Øyvind connected with Machine Learning evangelist and product manager Avi Latner, and lifelong gamer and management consultant Andreas Edesberg, finding an exciting common ground in their passion for creative technology. They found their first investors, incorporated the company, Sloyd was born, ...

Sloyd: Empowering Creators with Innovative 3D-Creation Tools

Sloyd is enabling creators to make 3D assets really fast and really easy.

Sloyd - Crunchbase Company Profile & Funding

We shared our thoughts along with a list of companies leading the way here: https://lnkd.in/gVnk-_Un ... 🚀 The Games Factory Talents | Connecting Passion &amp; Talent event is just around the corner, and the incredible sponsored challenges are happening right now: 🔮 Sloyd in-a-Ball Render ...

Sloyd | LinkedIn

We have a variety of sloyd knives ideal for carving spoons, bowls, ladles and other deep hollowed work.

Sloyd Collection - Flexcut Tool Company

Sloyd motivates its employees to accept increased responsibilities and fosters the spirit of teamwork amongst them. We actively appreciate talent and believe in maintaining a synergy between the wisdom &amp; knowledge of our experienced professionals and the fresh ideas of young talent. As an equal opportunity employer, we are actively looking for candidates who are aggressive, willing to learn and capable of driving innovation for the company...

Sloyd Ventures

Slöyd is a historical Scandinavian method of education that used woodworking to develop character in children. Still utilized today in some of the highest performing schools around the globe, key elements of the original Theory of Educational Sloyd by Otto Salomon have been replicated and ...

Sloyd Experience

Information on valuation, funding, cap tables, investors, and executives for Sloyd. Use the PitchBook Platform to explore the full profile.

Sloyd Company Profile: Valuation & Investors | PitchBook

Sloyd Ventures Private Limited | 540 followers on LinkedIn. NO MORE COMPROMISES BE SURE AS GOOD AS NEW | Sloyd’s sole purpose of existence is to pilot, pivot and commercialize new-generation business models based on simple but innovative consumer products and/or services conceived for the ...

Sloyd Ventures Private Limited | LinkedIn

A new platform for ecommerce with their innovative recommerce business wherein used electronic goods are within the reach of the masses.

Sloyd Ventures - Crunchbase Company Profile & Funding

Wood carving tools. Our Sloyd Knife comes razor sharp and ready for use.

Flexcut Sloyd KN50 - Flexcut Tool Company

Sloyd offers a three-dimensional (3D) modeling platform. It features a constantly growing library of generators and easy customization through sliders and toggles. The platform is primarily designed for video game developers. The company was founded in 2021 and is based in Oslo, Norway.

Sloyd - Products, Competitors, Financials, Employees, Headquarters ...

SLOYD VENTURES PRIVATE LIMITED - company information, business information and directors/partners details

SLOYD VENTURES PRIVATE LIMITED - Company, directors and contact ...

Founded by Andreas Edesberg, Avi Latner in the year 2021 · Provider of AI-powered 3D modelling software with UV-unwrapping technology

Sloyd | Tracxn

Sloyd (Swedish slöjd), also known as educational sloyd, is a system of handicraft-based education started by Uno Cygnaeus in Finland in 1865. The system was further refined and promoted worldwide, and was taught in the United States until the early 20th century.

Sloyd - Wikipedia

Welcome to Michigan Sloyd. I&#x27;m Dawson and I make all the things you&#x27;ll find here in my home shop in Harbor Springs, MI. Be sure to check out the videos and my instagram for a more detailed look into my process. About

Michigan Sloyd

Check Sloyd Ventures Private Limited registration details online. Get financial highlights, company network &amp; industry details. Sign Up now for more reports &amp; updates

SLOYD VENTURES PRIVATE LIMITED - Company Profile, Directors, Revenue ...

Instant customizable 3D assets! We create the models using a fancy algorithm, giving you unique results every time, so that you can get back to building your game.

Sloyd

For the past decade AI has been about automating the most mundane and repetitive tasks. Humans were still in charge of doing the creative work and the thinking. The boundary between humans and machines was clear. Machines can compute but humans write the algorithm. Or AI can help fix a photo that a human took. That type of automation brought a lot more opportunities than challenges. As a society, it held a promise that if we were able to utilize it properly, it would free up more time for relationships, self expression and creativity. Those things that give us meaning, things that are the core of our humanity. Then recently and more so in the past year, generative AI came into fruition. Stable Diffusion, Dalle, Midjourney and the likes can create professional images based on a text prompt and GPT-chat can answer questions and write essays. The machine has become creative! And that will shake up the boundary between humans and machines. It is going to make us question the core of our humanity. How will we operate in a world where a machine can effortlessly make every drawing and write any essay? What do we value and what will give us meaning? And why even bother to put an effort into anything? This is not about protecting jobs For the artists among us, there’s an added ironic twist. Not only could generative AI threaten their livelihood and make them question the meaningfulness of their life pursue, but also the machine does so by copying their work. Any artists’ work that’s put online is scraped without copyright approval, trained on and reproduced into new variations. If you copy from one person that’s plagiarism, but if you copy from everyone it’s potentially considered and is also untraceable. fair use No wonder that widespread protest has begun. Artists in Artstation, a website for showcasing CGI art and illustrations, to ‘no AI’, and that has forced Artstation to and now every item can be marked as ‘no AI’ indicating that it is not allowed to use it for training AI. That’s a change in the right direction, it forces AI companies to adhere to ownership rules. However it will not stop the automation of art all-together and it shouldn't. changed their profile picture change it’s policy Changing professions because of a technological breakthrough is inevitable. We’ve been through that cycle many times before. Elevator operators are a thing of the past. There aren’t many travel agents left, and there are many more examples. There is even precedence in creative work, the invention of photography drastically reduced the number of realistic artists, and later on the digital camera changed the photography industry. Moreover, it’s not ethical to try to stop technology to save jobs. That will be preferring the rights of a few, those whose jobs are threatened, over the rights of many others, those who can enjoy the fruits of this automation. But there are ways to tackle this threat. There are ways to replace jobs that will be lost to generative AI In a Pew Research conducted in 2017 most experts believed that just as some jobs become obsolete even more new jobs are created. Based on historical trends, the World Economic Forum that automation will create Twelve million more jobs than it relinquishes. survey estimated in 2020 I tend to think more like that under the current economic system, where capital always seeks to grow, all cost savings gained by automation is reinvested into production and people keep producing. But that people produce more to no end. New jobs are created, more products and materials are consumed, yet quality of life doesn’t increase. Therefore Jason, and other progressives, think that by slowing growth we can use those cost savings to provide everyone with a universal basic income and free up their time. Time that people can use for creative pursuits. Jason Hickel Whether we look at the near term, where jobs are transformed but not lost, as the World Economic Forum thinks, or at the longer term where we work less and consume less as Jason Hickel hopes, there’s a roadmap for tackling job loss. But a conversation has to start about how to preserve human creativity in an age of creative machines. Ethics in generative AI Ethics in AI used to be about creating , about upholding while under constant surveillance by software with face and object detection. Then when generative machine learning started ethics expanded to in a world with deep fakes, and about . All of those are true but there’s something wider at stake. Ethics in creative machine learning should also be about keeping humanity in humans. unbiased systems privacy rights preventing the spread of fake copyright In dystopian science fiction, such as space odyssey, the threat is always that the machine grows a self-will and violently turns against people. Reality is not turning out anything like that. Who would have thought that the machine would threaten us by drawing pictures and writing essays? Here are a few suggested policies that we should consider if we want to shape a fair, just and meaningful future. Some policies are more near term, others are harder to attain. But if human ingenuity can invent those machines it can also invent the policies to govern them. It must, our future depends on it. Update creative licenses - for the use in AI training Every piece of original creation: photos, art or code has a license that defines what can be done with it. Some creations are free, others offered for royalties. Some can be used for any use including commercial usages and others are just for private use and research. And so on. Using third party work to train a machine learning model is a new use-case. Therefore it needs to be a new category in licensing. A work is either allowed for machine learning training (for free or for royalties) or not depending on the license. Sloyd (the author is a co-founder) has artists creating 3D models and model parts especially for AI and they are compensated for it. When training data becomes more scarce, creators who will come up with new ways of expressions will have more time to enjoy the fruits of that new creative avenue before it is imitated by a machine. Or, those creators can decide to sell their creations for training AI at a fair value and cash out on their new creations quickly. Models already trained on mass public copyright protected work should belong to the public Then there are models already trained on vast amounts of creations without consent. ‘The ship has sailed’ and it cannot be undone. on what to do with past work that’s been used in training will go on for years, and the machine learning that’s out there now will be used billions of times before the litigation is settled. Litigation Moreover, there’s no fair way of redistributing the value created from those machines back to the creators. If the wealth cannot be redistributed, the next best thing to do is to offer it for free to the public. a dataset of links to images and matching descriptions used for text to image training, is already a non-profit (though it does not filter out based on copyright restrictions). Stability AI, the creator of stable diffusion, is an open source generative machine learning company. Using their machine is free and they make money out of add-ons. Similarly, as a settlement to get out of litigation, other companies will need to offer their machine learning tools for free or split up that product to a separate company who runs it as open source. LAION That might sound far fetched, but the FTC is already considering of breaking big tech companies to increase competition. Using the same policies to govern the biggest technology shift of our lifetime is not far-fetched. such policies Value AI that boosts creativity rather than diminishes it Companies and individuals designing and training AI should think about ways to empower people to be more creative. Technology review brings a where the machine enhances creativity and does not replace it: Text-to-image plugin into Photoshop; a Stable Diffusion plugin to Blender, and text-to-image widget for Office. few examples At Sloyd we think about AI assisted creation rather than created by AI. We started with a focus more on the automation of 3D models for environment and game props since most 3D artists love working on characters for their games but could use help automating the rest. We use paid community creators to create the training database and that database will always expand so there will always be creative human input into it. We try to provide ways to have direct manipulation of objects with user inputs so that users have better control of the output. In this case, the suggestion is an ethical guideline and not a policy suggestion. However, if we have a clear ethical guideline, in time we’ll be able to suggest a policy to support it. Factor in the true cost of training - including environmental impact We pay for electricity based on the cost of extraction of raw material and production, the environmental cost is not factored in. That’s true for every use, for heating and light and also for data centers running AI. Data centers of the total US energy and that share is expected to grow to 8%, to a large part driven by  AI energy consumption that . Training machine learning consumes a lot of energy, but also inference (using a trained model to create an output) is a resource intensive job. Right now it’s hard to find data on how much energy inference consumes and that’s part of the problem. With home appliances we know how much energy is consumed, we even have energy ratings. Why don’t we have similar energy ratings in software? (this was proposed by Øyvnind Sørøy, my colleague in Sloyd). consume about 2% doubles every 3 months If we start measuring and if we have to pay the true cost of energy, then in many cases we will find that the same objective could be achieved much more efficiently by a different type of automation or by more efficient AI. This is part of a bigger green revolution, but with data centers expected to be 8% of consumption and that in addition to home and office software consumption, software and AI in particular cannot be exempt. The discussion around generative AI ethics and policy has only just begone The options creative machines open are profound but so are the implications. If we can imagine the future we want, a future where humans find meaning through creativity, we can start putting the right guidelines to ethical generative machine learning. The ideas provided here can be a baseline for future policies, or maybe better ideas will come up. One thing that certain is that the understanding of implications and the discussions on the measures we’ll take is just starting.

Creative AI ‘Shakes’ the Core of Humanity and Requires a Broader Discussion About Ethics

La IA creativa 'sacude' el núcleo de la humanidad y requiere un debate más amplio sobre la ética

L'IA créative « ébranle » le cœur de l'humanité et nécessite une discussion plus large sur l'éthique

क्रिएटिव एआई मानवता के मूल को हिलाता है और नैतिकता के बारे में व्यापक चर्चा की आवश्यकता है

創造的な AI は人類の核を「揺るがし」、倫理についてより広範な議論を必要とする

IA criativa 'sacode' o cerne da humanidade e requer uma discussão mais ampla sobre ética

Trí tuệ nhân tạo sáng tạo 'làm rung chuyển' cốt lõi của nhân loại và yêu cầu thảo luận rộng rãi hơn về đạo đức

创造性的人工智能“动摇”了人类的核心，需要更广泛的伦理讨论

Exploring the Prolonged Slump in iPhone Sales and Strategies to Reignite Growth Apple, a tech titan renowned for its innovation and groundbreaking products, faces one of the in two decades, primarily driven by sluggish iPhone sales. longest streaks of sales slowdown In this post, we delve into the underlying factors contributing to Apple’s sales dip, examine the evolving smartphone market, and explore strategic measures the company can adopt to reignite growth and maintain its industry leadership. Unraveling Apple’s Sales Slowdown: A Shift in Market Dynamics Over the past two decades, Apple has been at the forefront of technological innovation, setting trends and captivating consumers with its flagship product, the iPhone. However, the recent streak of sales slowdown points to a shift in the dynamics of the smartphone market. One of the key contributors to Apple’s sales dip is the . As smartphone technologies mature, the gap between each new iPhone iteration narrows, reducing the incentive for users to upgrade frequently. prolonged upgrade cycle Consumers are increasingly content with holding onto their devices for longer periods, affecting Apple’s revenue growth. Moreover, increased competition from rival smartphone manufacturers has intensified pressure on Apple. Android-based devices, offering a plethora of options at various price points, have lured consumers away from the iPhone ecosystem, challenging Apple’s market share. Exploring the Evolving Smartphone Market and Consumer Preferences The smartphone market has evolved rapidly over the years, with significant . In this era of technological advancement, consumers seek more than just a device for communication; they demand a holistic digital experience. shifts in consumer preferences and behavior Apple’s focus on hardware and software integration has long been its competitive advantage. However, consumer preferences have extended beyond just hardware specifications. Customers now prioritize seamless integration with services, ecosystems, and wearables, seeking a comprehensive and interconnected digital lifestyle. Furthermore, the rise of budget-friendly and mid-range smartphones has democratized technology access, making advanced features more affordable and accessible to a broader audience. As consumers embrace these alternatives, Apple faces the challenge of catering to a diverse and evolving market while retaining its premium positioning. Reigniting Growth: Strategies for Apple’s Future Success To overcome the sales slowdown and chart a path to sustained growth, Apple must embrace innovative strategies that cater to changing market dynamics and consumer preferences. As smartphone sales face challenges, Apple can capitalize on its existing ecosystem to create additional revenue streams. Services such as Apple Music, Apple TV+, and Apple Arcade have shown promising growth, underscoring the potential of expanding its services division. 1 — Diversifying Revenue Streams: Investing in new services and enhancing user engagement can fuel revenue growth and reduce dependency on hardware sales. Apple’s legacy of innovation is the bedrock of its success. By continually pushing the boundaries of technology and design, Apple can recapture consumer excitement and inspire brand loyalty. 2 — Embracing Innovation: Exploring emerging technologies, such as augmented reality, artificial intelligence, and wearable devices, can position Apple as a pioneer in future-oriented solutions. While Apple enjoys a strong market presence in developed regions, emerging markets present untapped opportunities for growth. 3 — Nurturing Emerging Markets: Tailoring products and services to suit the unique needs and preferences of these markets can enable Apple to expand its customer base and drive sales in regions with immense growth potential. Conclusion Apple’s prolonged sales slowdown, particularly in iPhone sales, presents both challenges and opportunities for the tech giant. As the smartphone market evolves and consumer preferences shift, Apple must adapt to maintain its position as an industry leader. By diversifying revenue streams, embracing innovation, and nurturing emerging markets, Apple can reignite growth and build a resilient future. As the company navigates this transformative phase, its ability to innovate, cater to diverse markets, and deliver seamless experiences will be crucial to sustaining success in the highly competitive technology landscape.

Apple’s Sales Slowdown: Unraveling the Challenges and Charting the Path Forward

How to maintain healthy social media hygiene in an age of data exploitation and misinformation If you use the internet at all (which I assume you do if you’re reading this), you’ve probably received at least ten emails within the past week about updated for the apps and services you use. This is in response the the EU’s recent revision of the (General Data Privacy Regulation), which went into effect on May 25th, limiting the amount of data that can be collected — and how it can be used — by businesses. But, while the risks of data privacy are permeating through the consciousness of governments of as a result of high-profile events, including the during the 2016 US election and the recent , it seems that the general public has not yet internalized these risks, nor the fact that they are more relevant to us . That’s why I’d like to propose a shift in the conversation to what we, as users, can do to change our digital behavior and adapt to the ever growing data-economy and the risks associated with it. privacy policies GDPR corporations fake news controversy Cambridge Analytica scandal than anybody else Consumer Responsibility Proposition While we should, of course, put pressure on , and other platforms, themselves, to shift their policies and adhere to stricter standards, I would propose that the onus is at least partially on us —the users — to respond responsibly, and change our behavior to reflect the changes taking place in the digital world. While some have taken the route of deactivating or deleting their Facebook accounts altogether, the majority of users has gone on as if nothing happened. Neither of these is an ideal approach. Let’s look a simple analogy: Facebook social media If your wallet was stolen out of your back pocket, what would you do? A) Stop carrying a wallet altogether B) Expect wallet producers to start selling theft-proof wallets C) Put pressure on governments to impose heavier penalties on wallet thieves D) None of the above Most likely, your answer would be D, and you would simply start keeping your wallet in your pocket. Similarly, we, as frequent users of these data-driven platforms, cannot leave it entirely to those institutions who use — or regulate the use of — our data, to solve the problem completely. front Therefore, I propose a set of guidelines for those of us who have opted to remain connected — for which there are still many good reasons — so we may responsibly adapt to the changing digital environment. Because as the price of data goes up, so does the risk associated with dealing — and providing— it. How you sustain a business model in which users don’t pay for your service? do First, I believe some clarification is in order. What, really, is Facebook’s business model? They do not , as many tend to . They do, however, sell a user targeting service, which makes use of your data, to allow advertisers better reach their intended audience. sell your data believe Facebook’s business model is entirely ad driven, as made clear by founder Mark Zuckerberg in his recent regarding the Cambridge Analytica scandal. supreme court hearing With a better understanding of how Facebook uses our data, I believe we can better decide how to prevent it from being used in undesirable ways. I’ve created a convenient flowchart for your simple understanding, as well as outlined the steps in detail below, through each of which we will note the flow of data as essential theme, it being the bloodline running through the today’s social media industry, and the asset so valuable to advertisers: Users engage on Facebook, liking posts and pages, generating data on those users’ interests. Data generation through activity: Facebook aggregates that “liking data” into a set of generalized profiles, associating likes of a particular subject (person, place, movie, etc. etc) with the users’ personal information (age, gender, sexual orientation, etc.). They can then use these profiles to “predict” characteristics of the user that have not been explicitly stated (political ideology, religion, even intelligence level) . Data aggregation and profiling: Side note: I’d encourage all my readers to try this tool to see exactly how your likes can inform a general profile quite accurately (and don’t worry, the results are not stored and are used ONLY for informative purposes). Facebook uses these profiles to offer advertisers options to select of their target audience, making sure that ads reach the people who are likely to buy their product or service, or at the very least, give it a . Using profiles for targeted advertising : incredibly specific qualities most click More join the platform, and Facebook can increase ad prices. Facebook gets more and more revenue from advertisers, who recognize that it is the best advertising platform for a return on investment. advertisers As Facebook’s revenue increases, they can increase their budget for marketing, product development, and R&D, all of which serve to gain new users, and create a more “sticky” experience for existing ones, thus ensuring the generation of more and more new data. More users → more data. Facebook’s cycle of data gathering and use for targeted advertising. Note that nowhere in the process does the advertiser get to your — the user’s — data. There is no way for them to associate your name with your generalized profile (likes and interests), and as such, your personal privacy is relatively safe when the data is in the . But, we would be in error to believe that those are so adept as to avoid any or all fumbles, or that they don’t have an agenda of their own. So, despite the relative improbability of a future breach, there are still several concerning aspects to the usage of our data which I believe everyone should be aware of: ACCESS right hands right hands This problem is widely known and has been covered endlessly in relation to the Russian interference in the 2016 US presidential election, so I will expound more on problems 2, 3, and 4. Corruptibility of political campaigning and the integrity of democracy . Facebook also has the ability to profile your friends, solely based on activity (i.e. the activity and resulting profiles of a given user’s friend group). Referred to as , this method is actually what generates such incredible value to advertisers; they can accurately target individuals who may not have explicitly expressed their interests (through likes), but are simply connected to people who have. As such, by generating these profiles-by-association, Facebook ads can reach a much broader audience. What this means for the user, however, is that your likes can influence the ads that your friends see, and vice-versa. Exponentiation of profiling by association. your lookalike targeting Facebook’s data collection is not only limited to the activity contained within the platform itself, but is spread all across the web. From third party websites who have opted in to the Facebook Audience Network (“ ”), to apps that link with your Facebook profile, your data is going from your phone (or browser) into Facebook’s hands, making targeting even more accurate. Businesses can also track a user’s activity on their own website after launching an ad campaign on Facebook, and then based on that activity. Apart from resulting in more relevant ads, these operations represent a serious privacy threat which could reveal the most personal details about an individual — or even family — if compromised. Data from anywhere, data from everywhere. the power of Facebook ads, off Facebook tailor future ads As Facebook’s newsfeed algorithm gets to know what you views and interests are, it will start showing you a stream of content designed to ensure the highest likelihood of engagement (i.e. likes). What this means is that you’ll end up only seeing stories and content which reflect the viewpoints you already possess, leading to a cycle of belief reinforcement called . In the long run, this causes extreme polarization — making liberals more liberal, and conservatives more conservative — leading to more conflict, rage, and misunderstanding in the digital ecosystem. Echo chamber effect as a result of Facebook’s algorithmic feed, which shows users what they to see. want the echo chamber effect Not to mention other non-data-related risks posed by Facebook in the realm of . mental health What is social media hygiene? While we could go endlessly down the rabbit hole about the potential for data exploitation and the future possibilities opened up by , the last thing I want to do is provoke any kind of panic or paranoia. It’s certainly not a lost cause, and I am not trying to condemn Facebook as “evil”, nor will I inveigh my readers to delete their social media accounts completely (update December 2018: my position has changed, and I have argued that , and have since deleted my account. But for those who are not willing to go to such lengths, please read on). Rather, I will offer a few recommendations, which will allow us to make the most of our digital experience, without sacrificing the integrity of our data, our privacy, and quality of content we see. This is what I call practicing good “social media hygiene”. AI Facebook is evil very simple Tighten your grip on privacy Perhaps to it’s own dismay, Facebook does offer tools to configure from where and for what your data is being gathered and used. It’s simple to opt out of some of the more exploitative operations — that is, if you know to look. Therefore, I’d like to encourage my readers to take a vigilant approach to the settings we choose to enable, such as opting out of ads driven by data from third party and : where websites applications Go to “Settings” “Ads” and “Ad settings” to opt out of data sharing from third party websites. Go to “Settings” and “Apps and Websites” to opt out of data access from third party applications. Less likes, more comments Likes, and more recently “ ”, are a very simple tool for Facebook to gauge what a user is interested in (read: what a user “likes”). Therefore, by liking (or reacting to) fewer posts, we would be providing for Facebook to profile us — as well as our friends — leaving another, perhaps more constructive option for engagement — commenting. reactions less data Commenting can create a more meaningful connection between you and others by opening the door to two-way communication. As opposed to choosing from a preset list, commenting allows us to be more creative in our reactions, e.g. pointing out the intricacy of composition in a photo upload, or telling a friend about your experience in a mutual location on a “check-in” post. Commenting also opens up the possibility for learning new things. Ask questions, contest a viewpoint (a healthy debate never hurt anyone), offer tips, advice, experience. By sharing our knowledge and experiences on an individual level, rather than passively letting people’s lives scroll in front of our eyes, we can choose to maximize the gains of our social media usage — capitalizing on individuality, not generality, for the sake of mutual understanding, not for status or self-gratification. Avoid the skewed reality of Facebook’s Top Stories algorithm Does a Facebook post exist if no one’s there to like it? Due to the increasing amount of content shared, and to maximize user engagement, Facebook changed the way it presented information to users by introducing “Top Stories” in . Top Stories shows users content it “thinks” they will like, agree, and engage with. 2011 Top news stories are selected by the social networking system based on a ranking algorithm that incorporates an analysis of affinities for interests, users, and entities in the social networking system based on user interactions. (Quote from Facebook Inc.’s patent application: ) Selectively providing content on a social networking system As we have seen, such selectivity of content in our feeds could lead to some unintended negative consequences (namely, the echo chamber effect). But psychological effects aside, when we are exposed only to stories, we are seeing only that — the top — the surface — of what is really going on in our communities and within our network of friends. We are missing everything under that surface, that which may be liked by fewer users, but is nonetheless insightful or thought-provoking, inspiring or entertaining, — a joke or an observation, a photo of a sunset or a story about a recent scientific breakthrough. top The option can be found by clicking the three dots next to “ ” “Most Recent” News Feed Social media has made it possible for us to be anywhere in the world through photos and videos; to engage with people in different locations, of different cultures, with widely different backgrounds and worldviews, all in real time, all with the touch of a finger, all of which we can experience if we just look below the surface. And to do so, we simply have to switch to the “Most Recent” option on our news feed. Disassociate yourself Not from your friends, not from Mark Zuckerberg, but from yourself — the social media representation of yourself, that is. By changing your name on social media to one that is on legal agreements, IDs, and government documents, you’ll be able to distance your real-life activities from your virtual ones. In other words, whatever records of you there are in the real-world (purchases, contracts, mailing lists, etc), will not be attributable to your Facebook profile, and vice versa, in the case of a breach on either side. not found There are also several other good reasons for changing your name on social media, which I’ll leave for a future article. Choose who you follow wisely Given that any person nowadays can create a public Facebook page, relating to any topic of interest, any sub-culture, worldview or belief, in addition to the abundance of pages for public figures, obscure or renowned, it’s easy to understand that there are plenty of sub-par quality pages out there, some with not-too-pure intentions — whether to spread false information, sway opinion, or simply gain undue popularity. To filter out that poor quality content and make your feed fresh, fun, and informative, I’ve come up with a three-point recommendation to help guide our following decisions. Following a page, especially that of a high profile subject, does not necessarily give credit to the associated person or organization, as those pages are more often than not run by PR agencies, fans, or irrelevant parties. And as we’ve already learned, your like could reveal more about you to advertisers than you might expect. First: Follow pages for lesser known figures and organizations to make more of an impact. , and not only because they already have a large following. Virality is not a testament to consistent quality. Second: Follow individuals and organizations you can attest to of Facebook off While many news outlets can be legitimate, some are outright fake (read: do not publish real news), while others simply have an extremely biased agenda. On social media, it’s often hard to distinguish between the three, leading users to believe false information or adopt a one-sided view. For now, it’s best to get your news elsewhere (a newsletter, for example). Third: Keep news to a minimum. Now, with a newfound understanding of Facebook’s targeting, algorithms, and the implications of our engagement, let us continue forth into the digital utopia of social networking with a fresh attitude and a clean perspective. Let’s wash our hands of our old, careless ways of liking following, and immunize ourselves to the risks of misleading content. In doing so, we will strengthen our connections, express ourselves more genuinely, and gain maximum fulfillment from our social media experience, all while being confident in the integrity of our virtual actions and the effects they may have on the ourselves, our friends, and on society. Disclaimer: While Facebook is mentioned often, the principles above are can be easily adapted and applied to most other social media platforms, including Instagram, Twitter, and even LinkedIn.

Escaping from cyber-slobdom

Photo from pexels.com For a few weeks now, I have wanted to write an article about the slow-down of old iPhones. This desire started when I was having online conversations about it. In those conversations, many people did not understand clearly what was happening. Then I went to the Store to get my MacBook Pro fixed. On the way, I discovered that my Lyft driver totally misunderstood the problem. The final straw was that the Apple technician at the Genius Bar also did not understand the problem. Apple Then Apple announced that it was offering a $50 discount on battery replacement for old iPhones, and I assumed that that was the end of the matter, and that this article would be redundant. But no, people were still saying, “Apple slowed down old iPhones to make us buy new iPhones!” Apple write code that runs intentionally more slowly on older iPhones so that people would be forced to buy newer iPhones. Apple also get caught red-handed by people who found that replacing their battery sped-up their old iPhones. did not iOS did not What Actually Happened In the most recent releases of iOS, Apple added an algorithm intended to increase battery life and reduce shut-downs related to brown-outs in phones containing old batteries. A brown-out is a sudden loss of power. The intention of this was to user experience on older phones. improve An unfortunate, but somewhat anticipatable, result was that the old phones slowed down. This slow-down was noticed by some users who then reported it on social media. They discovered that replacing the batteries with new ones resolved the slowdown issue. Apple then reported that it had added this new mechanism for managing old batteries. Apple’s claim was supported by the reports of new batteries fixing the problem. I also replaced my battery in my iPhone 6 Plus, and my phone functioned at a normal speed again. All the evidence points to the fact that Apple was honestly trying to improve the experience for users of older phones containing older batteries. I imagine that it’s very hard to beta-test those battery management algorithms because it would require lots of old phones containing aging batteries. So Apple made a poor judgement call, and determined that releasing an iOS that extended battery life and reduced brown-outs on older batteries outweighed the potential, and perhaps unquantified, device slow-down effect. Apple made a mistake, and when it discovered that it had made a mistake, it was open and transparent and offered a solution: to replace the batteries at a large discount ($50 off). Apple didn’t need to do this. Apple had done nothing wrong. Old batteries are old and don’t work as well, and Apple had been trying to improve the performance of those older batteries. If Apple’s intention had been to simply slow down older models, it would have been much easier to make the new versions of iOS run more slowly on the older models, regardless of battery health. Determining the health of the battery and slowing down based on that would have been a completely unnecessary effort. Conclusion Apple acted with transparency and integrity. Apple was clearly trying to improve the experience on old iPhones, and it made a mistake. Yet most people seem to have heard Apple’s message and discounted almost all of it. Many people choose to hear only, “We slowed down old iPhones,” and then they insert a false additional message of “because we want people to buy the new models.” There is no evidence to suggest that Apple intentionally slowed down old models to make people buy new models. It’s also extremely unlikely that Apple would employ such a lack-mentality to business. Apple creates and enlarges pies; Apple does not desperately grasp at existing pies. I’m sure that Apple wants us to buy the new models, but it’s focused on making the new models faster and richer featured. Companies like Apple know that it’s not worth behaving unethically, because at some point those unethical behaviors will leak and harm the brand. If you liked this article, then give it some claps. If you didn’t like it, then tell me why in a response. If you want to read more like this, then follow me here on Medium.

The Truth About The Old iPhone Slowdown Fiasco

In 2013, A Time Traveler Warned Us About Our Bitcoin Future. How Right Was He?

2013 সালে, একজন টাইম ট্রাভেলার আমাদের বিটকয়েন ভবিষ্যত সম্পর্কে সতর্ক করেছিল। তিনি কতটা সঠিক ছিলেন?

2013 warnte uns ein Zeitreisender vor unserer Bitcoin-Zukunft. Wie recht hatte er damit?

En 2013, un viajero en el tiempo nos advirtió sobre nuestro futuro Bitcoin. ¿Cuánta razón tenía?

En 2013, un voyageur temporel nous a mis en garde sur notre avenir Bitcoin. Dans quelle mesure avait-il raison ?

2013 में, एक समय यात्री ने हमें बिटकॉइन के भविष्य के बारे में चेतावनी दी थी। वह कितना सही था?

2013 年、タイムトラベラーがビットコインの将来について警告しました。彼の警告はどれほど正しかったのでしょうか?

2013년에 한 시간 여행자가 비트코인의 미래에 대해 경고했습니다. 그는 얼마나 옳았습니까?

Em 2013, um viajante do tempo nos alertou sobre nosso futuro Bitcoin. Quão certo ele estava?

В 2013 году путешественник во времени предупредил нас о будущем биткойнов. Насколько он был прав?

2013 Yılında Bir Zaman Gezgini Bizi Bitcoin Geleceğimiz Konusunda Uyardı. Ne Kadar Haklıydı?

Vào năm 2013, một người du hành thời gian đã cảnh báo chúng tôi về tương lai Bitcoin của chúng tôi. Anh ấy đã đúng như thế nào?

2013 年，一位时间旅行者警告了我们比特币的未来。他说得对吗？

Inflation has brought a level of uncertainty to Wall Street in 2024 despite a record-breaking Q1 performance for the S&P 500. With much of the growth driving US markets down to the ongoing generative AI boom, could the threat of confounding consumer price index (CPI) data cause the GenAI bubble to burst? The first quarter saw the S&P 500 cross the 5,000 barrier for the first time as a watershed moment in a sustained rally that coincided with the launch of OpenAI’s ChatGPT generative AI large-language model (LLM). The index rallied more than 30% since the November 30th 2022 release of ChatGPT towards a peak of over 5,250 before the news of resurgent inflation rates forced a timely reality check. As news that CPI inflation data for March 2024 came in at a hotter-than-expected 3.5% increase in the same period in 2023, the S&P 500 tumbled back below 5,000 in a 5.46% dip from its peak in late March. Although US markets have become accustomed to high inflation data, there had been optimism that 2024 would see multiple Federal Reserve rate cuts taking place as inflation cooled. Confounding figures appeared to spark Wall Street to snap out of its long-term rally and address the prospect of higher-for-longer rates. Looking at one of the generative AI boom’s biggest stocks, Nvidia (NASDAQ:NVDA), we can see that NVDA’s momentum has slowed since March and even posted an 8% dip for the month of April. Although both the S&P 500 and Nvidia have shown resilience in the wake of the worrying inflation data, analysts remain fearful of what more bad news surrounding inflation estimates could do for undermining the momentum built by generative AI stocks. Could inflation pressures cause the generative AI bubble to finally burst? Or can we expect more resilience even in the midst of market uncertainty? Are we in a GenAI Bubble? According to Bloomberg Professional Services, the generative AI market is set to attain $1.3 trillion in revenue by 2032. However, such lofty expectations could be undermined by signs of a slowdown. “There's growing evidence that the hype machine is slowing down," notes Gerrit De Vynck, tech reporter at The Washington Post. While many major tech firms like OpenAI, Microsoft, and Google have been busy announcing new projects, the AI hype cycle is so far "yet to upend the way people work and communicate with each other." In addition to this, we’re yet to see leading firms, aside from hardware manufacturers, begin to access the massive pool of revenue forecasted for generative AI. According to John Naughton, professor of the public understanding of technology at the Open University, we’re not only in an AI bubble, but we’re already at its third-stage: euphoria. “Caution has been thrown to the winds and ostensibly rational companies are gambling colossal amounts of money on AI,” Naughton notes in his description of the euphoria stage of the AI bubble. Naughton surmises that the euphoria stage of the bubble will ultimately give way to profit-taking before reaching its conclusion at the ‘panic’ stage. Should we find ourselves inside a generative AI bubble, all eyes will be on its most impressive performer, Nvidia for signs of stress. Kristofer Barrett, equities manager at Swedbank Robur Technology, fears that the runaway success of Nvidia has pushed the firm into retail stock territory as Cathie Wood’s Ark Invest trimmed its exposure to NVDA last year while the share of ESG funds holding the stock fell to 15% at the end of 2023, down from a high of 20% in Q2 2023. Recent frailties in the S&P 500 off the back of CPI data have come at a time when investors have become accustomed to generative AI hype. For the market to be sustainable, the hype cycle will need to give way to implementation at some level. Whether or not we can reach the implementation stage of the GenAI boom will be down to whether it can deliver on its vast potential. Reasons to Remain Bullish Despite fears that the generative AI boom may be a bubble that’s readying to burst, the relative resilience of the S&P 500 which has been sustained by AI stock growth in recent months and leading GenAI stocks like Nvidia can be interpreted as a positive sign of sustainability. “Concerns about GenAI failing to meet expectations in 2024 should be seen in the context of the natural cycle of hype and maturity of new technologies,” explained Maxim Manturov, head of investment research at Freedom Finance Europe. “While some industry leaders have expressed frustration with the speed of progress in artificial intelligence and GenAI in their organizations, others remain optimistic about its potential,” Manturov added. “Companies heavily invested in GenAI are under pressure to prove profitability, and industry reports indicate a shift to more strategic AI initiatives in the coming years.” Nvidia CEO Jen Huang has corroborated the suggestion that AI initiatives are only gathering momentum in the current market. “Demand is surging worldwide across companies, industries, and nations,” Huang said. “Demand will continue to be stronger than our supply provides through the year, and we’ll do our best [to meet it].” According to Deloitte tech predictions for 2024, we’re likely to see ‘almost all’ enterprise software companies embed generative AI in at least some of their products this year. As a result, AI chip sales are set to reach more than $50 billion worldwide while software revenue could attain a $10 billion run rate by the end of 2024. Crucially, Deloitte found that more than 70% of companies are experimenting with generative AI at present, buy less than 20% are willing to spend more money than they already are on the technology. This data suggests that the pipeline of interest for GenAI solutions isn’t ready to slow down any time soon, and even if there are signs of saturation, falling entry costs would open the market for a far wider range of interested companies. If there are signs of the generative AI boom slowing, it would more likely take the form of a market correction than a bubble bursting. Could Inflation Interrupt the GenAI Boom? Tech stocks are always more vulnerable to difficult inflation data. The 2022 tech stock sell-offs on Wall Street were a timely reminder that more speculative and riskier stocks can struggle as macroeconomic conditions tighten. This means that confounding inflation data will always have an adverse impact on popular tech stocks, and given the frequency in which CPI inflation is exceeding expectations, investors may have to factor in short-term volatility when building their portfolios. For investors adopting a more long-term mindset, the prospect of generative AI flourishing into a $1.3 trillion industry will be a key draw. Whether such sky-high predictions can emerge from its hype stage into the implementation stage will be crucial, but for now, the generative AI boom is showing the resilience required for longevity. Inflation has brought a level of uncertainty to Wall Street in 2024 despite a record-breaking Q1 performance for the S&P 500. With much of the growth driving US markets down to the ongoing generative AI boom , could the threat of confounding consumer price index (CPI) data cause the GenAI bubble to burst? ongoing generative AI boom The first quarter saw the S&P 500 cross the 5,000 barrier for the first time as a watershed moment in a sustained rally that coincided with the launch of OpenAI’s ChatGPT generative AI large-language model (LLM). The index rallied more than 30% since the November 30th 2022 release of ChatGPT towards a peak of over 5,250 before the news of resurgent inflation rates forced a timely reality check. As news that CPI inflation data for March 2024 came in at a hotter-than-expected 3.5% increase in the same period in 2023, the S&P 500 tumbled back below 5,000 in a 5.46% dip from its peak in late March. hotter-than-expected 3.5% increase hotter-than-expected 3.5% increase Although US markets have become accustomed to high inflation data, there had been optimism that 2024 would see multiple Federal Reserve rate cuts taking place as inflation cooled. Confounding figures appeared to spark Wall Street to snap out of its long-term rally and address the prospect of higher-for-longer rates. Looking at one of the generative AI boom’s biggest stocks, Nvidia (NASDAQ:NVDA), we can see that NVDA’s momentum has slowed since March and even posted an 8% dip for the month of April. Although both the S&P 500 and Nvidia have shown resilience in the wake of the worrying inflation data, analysts remain fearful of what more bad news surrounding inflation estimates could do for undermining the momentum built by generative AI stocks. analysts remain fearful analysts remain fearful Could inflation pressures cause the generative AI bubble to finally burst? Or can we expect more resilience even in the midst of market uncertainty? Are we in a GenAI Bubble? According to Bloomberg Professional Services, the generative AI market is set to attain $1.3 trillion in revenue by 2032. However, such lofty expectations could be undermined by signs of a slowdown. attain $1.3 trillion in revenue attain $1.3 trillion in revenue “There's growing evidence that the hype machine is slowing down," notes Gerrit De Vynck , tech reporter at The Washington Post. While many major tech firms like OpenAI, Microsoft, and Google have been busy announcing new projects, the AI hype cycle is so far "yet to upend the way people work and communicate with each other." notes Gerrit De Vynck notes Gerrit De Vynck In addition to this, we’re yet to see leading firms, aside from hardware manufacturers, begin to access the massive pool of revenue forecasted for generative AI. According to John Naughton, professor of the public understanding of technology at the Open University, we’re not only in an AI bubble, but we’re already at its third-stage: euphoria. “Caution has been thrown to the winds and ostensibly rational companies are gambling colossal amounts of money on AI,” Naughton notes in his description of the euphoria stage of the AI bubble. Naughton notes Naughton notes Naughton surmises that the euphoria stage of the bubble will ultimately give way to profit-taking before reaching its conclusion at the ‘panic’ stage. Should we find ourselves inside a generative AI bubble, all eyes will be on its most impressive performer, Nvidia for signs of stress. Kristofer Barrett, equities manager at Swedbank Robur Technology, fears that the runaway success of Nvidia has pushed the firm into retail stock territory as Cathie Wood’s Ark Invest trimmed its exposure to NVDA last year while the share of ESG funds holding the stock fell to 15% at the end of 2023, down from a high of 20% in Q2 2023. retail stock territory retail stock territory Recent frailties in the S&P 500 off the back of CPI data have come at a time when investors have become accustomed to generative AI hype. For the market to be sustainable, the hype cycle will need to give way to implementation at some level. Whether or not we can reach the implementation stage of the GenAI boom will be down to whether it can deliver on its vast potential. Reasons to Remain Bullish Despite fears that the generative AI boom may be a bubble that’s readying to burst, the relative resilience of the S&P 500 which has been sustained by AI stock growth in recent months and leading GenAI stocks like Nvidia can be interpreted as a positive sign of sustainability. “Concerns about GenAI failing to meet expectations in 2024 should be seen in the context of the natural cycle of hype and maturity of new technologies,” explained Maxim Manturov, head of investment research at Freedom Finance Europe . Freedom Finance Europe Freedom Finance Europe “While some industry leaders have expressed frustration with the speed of progress in artificial intelligence and GenAI in their organizations, others remain optimistic about its potential,” Manturov added. “Companies heavily invested in GenAI are under pressure to prove profitability, and industry reports indicate a shift to more strategic AI initiatives in the coming years.” Nvidia CEO Jen Huang has corroborated the suggestion that AI initiatives are only gathering momentum in the current market. “Demand is surging worldwide across companies, industries, and nations,” Huang said . “Demand will continue to be stronger than our supply provides through the year, and we’ll do our best [to meet it].” Huang said Huang said According to Deloitte tech predictions for 2024 , we’re likely to see ‘almost all’ enterprise software companies embed generative AI in at least some of their products this year. As a result, AI chip sales are set to reach more than $50 billion worldwide while software revenue could attain a $10 billion run rate by the end of 2024. Deloitte tech predictions for 2024 Deloitte tech predictions for 2024 Crucially, Deloitte found that more than 70% of companies are experimenting with generative AI at present, buy less than 20% are willing to spend more money than they already are on the technology. This data suggests that the pipeline of interest for GenAI solutions isn’t ready to slow down any time soon, and even if there are signs of saturation, falling entry costs would open the market for a far wider range of interested companies. If there are signs of the generative AI boom slowing, it would more likely take the form of a market correction than a bubble bursting. Could Inflation Interrupt the GenAI Boom? Tech stocks are always more vulnerable to difficult inflation data. The 2022 tech stock sell-offs on Wall Street were a timely reminder that more speculative and riskier stocks can struggle as macroeconomic conditions tighten. This means that confounding inflation data will always have an adverse impact on popular tech stocks, and given the frequency in which CPI inflation is exceeding expectations, investors may have to factor in short-term volatility when building their portfolios. For investors adopting a more long-term mindset, the prospect of generative AI flourishing into a $1.3 trillion industry will be a key draw. Whether such sky-high predictions can emerge from its hype stage into the implementation stage will be crucial, but for now, the generative AI boom is showing the resilience required for longevity.

Could Stubborn Inflation Cause the Generative AI Bubble to Finally Burst on Wall Street?

একগুঁয়ে মুদ্রাস্ফীতি কি জেনারেটিভ এআই বুদ্বুদকে শেষ পর্যন্ত ওয়াল স্ট্রিটে ফেটে যেতে পারে?

Könnte eine hartnäckige Inflation dazu führen, dass die generative KI-Blase an der Wall Street endgültig platzt?

¿Podría la persistente inflación provocar que la burbuja generativa de la IA finalmente estalle en Wall Street?

Une inflation tenace pourrait-elle enfin faire éclater la bulle de l’IA générative à Wall Street ?

क्या जिद्दी मुद्रास्फीति के कारण वॉल स्ट्रीट पर जनरेटिव एआई बुलबुला अंततः फट सकता है?

根強いインフレにより、ウォール街で生成 AI バブルがついには崩壊する可能性があるか?

완고한 인플레이션으로 인해 생성 AI 버블이 월스트리트에서 마침내 터질 수 있습니까?

A inflação teimosa poderia fazer com que a bolha da IA generativa finalmente estourasse em Wall Street?

Может ли устойчивая инфляция привести к тому, что пузырь генеративного искусственного интеллекта наконец лопнет на Уолл-стрит?

İnatçı Enflasyon, Üretken Yapay Zeka Balonunun Sonunda Wall Street'te Patlamasına Neden Olabilir mi?

Lạm phát cứng đầu có thể khiến bong bóng AI sáng tạo cuối cùng bùng nổ trên Phố Wall?

顽固的通货膨胀会导致华尔街的生成性人工智能泡沫最终破裂吗？

Any views expressed in the below are the personal views of the author and should not form the basis for making investment decisions, nor be construed as a recommendation or advice to engage in investment transactions. Mayday Mayday Mayday Some of you degens were screaming “Mayday” as you watched crypto markets puke from mid-April until the present. There was so much pain that momentum-chasing paper hands like proclaimed that they were “done” with crypto. As if – she will dutifully return posting crypto thirst traps once Bitcoin is back trending up and to the right in short order. Irene Zhao The price action played out as I expected. US tax season, consternation over what the Fed will do, the Bitcoin halving sell the news event, and a slowdown of US Bitcoin ETF asset under management (AUM) growth coalesced over the prior fortnight to produce a well-needed market cleansing. The tourists will sit out the next phase on the beach… if they can afford it. Us hard motherfuckers will hodl, and if possible, accumulate more of our favorite crypto reserve assets such as Bitcoin and Ether, and/or high-beta shitcoins like Solana, Dog Wif Hat, and dare I say Dogecoin (the OG doggie coin). This is not meant to be a fully fleshed-out global macroeconomics, politics, and crypto essay. Rather, I want to highlight why the US Treasury, Federal Reserve (Fed), and the Republic First Bank bailout provide fiat liquidity or a path to increased fiat liquidity now and into the near future. I will quickly step through a few tables that underpin my boooolishness. QT Taper = QE When the average muppet equates quantitative easing (QE) with printing money and inflation, it spells trouble for the elites. Therefore they need to change up the nomenclature and method of providing the junkie, that is, the fiat financial system, its hit of monetary heroin. Reducing the pace of asset runoff from the Fed’s balance in accordance with their quantitative tightening (QT) program sounds benign. But make no mistake – by reducing the rate of QT from $95 billion to $60 billion per month, the Fed is essentially adding $35 billion per month of dollar liquidity. When you combine the Interest on Reserve Balances, RRP payments, and interest payments on US Treasury debt, the reduction in QT increases the amount of stimulus provided to the global asset markets each month. The Fed announced this week that it would taper QT by the aforementioned amounts at its May 2024 meeting. Using a handy chart, let us examine the dollar liquidity situation before and after the meeting. Before Size of Facility Rate PA Monthly Amount (USD Bn) Interest Expense NA NA $88.27 IORB 3271.706 5.40% $14.72 RRP 438.148 5.30% $1.94 QT NA NA -$77.59 Total $27.34 Note that the QT line item is the actual monthly average taper amount in 2024 based on the . As you can see, the Fed has undershot the monthly target of $95 billion. It begs the question of whether the target is $60 billion per month and whether the Fed will undershoot that as well. Undershooting the target pace is positive for dollar liquidity. Fed’s weekly reported balance sheet After Size of Facility Rate PA Monthly Amount (USD Bn) Interest Expense NA NA $88.27 IORB 3271.706 5.40% $14.72 RRP 438.148 5.30% $1.94 QT NA NA -$60.00 Total $44.93 Increase in $ Liq per Month 64.32% “High” interest rates, which require the Fed and US Treasury to hand out interest payment stimmies to rich folks, coupled with a reduction in the pace of QT, are even more stimulative. Please read “ ” to understand what each line item means. Kite or Board That’s what beta cuck towel boy Powell is up to. What about his dominatrix, Bad Gurl Yellen? US Treasury Quarterly Refunding Announcement (QRA) Because the US is in the throes of fiscal dominance, Bad Gurl Yellen's pronouncements are more important than those of any other monetary official. Every quarter, the US Treasury publishes the QRA to guide the market as to the quantity and type of debt that must be issued to fund the government. Before the 2Q24 QRA, I had questions: Would Yellen be borrowing more or less than last quarter, and why? What is the maturity profile of the debt to be issued? What would be the target Treasury General Account (TGA) balance? Question 1: During the April – June 2024 quarter, Treasury expects to borrow $243 billion in privately-held net marketable debt, assuming an end-of-June cash balance of $750 billion. The borrowing estimate is $41 billion higher than announced in January 2024, largely due to lower cash receipts, partially offset by a higher beginning of-quarter cash balance. [2] [3] Source: QRA That’s no bueno if you are a holder of Treasuries. There will be more supply, and tax receipts were underwhelming despite the roaring US economy and stonk markets. This hastens the pace at which the bond market throws a fit and ratchets long-end rates markedly higher. Yellen’s response to that will be some form of yield curve control, and that’s when Bitcoin begins its ascent for realz to $1 million. Question 2: Given current fiscal forecasts, the Treasury Department expects to increase the 4-, 6-, and 8-week bill auction sizes in the coming days to ensure sufficient liquidity to meet our one-week cash needs around the end of May.  Then, in anticipation of the June 15th non-withheld and corporate tax date, Treasury expects to implement modest reductions to short-dated bill auction sizes during early to mid-June.  Subsequently, throughout July, the Treasury Department anticipates returning short-dated bill auction sizes to levels at or near the highs from February and March. Source: QRA Yellen needs to increase the issuance of short-dated bills because the market couldn’t handle it if she swung her BSD at the long end of the curve. The added benefit of issuing more bills is that it drains the RRP, which adds dollar liquidity to the system. To understand why, please read “ ”. Bad Gurl Question 3: During the July – September 2024 quarter, Treasury expects to borrow $847 billion in privately-held net marketable debt, assuming an end-of-September cash balance of $850 billion. Source: QRA The TGA balance target is $850 billion. It currently stands at $941 billion, which equates to a roughly $90 billion reduction over the next three months. To understand why, please read “ .” Bad Gurl The impact of this QRA is mildly dollar liquidity positive. It is not a bombshell like the November 2023 announcement, which sent bond, stonk, and crypto prices flying. But it will help pump our bags slowly over time. Republic First Bank Have you ever heard of this tiny, piece-of-shit bank? I hadn’t, until they went bust. The fact that another non-Too Big To Fail (TBTF) bank failed is not noteworthy. But what is important is the response of the monetary mandarins in charge of the Pax Americana. The US government (via the FDIC) insures deposits in any US bank up to $250,000. When a bank fails, uninsured depositors should get zeroed. However, that is politically unpalatable in an election year, especially if the powers that be have continuously assured the public the banking system is sound. Here is an excerpt from the : FDIC As of January 31, 2024, Republic Bank had approximately $6 billion in total assets and $4 billion in total deposits.  The FDIC estimates that the cost to the Deposit Insurance Fund (DIF) related to the failure of Republic Bank will be $667 million. The FDIC determined that compared to other alternatives, Fulton Bank’s acquisition of Republic Bank is the least costly resolution for the DIF, an insurance fund created by Congress in 1933 and managed by the FDIC to protect the deposits at the nation’s banks. Understanding what happened in plain speech requires reading between the lines. Fulton agreed to purchase Republic First and ensure all depositors were made whole only if the FDIC ponied up some cash. The FDIC insurance gave Fulton $667 million so that all Republic First depositors were made whole. Why is the insurance fund being used for all deposits when some deposits were not insured? The reason is that if all deposits weren’t covered, then a bank run would start. Any large depositor with a non-TBTF bank would instantly transfer money to a TBTF bank, which sport a full government guarantee of all deposits. Subsequently, thousands of banks would go under across the country. That is not a good look in a democratic republic with elections every two years. Once the public is educated that the bank failures are 100% due to Fed and US Treasury policy, some overpaid idiots will have to get real jobs. Rather than suffer at the ballot box, those in charge essentially now guarantee all deposits in the US banking system. That is a stealth addition of $6.7 trillion, as this is the amount of uninsured deposits as . reported by the St. Louis Fed This leads to money printing because the FDIC’s insurance fund doesn’t have $6.7 trillion. Maybe they need to ask CZ for advice because funds ain’t SAFU. Once the fund is exhausted, the FDIC will borrow money from the Fed, which will print money to satisfy the loan. Like the other stealth money printing policies discussed in this essay, there is no massive liquidity injection today. However, we now know with full confidence that trillions of contingent liabilities have been added to the Fed’s balance sheet, which will be funded with printed money. Buy in May, Go Away! The slow addition of billions of dollars of liquidity each month will dampen negative price movement from here on out. While I don’t expect crypto to fully realize the recent US monetary announcements' inflationary nature immediately, I expect prices to bottom, chop, and begin a slow grind higher. As the northern-hemispheric summer kicks into full gear, crypto muppets will be out enjoying being pre-rich at all the usual hot spots. I see you at DC10, Scorpios, Chiltern … I see you playa. I certainly won’t be babysitting Bitcoin when I could be two-stepping. The recent intense puke out provides an excellent opportunity to unstake my and spend synthetic dollars on high beta shitcoins. USDe I’m buying Solana and doggie coins for momentum trading positions. For longer-term shitcoin positions, I’m upping my allocations in Pendle* and will identify other tokens that are “on sale.” I will use the rest of May to increase my exposure. And then it’s time to set it, forget it, and wait for the market to appreciate the inflationary nature of the recent US monetary policy announcements. 同志们好 China is not to be forgotten. The CNY will be devalued, but it won’t be against USD; rather, it will be against gold and Bitcoin. I will explain this theory in an in-depth essay later this summer. For those of you who need bullet points on my predictions, here you go: Yes Did Bitcoin hit a local low at around $58,600 earlier this week? A rally to above $60,000 and then range-bound price action between $60,000 and $70,000 until August. What is your price prediction? Yes. Are the recent Fed and Treasury policy announcements stealth forms of money printing? Yachtzee!! Disclaimer: I am an advisor to and investor in Pendle, and have received Pendle tokens as compensation for my advisory services.

Mayday

মে দিবস

Maifeiertag

May Day

Au secours

मई दिवस

メーデー

노동절

Socorro

Первое мая

Mayıs günü

ngày tháng năm

劳动节

This paper is under CC 4.0 license. available on arxiv Authors: (1) Zhe Liu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (2) Chunyang Chen, Monash University, Melbourne, Australia; (3) Junjie Wang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China & Corresponding author; (4) Mengzhuo Chen, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (5) Boyu Wu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (6) Zhilin Tian, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (7) Yuekai Huang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (8) Jun Hu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (9) Qing Wang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China & Corresponding author. Table of Links Abstract and Introduction Motivational Study and Background Approach Experiment Design Results and Analysis Discussion and Threats to Validity Related Work Conclusion and References 8 CONCLUSION Automated testing is crucial for helping improve app quality. Despite the dozens of mobile app GUI testing techniques, how to automatically generate the diversified unusual text inputs for fully testing mobile apps remains a challenge. This paper proposes InputBlaster which leverages the LLM to produce the unusual inputs together with the mutation rules which serve as the reasoning chains. It formulates the unusual inputs generation problem as a task of producing a set of test generators, each of which can yield a batch of unusual text inputs under the same mutation rule. The evaluation is conducted for both effectiveness and usefulness, with 136% higher bug detection rate than the best baselines, and uncovering 37 new crashes. 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