Josh Gordon

Open source ML @ Google NYC

[Josh Gordon @random_forests]

New Kaggle competition. Add reasoning capabilities to a small Gemma model using Tunix (a new popular RL library in JAX). This is really great, thanks to Wei on my team + many others for driving it. Check it out!

[Kaggle @kaggle]

📣 Hackathon Launch Alert! Google Tunix Hack - Train a Model to Show Its Work hosted by @googlecloud

🎯 Train Gemma models to show reasoning using Tunix
💰 $100,000 Prize Pool
⏰ Final Submission: Jan 12, 2026

https://t.co/tLRUv9bhvY

[Josh Gordon @random_forests]

New function calling guide with Gemma 3 & KerasHub -- really nice to be able to run locally.

[Samaneh Saadat @smn_sdt]

Function calling guide for Keras!

[Divyashree Sreepathihalli @divyasheess]

KerasHub now includes HGNetV2!
We’re excited to bring the high-efficiency, high-accuracy HGNetV2 image classification backbone into KerasHub’s model family.

Model details and quickstart notebook are available on Kaggle: https://t.co/ytUSn7j9xK

#keras #kerashub #HGNet

[Cristian Garcia @cgarciae88]

The JAX team is hosting a dinner / networking event during ICML on Thursday. Join us for an evening of food, drinks, and discussion of all things JAX.

@SingularMattrix
and other JAX team member will be attending. Please register early as capacity is limited.

RSVP: https://t.co/L7KoaqlTI9

[Mark McD ☠ @m4rkmc]

🎬 Generate videos with the Gemini CLI

Add:
🧑‍💻 GenMedia MCP servers for Imagen, Veo & Chirp
📝 A GEMINI܂md file explaining your ✨ creative process

And you too can take 🙀 Rusty the Cat on an adventure

⬇️ Full tutorial in the vid ⬇️

[Google AI Developers @googleaidevs]

Some interesting Gemini CLI use cases and tutorials 🧵⬇️

[Abheesht Sharma @penstrokes75]

We’re building Keras Recommenders at Google, and would love to hear from people working in RecSys to understand what they need. What features matter most to you?

DMs are open, feel free to reach out!

https://t.co/wWb67TnaSu

[Josh Gordon @random_forests]

People are getting monster offers to work on LLMs behind closed doors, and meanwhile this team from Stanford is doing everything in the open and making it available to everyone. Open science all the way!

[Percy Liang @percyliang]

Open development of language models in action!

[Josh Gordon @random_forests]

It was *so good* seeing everyone at the JAX and OpenXLA DevLab this week! Best event in a long time. Let’s do it again!

[Mark McD ☠ @m4rkmc]

I am PUMPED to finally share what we’ve been working on:

🖥️ Introducing the Gemini CLI!

It can code, sure, but with access to your system shell, files and MCP servers, it can also:

👩‍🔬 Do research
💽 Organise your MP3s
🪾 Resolve rebases
🔬 Even strace that weird hung process

Check it out: https://t.co/Onx60HtkRc

And I REALLY want to see how it helps you, so tag or share your workflows here!

[Josh Gordon @random_forests]

Here's more detail on how to load a Hugging Face checkpoint into a KerasHub model. Thanks for the walkthrough, @yufengg , @divyasheess, and @monicadsong !

https://t.co/JbFgdhY40Y

[Josh Gordon @random_forests]

You can find performance & scale optimized JAX models in MaxText and MaxDiffusion:

* https://t.co/NHuignJq4q
* https://t.co/FN8yTcu4EW

You can also use Keras / JAX to tune many Hugging Face Transformers model checkpoints by loading them into a KerasHub model. It's pretty cool!

* https://t.co/R1FfYWciVy
* https://t.co/1EJNBVB368

[Josh Gordon @random_forests]

@shresbm @thechrisperry @simpsoka @VNallatamby This is really great!

[Josh Gordon @random_forests]

@cgarciae88 100% back! Best event in a long time, felt like old times. The JAX team is killing it. Let’s scale up and do it again! (Also the healthcare research breakout was extremely cool).

[Samaneh Saadat @smn_sdt]

KerasHub supports loading checkpoints of many model architectures from HuggingFace.
So if there is a model checkpoint on HF that is not in the Keras format, you can easily load it in Keras and use it as a regular Keras model in any backends (JAX, TF, or PyTorch).

[François Chollet @fchollet]

If you're running JAX and you need to grab a model checkpoint from HuggingFace, KerasHub has you covered. Load, fine-tune, quantize, export for inference.

[Josh Gordon @random_forests]

You can find performance & scale optimized JAX models in MaxText and MaxDiffusion:

* https://t.co/NHuignJq4q
* https://t.co/FN8yTcu4EW

You can also use Keras / JAX to tune many Hugging Face Transformers model checkpoints by loading them into a KerasHub model. It's pretty cool!

* https://t.co/R1FfYWciVy
* https://t.co/1EJNBVB368

[Josh Gordon @random_forests]

Really excited for the upcoming JAX & OpenXLA DevLab this Monday! This is a small group deep dive on the latest techniques, with breakouts on special interests. We'll record the tutorials for everyone, too.

Opportunity: If you're interested in *healthcare research* with JAX / LLMs, we have a couple more seats available at that breakout. Send me a DM here if you'd like to attend.

https://t.co/WCucrY3XNS

[Josh Gordon @random_forests]

11/ You can find lots more examples in quickstarts folder in the cookbook.

Also check out the developer docs on https://t.co/ytwbvCfemM for lots more walkthroughs, and code examples for JS developers.

If you have questions or run into bugs, the best place to ask them is on https://t.co/H1qGcJtbq3

Have fun!

[Josh Gordon @random_forests]

Yes! And you can start developing with the Gemini Developer API in just a couple minutes.

If you're just getting started, here's a quick walkthrough that shows you how to get your API key and run a neat audio generation example in Colab.

1/ Visit https://t.co/3nMspvbzUK to get your API key

[Sundar Pichai @sundarpichai]

1/ A quick recap from another week of rapid shipping: 

Great response to our Gemini 2.5 Pro update now in preview. Find it in AI Studio, Vertex + @GeminiApp. 

And good news for @GeminiApp Pro plan members: your 2.5 Pro limit doubled from 50 to 100 queries per day.

[Josh Gordon @random_forests]

10/ You can play the audio right in Colab.

There's also a neat example that prompts the model to read a discussion between two speakers, like NotebookLM.

Add your own prompts and see what the model can do.