#data leaks

[notanotherzerofan]

I don't know if anybody has a Spoutible account, but there's been a huge data leak

Only heard of this site a few days ago and only heard about this happening just last night, but if you signed up for this site, you're personal info (e-mail, phone, etc) is at risk.

I bring this up as I see all the user-unfriendly practices going on with Twitter (as an outside observer) and people looking for alternatives.

Anyway, did a bit more digging and apparently this Christopher Bouzy guy bought the source code and barely changed anything making it so that if you know what to put in the site's url you can pretty much access any user's data. Also heard he doxxed someone who was trying to warn people of this situation (if I'm remembering correctly, plus he's been in some other shady stuff, but I'm not about to get into any of that).

There was also apparent an issue where initially you had to sign up using video verification showing both your face and your ID or passport, but from what I know it's been removed.

Anyway, here's a video kind of reiteration what I've just said (and probably explains things better than I did).

While I'm at it, I'll say this: with all these new sites popping up everywhere you probably shouldn't be jumping on day one, especially if there's been little to no transparency from the creators/owners.

Also, always read the TOS. i know it's a chore and full of confusing legal bs, but you could literally be consenting to something you don't agree with (like Cohost's weird wording terms on user content and ownership).

Please share this anywhere you can.

Also, I really shouldn't have to say this, but my post has nothing to do with politics. If you're not a fan of the guys in the video, fine. I literally have not idea who they are other than the fact one is a lawyer and that the guy they're interviewing is a programmer. Some things are more important, like not having you identity stolen and life ruined because of it.

EDIT: Spelling error

[shiningstar5022]

About the Spoutible Data Hack, It's All Slander

This thread explains more than I could, but basically, no data was actually leaked or sold & the security hole was already patched. The dude who made the video talking about it is sending in a SLAPP suit against the owner of Spoutible. If there WERE security concerns, they were immediately taken care of, this isn't a Hive Social situation.

Moral of the story, wait until some actual security experts (for example, the group that pointed out the security vulnerabilities of Hive) point things that are concerning, not a bunch of far right grifters.

[jcmarchi]

The Future of AI for Business Infrastructure: Why Private, Bare-Metal Solutions Powered by Apple Silicon Are Ideal for IT Departments

New Post has been published on https://thedigitalinsider.com/the-future-of-ai-for-business-infrastructure-why-private-bare-metal-solutions-powered-by-apple-silicon-are-ideal-for-it-departments/

The Future of AI for Business Infrastructure: Why Private, Bare-Metal Solutions Powered by Apple Silicon Are Ideal for IT Departments

As businesses, particularly small to medium-sized IT departments, look to incorporate AI into their operations, they face a complex and evolving market. While the promises of AI are exciting, the landscape is filled with uncertainties. Public AI chatbots are widely available but raise significant concerns about data sovereignty and security. SaaS providers are rapidly integrating AI, with new solutions for model training, inference, and data processing emerging daily. Amid these options, private, bare-metal infrastructure powered by Apple Silicon offers a compelling alternative to the uncertainties of shared services and public cloud options as well as offering significant power consumption to traditional GPUs.

The Data is Clear, AI in Enterprises is Rising and Apple Silicon is Poised to Lead

A McKinsey report from August 2023, “The State of AI in 2023: Generative AI’s Breakout Year,” reveals that many organizations are still in the early stages of AI integration and management. While 14-30% of survey respondents across industries use generative AI tools regularly, only about 6% claim their organizations are high-performing in AI. Mainstream organizations struggle with strategy, talent and data management, whereas high-performing AI organizations face challenges with models, talent, and scaling.

A key takeaway from the McKinsey report is that a significant portion of the industry seeks guidance on effectively leveraging AI in professional environments. Developing tailored offerings to meet this need can greatly expand market reach. Additionally, the report found that talent is a persistent challenge, with 20% of respondents identifying it as their primary obstacle. Hiring ML/AI engineers and data scientists is particularly difficult, but organizations are finding more success in recruiting general developers. This suggests that instead of establishing a dedicated AI department, a business analyst and a cross-functional IT team could suffice for testing AI strategies and evaluating their potential value.

Addressing the Core Challenges

One of the most pressing challenges is data security. Public AI chatbots make it too easy for employees to inadvertently share company-specific information, potentially leading to data leaks and a loss of control. Many companies are now seeking in-house, private AI solutions to ensure responsible use of these technologies without risking data exposure.

Furthermore, while SaaS AI features can be useful, they often come with hidden contractual complexities. Many solutions use company data to further train models, which can compromise data sovereignty. Even when data isn’t directly used for training, shared infrastructure across multiple customers poses a risk of data mingling and potential leaks. For businesses handling sensitive information, these risks are simply too high.

Additionally, there is a misconception that leveraging AI requires either extensive data science expertise or a significant investment in computing resources. This complexity can be a barrier for smaller IT teams looking to get started with AI.

By opting for private, bare-metal Apple Silicon-powered solutions, businesses can avoid these pitfalls. Apple Silicon’s unified memory architecture and integrated Neural Engine ensure high performance for AI workloads, including inference tasks, without the need for extensive expertise or overspending on hardware. It also offers predictable costs and energy efficiency, allowing businesses to implement AI solutions with more control and confidence in their infrastructure.

Value Proposition and Use Cases of Apple Silicon-Powered AI Infrastructure

Apple Silicon has quietly emerged as a preferred tech stack for running AI systems, as it can be more efficient than dedicated GPU and x86-backed hardware in several key areas. Its exceptional performance for AI inference tasks stems from the innovative unified memory architecture. This architecture allows the GPU, CPU, and memory to access the same memory pool, significantly reducing latency and improving efficiency when handling large datasets—critical for AI workloads. For example, the Mac Studio’s M2 Ultra chip supports up to 192GB of unified memory with 800GB/s bandwidth, making it ideal for running larger datasets and more complex AI models with ease.

Additionally, the integrated 32-core Neural Engine within Apple Silicon is designed for specific AI operations. By offloading complex AI tasks from the CPU and GPU, this engine accelerates inference times, allowing the system to execute workloads faster.

Beyond performance, Apple Silicon is also renowned for its energy efficiency. It delivers sustained high performance without the high power consumption and heat generation typically associated with traditional CPUs and GPUs. This efficiency makes it a cost-effective solution for businesses looking to integrate AI without overwhelming their infrastructure.

Apple Silicon-powered solutions seamlessly integrate into existing business operations, enabling teams to leverage AI without needing extensive technical expertise. These solutions work with open-source communities and leverage Apple’s unique APIs to streamline the integration process, making AI accessible to developers and businesses alike. Whether generating first drafts of documents, analyzing customer trends, or providing real-time customer service via AI-driven chatbots, Apple Silicon’s infrastructure empowers teams to harness the full potential of AI without compromising data security.

Looking to the Road Ahead

As the AI revolution continues to unfold, enterprises must carefully consider their infrastructure choices. Private, bare-metal solutions powered by Apple Silicon address critical concerns around data privacy, cost predictability and performance consistency while providing a secure and reliable environment for AI inference tasks. For businesses looking to navigate the complexities of AI, these solutions offer a compelling and forward-thinking solution.

[onetechavenue]

Navigating The Murky Waters of Data Abuse

Gibu Mathew, VP and GM APAC, Zoho Corp When data abuse is discussed, people immediately think of data breaches or data leaks. While data privacy and data security are interrelated, the two are not the same. Data breaches are easier to identify, and during the pandemic, Interpol found a surge in cybercrime and data theft throughout the Southeast Asia region. It is no surprise that findings from…

[starfishfairypeachpost]

[cuecrynsleep]

Smosh Video Stats from January 1 - June 30

Smosh Pit

Smosh Games

Smosh Overall

-Marathons weren’t included in the count as those were filmed in 2023.

-This is to recount how often we see Smosh members in half a year, despite this being made in August.

-The Smosh main announcement + Smosh sitcom trailer was included in the count.

-The count is based off of the desc. of who appears in every video.

-Lives and Members Exclusive videos aren’t included in the count.

-Angela & Chanse were credited for the tell-all episode of Smosh Mouth despite the desc. saying Amanda & Shayne.

[ct-anon]

Favorite Pokemon Survey

Hello everyone.

I am conducting a very simple survey on rotomblr in regards to what everyone’s favorite pokemon is.

You can find the survey here: https://docs.google.com/forms/d/e/1FAIpQLSeH3pKsxIkCEjUZyqfuAiOFXNgYzNniI7A_hbfNa1xAXAF6Qg/viewform?pli=1&pli=1

This survey will run until December 13th. I will send out weekly reminders of its presence. One response per person. Reblogging gives it more traction and helps the both of us.

When the time is finished, results will come around December 15th-17th. If there is enough traction, perhaps I will send out a small gift once the survey has concluded.

Thank you.

OOC info below

//HI! This is just something fun im doing :], ONE RESPONSE PER CHARACTER, NOT PER WRITER. Though if you have multiple characters please do not abuse it! Answer it as your character would! Preferably use your more active blogs!

If something sparks CT’s interest it will contact a character about it, the last question is for that, please answer yes if you’re ok with that! :3

That’s all!!! Have fun!!

Also: THIS IS ROTOMBLR ONLY. DO NOT ANSWER THIS SURVEY IF YOU DO NOT HAVE A ROTOMBLR BLOG. I WILL NOT RECORD YOUR ANSWER IF THE BLOG YOU MENTION IS OOC.

[sixthrock]

HOLY SHIT MASSIVE LEAK OF UNUSED POKEMON FROM GEN 3/4/5 HAPPENING RIGHT NOW

centroleaks on twitter and pokeleaks on reddit is where i'm following them

[notanotherzerofan]

Spoutible is leaking again.

So, you probably don't remember me mentioning this site (or if you've followed me after the fact, may not even heard of it).

As a refresher, it's one on the many Twitter alternatives that popped up after Muskrat took over.

It's also a site that after it's public launch was found to be leaving user data vulnerable. Well, another vulnerability was found recently almost exactly one year after the first one.

I still recommend you avoid this site, and if you do have an account, you may want to delete it, because the fact that this happened twice in less that two years without anyone even trying to force their way in means either they're not taking site security seriously or they're incompetent.

And before someone says 'but data breaches happen all the time,' it was not a data breach, but a leak.

To quote this article from the site UpGuard,

Data leaks are usually caused by organizations accidentally exposing sensitive data through security vulnerabilities, Such incidents are not initiated by cyberattackers. Data breaches, on the other hand, are usually the result of a cybercriminal's persistence to compromise sensitive resources.

TL;DR, if you use Spoutible, your data is very much at risk.

[jcmarchi]

RapidCanvas Secures $16M Series A to Bring AI Agents and Human Expertise Together for Scalable Business Transformation

New Post has been published on https://thedigitalinsider.com/rapidcanvas-secures-16m-series-a-to-bring-ai-agents-and-human-expertise-together-for-scalable-business-transformation/

RapidCanvas Secures $16M Series A to Bring AI Agents and Human Expertise Together for Scalable Business Transformation

As enterprises worldwide race to implement AI, the shortage of skilled technical talent poses a growing threat to innovation and scalability. Today, RapidCanvas announced a $16 million Series A funding round led by Peak XV, with participation from Titanium Ventures and existing investors Accel and Valley Capital Partners. This new investment brings the company’s total funding to over $23.5 million since its launch in 2021, fueling a radical new approach to delivering scalable, outcome-driven AI solutions without requiring armies of in-house data scientists and engineers.

A New Era of AI Implementation

Most enterprises understand the transformative potential of AI, yet struggle to operationalize it. Traditional solutions often demand deep technical expertise and lengthy implementation timelines. RapidCanvas, an AI platform that unites cutting-edge AI agents with the guidance of human experts, fundamentally changes this narrative. It enables organizations to build custom, high-performance AI solutions 10X faster and at 80% lower cost than conventional methods—without extensive data science or coding expertise.

By leveraging purpose-built AI agents, businesses can tackle complex data challenges, streamline decision-making processes, and deliver end-to-end AI solutions with minimal technical overhead. Drawing on trusted data and explainable logic, RapidCanvas ensures that every output is transparent, secure, and aligned with enterprise IT requirements. The company’s distinct approach is recognized by G2 as one of the top Data Science and Machine Learning platforms for customer satisfaction, and its Reliable AI framework guarantees enterprise-grade accountability and quality.

The RapidCanvas Approach: AI Agents and Human Expertise

RapidCanvas’s innovation lies in seamlessly blending automation and human judgment. Rather than simply using software as a tool, the platform’s AI agents autonomously handle tasks like data preparation, model selection, and data transformation—jobs that traditionally required extensive technical teams. Up to 75% of tasks typically handled by data scientists and engineers are automated, while the remaining expert tasks—creative design, hypothesis testing, strategic problem-solving—are guided by a small human team.

This hybrid model maintains the invaluable influence of human domain specialists at critical decision points. By focusing human effort where it matters most and letting AI handle the heavy lifting, enterprises can dramatically accelerate time-to-value. The result: demonstrable business outcomes in days or weeks, not months.

Series A Funding and Investor Backing

The $16 million Series A round—led by Peak XV and backed by Titanium Ventures, Accel, and Valley Capital Partners—validates RapidCanvas’s approach to making AI transformation both accessible and impactful. This fresh infusion of capital will fuel the company’s product enhancements, support global market expansion, and deepen integrations with existing data infrastructure and IT ecosystems. Investors see RapidCanvas’s model as a key to scaling AI-driven innovation across industries where technical talent is scarce.

Bridging the Global AI Talent Gap

Despite the pressing need for AI capabilities, enterprises face a persistent shortage of qualified experts. Gartner predicts that over 80% of enterprises will implement AI-powered processes in the near future, yet 68% of executives cite a lack of technical talent as a primary roadblock. RapidCanvas fills this gap by enabling business users to build, deploy, and maintain AI solutions without specialized data science backgrounds. The platform’s AI agents simplify complex workflows, and its intuitive, conversational canvas interface makes it easy for anyone—regardless of technical skill—to command sophisticated AI tools.

Service-as-Software: Moving Beyond SaaS

While Software-as-a-Service (SaaS) tools have long dominated the market, boosting efficiency through workflow automation, they still rely on human labor for execution. RapidCanvas pushes beyond this paradigm with its “Service-as-Software” model. Here, AI agents autonomously perform tasks at scale, freeing human experts to focus on strategic decisions rather than repetitive, manual chores.

This fundamental shift redefines ROI. Instead of capturing only efficiency gains, enterprises realize direct business outcomes—growth opportunities unlocked, operational costs reduced, and competitive edges sharpened. By treating AI solutions as directly correlated to tangible results, RapidCanvas transforms how companies measure success.

Accelerated Time-to-Value and Reduced Costs

The platform’s automation capabilities reduce the need for large technical teams, cutting overhead costs significantly. Achieving production-grade solutions in a fraction of the traditional development time, organizations gain immediate advantages—from faster insights to quicker market pivots. RapidCanvas’s customers routinely report dramatic improvements in operational efficiency and cost savings, proving that AI-powered transformations no longer need to be expensive, drawn-out endeavors.

Real-World Impact Across Industries

The measurable outcomes achieved with RapidCanvas stretch across multiple sectors:

Manufacturing: Companies streamline inventory and demand forecasting, boosting operational efficiency and saving hundreds of thousands of dollars.

Renewable Energy: Wind turbine failures are predicted weeks in advance, preventing costly downtime and ensuring consistent, clean energy generation.

Financial Services: Automotive finance providers enhance dealer engagement and reduce churn, creating more stable and profitable partnerships.

In each case, RapidCanvas’s blend of AI agents and human expertise turns raw data into actionable insights, fueling smarter decisions and improving bottom-line performance.

Expert Founders and Proven AI Pedigree

Behind RapidCanvas stands a leadership team with deep experience in AI-driven transformation. Co-founders Rahul Pangam and Uttam Phalnikar previously built Simility, an AI-powered risk management platform acquired by PayPal. The integration of their technology into PayPal’s global fraud detection operations is a testament to their proven track record. Supported by a seasoned leadership bench that has guided multiple startups to successful IPOs and exits, RapidCanvas leverages a wealth of expertise to ensure its solutions deliver real-world value.

“Our hybrid approach aligns the power of generative AI with the judgment of human experts,” says CEO and co-founder Rahul Pangam. “As AI automates the heavy lifting—data preparation, modeling, and coding—our human specialists verify and guide strategic decisions. With this Series A funding, we’ll expand our platform’s capabilities, making high-impact AI transformation available to more businesses, faster.”

Future-Ready, Trusted, and Scalable AI

As organizations scale their AI capabilities, security, transparency, and compliance become paramount. RapidCanvas meets Fortune 50–grade standards, providing robust privacy, explainability, and data governance measures. With a flexible deployment model (SaaS or private cloud) and the ability to integrate seamlessly into existing data infrastructures, the platform adapts as enterprises grow.

The Reliable AI framework ensures consistent, validated results, empowering organizations to rely on AI-driven insights without fear of hidden biases or data leaks. This focus on trust and reliability sets RapidCanvas apart in a market eager for dependable solutions that deliver sustained returns.

[brasstower]

deoxys stuff (source)

[spittyfishy]

Thoughts on the Typhlosion allegations/pokemon teraleaks?

Okay, here’s what I’ll say about that. (And fair warning, it is nothing positive)

I think the fandoms reaction to these “leaks” has been absolutely ridiculous. They are not canon, they do not change pre-existing information present in the games and anime. Concept art is interesting, but things that were scrapped and did not appear in the actual media should not be regarded as fact.

Especially the Typhlosion thing, it’s like if jk Rowling said ‘oh yeah at one point in the writing process I thought Harry Potter would be a girl, but I changed my mind’ and the fandom went ‘oh my god Harry’s been a girl this whole time!’ Like no, a lot of work and ideas go into the concept and development of works like these, and then creators pick and choose the best of their ideas and use that, but I think it’s very problematic to judge them on the concepts that they themselves already decided weren’t good enough to use.

I have very strict opinions about what counts as canon, and that very simply is ‘what is in the work itself’. Unused concepts, things a creator said years later online, and really popular headcanons don’t count. They’ll never count, sorry but that’s not how language works, you can’t just redefine canon to encompass anything that maybe could have been a part of the project. It can be super neat to look at what changes could have been made, but it needs to be understood that that does not impact what the actual game is like.

This Typhlosion thing especially, it *could* be neat if people just took the scrapped stories to go “oh yeah the Pokémon world could have had myths and legends similar to our own! That will be interesting to explore in fan works!” But that’s not what the majority of people did. Instead, people took it to mean that somehow all Typhlosion are secretly evil and shouldn’t be left alone with children and anyone who has one or likes that Pokémon should be ridiculed based on nothing.

Because the stuff that in those leaks (baring things about unreleased games) are nothing. Looking at them in the sense of seeing ‘How It’s Made’ is interesting, fine go for it yeah sure, but they have absolutely no bearing on the actual franchise itself. And I have no patience for the people taking them as gospel and insisting they be considered more true over the actual canon.

[the-daughter-of-lilith]

The reason I care about being in Cybersecurity runs much deeper to me than income.

I remember being 11 years old on YouTube and suddenly my video was bombarded with hundreds of antisemitic insults and threats. I knew I wasn't safe online.

If you are from Jewish descent please look into your OPSEC as soon as possible. The online interactions and influence isn't worth your safety. Form a community through decentralized and encrypted platforms to keep yourselves safe, please.

[project-sekai-facts]

The guy from perspective for smile is called daigo kiijima? I knew his name was kiijima but i haven't seen daigo anywhere

(TL by tsukasa's #3 fan on YT)

Yeah! He says it when he first introduces himself in chapter 1.

[booasaur]

The Morning Show - 3x02

Here at UBA, we pride ourselves on being transparent with all of our viewers. We consider you part of our family. Which is why I need to let you know that certain things may come to light, personal things that were never meant to be shared. While all of our lives are increasingly public, each of us has the right to our privacy. And this network will continue fighting for that right, no matter the cost. UBA as made a decision not to pay the ransom demanded by the individuals who have stolen the private data of thousands of dedicated employees.