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CUDA Toolkit VS Anything.so

Compare CUDA Toolkit VS Anything.so and see what are their differences

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CUDA Toolkit logo CUDA Toolkit

Select Target Platform Click on the green buttons that describe your target platform.

Anything.so logo Anything.so

Anything blends AI and human support to detect, delegate, and complete your tasks before they even reach your to-do list.
Visit Website
  • CUDA Toolkit Landing page
    Landing page //
    2024-05-30
  • Anything.so
    Image date //
    2025-09-29
  • Anything.so
    Image date //
    2025-09-29
  • Anything.so
    Image date //
    2025-09-29
  • Anything.so
    Image date //
    2025-09-29
  • Anything.so
    Image date //
    2025-09-29

Anything is the perfect blend of AI and human assistant.

We detect tasks directly from your world (email, calendar, life) and complete them before they even hit your to-do list. You swipe. We move. No dashboards, no micromanaging.

Unlike productivity tools that need constant input, or VA services that sell hours, Anything owns the follow-through. A stable lead assistant backed by automation and a trained human squad closes the loop for you.

What you get:

Detect early – We surface tasks before they steal your attention Delegate instantly – Say it once (or less), never babysit Done right – Human where it matters. AI where it doesn’t.

Built for professionals with more life than time. Skip the drag. Stay focused. We’ll handle Anything else.

CUDA Toolkit features and specs

  • Performance
    CUDA Toolkit provides highly optimized libraries and tools that enable developers to leverage NVIDIA GPUs to accelerate computation, vastly improving performance over traditional CPU-only applications.
  • Support for Parallel Programming
    CUDA offers extensive support for parallel programming, enabling developers to utilize thousands of threads, which is imperative for high-performance computing tasks.
  • Rich Development Ecosystem
    CUDA Toolkit integrates with popular programming languages and frameworks, such as Python, C++, and TensorFlow, allowing seamless development for AI, simulation, and scientific computing applications.
  • Comprehensive Libraries
    The toolkit includes a range of powerful libraries (like cuBLAS, cuFFT, and Thrust), which optimize common tasks in linear algebra, signal processing, and data analysis.
  • Scalability
    CUDA-enabled applications are highly scalable, allowing the same code to run on various NVIDIA GPUs, from consumer-grade to data center solutions, without code modifications.

Possible disadvantages of CUDA Toolkit

  • Hardware Dependency
    Developers need NVIDIA GPUs to utilize the CUDA Toolkit, making projects dependent on specific hardware solutions, which might not be feasible for all budgets or systems.
  • Learning Curve
    CUDA programming has a steep learning curve, especially for developers unfamiliar with parallel programming, which can initially hinder productivity and adoption.
  • Limited Multi-Platform Support
    CUDA is primarily developed for NVIDIA hardware, which means that applications targeting multiple platforms or vendor-neutral solutions might not benefit from using CUDA.
  • Complex Debugging
    Debugging CUDA applications can be complex due to the concurrent and parallel nature of the code, requiring specialized tools and a solid understanding of parallel computing.
  • Backward Compatibility
    Some updates in the CUDA Toolkit may affect backward compatibility, requiring developers to modify existing codebases when upgrading the CUDA version.

Anything.so features and specs

  • Proactive Task Detection
    Connects to your email and calendar to surface tasks before they hit your to-do list.
  • One-Swipe Delegation
    Review, approve, and delegate tasks in a tap. No back-and-forth. No dashboards. Just done.
  • Human + AI Assistant Squad
    Your lead assistant is backed by automation and a trained squad to handle work without micromanagement.

CUDA Toolkit videos

+ Add

1971 Plymouth Cuda 440: Regular Car Reviews

More videos:

  • Review - Jackson Kayak Cuda Review
  • Review - Great First Effort! The New $249 Signum Cuda

Anything.so videos

+ Add

What's Anything?

Category Popularity

0-100% (relative to CUDA Toolkit and Anything.so)

CUDA Toolkit

Anything.so

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Productivity
0 0%
Productivity
100% 100
Business & Commerce
100 100%
Business & Commerce
0% 0
AI
68 68%
AI
32% 32

Questions and Answers

As answered by people managing CUDA Toolkit and Anything.so.

What makes your product unique?

Anything.so's answer:

Anything blends AI and human support to detect, delegate, and complete tasks before they reach your to-do list. Unlike tools that need constant input or VAs that need managing, we own the follow-through, so work moves without you.

Why should a person choose your product over its competitors?

Anything.so's answer:

We’re not selling hours or more dashboards. Anything is a managed service powered by automation and a stable assistant squad. We detect tasks from your life, not just your tools, and we handle them end to end. No training, no micromanaging, just outcomes.

How would you describe your primary audience?

Anything.so's answer:

High-velocity professionals with more life than time: founders, freelancers, operators, and executives who are drowning in admin but allergic to drag. They don’t need help doing work, they need the work gone.

What's the story behind your product?

Anything.so's answer:

We built Anything because we were overwhelmed by the meta-work of running companies, yet tired of patching together tools and managing more people. We needed true delegation: fast, smart, and affordable. So we built the platform we wish existed.

Which are the primary technologies used for building your product?

Anything.so's answer:

  • AI task classification models
  • LLMs for message/action generation
  • Custom workflow orchestration
  • Secure integrations with Google Workspace and other APIs
  • Human-in-the-loop assistant ops system

Who are some of the biggest customers of your product?

Anything.so's answer:

  • Over 300 early professionals on the waitlist
  • Founders at Y Combinator–backed startups
  • Senior operators at growth-stage companies

User comments

Share your experience with using CUDA Toolkit and Anything.so. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, CUDA Toolkit seems to be more popular. It has been mentiond 41 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.

CUDA Toolkit mentions (41)

  • Empowering Windows Developers: A Deep Dive into Microsoft and NVIDIA's AI Toolin
    CUDA Toolkit Installation (Optional): If you plan to use CUDA directly, download and install the CUDA Toolkit from the NVIDIA Developer website: https://developer.nvidia.com/cuda-toolkit Follow the installation instructions provided by NVIDIA. Ensure that the CUDA Toolkit version is compatible with your NVIDIA GPU and development environment. - Source: dev.to / 5 months ago
  • 5 AI Trends Shaping 2025: Breakthroughs & Innovations
    Nvidia’s CUDA dominance is fading as developers embrace open-source alternatives like Triton and JAX, offering more flexibility, cross-hardware compatibility, and reducing reliance on proprietary software. - Source: dev.to / 8 months ago
  • Building Real-time Object Detection on Live-streams
    Since I have a Nvidia graphics card I utilized CUDA to train on my GPU (which is much faster). - Source: dev.to / 10 months ago
  • On the Programmability of AWS Trainium and Inferentia
    In this post we continue our exploration of the opportunities for runtime optimization of machine learning (ML) workloads through custom operator development. This time, we focus on the tools provided by the AWS Neuron SDK for developing and running new kernels on AWS Trainium and AWS Inferentia. With the rapid development of the low-level model components (e.g., attention layers) driving the AI revolution, the... - Source: dev.to / 11 months ago
  • Deploying llama.cpp on AWS (with Troubleshooting)
    Install CUDA Toolkit (only the Base Installer). Download it and follow instructions from Https://developer.nvidia.com/cuda-downloads. - Source: dev.to / over 1 year ago
View more

Anything.so mentions (0)

We have not tracked any mentions of Anything.so yet. Tracking of Anything.so recommendations started around Sep 2025.

What are some alternatives?

When comparing CUDA Toolkit and Anything.so, you can also consider the following products

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.

Howie the peoples secretary - Howie is an email-based secretary who manages your calendar with the finesse of a world-class EA and the precision of a bleeding-edge AI.

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

3D Reshaper - Point cloud process, 3D Meshing, CAD surface reconstruction, dental CAD

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

ActorDO - AI Assistant for busy professionals. Simplify your Email, Calendar and Daily Agenda with AI.

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