when a talkative old man is more interesting than a tongue-tied young one, and when to be an eminent mathematician, say, or to edit a daily paper, seems as fine an ambition as any girl need aspire to. Bechaniel was to have helped her to attain that in the most expeditious manner, and here he is beside her, talking enigmatical phrases about passion, looking at her with the oddest expression, and once, and that was his gravest offence, offering to kiss her. At any rate he has apologised. She still scarcely realises, you see, the scrape she has got into. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. H. G. Wells (2009). The Wheels of Chance. Urbana, Illinois: Project Gutenberg. Retrieved October 2022, from https://www.gutenberg.org/files/1264/1264-h/1264-h.htm This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org, located at https://www.gutenberg.org/policy/license.html.

OF THE ARTIFICIAL IN MAN, AND OF THE ZEITGEIST

S treaming the 'spirit of the times' in culture / tech / startups / future and chill, every Tuesday ✌️ 📺📺📺 and Chill? Ultra HD Lioness Takedown 🍿 — “Intellectual” (and not) fodder for your streaming addiction what I’m binge-streaming on Netflix right now— The Stranger Night on Earth why I think you should binge it too— This show, while not intended to be hilarious, never misses an opportunity for relief—and whether phallic or llama-shaped in nature, every moment is a gosh-darn delight. Think meets Three words: English. Comedic. Timing. JoJo Rabbit Revenge. , though, (not) regrettably, still too soothing to keep me awake for a sustained length of time. Samira Wiley (Poussey Washington, Orange Is the New Black; Moira, The Handmaid's Tale) makes for a refreshing update on Attenborough latest Netflix news from around the web— written by for Netflix Tech Stack Has No Chill: How To Account for 15% of the World's Bandwidth Abhishek Kumar hackernoon raised by _ on Night on Earth on Netflix CGI? I watched about 20 minutes and I’m convinced its nearly all CGI. I thought the “low light thermal” cameras were just a way to hide imperfections in the rendering. When the lions attack things you can tell theyre not even tracked correctly...? Am I wrong? u/FlatBox reddit.com/r/vfx/ ( •_•)ノ墓ε*✝( ͡° ͜ʖ ͡°) The Cult of Coverage Around: #CoronaVirus 🤞 —kulture news to keep us all up-to-date & kewl this week what the kids are talking about — Coronavirus. some options for what you might say when you talk about it too — " Coronavirus Crisis Shows China's Governance Failure " : "As the Communist Party cements control, more officials worry about pleasing their bosses than taking care of the people." — nytimes other hot techulture news from around the web this week — Google (sort of) just launched a TikTok competitor: The new app is called and it resembles apps like TikTok and Instagram with its vertically-oriented short-form videos. What sets Tangi apart, however, is that the app is intended for how-to videos specifically, and creators need to apply to participate. Tangi — producthunt Europe has a plan to break Google and Amazon's cloud dominance : By now, you’ve likely come to terms with the fact that escape from Jeff Bezos is impossible. You may have weaned yourself off that sweet sweet next day delivery, procuring all your worldly needs from a boutique array of small local shops, but if you venture online, Bezos still wins – cutting out Amazon’s cloud computing services renders the . internet literally unusable Now Europe has a plan to challenge this US and Chinese cloud dominance – it's called Gaia-X. — wired 🤖🤖🤖 nobody listens to techno: AI predicts Coronavirus 🤯 —humans using their brains to talk/write about machines using their brains An AI Epidemiologist Sent the First Warnings of the Wuhan Virus : The US Centers for Disease Control and Prevention had gotten the word out a few days earlier, on January 6. But a Canadian health monitoring platform had beaten them both to the punch, sending word of the outbreak to its customers on December 31. uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan. BlueDot — wired 👩‍💻👩‍💻👩‍💻 Synchronous Communication, Thinking About Thinking About Thinking, Building Values-Driven Businesses stop start continue 💚 —new ideas around how to be a better colleague and/or human this week Synchronous Communication: stop — Synchronous Communication is the New Cocaine in Silicon Valley : Today's synchronous (real-time) communication tools and methodologies are increasing your company-wide anxiety quotient. — PSNinja Thinking About Thinking About Thinking: start — Lessons on Thinking: Learn from James Clear, Scott Young, Shane Parrish and More : Clear thinking is tied to how much we know about the world, our ability to learn continuously and building a latticework of mental models. — Andreea Serb Building Values-Driven Businesses: continue — 5 Prompts to Help You Define Core Values at Your Early-Stage Startup : Good core values should outlast founders. — IbaM 🎧🎧🎧 challenge thy ear holes with our weekly "I’d Hack To This" playlist 🎹 —curated by the Hacker Noon Team (mostly Austin ) that's all for today, folks! ✌️ see you next week, same time, same format (probably)

The Zeitgeist Digest 01—Tuesday, 4 February, 2020

A Dozen (or so) Learnings From 15 Years of Software Incident Management

সফ্টওয়্যার ঘটনা ব্যবস্থাপনার 15 বছর থেকে এক ডজন (বা তাই) শিক্ষা

Ein Dutzend (oder so) Erkenntnisse aus 15 Jahren Software-Vorfallmanagement

Una docena (más o menos) de aprendizajes de 15 años de gestión de incidentes de software

Une douzaine (ou deux) d'enseignements tirés de 15 ans de gestion des incidents logiciels

सॉफ्टवेयर घटना प्रबंधन के 15 वर्षों से एक दर्जन (या लगभग) सीखें

15 年間のソフトウェア インシデント管理から学んだ 12 の教訓

15년간의 소프트웨어 사고 관리 경험을 통해 얻은 12가지 정도의 교훈

Uma dúzia (ou mais) de aprendizados de 15 anos de gerenciamento de incidentes de software

Дюжина (или около того) уроков за 15 лет управления инцидентами с программным обеспечением

15 Yıllık Yazılım Olay Yönetiminden Bir Düzine (ya da O Kadar) Ders

Hàng chục (hoặc hơn) bài học từ 15 năm quản lý sự cố phần mềm

从 15 年的软件事故管理中学到的十几个经验

Like most people in tech, I have been enthralled by the possibilities of this new wave of AI. Machine learning has been in the zeitgeist for the greater part of the 2000s. It has powered things like your and recommendations long before ChatGPT came along. However, the simplicity of outcomes and how achievable this now is for the average joe is the real headline grabber. Amazon Spotify I am on a quest to better understand the foundational blocks of where this space is at. I expect this to be the bedrock of most modern software application building from this point on. As I continue to expand into the fog of war ( ), I expect this map to be refined and updated with time. shoutout to all the Age of Empires players out there Here is the skeletal outline of the pieces I have encountered so far — Basics about ML models Foundation Models Large Language Models Making the models useful Fine tuning RAG (Retrieval Augmented Generation) Inference Local LLMs You have to, of course, start with LLMs (Large Language Models), the space that OpenAI broke into with a sledgehammer. While there were plenty of incumbents in this space (namely models like BERT or proprietary domain models held closed-source by companies like Google or Meta or Spotify), ChatGPT pulled the rug on this space and brought things out in the open. Basics about ML models There is plenty of literature out there on LLMs and how they work (check the resources section for some of the good ones I encountered), but let’s get into some of the basics — Foundation Models Foundation Models [FMs] (or base models) are built using a LOT of data — the data we are talking about could be in the 100s of petabytes range, if not more. The purpose of this process is to go wide, not deep. Datasets could span several domains, formats, and timespans — all in the hope of pre-training the base model with unlabeled and self-supervised data. Foundation models are capable of performing a variety of general tasks such as generating text, visual comprehension, and conversing in natural language. Foundation models can be refined to develop more specialized downstream models for specific applications. You can think of Foundation models as being a superset of LLMs. Large Language Models Large language models are foundational models specifically trained on a massive text dataset. The refined output produced is a subset (or instances) of the Foundation models that are applied specifically to text and text-like things (eg. code). LLMs are still huge models when it comes to parameter count. A parameter is a value the model can change independently as it learns new things and the more parameters a model has, the more complex it can be. For eg. GPT is the LLM behind OpenAI’s ChatGPT. GPT-3 has 175 million parameters. GPT-4 is estimated to have a total of 1.76 trillion parameters. Creating LLMs consists of 3 main steps: Collecting the “right” datasets Determining the architecture used to process the datasets Executing training by processing the datasets using the architecture A bit more about the architecture The “Transformer” architecture allows the model to handle sequences of data like sentences and it allows understanding the meaning of each word in the context of the other words in the sentence. This way the model can comprehensively understand what the sentence is and what it means in aggregate. This architecture is trained on the datasets mentioned above and during the training process, the model is constantly adjusting its parameters based on how close the actual output is compared to the predictive output. It is trained until it produces about as close to the expected sentence structure in various scenarios. : Now that you know this, you know what GPT (Generative Pre-trained Transformer) means. In reverse, to follow things chronologically — > — The deep learning architecture used on the data > — The fact that it is already trained for usage, by using the datasets and parameters I mentioned before > — The ability of the model to construct expected sentence structures based on inputs (prompts) from the external world. Fun fact Transformer Pre-trained Generative Making the models usable Now you have these enormous models — either Foundation models or LLMs, but you want to use them to assist you in very specific problem domains. How would you do that? Well, there are 2 broad ways to do so: Fine-tuning RAG (Retrieval Augmented Generation) 1. Fine-tuning Large models can be trained on specific subsets/corpus of data to make them experts at certain tasks. This process is called “Fine tuning”. Fine-tuning helps with understanding the context of the question without requiring the prompter to provide additional information. It must be noted, that fine-tuning is a far less computationally intensive process than the training step for LLMs/FMs. (For more details, you can read ) this 2. RAG RAG or Retrieval Augmented Generation is a really complicated way of saying “Knowledge base + LLM”. It describes a system that adds extra data, in addition to what the user provided, before querying the LLM. Where did that extra data come from? Well, it could be from any number of external sources. As shown in the diagram above, based on the prompt provided by the user, the server system could fabricate a query that it believes would enhance the quality of the response provided by the LLM. To do so, it could query external knowledge sources (outside of the training data of the LLM) like: ephemeral data using vector database search indexes using Lucene another pre-trained LLM that responds with a very specific set of context This is the “Retrieval” step. Once the extra data has been received, the server then sends the prompt with this additional data (the “augmentation” step) to the LLM which “generates” the response sent back to the user. I recently read which rang the death knell on RAG by proposing an “Intelligent Agent” approach, but this approach doesn’t have widespread adoption thus far. this article Inference We already discussed how models get trained. The process of using these trained models to accept “live” inputs (i.e. prompts) from the user to make deductions of the response from the data, is called “Inference”. Naturally, this step can be pretty expensive if this is being run in the cloud, since for low latency outputs to be provided to the user, these inference systems need to be run on GPU compute. Local LLMs Something that I have been fascinated by is the “recent” (maybe 8 or so months old) phenomenon of running LLM inferences locally. Local could be your personal computer, your trusted network host, etc. It just means you don’t need to use cloud providers or 3rd party sources to run inferences. This has a few amazing benefits — Avoid the costs of running inference on the cloud or a third-party provider. Avoid vendor lock-in, since you could run these inferences on your commodity hardware. Data is yours, and you don’t need to worry about data corruption or leakage. There are a couple of pre-eminent players in this space particularly and . I have been using Ollama for the last week or so and have been amazed by the capabilities it unlocks. I can get into this in an upcoming post. Ollama LMStudio There are a couple of things required to make local LLMs happen — Now I must express, that these two points are not specific ONLY to local LLMs but to the broader model definition process. However, they become doubly as important when we talk about the local constraints. — When you can’t rely on cloud scale, obviously you are limited by the storage and memory constraints of your local hardware, There are several ways to reduce model sizes such as sharding, compression etc. One such technique is called . An LLM is represented by a bunch of weights and activations. These values are generally represented by the usual 32-bit floating point (float32) datatype. Quantization is the process of representing an LLM using something that has lower fidelity than 32 bits. It does mean that the accuracy of the model reduces, but so does its size and thereby memory requirements. Depending on the type of task you are conducting, that could be a worthy tradeoff. Model sizes quantization — There are several file formats to store LLM models for inference. Examples of these include GGML(GPT-Generated Model Language), GGUF (GPT-Generated Unified Format), GPTQ and the list goes on. GGUF has been a pretty popular format, especially for local LLMs since it allows for inference execution on the CPU, and uses the GPU (if available) only to speed up specific layers. While the CPU is slower than the GPU for executing this ( to get a look behind the curtains for the why), it enables inference on local computers like Windows and Macbooks. What a time to be alive! Model formats this is a great article That’s all I have for now. I’ll cover some other interesting aspects of Local LLMs and developing using them in an upcoming post. 👏 If this content is interesting to you, hit that button or subscribe to my newsletter here → . It gives me the feedback that I need to do more or less of something! Thanks ❤️ https://a1engineering.beehiiv.com/subscribe Resources https://www.youtube.com/watch?v=5sLYAQS9sWQ&t=2s&ab_channel=IBMTechnology https://aws.amazon.com/what-is/foundation-models/ https://deepchecks.com/glossary/model-parameters/ https://www.projectpro.io/article/foundational-models-vs-large-language-models/893 https://www.maartengrootendorst.com/blog/quantization/ https://medium.com/@phillipgimmi/what-is-gguf-and-ggml-e364834d241c https://aws.amazon.com/what-is/retrieval-augmented-generation

Decoding LLMs, Local LLMs, and RAG

Have you ever stumbled upon a meme that made you pause, not just because it was funny, but because it felt like a direct commentary on your life? Picture the "This Is Fine" dog, sitting calmly amidst flames, a cup of coffee in hand. It's funny, yes, but isn't it also a striking metaphor for how we often cope with chaos in our own lives? Memes have transcended their origins as internet jokes to become mirrors reflecting society's psyche. They're making us laugh, think, feel, and sometimes question. Let's dive into how these digital snippets have become the cultural artifacts of our time. Memes as Cultural Artifacts Consider the "Distracted Boyfriend" meme: a man turning his attention away from his partner to admire another. At first glance, it's just a funny take on infidelity. But if you stare at it for one too many seconds, you'll find layers of social commentary on loyalty, distraction, and the human tendency to desire what we don't have. Basically, it’s a modern take on ‘your grass is greener on the other side of the fence’. Memes like these capture the zeitgeist of our era, encapsulating complex societal norms and behaviors in a single image. Read: Elmo Checks In, Everything Is Not Okay: A Lesson in Empathy for Brands Virality and Relatability Why do certain memes, like the "Bernie Sanders at Inauguration" with his mittens, capture our collective imagination? It's their relatability. In Bernie's case, it was the universal feeling of wanting to be comfortable anywhere, even at a presidential inauguration. These moments go viral because they tap into shared emotions and experiences, making us feel part of a larger narrative. And we love to be part of something more than just ourselves. Memes and Social Commentary Memes often serve as a platform for subtle social critique. Take the "Area 51 Raid" meme, which started as a joke but soon evolved into a commentary on government transparency and collective action. What does it say about our society when a meme mobilizes hundreds to "see them aliens"? Dissecting Why Memes Work From a psychological standpoint, memes do more than just entertain; they fulfill several intrinsic human needs. At their core, memes can reinforce a sense of belonging by creating an 'in-group' where shared knowledge and humor signify membership. This aligns with Abraham Maslow's hierarchy of needs, where belongingness is a crucial step toward achieving esteem and self-actualization. Memes also serve as a vehicle for catharsis, allowing individuals to express frustrations, fears, and desires in a socially acceptable manner. The popularity of memes expressing existential dread or the absurdity of adult responsibilities speaks to a collective need to voice and validate our anxieties in a world that often demands stoicism. Furthermore, the virality of memes can be attributed to their simplicity and the cognitive ease with which they can be processed and shared. This simplicity, however, belies their complexity as cultural artifacts capable of influencing public opinion and shaping discourse. They act as a barometer for societal values, norms, and tensions, offering a snapshot of the zeitgeist in a way that is accessible and immediately relatable. The Future of Memes: Deciphering the New Lexicon Today, it is evident that memes have evolved into a language of their own—a lexicon so rich and nuanced that understanding a single tweet might require fluency in multiple meme dialects. Consider the depth of knowledge required to navigate the layers of meaning in a tweet that references not one, but five different memes. Each meme, a building block of a larger narrative, contributes to a complex web of cultural references that are instantly recognizable to the initiated. This phenomenon has created a unique in-group—those "chronically online"—who communicate in shorthand so dense that someone not versed in the latest internet lore might find themselves adrift in a sea of seemingly nonsensical exchanges. Take, for example, the statement about an unkillable mushroom: " ." Out of context, it's an absurd declaration. Yet, within the meme culture, it represents so much more. Reddit You cannot kill me in a way that matters It’s like memes have become the Rosetta Stone of the internet age, allowing us to share jokes, insights, and solidarity across linguistic and geographic boundaries. This way, we are basically compressing intricate thoughts and emotions into a format that is digestible and relatable on a universal scale. Conclusion So, next time you come across a meme that makes you chuckle or pause in thought, remember: you're engaging with a piece of cultural history, a snapshot of our collective psyche. What does that meme say about us, and what does our reaction to it reveal about our values, fears, and hopes? In the meme economy, every share, every like, every comment is a contribution to the ongoing discourse of our time. What will your contribution be?

Understanding Internet Culture: Why Are Memes Such a Hit?

Meta versus Apple: A Civil War Amongst VR Giants? It's hard to browse any media outlet or social platform without encountering the (AVP) plastered across a user’s feed—and for good reason. The Apple Vision Pro is truly . Apple Vision Pro impressive Perhaps more importantly, Apple has achieved something Meta has struggled to accomplish: capturing global attention and integrating Spatial Computing (VR) into the cultural zeitgeist. An influx of mainstream celebrities, thought leaders, entrepreneurs, and YouTubers have shared their thoughts, signaling it as the most novel and groundbreaking technology in recent memory. Within as little as a week, it appeared was stealing the show from the one company that had bet everything on making VR a reality— . Apple Meta For a quick historical background, modern consumer VR made its first appearance in 2013 when Palmer Luckey built and shipped the Oculus DK1. Funded by Kickstarter and VR enthusiasts, the DK1 introduced the idea that consumer VR was possible. It was in 2014 that Meta (then Facebook) bought into the vision by acquiring Oculus for $2 billion. Since then, Meta, through its Reality Labs department, has introduced many devices that have made the industry both consumer and venture-viable—from the PC-only enabled Oculus Rift (driving the first real wave of consumer VR) to now controlling a majority of the market share with the standalone Quest headsets. Meta’s headset growth has been objectively positive, selling over 25 million units, a remarkably high number compared to other manufacturers. Zuckerberg Strikes Back Until the release of the Apple Vision Pro (AVP), Meta’s products were viewed as esoteric and cringe-worthy, a result of poor marketing and a disconnect between Meta’s corporate-safe—may I say bland—branding compared to the young and edgy audience it needs to appeal to. After a week of standing in the shadow of the AVP, Zuckerberg released an unexpected video comparing the Apple Vision Pro to his latest Quest3 headset. The video has left viewers divided—primarily because of Mark's tone, which can be summarized as "factual, but defensive." Being a neutral third party that has invested ~$15m into the virtual reality industry in the last 2 years, let’s dissect some of Zuckerberg’s points. “Quest isn’t just a better value, but a better product, period.” - Mark Zuckerberg Quest is undeniably a better value. With a 7x price increase from the Quest 3 to the AVP, the difference is so significant that it's challenging to argue otherwise. However, there is some nuance to this point—the two brands are targeting different customer bases. The AVP appeals to buyers already part of the Apple Ecosystem—49% of Americans have iPhones, and 64% own an Apple Product. Already two weeks after launch, we're seeing consumers in the Apple walled garden become intrigued by VR tech solely as a consequence of Apple joining the ecosystem, irrespective of the growth of Meta or other VR companies. To take an opposing stance to Zuckerberg’s seemingly zero-sum view: Apple’s innovation is manifest destiny to expand the VR TAM and not a civil war for current market share. “Quest is better for the vast majority of what people use Mixed Reality for” & “We’ve designed it for many different things: Moving around playing games, socializing with friends, working out and more” - Mark Zuckerberg In comparison to immersive virtual reality, mixed reality via head-mounted displays is more nascent with fewer total applications built. While passthrough for mixed reality has been on headsets for a few years, it wasn’t until the Quest Pro’s (launched in late '22) color pass-through made it viable and enjoyable. In 2023, there was a tailwind for mixed reality development, with color passthrough launched on the Quest 3. The claim that mixed reality apps are better on Quest is debatable, as Apple’s approach for XR design thus far is oriented toward productivity (more skeuomorphic design akin to monitors) and passive consumption (movies). Meta’s vast number of apps on the other hand tend to focus on use-cases within gaming, more effectively enabled by their controller-based navigation. “Apple’s eye-tracking is really nice, but not good for all tasks, like typing” - Mark Zuckerberg Eye tracking is the next logical step in UI and software control—following the pattern of reducing friction between intent and action. Apple’s design and implementation are second-to-none, and more importantly, instantly intuitive for users who have never put on a VR headset. The Quest Pro had eye-tracking, but unfortunately, the feature was dropped in the Quest 3. Meta sees the mistake in not adding it and will implement it again. However, the looming cost of eye-tracking is that it is oriented toward consumption, not production. To have a productive work session, a Bluetooth keyboard is required. As for most games, hand tracking isn’t quite feasible either. “Quest’s Immersive Library is a lot deeper” - Mark Zuckerberg Apple’s silence and relatively close-to-launch announcement for the AVP left its App Store feeling barren and desolate, with only 600 apps. Meta’s library of Apps, across its main store, App Lab, and WebXR, greatly exceeds the total number of experiences available on the AVP. “In this next generation, Meta is going to be the open model, and I want to make sure the open model wins again” - Mark Zuckerberg The implication Zuckerberg had made here was that open tech ecosystems (akin to 90s-00s Microsoft home computer dominance) would return over the closed ecosystem of Apple that won on mobile for the last decade. Open source and cross-device interoperability are great—but it isn’t self-evident that Meta is building that ecosystem. While it runs on AndroidOS and supports WebXR, Meta’s app marketplace is notoriously difficult to get onto, needing a series of approvals to get on App Lab (Beta Apps) and even more approval to get to the main store. The ability to AirLink and sideload are behaviors more inclusive of an open ecosystem. The Takeaway Mark’s words were generally correct. The Quest 3 is a better value. The Quest 3 has more total use cases. Meta has a deeper library of content. However, Mark's need to assert something (without acknowledging any of the novel features of the AVP) seems like a reassertion of control that was lost with the entrance of Apple into the market. As for Meta's significant oversight in not having a headset that anyone could put on and have an intuitive understanding of—the hallmark of Apple UX—the Quest still presents too much friction for mainstream use. But this is likely to change over the coming months as Meta takes inspiration from the AVP’s best design choices. Neither camp should be underestimated in bringing VR to the masses, as Apple commands around 2 billion devices around the world that become enhanced by the Vision Pro, while Meta boasts 3.6 billion monthly active users across its platforms that can be guided towards its Quest line.

How Right Is Mark Zuckerberg in His Analysis of the Apple Vision Pro?

Every year, in early January, tens of thousands of tech aficionados descend on Las Vegas for the . It’s an event best known for capturing the tech world’s current zeitgeist; 2023 was heavy on , while 2022 revolved around . Unsurprisingly, CES 2024 was all about AI. , , … this year had it all. Customer Electronic Show (CES) EVs and sustainability improved hardware and gaming setups AI for headsets AI for babies AI for pets Obviously, the press unofficially crowns winners and losers at the end of the event. There is a variety of opinions on the losers ( ), but indisputable; . Google seems to be getting a lot of votes the winner is it’s the Rabbit R1 In short, R1 is a compact, AI-powered handheld device designed to streamline daily tasks. You talk into it like you would a walkie-talkie (by pressing a side button), and get the Artificial Intelligence to tasks historically done through apps. This includes, as per the demo, planning itineraries, ordering food, or booking a taxi. Speak, then validate with a click, without browsing / tinkering. The device is equipped with a 360° camera that allows it to “see” and better answer questions regarding the physical world. Finally a piece of software accessible via a PC allows its users to “teach” it repeatable tricks to save even more time. autonomously execute https://www.youtube.com/watch?v=22wlLy7hKP4&embedable=true Lauded for its efficiency and simplicity, the R1 is aiming to be a to our Tony Stark. A perfect assistant. , the company making it, has already pre-sold ! J.A.R.V.I.S. Rabbit at least 30,000 units Sadly, this ( ) cute piece of tech is severely over-hyped and doomed to fail. very The Rabbit R1: the Most Over-Hyped Project in the Tech World Right Now In , Rabbit’s founder contends that Amazon’s Alexa, Apple’s Siri and Microsoft’s Cortana may understand us, but are unable to complete actions. They’re a way to use Google verbally. Hardly . He portrays the Rabbit R1 as an AI companion able to do much more, from planning a complex holiday in a few sentence to accessing your favorite artists’ concert dates. And that’s a great idea! his keynote just assistants But it’s just idea. One idea . one that could easily and entirely fit inside a single app created by a larger player Rabbit may be the first out the gate (and props to them for that), but every single device maker has had the same plan for the past 18 months. . Microsoft recently announced , specifically for its Copilot AI assistant. , meanwhile, has been a Mac staple for a while now, and is also accessible at a click of a button. Even I’ve had this idea a year ago it is adding a new key to PC keyboards for the first time since 1994 Raycast The only reason we don’t have more examples is because natively integrating app in a vast universe of products and services takes time. This is however where the value will come from: a flywheel effect wherein an actor like Apple, being already connected to all your apps (and location) via iPhone iCloud data is able to better assist you by better knowing you. yet one and Having built a whole device for a functionality literally every smartphone is going to introduce and improve on in a few months, Rabbit is essentially just another . The only reason this is a separate device instead of an app is because the company needs to have unfettered access to a camera and microphone without Apple or Google stopping them. AI wrapper Which brings us to another obvious challenge: most individuals prefer carrying or using a single device, with their phones serving as the ideal choice ( ). My iPhone will soon do what the Rabbit does… and already does so much more, today. Should you purchase a Rabbit, it will absolutely stay home when you go out. when was the last time you bought a flashlight Then we get to the R1’s party trick. The device can connect to one’s apps (Spotify, Uber, Doordash…) to take actions on one’s behalf without having to visit said apps (with the user’s permission / login via a PC). This is neat… but what if tech giants like Meta or Google or Apple refuse to play ball and make integrations with the R1’s software more complex? And what if the apps no longer want to be accessed by an AI? This type of device could seriously hurt their ad or pull-through revenues. ; how will this be any different? We’ve already seen lawsuits aimed at OpenAI / ChatGPT Strategically, this is a massive vulnerability. On the other side of the spectrum, not only do large actors like Apple and Microsoft have a breadth of offers to concatenate, they also have the power to negotiate with apps makers to provide their services via AI… and pay them for it. Which leads us to the device’s economics. , an unusually low one-time (!) price for such a product. Again, good for them, … the R1 does not use fully local AI, so you’re using their cloud. And running a cloud is expensive ( ). It’s so expensive, in fact, that a one-time purchase rather than a subscription model makes little sense, and is unlikely to last. This means the company is likely to look for new growth avenues. If I were a betting man, I’d put my money on all the “privacy-first” promises disappearing when they realise data can be sold at a good price. The Rabbit R1 is priced at $199 but 110k$ a day for ChatGPT A local AI would have been a game changer. In the future, every device, such as TVs, cars, phones, and individual applications will come equipped with built-in natural language models. These models will be small, local and limited to their purpose. What we got instead is a Pokedex connected to the Cloud. Other issues, in bullet-points, because you only have so much time to study bad tech in details During CES, Google announced it was ’s “brain”. That obsolete functions include “Checking personal travel itineraries by voice” and “making a reservation”… which were both in the R1 demo! Google has enough data to know what it’s doing: no one is using an AI assistant to do these things. removing “under-utilized features” from its AI assistant The hardware looks cool, but is pretty dreadful in terms of wasted space; around 20% of the device is empty / unused. The keyboard works poorly (allegedly), which is unfortunate : people text input because they have needs that are detailed and complex, which are not easily expressed or recorded through voice. need AI hallucinations are not addressed. Since this is an AI and nothing else, how does one check the veracity of its statements? It’s supposedly very fast (though the problem with ChatGPT was never its speed). But in the demo, I wasn’t convinced it was faster than ChatGPT4. What if you're left-handed? I could be wrong about the R1. Its first batch sold out on day One and pre-orders are through the roof. It has generated considerable consumer interest. They are the first(ish) on the market with such a gadget, and though they will be trounced by Siri 2.0, the team should be proud. It definitely seems like the early days of a tech wave. There were all kinds of weird off-the-wall designs and ideas for phones at the beginning of the smartphone wave as companies were exploring to try and find niches and see what was possible. It’s kinda fun and I’m excited to see what other weird things people come up with. Good luck out there. Also appears . here

The Rabbit R1 May Be the Most Over-Hyped Tech Gadget at CES 2024

CES 2024-এ খরগোশ R1 সবচেয়ে বেশি হাইপড টেক গ্যাজেট হতে পারে

Der Rabbit R1 ist möglicherweise das am meisten gehypte Tech-Gadget auf der CES 2024

El Rabbit R1 puede ser el dispositivo tecnológico más publicitado en CES 2024

Le Rabbit R1 pourrait être le gadget technologique le plus surfait du CES 2024

रैबिट R1 CES 2024 में सबसे अधिक चर्चित टेक गैजेट हो सकता है

Rabbit R1 は CES 2024 で最も誇張されすぎたテクノロジー ガジェットになる可能性があります

Rabbit R1은 CES 2024에서 가장 과장된 기술 장치일 수 있습니다.

O Rabbit R1 pode ser o gadget tecnológico mais badalado na CES 2024

Rabbit R1 может стать самым разрекламированным техническим гаджетом на CES 2024

Tavşan R1, CES 2024'te En Çok Abartılan Teknoloji Gadget'ı Olabilir

Rabbit R1 có thể là tiện ích công nghệ được thổi phồng quá mức tại CES 2024

Rabbit R1 可能是 CES 2024 上最被炒作的科技产品

Meme coins, once just thought of as internet jokes, have undergone a transformative journey within the cryptocurrency space, marked by 3 distinct shifts. Their evolution mirrors broader trends in internet culture and creative expression, making us wonder about the potential fourth shift—a new era that could redefine meme coins' role and foster greater adoption within the Web3 landscape. Shift 1: Doge & Copy-Paste The narrative began with Dogecoin, a pioneer rooted in the dog/inu meme theme. Its astounding success, now boasting a market cap of around $13.8B, set the stage for future meme-based digital currencies. Initially, the meme coin space was predominantly occupied by dog or inu-themed tokens, following Dogecoin's trailblazing path and leading to the rise of another notable player, Shiba Inu. Most meme coins followed a wave of copy-paste until another turning point approached. Shift 2: Diverse Themes Pepe's success shattered the notion that the meme coin market was limited to dog-themed tokens. Pepe, a frog-themed meme coin, opened the floodgates for a broader range of creative concepts, sparking an explosion in meme coin creation. Many new tokens, inspired by various topics, surfaced on social media platforms like Twitter. While the majority initially resonated more with crypto-native communities, the trend is steadily expanding. Shift 3: Real-Life Events and Personalities The next notable trend in meme coins came from trending news and notable figures like Elon Musk. Musk’s influence in the tech world translates into substantial sway in cryptocurrency markets. The need for speed in terms of catching trends in real-time to launch memes in the essence of the moment is also interesting. For example, the meme coin Grok, affectionately linked to Elon Musk's AI program 'Grok’ or GFY (short for "go f--k yourself") inspired by Musk's interview where he directed those strong words toward advertisers withdrawing from his social network X. The success of a meme coin often hinges on its ability to resonate with the zeitgeist. Shift 4: From Niche to Brand Building The fourth shift hints at a potential evolution of meme coins into a new form of brand creation and community building. Drawing parallels with the trajectory of certain NFTs like Bored Ape Yacht Club (BAYC) and CryptoPunks, meme coins could transition from niche digital assets to globally recognized brands. Not everyone may possess the skills to design successful NFT art collections, but the ability to identify trending, meme-worthy topics is becoming more accessible. Advances in AI and content creation tools lower the barrier, ushering in a new era of meme coin creation. In this context, meme coins could transcend their initial perception as mere jokes or fun tokens, gaining more substantial value and community support. This evolution reflects the fluid nature of what constitutes 'money' and 'value' in an increasingly digital and interconnected world.

The Meme Coin Waves: More Than Just a Joke

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500+ HackerNoon humans voted asking what would happen in , overwhelmingly chosing the option that Sam Altman would eventually return to OpenAI as CEO. on our poll yesterday the unpredictable roller coaster ride that can only be described as an epic-fail, attempted coup by the (now defunct) OpenAI Board And HackerNoon readers are right! The last & final negotiation to ‘bring Sam back or we’ll quit’ by OpenAI employees and ‘bring Sam, or we’ll pull out” by OpenAI investors, led largely by Microsoft CEO Satya Nadella and the heavyweights of Silicon Valley (I’ll discuss them later in this article) finally came to its “happy ending.” The coup failed. Sam & Greg would now be welcomed, in their triumphant return, by 95% of OpenAI (738 out of 770 employees, per Bloomberg, signed the letter), a brand new Board, and more fame & power than ever! The smoking gun is still not out yet (and it’s unclear whether it will ever be clarified), but I’m still semi-confident that more research papers, lawsuits, and even policy changes will come out in the next months or years to shed light on what happened. And this is not the end of the turmoil at OpenAI just yet. But first, a quick recap To be caught up 100% on this drama, you should go ahead and read and . When we left off, Sam and Greg were still on their way out the door and to join Microsoft, to be (lol). A new interim CEO was announced (replacing the already interim CEO Mira Murati, who turned out to be a Sam loyalist): Emmett Shear, best known for being the ex-CEO of Twitch. Yup, Twitch. The game streaming platform. Nothing AI-related. my story on Friday, which announced and speculated on the details of Sam Altman’s firings the one on Monday, which laid out a chronological timeline of what transpired over the weekend just another corporate normie Satya Nadella, Microsoft CEO, while very positive and upbeat in all his and , indicated strongly that changes would absolutely need to be made on the Corporate Governance level, and there should be no more surprises for Microsoft, a 49% stakeholder, and the most important institutional partner of OpenAI. I read that as: Board has to be fired, and there’s no way Microsoft will be in this situation ever again with the new Board. public appearances annoucements And then, around midnight Tuesday, Nov 21/ early morning Wednesday, Nov 22 - Open AI you-know-what, the news that Sam & Co & most Silicon Valley optimists have been waiting for: announced SAM 👏 IS 👏 BACK 👏 That same announcement mentioned that the new Board of OpenAI will consist of Bret Taylor (Chair), Adam D’eangelo, and Larry Summer. Notably, it does not mention Sam Altman, Ilya Sutskever, Tasha McCauley, and Helen Toner. The /For-Profit Misalignment: The Bane of OpenAI’s Existence NonProfit I think the most plausible theory as to why the coup was allowed to happen is the following: the (now defunct) Board of OpenAI, a nonprofit that controls the for-profit LLC (go figure), is supposed to have no incentive whatsoever to maximize profit, which is the main point of the OpenAI that is the maker of the Chatgpt, that raised 13 billion from Microsoft, and that had a fiduciary duty to make money for its investors. All voting members of the Board, including Altman himself, hold no shares of OpenAI. Their mission, as stated in the company bylaws, is to “ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity.” In other words, the nonprofit Board, which oversees the for-profit LLC, , Microsoft computing powers (which is absolutely required to do the kind of research needed to roll out AGI), or the fact that OpenAI since the release of ChatGPT had become the de-facto zeitgeist tech company in decades. All it was interested in, and was legally required to oversee was the safe rollout of Artificial General Intelligence, or AGI. It was, in theory, perfectly happy not to make any more money, shrink, and return to a small elite research group. has no interest whatsoever in making money back for the investors This theory I thought, was the most plausible because (as mentioned in ) of the fact that I , OpenAI Cofounder and Chief Scientist, was part of the original Board faction that ousted Sam in the first place. (He later on regretted his decision and made a U-turn that it’s safe to say surprised absolutely everybody) He is a brilliant mind and is widely believed to be the brain of the Operation. In fact, he was courted to OpenAI by Elon Musk himself (from Google Deepmind), which, , caused an apparent fracture in Elon Musk and Google CEO Larry Page’s longtime friendship. The fracture at the time (back in 2015/2016) was around AI safety. Ilya cared about AI safety, and so did Elon, while Larry didn’t. So, Ilya became team OpenAI. my last story lya Sutskever according to Musk Another reason why I thought this is a fundamental disagreement/misalignment around AI Safety is the fact that Helen Toner, one of the 3 Board members who voted to oust Sam, recently that (as reported by the New York Times) was in favor of OpenAI’s direct competitor Anthropic and critical of OpenAI’s approach to roll out AGI. Anthropic, mind you, was created exactly because of this AI safety tension. Its founders are Dario Amodei, OpenAI’s former vice president of research, and his sister, Daniela Amodei, who was OpenAI’s vice president of safety and policy. Several other OpenAI research alumni were also on Anthropic’s founding team. Even weirder, Anthropic CEO Dario was reported to have been poached by the old Board re/ a potential merger with OpenAI (lol, the company it departed from in the first place) and refused. wrote a research paper And lastly, just yesterday, mere hours before the news of Sam and Greg’s triumphant return broke, Elon Musk, the original founder and investor in OpenAI himself, shared on his own owned platform X, a letter from “concerned” former employees of OpenAI about, among many things, a disturbing pattern of behaviors from Sam Altman and co, to not listen to the safety researchers. See the full letter . In other words, most of the people who have been in major disagreement with Sam re/ AI safety over the years have left. What’s left of OpenAI, for the most part, is Sam’s loyalists. here Meet the OpenAI’s New Board of Directors In the negotiation to have Sam Altman return as CEO, the (old) Board agreed to have these 3 initial individuals on the Board. So, let’s meet them. Bret Taylor Bret Taylor is one of the most well-connected and respected technologists in Silicon Valley. He is best known for serving as the former CEO of Salesforce, the leading company in cloud-based software services. But even more notably, Taylor played a pivotal role as the Chair of (the former)Twitter's Board of Directors, where he was instrumental in (forcing) the acquisition of Twitter by Elon Musk after the billionaire flip-flopped out of the 44 billion dollar deal (see , and ). here here here Larry Summer Lawrence "Larry" Summers is an American economist, former Vice President of Development Economics and Chief Economist of the World Bank, and former U.S. Secretary of the Treasury. He is best known for serving as the 27th President of Harvard University. During his tenure at Harvard, Summers sparked controversy with his comments about women in science, suggesting intrinsic differences in aptitude between men and women could be a reason for the underrepresentation of women in science and engineering fields. These remarks led to widespread criticism and played a significant role in his eventual resignation from the presidency of Harvard. Go figure. Adam D’Angelo Adam D'Angelo the CEO of Quora, a popular question-and-answer website. Prior to Quora, he was the Chief Technology Officer at Facebook, and might also have been one of its many cofounders besides Mark Zuckerberg. Most notably, he’s the only standing member of the OpenAI Board that will still serve in this new board. Yup, the Board that ousted Sam in the first place. Hmmm a superb business deal-maker ( ), an influential albeit controversial economist would not have bode well with the ousted board members, both of whom women!), and a mysterious CEO who rarely gave interviews (nobody knows why Adam (allegedly) ousted Sam, even to this day)… those are the people who we current have controlling the fate of the arguably most influential technology of our time. the only adult in a room who could make Elon adhere to his legally binding contract to buy Twitter (Larry’s sexist comments about women's intellect Concluding thoughts (hopefully for the last time on this saga, for now) AI might be the most important technology of this decade and the decades to come. But the story unfolded this past weekend just shows us how incredibly flawed the people under peril of whose it’s being controlled are. Savvy tech + flawed humans = pretty disastrous combo, IMHO. No matter how flawed, irrational, and seemingly out of their mind insane the now-defunct OpenAi board seems in their decision to fire Sam; there’s still a big, giant, and humongous elephant in the room that is the event that triggers the decision in the first place. It was reported that Sam has fundamentally agreed to a thorough investigation upon returning. Until then, I will remain skeptical at best at this new Board’s ability to simultaneously uphold OpenAI’s lofty mission to save humanity from the super smart robots (paraphrased) while making lots of money simultaneously. Seems a paradox, just like capitalism, effective altruism, and human beings for that matter.

On OpenAI Failed Board Coup of Sam Altman & the Danger of Leaving AI Fate in the Hands of a Few

স্যাম অল্টম্যানের ওপেনএআই ব্যর্থ বোর্ড অভ্যুত্থান এবং কয়েকজনের হাতে এআই ভাগ্য ছেড়ে দেওয়ার বিপদ

Über den gescheiterten OpenAI-Board-Coup von Sam Altman und die Gefahr, das KI-Schicksal in den Händen einiger weniger zu lassen

Sobre el fallido golpe de Sam Altman en la junta directiva de OpenAI y el peligro de dejar el destino de la IA en manos de unos pocos

Sur l'échec du coup d'État de Sam Altman au sein du conseil d'administration d'OpenAI et le danger de laisser le destin de l'IA entre les mains de quelques-uns

ओपनएआई के असफल बोर्ड पर सैम ऑल्टमैन का तख्तापलट और एआई का भाग्य कुछ लोगों के हाथों में छोड़ने का खतरा

OpenAI 失敗したサム・アルトマン取締役会クーデターと AI の運命を少数の手に委ねる危険性について

OpenAI에서 Sam Altman의 실패한 이사회 쿠데타와 AI 운명을 소수의 손에 맡길 위험

On OpenAI fracassou no golpe de Sam Altman e o perigo de deixar o destino da IA nas mãos de poucos

О неудачном перевороте Сэма Альтмана в совете директоров OpenAI и опасности оставить судьбу ИИ в руках немногих

OpenAI'nin Sam Altman'ın Başarısız Yönetim Kurulu Darbesi ve Yapay Zekanın Kaderini Birkaç Kişinin Ellerine Bırakmanın Tehlikesi Üzerine

Về cuộc đảo chính thất bại của Sam Altman trong hội đồng quản trị OpenAI và nguy cơ giao số phận AI vào tay một số ít

论 OpenAI 失败的 Sam Altman 董事会政变以及将 AI 命运留在少数人手中的危险

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Why Cronos Accelerator is the Launchpad for Next-Gen AI and Blockchain Startups Welcome to our special feature where we delve into the groundbreaking work of the Cronos Accelerator, the program aimed at catalyzing innovative startups at the intersection of blockchain and AI. Today, we have the privilege of speaking with , a prominent figure in the tech space, to shed light on how is fostering innovations that are shaping the future of blockchain technology and AI. Charlotte Kapoor Cronos Ready to transform your vision into reality? Join the Cronos Accelerator and be part of a future where innovation thrives. Register by November 24th, 2023 at . https://cronos.org/accelerators Hi Charlotte, it’s an honor to have you here for our "Behind the Startup" series. Can you share with us a bit about your professional journey and your involvement with Cronos Accelerator? Ishan Pandey: Thank you. Before joining the Cronos Labs team in January this year, I was a Partner at Outlier Ventures. I spent 5 years at Outlier where I spent time understanding the needs and requirements of web3 startups. I now oversee all aspects of the Cronos accelerator strategy and execution, my responsibilities encompass diverse areas, ranging from assisting teams with founders fundraising efforts and investor relations, to refining teams positioning and preparing projects for token launches. Prior to my venture into the blockchain space, I had a background in communications, which allowed me to gain valuable insight into consumer behavior. Charlotte Kapoor: Ishan Pandey: The vision behind Cronos Accelerator is intriguing. Could you elaborate more on how Cronos is shaping the convergence of blockchain and AI and fostering innovations in this realm? We see the confluence of crypto with artificial intelligence as a powerful accelerant. Blockchain technology is maturing and AI brings unparalleled speed and efficiency to take products to market. It's hard to find two technologies more of the zeitgeist, by 2025, the market size of Web3 and AI is projected to reach $39.7 billion and $126 billion, respectively, this offers ample opportunities for builders to create impactful and user-centric products. Charlotte Kapoor: The Cronos accelerator works with numerous businesses at this intersection including Google Cloud and Amazon Web Services (AWS). AWS and Google Cloud offer AI-related workshops and mentorship sessions to the participating projects. It’s founders that are looking to leverage this opportunity that we are keen to work within the accelerator. Ishan Pandey: There are a myriad of accelerators focusing on blockchain and AI. What distinguishes Cronos Accelerator from the others, and could you share some insights into the future directions and plans of Cronos? The Cronos accelerator is focused on building practical use cases to drive increased adoption of dApps, that genuinely attract users and contribute to real-world usage. We are looking for teams that help to grow the market, building on the primitives that are already there. We extend an open invitation to builders with original concepts and the willingness to turn them into a working product. We’re looking for novel proposals that solve real problems while demonstrating ingenious uses for AI, blockchain, and decentralized technology. We want to continue to grow our vibrant ecosystem which currently has over 500 dApps and partners to help deliver on our mission is to make it easy and safe for the next billion crypto users to adopt Web3. Charlotte Kapoor: Ishan Pandey: Accelerating mainstream adoption of AI and blockchain is crucial for the evolution of technology. How is Cronos playing a pivotal role in this, and what initiatives are underway to broaden awareness and utilization of Cronos’s offerings? While big tech has favored centralized AI models, Web3 aims to democratize AI for broader accessibility and neutrality. Consumer applications, one of the key areas of focus for the accelerator, are likely to lead the way in adoption, poised to drive rapid innovation, building on the Cronos chain offers a significant advantage, granting access to our ecosystem partner 's 80 million active user ecosystem. Charlotte Kapoor: Crypto.com Cronos is designed with the mindset of bringing billions of everyday users into the Web3 world powered by multiple public chains. Built on the Cosmos SDK while being Ethereum Virtual Machine (EVM) compatible, Cronos is uniquely positioned to connect the EVM chains and Cosmos ecosystem to enable seamless crypto assets and dApps interoperability in the multichain world. Developers on Cronos can benefit from the support of Cronos Labs, a Web3 startup accelerator and ecosystem development fund. Builders and creators can tap into its $100m EVM fund. Ishan Pandey: AI and blockchain technologies have the potential to redefine multiple industries, including finance. In your perspective, what transformations can we anticipate in traditional sectors with the advent of these technologies, and how is Cronos contributing to this change? Businesses globally are looking at how they can adopt AI to promote the efficiency and performance of their human workforce. Based on more than 600 startup applications that the Cronos accelerator program has evaluated so far we’ve seen innovation from AI and blockchain technology in almost every area of industry. Charlotte Kapoor: In terms of Cronos’s disruption, it is designed to support the creator economy with Web3 applications such as DeFi and GameFi, ultimately serving as the foundational infrastructure for an open metaverse. As an open-source Layer 1 blockchain, Cronos aims to massively scale the Web3 user community by providing builders with the ability to instantly port apps and crypto assets from other blockchains. This contributes to the scaling of an open metaverse, enabling users to experience the full promise of self-custody of digital assets fundamentally transforming the way users share and create value. Ishan Pandey: As we witness the synergy between AI and blockchain, how do you perceive the societal implications of this integration, and what proactive measures is Cronos implementing to navigate the shifts in the technological landscape? The convergence of AI and blockchain is mutually beneficial. If AI is used properly, it can enhance the abilities of decentralised networks, enabling them to process data faster and make better decisions in hashing algorithms. While decentralizing AI aims to make it more accessible and neutral by democratizing it. Charlotte Kapoor: The Cronos accelerator is looking for teams who are looking to harness the power of both technologies and use them for real world applications that benefit society. To give some examples, this could be projects using blockchain to deliver improved access to AI, offering censorship resistance or finding ways to authenticate a specific AI model that is being used by a dApp. There could also be projects that are using AI to enhance the Web3 experience e.g. chat bots or no-code algo trading bots that help abstract complicated UX. Or in the consumer dApps space, AI-powered gaming infrastructure where non-playable characters can change and react to what the player does, or applications that embrace and cater to AI agents. The technological landscape is shifting quickly and we see a lot of room for apps that offer Web2-like interfaces driven by Web3 tech, solving real-world needs. Are you a startup eager to innovate and make a significant impact in the realms of blockchain and AI? You can still apply to the Cronos Accelerator and accelerate your venture in the thriving ecosystem of Web3 and AI! Apply for the Cronos Accelerator now at - Registration closes on the 24th of November, 2023. https://cronos.org/accelerators A big thank you to Charlotte for offering invaluable insights into the Cronos Accelerator and how it’s nurturing startups to build the next generation of blockchain and AI innovations. Stay tuned for more insightful discussions on the developments reshaping the tech landscape. Don’t forget to like and share the story! : Vested Interest Disclosure This author is an independent contributor publishing via our . Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR brand-as-author program

Discover the Next Big Thing in AI & Blockchain with Charlotte Kapoor:  Cronos Accelerator

শার্লট কাপুরের সাথে AI এবং ব্লকচেইনে পরবর্তী বড় জিনিস আবিষ্কার করুন: Cronos Accelerator

Entdecken Sie mit Charlotte Kapoor das nächste große Ding in KI und Blockchain: Cronos Accelerator

Descubra la próxima gran novedad en IA y Blockchain con Charlotte Kapoor: Cronos Accelerator

Découvrez la prochaine grande nouveauté en matière d'IA et de blockchain avec Charlotte Kapoor : Cronos Accelerator

चार्लोट कपूर के साथ एआई और ब्लॉकचेन में अगली बड़ी चीज़ की खोज करें: क्रोनोस एक्सेलेरेटर

シャーロット・カプールと一緒に AI とブロックチェーンの次の大きなことを発見しましょう: Cronos Accelerator

Charlotte Kapoor와 함께 AI 및 블록체인의 차세대 혁신을 발견하세요: Cronos Accelerator

Descubra a próxima grande novidade em IA e Blockchain com Charlotte Kapoor: Cronos Accelerator

Откройте для себя новое большое достижение в области искусственного интеллекта и блокчейна вместе с Шарлоттой Капур: Cronos Accelerator

Charlotte Kapoor ile Yapay Zeka ve Blockchain'de Bir Sonraki Büyük Şeyi Keşfedin: Cronos Hızlandırıcı

Khám phá điều quan trọng tiếp theo trong AI & Blockchain với Charlotte Kapoor: Máy gia tốc Cronos

与 Charlotte Kapoor 一起探索人工智能和区块链的下一个重大事件：Cronos 加速器

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Building a presence in the crypto ecosystem, and capturing the customer opportunities that arise from it, can be daunting for non-native businesses. Oftentimes, knowledge gaps can work to reinforce stereotypes that the space is inscrutable, or off-putting for the uninitiated. Thankfully, crypto companies are stepping up to break down these barriers by putting digital asset transactions within reach for companies that want to tap into the growing zeitgeist. New platform-as-a-service (PaaS) offerings are becoming common access points for businesses of all sizes looking to quickly level-up their presence and/or performance in the digital economy. Finding the pathway best suited to your organization requires the consideration of several key benefits, and strategic deliberation in selecting the right PaaS partnership. How can the right PaaS provider serve your business and its customers? Read on… Diversify your offerings Walk into any retailer and you’re bound to see something that, at first glance, seems out of place. Crisps at the DIY shop. Clothing hawked at the grocer. Umbrellas for sale at the mechanic. However, what at first feels incongruous is actually the result of careful study by the proprietor to engage more fully with their customers. These little add-ons can serve crucial functions as tools for navigating the world, or provide light refreshment for folks as they go about their day. With this line of thinking, integrating crypto services can be like putting gum and candy by the register. Regardless of a businesses’ scope of sale, the continued growth and acceptance of digital assets in global finance presents a case for broadening such offerings. Where a chocolate bar can offer a brief boost of energy, the purchase of digital assets can help fortify consumer feelings of inclusion, and diversified financial empowerment during periods of evolving usage. Business leaders in the space often partner with legacy and emerging service providers in an effort to maintain an inviting, intuitive transacting environment for their customers. From credit/debit cards, to bank transfers, and branded payment services like PayPal, Google Pay, and Apple Pay, PaaS integrations grant additional customer throughways for the participating business. As such, the management of customer data pertaining to these payment rails is also handled by the PaaS provider as part of the overall agreement, taking a significant load off company resources. Once the API is mapped to the businesses’ exact specifications, proprietors can rest easy knowing their crypto storefront is fully operational and ready to further bond customers with your brand. Customizable API Speaking of tailoring crypto offerings, most PaaS integrations offer businesses the opportunity to pick and choose accommodations that best suit their clientele. The digital economy is itself a constellation of projects and protocols, and zooming in on each constituent part often reveals an ecosystem in its own right. Most crypto companies operate in a similar fashion. They can encompass instant buy and sell rails for select digital assets, custodial wallet services, trading platforms, and where regulations permit, opportunities to participate in staking and saving programs. However, by choosing a PaaS partner with a customizable API and experienced account team, businesses looking to tap into this additional revenue stream can ensure services are UI/UX-optimized for client-specific needs. Once you’ve partnered with a PaaS and launched offerings, the partnership can also offer unique insight into how solutions are being embraced by customers post-integration. Perhaps you’ll learn that they prefer to buy digital assets, or conduct fiat-to-crypto or crypto-to-fiat conversion, or sell crypto they acquired elsewhere. By isolating these patterns through backend dashboards, proprietors can track customer usage, and further tailor their business’ available crypto offerings. Going forward, physical and online vendors alike stand to benefit from integrating and refining a suite of best-in-class crypto services to align with customer demand. Not only can responding to such behavior increase customer loyalty, but correctly anticipating community needs can help put your business ahead of the pack. Stay agile Going beyond the choice architecture of products mentioned above, integrating DeFi services can help businesses keep pace in a changing economy. While regulatory uncertainty lingers in some regions, the majority of world markets agree on the usage and inclusion of digital assets in the global monetary landscape. Companies that questioned crypto during its early days would be right to reconsider their approach in light of changing sentiment. Not to mention, it’s never been easier to adapt and compete with the aid of a trusted crypto guide. While the overall nature of payments is trending to the digital, users in all jurisdictions are becoming less invested in their native fiat currencies. Whether due to popular trends in the case of meme tokens, or savvy placements informed by white paper research observed with more trusted digital assets, individual users remain the lifeblood of the crypto ecosystem. Since it’s easier than ever to transact with a minimal digital footprint, retail usage is increasingly informing how leaders conceptualize development within the crypto space. For non-crypto native proprietors, it can be difficult to know where to prioritize one’s efforts. Thankfully, PaaS integrations make crypto solutions more accessible by alleviating the pressure put on businesses to navigate the global regulatory landscape, by sharing their reputation, resources, and expertise. Leapfrog licensure PaaS offerings place a premium on simplicity, which in large part stems from the convenience of jumping on existing regulatory licensure. In essence, businesses that integrate with a PaaS can piggy-back off established good standing, to extend the offering of trusted DeFi services. This can help expedite the availability of new verticals to any enterprise, while ensuring that all products and access remains above board, and in accordance with the highest industry standards. In light of recent and ongoing litigation in the space, choosing a crypto partner with tenured experience complying with regulators can circumvent major headaches down the line. Rather than starting from scratch on complex, and often regionally-specific application processes, it’s worth considering a partner who’s already blazed those trails with a proven track record of success. In the current landscape, this can require the expertise of legal, compliance, and financial professionals working in concert to apply for and maintain all necessary licensure. This often requires regular audits to ensure services are being properly conducted, and that customer data is handled in accordance with local regulations. To engage in an industry of near-constant flux, it’s critical to partner with trustworthy service providers who can manage the thornier contours of the digital economy. Strength in numbers Many forget that the phrase “jack of all trades” is rightly followed by the rejoinder “master of none.” While anyone can dabble, it takes dedication to truly grasp a field or discipline. And sitting at the intersection of finance, technology, and economics, crypto requires a broad skillset before understanding can be achieved, let alone mastery. That’s why partnerships and collaborations are essential for functioning and remaining relevant in a shifting marketplace. By joining forces and integrating with a PaaS, businesses stand to gain a legion of nested solutions to augment their existing offerings. But choosing to partner with a legacy crypto leader is more than just an integrated set of customizable amenities. Reputable crypto companies are composed of experts and enthusiasts tasked with safely streamlining access to the digital economy. This helps ensure a high caliber of service, and fosters a professional environment that strives to anticipate customer needs. By maintaining a posture of self-reflection, responsible PaaS providers undergo near-constant refinement and innovation to meet and resolve change. That way, proprietors can more strategically apply their energy, and rest assured knowing a trusted crew is standing by if the waters get choppy.

5 Reasons to Integrate Your Business with a Crypto Platform

Facebook struck launch gold with Threads, passing 100 million users in its first week by creating a frictionless sign-up via Instagram and keeping the product simple. In doing so, Threads has - despite the predicted drop-off that has it averaging around 20 million daily active users - cemented itself as Meta’s first successful product launch since Facebook. The surprise launch and stronger-than-expected user numbers of the “Twitter-killer” to be has invited pundits to take a trip down memory lane and recall all of the times Meta botched similar roll-outs: “Snapchat killer” Poke, “Gmail killer” Facebook E-Mail, “bitcoin killer” Libra, “FaceTime killer” Portal, “iPhone killer” Facebook phone, and so on and so forth. But there’s one lesser-known failure that is rarely given a proper look despite being a natural product extension and clear multi-billion dollar opportunity: Facebook Gifts. The Tale of Facebook Gifts Facebook Gifts was announced at the end of 2012 in a : the social network allowed users to send gifts to friends, with special emphasis on the previously-almighty Facebook birthday, engagements, or other life achievements. company blog post The gift-giver would select a gift, attach a digital card, and hit send. The recipient would see a “wrapped” gift on their wall, open it to reveal the gift and a personal message, enter their physical address, and receive the gift a few days later. Facebook even offered the recipient the opportunity to modify colors, sizes, and flavors, or exchange the gift for something of equal value. This may read like feature creep and a cheap attempt to jumpstart Meta’s struggling social e-commerce efforts in 2023, but it’s important to remember the context of 2012: when Facebook was a birthday juggernaut. The Facebook birthday became so prevalent and part of the zeitgeist, multiple articles were penned by people who described being . At its peak, an estimated 20% of one’s Facebook friends could be expected to post on your wall, resulting in an average of more than 100 notifications on one’s birthday. overwhelmed by the volume of birthday wishes Birthdays were such a high-traffic part of the Facebook experience that company product manager the question, “How would you improve Facebook Birthdays?” interviews once included The improvement of choice became deeper engagement: Facebook Gifts was born. Analysts and reporters were bullish on the concept, sure Gifts would turn into a profit center worth hundreds of millions in revenue. The Facebook Gifts marketplace launched with typical gift fare: chocolates, stuffed animals, and gift cards. If that doesn’t excite you, you’re not alone. So few people purchased physical gifts that Facebook pivoted the product to focus on digital gift cards. The pivot kept the feature afloat, but Facebook made a few errors that kept it from ever truly taking off. Facebook, which has never been shy about leveraging its interest graph and user data to drive advertising outcomes, prevented Facebook Gifts from doing the same. It seems like there are so many simple opportunities: Facebook knows who my dad is, when it’s his birthday, that he likes golf, and (probably, at the time) a bunch of location data that would have enabled a meaningful offer from any major golf brand. Targeted commerce transactions with clear attribution, like the one I just described, would be an easy sell for a direct-to-consumer brand or online re-seller, but Facebook’s sales org never got a crack at it as they instead chose to focus on mass appeal. Even those who enjoyed the Facebook Gifts experience likely never got to use it for a second full cycle: if your mom enjoyed the Facebook Gift she received in 2013, you had to go find it elsewhere in 2014. Facebook’s convictions were so weak here, they shut it down after about a year. The biggest miss isn’t the millions (or billions) of incremental revenue they should have earned in the past decade; it’s they didn’t take advantage of this window of opportunity to build a strong commerce arm that they so sorely need today. Their current efforts to deliver commerce on social (primarily via Instagram) are still clunky, and they’re still struggling to onboard great partners. Their failure to activate the next layer of birthdays on Facebook accelerated the drift into irrelevance for Facebook's Birthday. By my own experience ( ), Facebook birthdays are down 90% from their peak a decade ago. and confirmed by others While a person might expect to receive more than 100 birthday messages on the platform in 2013, that number has shrunk to 6-12. This is despite adding 1.6 billion new users since then - all of whom have birthdays. To their credit, Facebook to keep birthday engagement alive. In 2013, they started notifying you when your friends had birthdays. In 2014, they started doing cards, and in 2015, prompted people to leave video birthday wishes. tried The platform started creating celebratory videos from previously-uploaded content in 2016 and rolled out birthday charity fundraisers in 2017. But this doesn’t seem like innovation or anything that leads to the kind of opportunity they fumbled with Gifts. It reads like desperation to re-capture that Facebook birthday magic, and trying a little too hard. Coupling this trend with the rapid fragmentation of social media, with people retreating into their niche social networks and private group corners where they find more signal and less noise, it should be no surprise that Facebook features have also splintered off. Startups like use some special magic sauce to create a single-use app that brings birthdays back to the basics: ensuring that you don’t become that bad friend who misses your friend’s birthday. Birthday App Birthday App doesn’t push you to post publicly or over-complicate things, they just encourage simple engagement with your friend on their special day. It’s not surprising the app is gaining traction, but it is interesting to see Gen Z talk about it on Tik Tok, especially given their general distaste for Facebook and lack of history with the Facebook birthday experience. If recent history is any indication, it won’t be long before Facebook attempts to capture that Gen Z attention with a standalone Birthday app of their own - likely with a sign-on via Instagram.

Facebook’s Not-So-Happy Birthdays Offer New App Opportunity 

111 Stories To Learn About Building The Metaverse

Let's learn about via these 54 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Seo Techniques /Learn Repo Read all about the Tips, Tricks & Strategies to up your SEO game. 1. An Introduction to Local SEO and How it Can Add Profitability to Your Business Local business owners like a bakery, cake shop, food vendors, etc. need to optimize your website for local SEO. Read to know more about these effective tactics 2. Proven Tips and Tricks to Write a Great SEO Blog Post Struggling to rank your article on page#1? Check out my tips on writing a great SEO blog post. 3. 5 Ways to Protect Your Website From Google Penalties Learn how to protect your website from google core updates and penalties. Explore how to convert every Google algorithm update to opportunities. 4. A Brief SEO Checklist for 1-Person Teams Don't have hours to do SEO? Try to at least do everything on this checklist. 5. 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Many SEOs and my clients ask me this questions all the time. 50. A Beginner's Handbook for Search Engine Optimization A Search Engine Optimization (SEO) handbook for beginners in the context of Information Retrieval, with a focus on organic search results. 51. How Can I Boost My Organic Click-Through Rate (CTR)? Organic Click-Through Rate is the number of clicks on an organic result vs the total number of impressions. Here are some SEO tactics to help boost your CTR. 52. 25 SEO Mistakes That Will Hurt Your Website Rankings in 2020 53. 12 Actionable SEO Tips Guaranteed To Boost Your Organic Traffic I agree, most lists of SEO tips are overwhelming. 54. SEO, Data Science & Correlative Analysis For Google Organic Traffic This article will touch on how data science can be used in SEO and look at how correlative analysis should be used during the content creation process. For those not familiar with these topics, there will be examples and pictures but as should be expected when covering any complicated topic, the scope of the article will be limited to the main purpose. Thank you for checking out the 54 most read stories about Seo Techniques on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

54 Stories To Learn About Seo Techniques

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