TensorFlow, every mention
17 scenes, the whole family · ← back to TensorFlow
tap a year for its mentions
every year anyone Jeremy Howard 4George Hotz 3Chris Lattner 3Alessio Fanelli 3Shawn Wang 1Sarah Chieng 1Michael Royzen 1Lin Qiao 1Ankur Goyal 1Akshay Agrawal 1
Verbatim, from the transcripts: the passages where TensorFlow comes up
🕰️ The Oral History of Windsurf (ft. Varun Mohan, Scott Wu, Jeff Wang, Kevin Hou, Anshul R)
- ▶ 2:34:10 Shawn Wang You can't just use VLLM and TensorFlow.
⚡️The Future of Notebooks - with Akshay Agrawal of Marimo
- ▶ 2:43 Akshay Agrawal It was a while ago, but I was an engineer on TensorFlow.
The Shape of Compute (Chris Lattner of Modular)
- ▶ 49:27 Chris Lattner TensorFlow, remember that? 3 times in the scene
DeepSeek V3, SGLang, and the state of Open Model Inference in 2025 (Quantization, MoEs, Pricing)
- ▶ 20:36 unnamed speaker We have customers on, on based end that are using TensorFlow and we have ones that are using VL and we have a growing number that are using SGLang too.
Windsurf: The Enterprise AI IDE
- ▶ 57:22 unnamed speaker You can't just use VLLM and TensorFlow.
[Paper Club] Weight Streaming on Wafer-Scale Clusters (w/ Sarah Chieng of Cerebras)
- ▶ 39:36 Sarah Chieng Um, okay, so the Cerebris Graph Compiler, um, the CGC right here integrates with machine learning frameworks, such as, such as TensorFlow and PyTorch.
Why Compound AI + Open Source will beat Closed AI — with Lin Qiao, CEO of Fireworks AI
Production AI Engineering starts with Evals
- ▶ 1:23:24 Ankur Goyal We're writing only TensorFlow before.
A Comprehensive Overview of Large Language Models - Latent Space Paper Club
- ▶ 24:12 unnamed speaker So, things like, um, the libraries that we're using, um, JAX, PyTorch, TensorFlow, amongst others, um, there's this idea of distributed training, which means that, um, can we use multiple GPUs to train our models so that we are able to…
- ▶ 38:17 unnamed speaker So, um, essentially what happens is that if you go to maybe say, um, TensorFlow datasets or Hugging Face, you'll be able to download them, um, and then you'll be able to observe, um, these datasets, uh, by itself.
Open Source AI is AI we can Trust — with Soumith Chintala of Meta AI
- ▶ 10:35 unnamed speaker He mentioned when he was at Google, TensorFlow, it's trying to be optimized to make TPUs go brr, you know, and go as fast.
The State of Silicon and the GPU Poors - with Dylan Patel of SemiAnalysis
- ▶ 11:08 Alessio Fanelli We had, um, Chris Landner on the show, which I know, you know, um, he used to work on TensorFlow and Google, and he did mention that 2 times in the scene
Beating GPT-4 with Open Source Models - with Michael Royzen of Phind
- ▶ 1:03 Michael Royzen Um, I remember when, like, TensorFlow came out, and, like, people started talking about, oh, obviously at the time, the, um, after AlexNet, the deep learning revolution was already, you know, in flow, and, um, good computer vision models…
The End of Finetuning — with Jeremy Howard of Fast.ai
- ▶ 59:48 Jeremy Howard You know, and so this felt like, okay, I, you know, well, you know, what are you going to do? 4 times in the scene
RWKV: Reinventing RNNs for the Transformer Era
- ▶ 4:30 unnamed speaker Yeah, ok so, and, and, ah, just to, and because I had this initial confusion, Brain.js, ah, has nothing to do with TensorFlow, even though I think both were run by Google? 2 times in the scene
Ep 18: Petaflops to the People — with George Hotz of tinycorp
- ▶ 5:33 Alessio Fanelli And they started from TensorFlow and then they, they made the chip after.
- ▶ 12:11 George Hotz Oh, you're gonna be, you're gonna be, you're gonna be diving down a long stack from Python to C to custom libraries to dispatchers to, and then I don't even know how to read TensorFlow. 3 times in the scene