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Parsec VS TensorFlow

Compare Parsec VS TensorFlow and see what are their differences

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Parsec logo Parsec

Streams games locally or over the internet

TensorFlow logo TensorFlow

TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
  • Parsec Landing page
    Landing page //
    2023-10-09
  • TensorFlow Landing page
    Landing page //
    2023-06-19

Parsec features and specs

  • High Performance
    Parsec provides low latency and high-quality streaming even for demanding tasks like gaming and video editing.
  • Cross-Platform Support
    Parsec is available on multiple platforms, including Windows, macOS, Linux, Android, and iOS, allowing users to connect from various devices.
  • Ease of Use
    The application features a user-friendly interface that makes setup and connection straightforward, even for beginners.
  • Collaboration Features
    Parsec allows multiple users to connect and control a single machine, making it useful for collaborative projects and remote work.
  • Security
    Parsec uses SSL and DTLS encryption to ensure data integrity and privacy during remote sessions.
  • Customization
    Users can fine-tune settings for resolution, bitrate, and frame rate to optimize performance based on their network conditions.

Possible disadvantages of Parsec

  • Internet Dependence
    High-quality and low-latency performance heavily depends on a stable and fast internet connection, which can be a limitation in some areas.
  • Subscription Cost
    Advanced features and commercial use require a paid subscription, which may be a barrier for some users or small businesses.
  • Resource Intensive
    The host machine needs to be powerful enough to handle the encoding required for high-quality video streaming, which can be demanding on system resources.
  • Limited Offline Capabilities
    Parsec primarily functions as an online solution and lacks robust offline features for situations where internet access is intermittent or unavailable.
  • Compatibility Issues
    Despite wide platform support, there can still be compatibility issues with certain hardware or software setups, which may require troubleshooting.
  • Privacy Concerns
    Users might have concerns about sharing control of their machine or files when collaborating, posing potential security risks if not managed carefully.

TensorFlow features and specs

  • Comprehensive Ecosystem
    TensorFlow offers a complete ecosystem for end-to-end machine learning, covering everything from data preprocessing, model building, training, and deployment to production.
  • Community and Support
    TensorFlow boasts a large and active community, as well as extensive documentation and tutorials, making it easier for beginners to learn and experts to get help.
  • Flexibility
    TensorFlow supports a wide range of platforms such as CPUs, GPUs, TPUs, mobile devices, and embedded systems, providing flexibility depending on the user's needs.
  • Integrations
    TensorFlow integrates well with other Google products and services, including Google Cloud, facilitating seamless deployment and scaling.
  • Versatility
    TensorFlow can be used for a wide range of applications from simple neural networks to more complex projects, including deep learning and artificial intelligence research.

Possible disadvantages of TensorFlow

  • Complexity
    TensorFlow can be challenging to learn due to its complexity and the steep learning curve, particularly for beginners.
  • Performance Overhead
    Although TensorFlow is powerful, it can sometimes exhibit performance overhead compared to other, lighter frameworks, leading to longer training times.
  • Verbose Syntax
    The code in TensorFlow tends to be more verbose and less intuitive, which can make writing and debugging code more cumbersome relative to other frameworks like PyTorch.
  • Compatibility Issues
    Frequent updates and changes can lead to compatibility issues, requiring significant effort to keep libraries and dependencies up to date.
  • Mobile Deployment
    While TensorFlow supports mobile deployment, it is less optimized for mobile platforms compared to some other specialized frameworks, leading to potential performance drawbacks.

Analysis of Parsec

Overall verdict

  • Overall, Parsec is considered a good option for anyone needing remote access or streaming capabilities. Its robust performance and user-friendly interface make it a reliable choice for various applications.

Why this product is good

  • Parsec (parsec.app) is widely appreciated for its low-latency, high-quality remote desktop and game streaming capabilities. It allows users to access and control their computers from anywhere, making it a versatile solution for gamers, creatives, and professionals alike. The software's ease of setup and use, combined with its strong performance even in low-bandwidth environments, contribute to its positive reputation.

Recommended for

  • Gamers looking for low-latency game streaming to play with friends remotely.
  • Professionals needing access to their desktop environment from different locations.
  • Creative professionals who require remote collaboration or access to powerful hardware for rendering tasks.
  • Anyone seeking a high-quality remote desktop experience with minimal setup complexity.

Parsec videos

+ Add

Is Parsec any good? First Impressions with UNIST, Skullgirls, and DBFZ

More videos:

  • Review - Gaming On A $17 Office PC with Parsec! | OzTalksHW
  • Review - Parsec Cloud Gaming Review

TensorFlow videos

+ Add

What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks

More videos:

  • Tutorial - TensorFlow In 10 Minutes | TensorFlow Tutorial For Beginners | Deep Learning & TensorFlow | Edureka
  • Review - TensorFlow in 5 Minutes (tutorial)

Category Popularity

0-100% (relative to Parsec and TensorFlow)

Parsec

TensorFlow

Game Streaming
100 100%
Game Streaming
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Games
100 100%
Games
0% 0
AI
0 0%
AI
100% 100

User comments

Share your experience with using Parsec and TensorFlow. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Parsec and TensorFlow

Parsec Reviews

Top Remote Desktop Software for Gaming
Like AnyDesk or TeamViewer, Parsec was not initially an RDP gaming solution. It was developed primarily for developers and engineers who needed a remote connection to work on their projects. Thus, a main feature Parsec offered was great graphics.
Source: cloudzy.com
Moonlight game streaming alternatives
Released 6 years ago, Parsec is an application that lets users capture their desktop. This is mainly used by players to play games on their computers from different devices. Players can stream their games on their own personal computers for free through Parsec. But there is also an option to rent servers to play games on. Moreover, it prioritizes user safety over everything...
Source: androidgram.com
15 Best Parsec Alternatives [Remote Desktop Tools] in 2022
Parsec is a proprietary desktop capture application primarily used to play games via video streaming. Using Parsec, users can stream video game footage over an Internet connection, allowing one person to run the game on one computer but play it remotely from another device. While its primary focus is gaming, Parsec can also be used as a low-latency desktop sharing software.
Source: phreesite.com
10 Best Hamachi Alternatives for Virtual LAN Gaming
Parsec is a desktop capturing application mainly used for playing video games through video streaming. Still, it also allows the creation of virtual LAN gaming servers using the local co-op feature.
Source: techviral.net
11 Best Parsec Alternatives & Similar Apps
Parsec has been known for its ability to connect your smartphone to the desktop. However, some Parsec alternatives are also known for offering a lot more to their users.
Source: www.regendus.com

TensorFlow Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks such as machine learning, computer vision, and natural language processing. It provides excellent support for deep learning models and is widely used in several industries. TensorFlow offers several pre-trained models for image classification, object detection,...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be...
Source: www.assemblyai.com

Social recommendations and mentions

Based on our record, Parsec seems to be a lot more popular than TensorFlow. While we know about 370 links to Parsec, we've tracked only 7 mentions of TensorFlow. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Parsec mentions (370)

  • Comet open source remote KVM from GL-iNet
    There's not much to it to be honest. If you've got Home Assistant running then https://www.home-assistant.io/integrations/wake_on_lan/ will sort you out, and I have Parsec (https://parsec.app) installed on my desktop so that it starts on boot. - Source: Hacker News / 3 months ago
  • Raspberry Pi 5 now supports Valve's Steam Link
    Parsec[1] would be interesting to compare. [1] https://parsec.app/. - Source: Hacker News / 6 months ago
  • How I created my first open-source project.
    Everything started with me trying to log into my AWS EC2 machine. Every time I wanted to connect to AWS EC2 using Parsec, I had to type the entire OS password, because there isn't a way to paste over Parsec. And yes, it is a large password. Is it a boring activity? Yes! I did it every time until my patience ran off and my laziness took over. - Source: dev.to / 10 months ago
  • SF's AI boom can't stop real estate slide, as office vacancies reach new record
    Yep I agree. The other advantage Vancouver always had is that there's a pretty significant amount of residential Downtown and near Downtown, and so Downtown didn't fully empty out as badly as many American cities, and there are a massive amount of workers that can walk and bike to work. I don't have familiarity with the needs of digital effects workers, but I'm unsure that there were any technical barriers for the... - Source: Hacker News / 11 months ago
  • Are the Apple addicts ok?
    If that's an option, you could use a Macbook air and something like https://parsec.app/ to stream from a windows machine. Source: over 1 year ago
View more

TensorFlow mentions (7)

  • Creating Image Frames from Videos for Deep Learning Models
    Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 2 years ago
  • Need help with a Tensorflow function
    So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 3 years ago
  • Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
    Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 3 years ago
View more

What are some alternatives?

When comparing Parsec and TensorFlow, you can also consider the following products

Moonlight-Stream.org - Moonlight allows you to stream your collection of games from your GameStream-compatible PC to any...

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Geforce Now - Underpowered PC can now pack the punch of high-performance GeForce GTX GPUs with GeForce NOW.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Shadow - Transform any device into a supercharged gaming machine.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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