Bend

Write parallel code for multi-core CPUs & GPUs without being a C/CUDA expert. Deploy on our network with instant access to hundreds of Distributed GPUs.

[Bend @UseBendAi]

@PowerGPU We need some more 👀

[Bend @UseBendAi]

🛡️ Instant access to over 1,000+ Distributed GPUs, available to deploy instantly, with Bend.

[NVIDIA Newsroom @nvidianewsroom]

NVIDIA CEO Jensen Huang unveiled what’s next for AI — from the $1T inflection point to breakthroughs in robotics, data centers, and accelerated computing.

Here’s a quick recap from the #GTC25 keynote 🧵

[Bend @UseBendAi]

Bend is celebrating 1 year on X!

[Bend @UseBendAi]

@bhrugsy 👋 Start programming with Bend! You can compile to CUDA and deploy to our network of distributed GPUs.

[Bend @UseBendAi]

Ever dreamed of coding parallel programs that fly without breaking a sweat? Bend’s genius syntax delivers jaw-dropping speed and simplicity.

Check it out: https://t.co/8g5dIS2Yfg

#Bend #AI #GPU

[Bend @UseBendAi]

You read the Bend documentation but found it too technical? We’ve got you covered.

1⃣ The Problem

Graphics Processing Units (GPUs) power modern computing, but programming them requires complex low-level languages like CUDA and C++.

2⃣ The Solution

Bend simplifies parallel programming on GPUs, making it as simple as Python. Plus, it offers a network of Distributed Compute Nodes—on-demand GPUs you can rent anytime.

Say goodbye to complex GPU coding. Just BEND it.

#Bend #GPU

[Bend @UseBendAi]

See how Bend's concise, high-level syntax outperforms the verbosity of traditional C# code.

Write faster, cleaner, and more scalable programs optimized for parallelism with ease.

Check it out: https://t.co/ryiAmYNQHA

#Bend #GPU

[Matthew Berman @MatthewBerman]

Test Time Compute is bigger than anyone realizes.

It's the most important breakthrough in AI since Transformers.

Let me explain...🧵

[Antonio García Martínez (agm.eth) @antoniogm]

OpenAI hiring more and more engineers at ever higher salaries tells you what you need to know about the impact of AI on software engineering.

[Bend @UseBendAi]

The secret behind training trillion-parameter AI models like GPT-4 and delivering instant responses to millions?

Connecting thousands of GPUs into a seamless pool, working together like a supercomputer.

Here’s why GPU pooling changes the game:
1️⃣ Speed: Faster training and inference.
2️⃣ Scalability: Add GPUs as demand grows.
3️⃣ Efficiency: Maximized resource usage.

And with tools like Bend, writing code to leverage GPU pools is as simple as Python. 🖥️⚡

What’s your take on GPU pooling? The future or just a stepping stone? 🤔

[el.cine @EHuanglu]

NVIDIA just shocked the AI world with its new AI agents

Meet NVIDIA Project R2X, an AI powered digital human interface for AI enthusiasts building AI agents

Here are 8 key highlights you can't afford to miss:

[Bend @UseBendAi]

@Alexandersign Coding with Bend is like any other language, syntax almost resembles python! You can compile it to 4 runtimes. More here: https://t.co/tQl1ZRqqdU

[Bend @UseBendAi]

Most programming languages run on only 1 Core of the computer's CPU. This means parallel operations are deadly slow. 🦥

By writing multi-core code with Bend for GPUs we can leverage 10,000x as many threads than a single CPU has.⚡

[Bend @UseBendAi]

8/ TLDR...

GPUs turned AI from a study into a transformative force in our lives.

As we explore new hardware and software, what are your predictions for the future of GPUs in AI? Let’s chat! 👇

[Bend @UseBendAi]

How GPUs Revolutionized AI (and What’s Next...) 🧵

[Bend @UseBendAi]

7/ The Role of Software:

New tools are emerging to simplify GPU programming for AI:

- Python-based libraries like PyTorch Lightning.
- Languages like Bend, bringing GPU coding to everyone.

Software innovation will drive the next wave of AI advancements. 🚀