Reddit’s r/place is one of the most oddly inspiring events on the internet, as diverse communities from across the platform come together to paint together on the same massive digital canvas. But amid ongoing controversy over Reddit’s changing API prices, which put many indie developers out of business, this year’s r/place serves as an opportunity for Reddit users to continue their ongoing rebellion.
The origin of r/place dates back to 2017, when then-Reddit engineer Josh Wardle created it as an April Fools’ Day event (yep, that’s the same guy who made Wordle! ). On a canvas of one million pixels, any registered Redditor can place one single colored pixel every five minutes. So, individual subreddits will work together to make their mark on the massive, collaborative art piece — in the past, we’ve seen giant Brazil flags, pixel-perfect recreations of the Mona Lisa, innumerable rainbows, and Pizza Johns that stare into your soul. The project came back for a second time in 2022, attracting almost 11 million users, so Reddit decided to bring r/place back again this year. The event was scheduled for June 23, but it was delayed, because at the time, numerous subreddits had shut down to retaliate against API changes.
“So what they are saying is that they have fucked up so bad that they are going to try to distract us with r/place,” one Redditor commented on the announcement.
Following Twitter’s (also controversial) lead , Reddit announced in early June that it would start charging developers for access to its API, which limits the community’s ability to create plug-ins and features that make Reddit more accessible and enjoyable. Christian Selig, developer of the popular iOS client Apollo , said that it would now cost him $20 million per year to keep his app online, so at the end of June, he shut it down for good. Other apps like Sync for Reddit, BaconReader and Boost for Reddit have shut down too, while the developers for Relay , Now for Reddit and Narwhal decided to start charging subscriptions. Not everything on the internet can be free, but these resources have been such a core part of Reddit for so long that these changes can feel like a slap in the face.
Instead of listening to the community, Reddit CEO Steve Huffman — known as u/spez on the site — doubled-down in defense of the API changes. Redditors see him as a representation of how Reddit has changed for the worse, so now, r/place is covered with messages that say “fuck spez.” At the time of publication, there are around 50 different variations of “fuck spez” on r/place (… and within another 15 minutes or so, a few of those messages were covered up with a rainbow “DICKS”). A German community got particularly creative, writing “u/spez ist ein hurendsohn,” which roughly translates to “u/spez is a son of a bitch.” Ouch.
The canvas changes quickly, and it will likely be unrecognizable by the end of the project. But so far, r/place is sending a clear, unified message that the user base of Reddit isn’t happy with Huffman’s leadership. Even within these protesting groups, there are divisions — some people want to paint the whole canvas black, and have begun their efforts in what they are calling “the black hole.” Others are on the “fuck spez” train. And some people think that simply engaging in r/place is giving the Reddit executives what they want, which is more and more clicks on their site.
Image Credits: Reddit
Image Credits: Reddit
It’s not likely that any amount of “fuck spez”-es will change Huffman’s mind about Reddit’s API pricing. But at the very least, these efforts show that users aren’t willing to back down just yet.
Meta announced new parental control tools across Instagram, Facebook, and Messenger today. This includes a new parental supervision hub in Messenger, a feature that pre-emptively blocks unwanted DMs on Messenger and Instagram, and nudges to remind teens that they should take a break.
Messenger supervision controls, which will be available in Meta’s Family Center , are rolling out first in the U.S., the U.K., and Canada. These tools will let guardians see their teens’ privacy and safety settings, changes in the Messenger contact list, and how much time they are spending in the app. Guardians will also get a notification when a teen reports someone — however the child has to explicitly allow this notification.
Parents can also look at settings like who can message their teens — only their friends, friends of friends, or no one — and who can view their stories. The guardians will also get a notification if the child changes any of these settings.
Image Credits: Meta
Image Credits: Meta
In the last few years, Instagram has taken multiple steps to limit teen interaction with unknown adults. In the latest move, the company will ask people who are not connected with a certain user to send an invitation to ask for permission to interact. Instagram said that these are text-only invites, and the sender can send just one at a time.
Image Credits: Meta
Image Credits: Meta
The company is also rolling out some controls to reduce prolonged usage, encouraging users to take a break. Instagram first introduced a “Quiet mode” in January , which allowed users to pause notifications and auto-reply to DMs that they are taking a break. At that time, it will available to users in the U.S., the U.K., Ireland, Canada, Australia, and New Zealand. Today, the company said that “Quiet mode” is rolling out globally.
Instagram has been testing features that encourage you “take a break” and nudge users after a continual usage of defined minutes to put their phone down. Meta is now extending this to Facebook, notifying users after 20 minutes of usage to take a break. Additionally, the company will also notify teens watching Reels at night to close the app.
Image Credits: Meta
Image Credits: Meta
Meta is also sending teens a new notice on Instagram to let their guardians supervise their accounts for protection. The company said that parents can now view mutuals for accounts that a teen follows or accounts that follow them.
The jury is still out on whether AI adoption really will spell the end of humanity as we know it, but in the meantime, we’re continue to see a boom of AI startups and AI dealmaking. In the latest development, a generative AI-based language learning startup called Loora is coming out of stealth with $9.25 million in seed funding to improve people’s conversational English skills, no matter the topic, by way of on-the fly, voice-based interactions with the eponymous Loora iOS assistant.
Unlike many of the majority of generative AI applications right now that are text-based — you write out prompts for ChatGPT, Midjourney, and the rest — Loora is completely focused on audio. That is to say, you speak to it to learn, as you might do with a human tutor, and Loora speaks back to you. The startup claims that its AI tutor can understand and help improve anyone’s bad English, and bad English accent, across any topic under the sun.
The funding is coming mainly from three early-stage investment specialists, Emerge leading the round, with Two Lanterns Venture Partners and Kaedan Capital, and various angels participating.
Tel Aviv-based Loora, started in 2020, may be coming out of stealth today, but Roy Mor, the CEO who co-founded the company with Yonti Levin, noted that it’s been quietly operating for a while now and has already signed up “thousands” of paying customers — consumers and prosumers who want or (for work) need to improve their English-speaking skills and are using Loora’s app to do so.
And in turn, Loora is using that interactivity to continue expanding its knowledge base.
Mor, a machine learning alum from Mobileye, said that he and Levin (Loora’s CTO) decided to focus on language tuition, and English specifically, for a couple of reasons.
The first is that English is, by far, the most common language being learned right now, with more than 1 billion learners globally. (And the plan is to stay around English for now.)
The second is that while there are dozens (if not more) popular online language-learning platforms out in the world already, they found a gap when it came to mastering conversational English in a one-to-one learning environment.
At one end are language learning apps. Platforms like Duolingo, Memrise and Babel, Mor said, “do a great job but they mostly cater to a casual audience.” A typical user might just as easily be on TikTok as on one of these apps, and it might give you basic skills, but not much more. “Being able to order a coffee is great,” said Mor, “but if you want to work in English, it’s not relevant enough.” And they are limited around what they can do with the voice-based interactions that they do have.
At the other end are human tutors, either in person or online through video meetings, who can hone in on specific topics that you might want or need to cover, listen to you and shape their teaching based on your particular needs. “But for many, those actual tutors are prohibitively expensive,” he explained.
The solution, inevitably, has come by way of advances in tech. Leaning on the new wave of generative AI — popularized by services like ChatGPT form OpenAI and the Midjourney illustrator that creates images based on verbal prompts — Loora has built an English-language tutor that responds to conversation prompts, comes up with conversation prompts when you don’t have one to mind, and understands and responds to what you say to it in order to give you guidance on how to improve your spoken English.
Mor said that initially, in 2020, Loora built its own large language models. But now that these have become widely available it’s tapping a variety of them for its service — some are suited better to different tasks, so different LLMs are used, for example, for openers (when someone starts using the app), for first conversations, subsequent conversations, different topics, and a different one for the app’s “memory” of each user. Loora uses these third-party LLMs, he said, “but we train on our own data.”
To be clear, Loora is not ingesting audio per se — that is still a very nascent area, with companies like Meta launching Voicebox , its first effort in that space, only earlier this month; and others in academia just starting to look at how and where voice-based-input and interfaces might work. But it is using a mix in which the audio is an essential component, given that the aim is to improve spoken English.
“We use a speech-to-text model since our conversational and grammar feedback models rely on textual input,” Mor said, but along with that, “We also use the speech itself in order to assess and give feedback on pronunciation, prosody, and fluency, as well as understand the sentiment.”
That also means there is an inherent limitation to the app as it exists: Loora is focused on speaking, not reading and writing, and it seems that you have to have at least some knowledge of English — rather than none at all — to get started. There will be some reading introduced, Mor said, with an upcoming module that will provide texts to read as the anchor of a subsequent discussion. But writing is not really on the table right now.
This means that although Loora is certainly setting out to do something different from what other language learning apps on the market provide now, if you want to master a language, as with the others, you will still likely need to use it in tandem with other learning experiences.
Nevertheless, Loora’s arrival is seems like a notable advance in what’s out in the market today, and longer term likely to be just one of the many efforts to advance audio interfaces for generative AI services.
“We have been partnering with trailblazing AI companies since 2016, so Loora was a natural fit in our portfolio. In 2020, co-founders Roy Mor and Yonti Levin already recognized the potential of generative AI for language learning and set out on a mission to harness it for the benefit of society, far before the introduction of ChatGPT,” said Liad Rubin, general partner at Emerge, in a statement. “General-purpose generative AI models are effective in the execution of generic tasks, but there is a massive advantage in building and training an AI specifically for a domain. This is why Loora envisioned and built their AI tutor with the sole purpose of teaching English, creating an unparalleled, next-gen solution for virtual English education. We’re excited to be part of this journey.”
Another chapter was published this week in the long and bizarre saga of Terraform Labs’ Do Kwon. The disgraced crypto founder will spend four months in a jail in Montenegro for falsifying official documents.
A Basic Court in Podgorica, the capital of Montenegro, this week sentenced Kwon and the former chief executive officer of Terraform Labs, Chang-joon Han, to four months in prison for forging travel documents.
The sentences include the time the two men have already spent in detention, 85 days, after being arrested at Podgorica Airport in March while trying to fly to Dubai, according to the court statement. The two men will be able to appeal the verdict within eight days of receiving the court’s written copy of the ruling.
Kwon and Han pleaded not guilty at their first court hearing in May to charges of passport and travel document forgery. At the time, authorities confiscated falsified documents that included two Costa Rican passports, two Belgian passports and two identity cards.
The next step for Kwon is still unclear since both the U.S. and South Korea have been seeking to extradite him over charges in both countries relating to the collapse of Terraform Labs.
In February , the U.S. Securities and Exchange Commission (SEC) charged Kwon and Terraform with defrauding U.S. investors who purchased Terra USD and Luna tokens.
“We allege that Terraform and Do Kwon failed to provide the public with full, fair, and truthful disclosure as required for a host of crypto asset securities, most notably for LUNA and Terra USD,” said SEC Chair Gary Gensler. “We also allege that they committed fraud by repeating false and misleading statements to build trust before causing devastating losses for investors.”
“Investigating the case in South Korea would be the most efficient way of bringing justice,” as most key accomplices and evidence linked to the Terraform incidents are based in South Korea, Dan Sunghan, Korean prosecutor, told WSJ last month.
The U.S. and South Korea do not have extradition treaties with Montenegro.
Businesses generate vast amounts of data every day. This data can come from a variety of sources, including sales figures, customer interactions, website traffic, and social media. Managing and analyzing this data can be a daunting task, but it’s essential for businesses to stay competitive. This is where data warehousing and data warehousing consulting services comes in. A data warehouse is a centralized repository that stores and organizes large amounts of data from multiple sources. In this article, we’ll discuss the benefits of implementing a data warehouse for your business.
Improved Decision-Making
One of the most significant benefits of implementing a data warehouse is improved decision-making. With a data warehouse, businesses can access and analyze large amounts of data quickly and easily. This enables businesses to make informed decisions based on data-driven insights. For example, a retailer could analyze sales data from different stores and channels to identify trends and make more informed decisions about inventory management and marketing campaigns. By using data to inform decision-making, businesses can increase their chances of success and stay ahead of the competition.
Better Data Organization and Management
Data warehousing also provides better organization and management of data. With a data warehouse, businesses can centralize data from different sources and organize it in a logical and consistent manner. This makes it easier to analyze data and identify patterns and trends. Additionally, a data warehouse can help ensure data accuracy and consistency by providing a single source of truth. This is particularly important for businesses that rely on data to inform critical decisions.
Increased Efficiency
Implementing a data warehouse can also increase efficiency. By centralizing data and making it easier to access and analyze, businesses can save time and resources. For example, instead of manually pulling data from different sources and organizing it in spreadsheets, employees can access the data warehouse and quickly retrieve the information they need. This can lead to increased productivity and faster decision-making.
Scalability
Another benefit of implementing a data warehouse is scalability. As businesses grow and generate more data, a data warehouse can scale to accommodate the additional data. This is because data warehouses are designed to handle large volumes of data and are optimized for data retrieval and analysis. This means businesses can continue to rely on their data warehouse as they grow and expand.
Real-World Examples of Data Warehousing Benefits
To illustrate the benefits of implementing a data warehouse, let’s look at some real-world examples.
A retailer implemented a data warehouse to analyze sales data from different stores and channels. By doing so, they were able to identify which products were selling well, which stores were performing well, and which marketing campaigns were most effective. This allowed the retailer to make more informed decisions about inventory management, marketing, and store operations.
A healthcare organization implemented a data warehouse to analyze patient data from electronic health records (EHRs). By doing so, they were able to identify patterns and trends in patient outcomes, treatment effectiveness, and disease prevalence. This enabled the healthcare organization to make more informed decisions about patient care and public health initiatives.
A financial institution implemented a data warehouse to analyze transaction data from different channels. By doing so, they were able to identify patterns and trends in customer behavior, detect fraud more effectively, and manage risk more efficiently. This allowed the financial institution to make more informed decisions about product development, customer acquisition, and risk management.
Implementing a data warehouse can bring many benefits to businesses, including improved decision-making, better data organization and management, increased efficiency, and scalability. By leveraging data in this way, businesses can gain valuable insights and make more informed decisions. Whether you’re a retailer, healthcare organization, or financial institution, a data warehouse can help you stay ahead of the competition and achieve your business goals.
In today’s data-driven world, businesses of all sizes generate massive amounts of data. From customer transactions and web traffic to sales figures and product inventories, companies have access to more information than ever before. But having data is one thing; making sense of it is another. That’s where data warehousing and data warehousing consulting services comes in.
What is Data Warehousing?
Data warehousing is the process of collecting, organizing, and managing large sets of data from different sources. The purpose of data warehousing is to provide a centralized location for storing and analyzing data. This enables businesses to make better decisions based on data-driven insights.
Why is Data Warehousing Important?
Data warehousing is important for several reasons. First, it allows businesses to access and analyze data quickly and efficiently. This is critical in today’s fast-paced business environment, where decisions need to be made quickly. Second, data warehousing allows businesses to integrate data from different sources. This can provide a more complete picture of a business’s operations, enabling more informed decision-making. Third, data warehousing can help businesses identify trends and patterns in their data. This can lead to insights that would be difficult or impossible to uncover otherwise.
How Does Data Warehousing Work?
Data warehousing involves several steps. First, data is extracted from different sources and loaded into the data warehouse. This can include data from operational systems, such as customer relationship management (CRM) and enterprise resource planning (ERP) systems, as well as data from external sources, such as social media and web analytics. Once the data is loaded into the data warehouse, it is organized and structured in a way that makes it easy to analyze. This involves creating a schema, which is a logical representation of the data that describes the relationships between different tables and columns.
After the data is structured, it can be analyzed using various tools and techniques. This can include SQL queries, data visualization tools, and machine learning algorithms. The goal of data analysis is to uncover insights that can help businesses make better decisions. This can include identifying trends, predicting future outcomes, and identifying areas for improvement.
Common Examples of Data Warehousing
Data warehousing can be used in a variety of industries and contexts. Here are a few examples:
Retail: A retailer might use data warehousing to analyze sales data from different stores and channels. This can provide insights into which products are selling well, which stores are performing well, and which marketing campaigns are most effective.
Healthcare: A healthcare organization might use data warehousing to analyze patient data from electronic health records (EHRs). This can provide insights into patient outcomes, treatment effectiveness, and disease prevalence.
Finance: A financial institution might use data warehousing to analyze transaction data from different channels. This can provide insights into customer behavior, fraud detection, and risk management.
Data warehousing is a critical component of modern business. It enables businesses to collect, organize, and analyze large sets of data from different sources, providing insights that can help inform decision-making. While data warehousing can seem complex, the basics are relatively straightforward. By understanding the key concepts and benefits of data warehousing, businesses can better leverage their data to drive success.
