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xAI

@xai

6 hours

Come meet the team at 11am opposite the main entrance at ICLR Vienna!

Toby Pohlen

@TobyPhln

6 hours

We ( @xai / @grok crew) will do a Meet & Greet opposite the main entrance of @iclr_conf at 11am local time today. Come by to chat about research, engineering, and life at xAI!

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xAI

@xai

27 days

we're hiring designers, engineers, product, data, infra, and ai tutors - join us!

Careers

See our latest job posts and career opportunities.

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@xai

27 days

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@xai

27 days

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Grok-1.5 Vision Preview

Connecting the digital and physical worlds with our first multimodal model.

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@xai

1 month

Announcing Grok-1.5

Grok-1.5 comes with improved reasoning capabilities and a context length of 128,000 tokens. Available on 𝕏 soon.

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Igor Babuschkin

@ibab

2 months

Open Release of Grok-1

We are releasing the weights and architecture of our 314 billion parameter Mixture-of-Experts model Grok-1.

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Yuhuai (Tony) Wu

@Yuhu_ai_

4 months

Euclidean geometry problems have been my favorite math puzzles since middle school. The most intriguing part of it is the creation of auxiliary lines, which opens a space for imagination and the freedom to explore various diagrams. Once a proof is found, these auxiliary lines…

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@X

5 months

the following countries can now grok: - australia - bahamas - barbados - belize - botswana - cameroon - canada - dominica - eswatini - fiji - gambia - ghana - grenada - guyana - india - jamaica - kenya - liberia - malaysia - malawi - malta - mauritius - namibia - new zealand -…

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xAI

@xai

5 months

Come meet the team in an hour by the registration desk at NeurIPS!

Jimmy Ba

@jimmybajimmyba

5 months

Excited to arrive at NeurIPS later today alongside some of my colleagues. @xai / @grok crew will have a Meet & Greet session on Thursday at 2:30pm local time by the registration desk. Drop by for some fun, giggles, and good roasts!

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Yuhuai (Tony) Wu

@Yuhu_ai_

5 months

Coming to #NeurIPS23 now. Will be there until Friday night. DM me to chat about: reasoning, AI for math, and what we’re doing @xai . Also will be at #MATHAI workshop panel discussion on Friday morning. See you there!

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Jimmy Ba

@jimmybajimmyba

5 months

Excited to arrive at NeurIPS later today alongside some of my colleagues. @xai / @grok crew will have a Meet & Greet session on Thursday at 2:30pm local time by the registration desk. Drop by for some fun, giggles, and good roasts!

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Igor Babuschkin

@ibab

5 months

Join the Grok community here on X if you want to help us improve Grok, or to see how others are using Grok.

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Elon Musk

@elonmusk

5 months

Grok is rolling out to 𝕏 Premium+ subscribers with the latest app release. Have fun!

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Toby Pohlen

@TobyPhln

6 months

You can now submit feedback to help us improve Grok. Feedback can range from a simple "this conversation is good/bad"-rating all the way to an entirely rewritten conversation.

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Greg Yang

@TheGregYang

6 months

1/ μP is optimal scaling rule of learning rate & init as network width → ∞. Been confused? 🆕μP = holding the "natural" (I'll explain) operator norm constant for every weight W & its updates ΔW: μP <=> ‖W‖_nat = Θ(1) = ‖ΔW‖_nat. 🆕Frobenius norm is the wrong norm to measure!

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Chris Bakke

@ChrisJBakke

6 months

If anyone is feeling the Sunday Scaries heading into work tomorrow, @xai is hiring for many roles:

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xAI

@xai

6 months

Announcing the xAI PromptIDE The xAI PromptIDE is an integrated development environment for prompt engineering and interpretability research. It accelerates prompt engineering through an SDK that allows implementing complex prompting techniques and rich analytics that visualize…

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Announcing Grok! Grok is an AI modeled after the Hitchhiker’s Guide to the Galaxy, so intended to answer almost anything and, far harder, even suggest what questions to ask! Grok is designed to answer questions with a bit of wit and has a rebellious streak, so please don’t use…

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Greg Yang

@TheGregYang

7 months

Nontrivial ∞width neural nets are either kernel machines or feature learners. Latter's scaling makes optimal hyperparams invariant to width What if depth→∞as well? 🆕 Feature diversity is key; maxed out by abs (not relu); gives invariance to depth! But GPT flawed 🧵

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