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Shadow VS PyTorch

Compare Shadow VS PyTorch and see what are their differences

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Shadow logo Shadow

Transform any device into a supercharged gaming machine.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Shadow Landing page
    Landing page //
    2023-10-04
  • PyTorch Landing page
    Landing page //
    2023-07-15

Shadow

Website
shadow.tech
$ Details
-
Release Date
2015 January
Startup details
Country
France
State
Ile-de-France
City
Paris
Founder(s)
Asher Kagan
Employees
100 - 249
Edit details

PyTorch

Website
pytorch.org
$ Details
Release Date
-
Edit details

Shadow features and specs

  • High-Performance
    Shadow provides a high-performance virtual computer with dedicated resources, ensuring smooth operation for demanding applications and games.
  • Accessibility
    Users can access their Shadow PC from various devices including Windows, macOS, Android, and iOS, making it versatile and highly accessible.
  • Cost-Effective
    For users who require high-end hardware but cannot afford the upfront cost, Shadow's subscription model provides access to powerful technology for a manageable monthly fee.
  • Security and Updates
    The service includes regular updates and security measures, so users don’t need to worry about maintaining their hardware or software.
  • Storage
    Shadow offers substantial cloud storage, which can be a significant advantage for users needing large amounts of space for their projects and files.

Possible disadvantages of Shadow

  • Internet Dependency
    Shadow requires a stable and fast internet connection to function properly. Poor connectivity can result in lag and reduced performance.
  • Bandwidth Usage
    Streaming a virtual computer can consume a lot of data, which may be an issue for users with limited bandwidth or data caps.
  • Subscription Cost
    Although cost-effective for some, the subscription fee can become expensive over time compared to owning your own hardware outright.
  • Latency
    Despite high performance, users may still experience latency issues, especially in high-speed applications like competitive gaming.
  • Limited Offline Use
    The reliance on cloud means that there is no offline mode, so users can’t access their virtual machine without an internet connection.

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Analysis of PyTorch

Overall verdict

  • Yes, PyTorch is considered a good deep learning framework.

Why this product is good

  • Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
  • Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
  • Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
  • Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
  • Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.

Recommended for

  • Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
  • Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
  • Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.

Shadow videos

+ Add

Shadow - Movie Review

More videos:

  • Review - Shadow Cloud Gaming Review
  • Review - Shadow - Movie Review

PyTorch videos

+ Add

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Shadow and PyTorch)

Shadow

PyTorch

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

User comments

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Reviews

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

Shadow Reviews

11 Best Parsec Alternatives & Similar Apps
Still, it can consume your battery. All in all, Shadow is a worth-trying app for those who love games and want to always connect with their games regardless of the location.
Source: www.regendus.com
7 Best Cloud Gaming Services for 2020 (No. 3 is My Favorite)
Although games are a popular use of Shadow, and work well on it, Shadow’s core service is more than just games. While that’s a pro for some, it may be extra weight for people who want to keep things simple.
Source: hostingpill.com
Stream games with these Google Stadia alternatives
The Shadow cloud gaming model is about to be updated, and it will make it quite the formidable foe. For the basic monthly investment of £13, you gain access to a timeshare comprised of an Intel Xeon CPU, an Nvidia GTX 1080 equivalent graphics card, 12GB of DDR4, a 256GB SSD, and an internet connection that’ll make you weep in awe. It’s 1Gbps, so you absolutely don’t need to...
Source: www.pcgamesn.com
15 game streaming services you can try before Google Stadia arrives
You might not have heard of Shadow, but it’s a real cloud game streaming service based in the United States. Like other similar platforms, Shadow works by giving you a virtualized computer with the means to play 3D games. Currently, Shadow is operational in 38 out of the 50 states, with more on the way.
Source: www.theverge.com
The Best Cloud Gaming Services for Streaming Video Games
Shadow: Cloud gaming at a fixed price. Shadow functions as a subscription service, with a price of $35 a month no matter how much time you spend playing. For those of you that play way more than you should, this service may be for you. It’s also similar to Parsec in that it’s essentially a computer in the cloud, so you can run any app you want in it.
Source: www.howtogeek.com

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
Source: www.assemblyai.com
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Shadow should be more popular than PyTorch. It has been mentiond 320 times since March 2021. 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.

Shadow mentions (320)

  • 🚀 Get a 5€ Discount on Your ShadowPC Subscription with Code: 80EDA79
    Upgrade your gaming experience with ShadowPC! Use my referral code "80EDA79" at checkout to snag a cool 5€ off your first subscription. Game on! 🚀. Source: over 1 year ago
  • PCVR on Mac?
    I had Shadow. There quite affordable when I registered and the hardware was top line. I was using it as my gaming PC for a long time (mainly for PCVR). I live in Spain and these days there wasn't dedicated servers here so I connected through Paris nodes (and that increased a bit the latency) but I play HL Alyx and a lot of games that way with good graphics (in that moment Shadow has a GTX1080 GPU) and great... Source: almost 2 years ago
  • Journeyperson save on a potato? Or stuck to one large nation/several small ones?
    Https://shadow.tech/ It’s a cloud PC. I used to use it until I got my current laptop. Not cheap but very good. Source: about 2 years ago
  • Apple's game porting toolkit is fantastic. Cyperbunk 2077 at Ultra on an M1 MBP
    > But then Apple doesn't ship devices with actually powerful GPUs, so it can never compete with the gaming PCs which are far less expensive and far more powerfull graphics-wise. It is still expensive to have to use Windows just so you can game. Or put all the effort into dual booting Linux. Most people just use a Macbook and then get an Xbox/Ps5/Switch/Quest2. For games I can't use on those you can get Shadow PC... - Source: Hacker News / about 2 years ago
  • Stream pirated Games
    There is shadow.tech, which just gives you a full Windows Desktop with a little persistent disk. This should in theory work the way you want to. Source: about 2 years ago
View more

PyTorch mentions (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 27 days ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / about 1 month ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / 2 months ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 4 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 4 months ago
View more

What are some alternatives?

When comparing Shadow and PyTorch, you can also consider the following products

Parsec - Streams games locally or over the internet

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.

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.

Stadia - A new gaming platform from Google

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

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