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Sending everybody the same message on Snapchat is possible now. You can do so by creating a group on Snapchat. But, how to make a group chat on Snapchat? The doable steps are given here:
What Is a Snapchat Group Chat?
Snapchat group chat is a useful option to add multiple contacts in a common place. It’s used to put all contacts together on Snapchat and then send things together. This is a free option on the platform, and the most useful as well. Learn how to create group chat on Snapchat.
How To Make A Group Chat On Snapchat
Create a group on Snapchat using this quick and simple step guide:
Open your Snapchat app.
Swipe right to the screen to get a chat screen.
Ta on the chat bubble with a pencil on the top right corner.
Select the option called ‘new group.’
Now, select the contacts from your list to add to the group.
Select the option to chat with the group.
Finally, send a message.
Last Words
We discussed the actual steps to create a group chat on Snapchat. You can try the steps on your Snapchat app or mobile browser. Get the more details on this in the link below.
https://digihubexpert.com/how-to-make-a-group-chat-on-snapchat/
Pinning a comment on Instagram is an effective way to highlight important messages on your posts. To pin a comment on Instagram, start by ensuring you have the latest version of the app. This feature is available for both personal and business accounts, making it accessible to a wide audience.
Here’s how to do it: navigate to the post where you want to pin the comment. Scroll through the comments until you find the one you wish to pin. Tap on the speech bubble icon located below the comment. Once you see the options pop up, select the pin icon (it looks like a thumbtack). This will elevate the comment to the top of the comment section, making it more visible to your audience.
It’s important to note that you can pin only one comment at a time. If you want to replace a pinned comment, simply pin another one, and the previous will be unpinned automatically. This feature not only helps you engage with your audience but also encourages meaningful conversations on your posts. Pinning comments is especially useful for sharing important information, responding to FAQs, or featuring your followers’ insights.
By using this tool, you can direct your audience's attention to specific thoughts or announcements, improving interaction and potentially increasing your post's reach. So, next time you post, consider how to pin a comment on Instagram to enhance your engagement and connection with your followers!
Read more : https://neriblog.org/how-to-pin-a-comment-on-instagram/
The cancellation of "Overflow" Season 2 left fans disappointed and searching for answers. Despite the popularity of the first season, several factors contributed to the decision to halt production on a second season. So, why was "Overflow" Season 2 cancelled?
One of the primary reasons is the controversial nature of the series. "Overflow" faced criticism for its explicit content, which led to backlash from various groups and organizations. This negative reception likely influenced the decision to cancel the show, as producers may have been wary of further controversy and potential impact on their reputation.
Another factor is financial viability. While "Overflow" garnered a significant fanbase, it may not have generated enough revenue to justify the costs of producing a second season. In the competitive world of anime production, profitability plays a crucial role in the continuation of any series.
Lastly, the source material may have influenced the decision. If the original manga or light novel series did not have enough content to sustain a new season or if the storyline concluded in a satisfying manner, the creators might have chosen to end the series on a high note.
In summary, overflow season 2 cancelled why can be attributed to a combination of controversy, financial considerations, and the status of its source material. While fans are understandably disappointed, these factors provide some insight into the challenging decisions faced by anime producers.
Read more - https://www.lcarscom.org/overflow-season-2-date/
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*Coins, Shells, and the Weight of Old Habits*
Villages along the Dutch coast kept private rituals long before any
commercial venue existed. Fishermen in Volendam once buried a single
guilder beneath the doorstep of a new boat, convinced it would draw a
fuller net. Nobody wrote the custom down. It simply passed from father to
son, the way a recipe or a grudge might.
Commercial expansion in neighboring European economies has become a
frequent talking point among Dutch operators watching how licensing
frameworks evolve just across the border. That modern conversation feels
distant from doorstep rituals and buried coins, yet both share a common
root: people trying to manage what they cannot control
https://mgacasino.nl/ Economists
rarely connect superstition to spreadsheets, but the impulse behind each is
nearly identical.
In Limburg, an old carnival tradition involved tossing dried peas into a
fountain while reciting the names of family members. Whoever's name came up
attached to the pea that sank first was expected to host next year's
gathering. The custom still shows up in small towns, mostly ignored by
anyone under thirty, though a few grandmothers insist on it every February
regardless of complaints.
Commercial market expansion doesn't explain why a fountain ritual in
Limburg has outlasted three generations of technological change. Folklore
doesn't need economic logic to survive; it needs repetition and a willing
audience. That's a different kind of durability than the one driving
cross-border licensing debates.
Dutch sailors carried their own set of maritime superstitions well into the
twentieth century. Whistling on deck was thought to summon storms, so
social table games and dice activities became the accepted alternative for
passing long, idle hours at sea. Losing a hand meant nothing beyond wounded
pride. Winning, occasionally, meant an extra tot of gin from the ship's
stores, a tradition some coastal pubs still honor during maritime festivals.
Amsterdam's canal houses hold quieter traditions. Merchant families once
tossed loose change into the water on New Year's Eve, a gesture meant to
buy favor from whatever spirits governed trade and travel. The habit has
faded into a handful of families who still do it out of nostalgia rather
than belief. Nobody expects the canal to answer back.
Regulated venues entered Dutch life much later, arriving in the late
twentieth century, long after these folk customs had already taken root.
They occupy a separate cultural space, drawing a different crowd for
different reasons. The pea-tossing families of Limburg and the doorstep
guilders of Volendam persist regardless of what happens inside any
recreational hall.
What survives from these older customs isn't the wager itself. It's the
shared act of turning uncertainty into something communal, something small
enough to hold in one hand and pass down without ever needing to explain
why.
Can I Run It is a practical online resource for benchmarking, comparison, and performance research, presented through the DoBenchmark platform. It exists to help people evaluate their options with clear reference points and useful data rather than relying on assumption or hearsay. In a world where performance claims are abundant and technical specifications are often difficult to interpret, this resource provides a straightforward way to understand how different systems and software actually measure up. The platform focuses on benchmarking, which means it offers consistent, repeatable methods for assessing performance. This allows users to compare options side by side, whether they are deciding between hardware upgrades, checking whether a new game will run on their current setup, or simply researching trends in performance. The underlying goal is accessibility: no one should need to be a technical expert to determine whether a particular product or configuration is right for them. By presenting information in a clear and practical format, DoBenchmark helps users move from confusion to confidence. It turns complex data into meaningful insights, making it easier to identify strengths and weaknesses among different choices. The resource is designed for real-world relevance, ensuring that the measurements and comparisons reflect actual usage scenarios. This is especially important for gamers, professionals, and everyday users who rely on technology for work or leisure. With a focus on clarity, DoBenchmark acts as a dependable reference point. It does not overpromise or obscure; rather, it gives people the tools they need to make informed decisions. Whether the task is verifying system requirements, estimating performance potential, or understanding the gap between models, the platform delivers practical answers. It also encourages a more thoughtful approach to research, turning what might feel like a daunting process into something manageable and transparent. Ultimately, Can I Run It through DoBenchmark is about empowering users with evidence-based knowledge, turning performance research into a simpler and more rewarding experience. https://dobenchmark.com/
Hello everyone,
I would like to share a technical overview of Seedance 2.5(https://seedance25ai.cc/), an integrated multimodal AI audio-video generation model developed by ByteDance’s Seed research team, and invite discussions from peers working on generative vision, video synthesis and multimodal alignment research. This post focuses purely on its technical architecture and functional upgrades rather than commercial applications, suitable for our list’s computing and AI research discussions.
A core limitation of most mainstream text-to-video generative models is the constraint on single-shot generation length, often limited to under 16 seconds with severe character drift and broken scene continuity. Seedance 2.5 addresses this by supporting native single-pass continuous video rendering up to 30 seconds, with optimized temporal consistency modules to stabilize facial features, object textures and camera trajectories throughout long narrative clips. It also supports multi-round clip extension to assemble longer sequential footage while retaining uniform visual identity, a valuable improvement for researchers studying long-form video storytelling and temporal coherence algorithms.
Its multimodal reference control framework is a standout technical feature. The model accepts up to 50 combined reference inputs including static images, reference video snippets and audio tracks simultaneously. Researchers can inject fixed character prototypes, scene style references, target cinematography motion samples and audio rhythm guides to constrain generation outputs, which offers a practical testbed for research on multi-condition constrained generative diffusion models. It also natively supports green screen assets, facilitating composite video generation experiments for computer vision practitioners.
The timestamp-based localized editing module solves a major workflow pain point in generative video research. Conventional models require full re-rendering to revise partial frames; Seedance 2.5 allows targeted modification of specific time segments while preserving untouched frames’ motion, lighting and audio alignment. This reduces redundant computation in iterative model testing and provides new angles for studying partial latent space editing in video diffusion pipelines. Its joint audio-video native architecture synchronizes visual motion, ambient sound and voice generation within one unified latent space, mitigating the persistent audio-video desync issue common in separate text-image and audio generation stacks.
The model outputs high-resolution 4K video compatible with standard open-source post-processing and evaluation tools, making it easy to integrate into existing research benchmark pipelines. While it still exhibits minor artifacts in dense multi-character crowd scenes, its overall temporal stability and multi-condition controllability represent clear progress compared to earlier video generation architectures.
I am curious to hear insights from others on this list: Has anyone tested Seedance 2.5 for multimodal generative research benchmarks? Do you see potential applications of its temporal consistency or local editing modules in your own computer vision work? Feel free to share technical observations or comparative analysis of competing video generation frameworks below. https://seedance25ai.cc/
Best regards,