Fei Hu

[Fei Hu @Fei__Hu]

@river_ai_inc Congrats!!🚀🚀

[River AI @river_ai_inc]

We are incredibly excited to announce River AI. Our mission is to create personal AI that is owned and shaped by you.

Today’s best AIs are controlled by a few large corporations. We are building the alternative: a new, personal stack for AI that works entirely for you, shares your values, and operates on your terms.

[Fei Hu @Fei__Hu]

@archanfel_anoth All the best!! 🐐🐐

[Fei Hu @Fei__Hu]

@radixark @Accel @sparkcapital Big congrats!!

[Fei Hu @Fei__Hu]

@Yihe__Deng All the best!

[Fei Hu @Fei__Hu]

@JackCaiXun All the best! 🐐🐐

[Fei Hu @Fei__Hu]

@hsu_byron @xai @periodiclabs Congrats Byron! 🐐

[Fei Hu @Fei__Hu]

@HeinrichKuttler @xai @elonmusk 🐐🐐

[Fei Hu @Fei__Hu]

@Guodzh Thank you for everything, Captain! 🫡🫡

[Fei Hu @Fei__Hu]

@hyhieu226 @OpenAI @xai Take care, Hieu!

[Fei Hu @Fei__Hu]

@hongyuan_mei All the best!

[xAI @xai]

Introducing Grok Imagine 1.0, our biggest leap yet.

1.0 unlocks 10-second videos, 720p resolution, and dramatically better audio.

Imagine has generated 1.245 billion videos in the last 30 days alone.

Try it now: https://t.co/zGhs9czkC5

[Ying Sheng @ying11231]

We've been running @radixark for a few months, started by many core developers in SGLang @lmsysorg and its extended ecosystem (slime @slime_framework , AReaL @jxwuyi). I left @xai in August — a place where I built deep emotions and countless beautiful memories. It was the best place I’ve ever worked, the place I watched grow from a few dozen people to hundreds, and it truly felt like home. What pushed me to make such a hard decision is the momentum of building SGLang open source and the mission of creating an ambitious future, within an open spirit that I learnt from my first job at @databricks after my PhD.

We started SGLang in the summer of 2023 and made it public in January 2024. Over the past 2 years, hundreds of people have made great efforts to get to where they are today. We experienced several waves of growth after its first release. I still remember the many dark nights in the summer of 2024, I spent with @lm_zheng , @lsyincs , and @zhyncs42 debugging, while @ispobaoke single-handedly took on DeepSeek inference optimizations, seeing @GenAI_is_real and the community strike team tag-teaming on-call shifts non-stop. There are so many more who have joined that I'm out of space to call out, but they're recorded on the GitHub contributor list forever. The demands grow exponentially, and we have been pushed to make it a dedicated effort supported by RadixArk. It’s the step-by-step journey of a thousand miles that has carried us here today, and the same relentless Long March that will lead us into the tens of thousands of miles yet to come.

The story never stops growing. Over the past year, we’ve seen something very clear:
The world is full of people eager to build AI, but the infrastructure that makes it possible is not shared. The most advanced inference and training stacks live inside a few companies. Everyone else is forced to rebuild the same schedulers, compilers, serving engines, and training pipelines again and again — often under enormous pressure, with lots of duplicated effort and wasted insight.

RadixArk was born to change that. Today, we’re building an infrastructure-first, deep-tech company with a simple and ambitious mission:
"Make frontier-level AI infrastructure open and accessible to everyone."

If the two values below resonate with you, come talk to us:

(1) Engineering as an art.
Infrastructure is a first-class citizen in RadixArk. We care about elegant design and code that lasts. Beneath every line of code lies the soul of the engineer who wrote it.

(2) A belief in openness.
We share what we build. We bet on long-term compounding through community, contribution, and giving more than we take.

A product is defined by its users, yet it truly comes alive the moment functionality transcends mere utility and begins to embody aesthetics.

Thanks to all the miles (the name of our first released RL framework; see below).

https://t.co/2vio4Eiiac

[Juntang Zhuang @archanfel_anoth]

Heading to neurips, excited to see old and new friends! I’m actively hiring for pretrain team, open topics like reinforcement pretrain, and native unified mm model, pushing intelligence frontiers, or anything interesting. Feel free to stop by or have a coffee chat!

[xAI @xai]

Introducing Grok 4.1, a frontier model that sets a new standard for conversational intelligence, emotional understanding, and real-world helpfulness.

Grok 4.1 is available for free on https://t.co/AnXpIEOPEb, https://t.co/53pltyq3a4 and our mobile apps.

https://t.co/Cdmv5CqSrb

[Andrej Karpathy @karpathy]

I took delivery of a beautiful new shiny HW4 Tesla Model X today, so I immediately took it out for an FSD test drive, a bit like I used to do almost daily for 5 years. Basically... I'm amazed - it drives really, really well, smooth, confident, noticeably better than what I'm used to on HW3 (my previous car) and eons ahead of the version I remember driving up highway 280 on my first day at Tesla ~9 years ago, where I had to intervene every time the road mildly curved or sloped. (note this is v13, my car hasn't been offered the latest v14 yet)

On the highway, I felt like a passenger in some super high tech Maglev train pod - the car is locked in the center of the lane while I'm looking out from Model X's higher vantage point and its panoramic front window, listening to the (incredible) sound system, or chatting with Grok. On city streets, the car casually handled a number of tricky scenarios that I remember losing sleep over just a few years ago. It negotiated incoming cars in tight lanes, it gracefully went around construction and temporarily in-lane stationary cars, it correctly timed tricky left turns with incoming traffic from both sides, it gracefully gave way to the car that went out of order in the 4-way stop sign, it found a way to squeeze into a bumper to bumper traffic to make its turn, it overtook the bus that was loading passengers but still stopped for the stop sign that was blocked by the bus, and at the end of the route it circled around a parking lot, found a spot and... parked. Basically a flawless drive.

For context, I'm used to going out for a brief test drive around the neighborhood to return with 20 clips of things that could be improved. It's new for me to do just that and exactly like I used to, but come back with nothing. Perfect drive, no notes. I expect there's still more work for the team in the long march of 9s, but it's just so cool to see that we're beyond finding issues on any individual ~1 hour drive around the neighborhood, you actually have to go to the fleet and mine them. Back then, I processed the incredible promise of vehicle autonomy at scale (in the fully scaleable, vision only, end-to-end Tesla way) only intellectually, but now it is possible to feel it intuitively too if you just go out for a drive. Wait, of course surround video stream at 60Hz processed by a fully dedicated "driving brain" neural net will work, and it will be so much better and safer than a human driver. Did anyone else think otherwise?

I also watched @aelluswamy 's new ICCV25 talk last week (https://t.co/RdaM23kvez) that hints at some of the recent under the hood technical components driving this progress. Sensor streams (videos, maps, kinematics, audio, ...) over long contexts (e.g. ~30 seconds) go into a big neural net, steering/acceleration comes out, optionally with visualization auxiliary data. This is the dream of the complete Software 1.0 -> Software 2.0 re-write that scales fully with data streaming from millions of cars in the fleet and the compute capacity of your chip, not some engineer's clever new DoubleParkedCarHandler C++ abstraction with undefined test-time characteristics of memory and runtime. There's a lot more hints in the video on where things are going with the emerging "robotics+AI at scale stack". World reconstructors, world simulators "dreaming" dynamics, RL, all of these components general, foundational, neural net based, how the car is really just one kind of robot... are people getting this yet?

Huge congrats to the team - you're building magic objects of the future, you rock! And I love my car <3.

[xAI @xai]

xAI Hackathon – the ultimate arena for the most hardcore product builders.

24 hours &amp; exclusive access to upcoming Grok models &amp; X APIs

Apply by 11/22 🔗 https://t.co/zsbk9SHglq

[spencer @SpencerSharkey]

Growing up, I’ve always wanted to help build the biggest computers… this year I’m proud to say it’s happening.

It’s sort of like building your first gaming PC, except there’s no video tutorial. You need a crane to install the PSU, a forklift to move the GPU, and your liquid cooling radiators are larger than a school bus.

We have a kick-ass team at Colossus 2. Join us at @xai if you like building big computers, too.

[xAI @xai]

Introducing Grok 4 Fast, a multimodal reasoning model with a 2M context window that sets a new standard for cost-efficient intelligence.

Available for free on https://t.co/AnXpIEOhOD, https://t.co/53pltypvkw, iOS and Android apps, and OpenRouter.

https://t.co/3YZ1yVwueV

[Ethan He @EthanHe_42]

You can now chat with PDF on @grok