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Which is more popular?
Based on our record, Tildes
seems to be more popular. It has been mentioned
248 times
since March 2021.
social mentions
248 vs 0
Social Networks popularity
100% vs 0%
Base details
Website, pricing, platforms and company facts side by side.
Privacy Focus Tildes is highly focused on user privacy, with no advertisements or trackers, enhancing user trust and experience.
Thoughtful Discussions The platform promotes in-depth and civil discussions, often attracting a quality audience interested in serious topics.
Non-Profit Model Being non-profit, Tildes is less driven by commercial interests, which often aligns the platform's goals with user benefits.
Transparent Moderation Moderation policies and actions are transparent, providing users with more clarity and trust in the management of the community.
User Control Users have more control over their content and interactions compared to many other social media platforms.
Possible disadvantages
Limited User Base Tildes has a smaller user base compared to mainstream platforms, which can limit engagement and the diversity of viewpoints.
Niche Community The community might be niche and not cater to general or mainstream topics, making it less appealing to a broader audience.
Limited Features As a relatively new and developing platform, Tildes might lack some advanced features present in more established social media.
Less Entertainment Content The focus on thoughtful discussion means there is less entertainment or casual content, which might not attract those looking for light-hearted engagement.
Slower Growth The intentional slow growth strategy can mean fewer updates and slower improvements in platform capabilities and user base expansion.
Efficient Data Curation Lightly uses active learning and self-supervised learning techniques to help teams select the most valuable and diverse subset of data for labeling, reducing the amount of data needed for training while maintaining model performance.
Reduces Labeling Costs By intelligently selecting which images or videos to label, Lightly can significantly cut down on the manual annotation costs and time required for building computer vision datasets.
Self-Supervised Learning Integration The platform leverages self-supervised learning methods to extract meaningful embeddings from unlabeled data, enabling better understanding of dataset structure and redundancy before labeling.
Scalable for Large Datasets Lightly is designed to handle large-scale image and video datasets, making it suitable for enterprises dealing with massive amounts of visual data in computer vision projects.
Integration with ML Workflows Lightly offers APIs and integrations that allow it to fit into existing machine learning pipelines, working alongside popular annotation tools and cloud storage solutions.
Possible disadvantages
Learning Curve Teams new to active learning and self-supervised learning concepts may face a learning curve in understanding how to best utilize Lightly's data curation capabilities.
Narrow Use Case Focus Lightly is primarily focused on computer vision data curation, which may limit its usefulness for teams working with other data types such as text, audio, or tabular data.
Dependency on Data Quality The effectiveness of Lightly's curation algorithms depends heavily on the quality and representativeness of the initial dataset, which can limit results if the source data is poor.
Pricing for Smaller Teams Depending on the pricing tier, smaller teams or individual developers might find the cost of enterprise-level data curation features less accessible compared to open-source alternatives.
Requires Technical Expertise Effectively leveraging Lightly's advanced features like self-supervised learning models may require a certain level of machine learning expertise, which could be a barrier for less technical teams.
Analysis
An editorial look at what each product does well and who it suits.
TildesLightly
Overall verdict
Tildes can be considered a good platform for those looking for a more meaningful and distraction-free online discussion experience.
Why this product is good
Tildes is valued for its focus on deep, high-quality discussions and its commitment to user privacy. It has a small, tight-knit community that encourages thoughtful debate and exploration of topics without the clutter of ads or algorithms.
Recommended for
Individuals interested in sincere and in-depth discussions
Users who prioritize privacy and community over the typical social media experience
People who prefer an ad-free browsing environment
Overall verdict
Lightly is a solid, well-regarded platform for data curation and active learning in computer vision, offering strong tooling for selecting the most valuable images/frames to label, which helps teams reduce annotation costs and improve model performance efficiently.
Why this product is good
Focuses on smart data selection and curation, helping avoid wasted labeling budget on redundant data
Offers both open-source (Lightly SSL) and commercial (Lightly Worker/Platform) options for flexibility
Uses self-supervised learning techniques to find diverse, representative, or edge-case samples
Integrates with common MLOps and labeling tools, fitting into existing computer vision pipelines
Scales to large unlabeled datasets, making it useful for teams with massive raw data but limited labeling resources
Provides visualization and embedding tools to explore dataset distribution and detect biases or gaps
Recommended for
Computer vision teams looking to reduce labeling costs through smarter data selection
ML engineers building active learning pipelines
Companies with large volumes of unlabeled image or video data
Teams wanting to improve model performance by curating more diverse or representative training sets
Organizations needing to detect dataset bias, redundancy, or edge cases before annotation
Https://lobste.rs? I know other communities that I really doubt would appeal to anyone here. However, Lobsters is basically Hacker News, but anti-AI, smaller, and with a (low) barrier to entry. Two more: https://tildes.net, and...
- Source: Hacker News
/
about 20 hours ago
Person of Interest
I watched the show in 2014 and it drove my interest to study and work in the AI sector (today I run an AI lab). I loved Westworld as well, which was the follow-up from POI. Most people don't like the later Westworld seasons but they are...
- Source: Hacker News
/
2 days ago
Old.reddit.com Gone
May I introduce [tildes.net](https://tildes.net) Invite only, text based, smaller community, engaging discussions. And I guess hacker news and lobsters. Others can add more. (There was hesitation in adding this, you don’t want more...
- Source: Hacker News
/
13 days ago
Reddit gives you the best of the internet in one place. Get a constantly updating feed of breaking news, fun stories, pics, memes, and videos just for you.
