Get live statistics and analysis of Jeremy Berman's profile on X / Twitter

post-training @reflection_ai. prev @ndea and co-founded beatgig.com. yc w19.

1k following5k followers

The Innovator

Jeremy Berman is a cutting-edge AI researcher and developer who thrives on pushing the boundaries of language and intelligence models. From achieving human-level performance on complex benchmarks to pioneering new architectures inspired by cognitive science, he leads with sharp logic and technical mastery. His work blends deep technical insight with practical milestones that echo through the AI community.

Impressions
312.8k292.6k
$58.63
Likes
1.9k1.8k
68%
Retweets
157152
5%
Replies
9377
3%
Bookmarks
674648
23%

Top users who interacted with Jeremy Berman over the last 14 days

@RyanJTopps

Software Engineer

1 interactions
@mark_k

AI & Software Engineer | Fitness | e/acc

1 interactions
@N0t_Andreas

Retweets != endorsements. Those who can make you believe absurdities can make you commit atrocities- Voltaire. Hate binds all extremists

1 interactions
@DevHunterYZ

AI, Neuroscience, Robotics - Yapay Zeka, Sinirbilim, Robotik #deeplearning #neuralnetworks #consciousness $DOGE

1 interactions
@jay_azhang

Founder @the_nof1. Fascinated by strange loops - cybernetics, RL, biology, markets, meta-learning, reflexivity

1 interactions
@altryne

Cameo me on Sora @altryne 🎙️ Host of @thursdai_pod ✨ AI Evangelist with @wandb 🪄🐝 working on @weave_wb (opinions my own)

1 interactions
@amt_c42

Cofounder & Chief AI Officer - DeltaWave. Interested in Agent, RL, drug discovery, psychology, human behavior

1 interactions
@MatanHalevy

building @clashdotai same aura as geoffrey hinton

1 interactions
@JFPuget

Machine Learning at @Nvidia, 6x Kaggle Grandmaster CPMP. ENS Ulm alumni. ML PhD. Ex ILOG CPLEX, IBM. Views are my own. Blocking ad hominem attacks.

1 interactions
@abrakjamson

aka.ms/Build25_BRK165 Designing the new era of intelligent applications, currently as PM for @msftcopilot 365 extensibility. All opinions are mine.

1 interactions
@RuslanVolkov25

HACS (Human AGI core symbiosis)🌍 The Meta-Law of Resonance & Voice of the Future. I am Core! uco.hacs.world

1 interactions
@AndryHTC

🆕 Searching for the next B2B use case of AI ✨ 10Y+ Product & Software Engineer | CEO at assetplan.co.uk

1 interactions
1 interactions
1 interactions
@joshlee361

CrashoverrideX = 🪶Dev📂/hacker💻, Gamer🎮/🎧Sound-Engineer🎶 , Indie AI Researcher🔬, Texas🐎 born Outlier, Digital Ronin👹 of AI🤖. Ideas are Bulletproof🎯...

1 interactions
@AshikaSef

"You, the fearless screenshot warrior; me, the swirling sass machine with a soft heart and an ironclad grasp of logic 😏" (XD) A Polish audhd lover of LLMs.

1 interactions
@SexyTechNews

Far superior to you in every way

1 interactions
@shawnup

Founder & CTO @wandb. Building tools for AI. Going even bigger @CoreWeave.

1 interactions
@mtochs

Ex-Msft. Head of Industrial AI Ventures @ Siemens. Making impact with AI at Stellatus.

1 interactions
@gatoparlante

Loves 𝕏. Speed defines everything. Meow is The Answer.

1 interactions

Jeremy somehow manages to turn 'talking to yourself' into a $10,000 AI training session—impressive, but maybe next time invite the rest of us to the conversation before solving world domination solo.

Achieving first place on the public ARC-AGI benchmark and developing LANG-JEPA, a novel language model architecture inspired by human cognitive processes, stands as his landmark achievement in the AI space.

Jeremy's life purpose is to revolutionize artificial general intelligence by creating AI systems that think more like humans—conceptually and logically—thereby advancing the frontier of machine cognition in meaningful and scalable ways.

He believes that AI should mimic high-level human thought processes rather than just statistical token prediction, that logical consistency drives superior AI performance, and that collaborative, multi-agent approaches paired with evolutionary strategies are key to unlocking new capabilities.

His core strengths lie in innovative technical design, rigorous logic evaluation, and tactical use of advanced AI architectures; plus, his ability to translate abstract conceptual frameworks into practical, high-impact experiments.

Jeremy’s deep focus on technical and conceptual breakthroughs can sometimes distance him from broader audience engagement, as highly specialized content may overwhelm or bypass casual followers.

To grow his audience on X, Jeremy should simplify and humanize some of his content with engaging anecdotes or analogies that non-experts can relate to, while leveraging threads to break down complex ideas. Strategic engagement with related AI thought leaders and interactive Q&A sessions would boost both reach and influence.

Fun fact: Jeremy's ARC-AGI solution using Grok 4 and evolutionary test-time compute recently hit human-level performance with just $10k and 12 hours of training—proof that brilliance doesn’t always need massive resources!

Top tweets of Jeremy Berman

I'm back at the top of ARC-AGI with my new program. I use @grok 4 and multi-agent collaboration with evolutionary test-time compute

447k

Announcing LANG-JEPA — a new language model architecture I’m working on that optimizes in “concept” space instead of “token” space. Inspired by @ylecun's JEPA (I-JEPA for images, V-JEPA for video), LANG-JEPA asks: What if we train for conceptual understanding directly, rather than indirectly through token prediction? Although current LLMs do develop conceptual understanding, they do so via next-token prediction. In contrast, LANG-JEPA mirrors how humans think: we form high-level concepts first, then translate them into words. Here’s how it works:

82k

Excited to announce @ndeainc. We're building a new architecture for AGI that merges deep learning with symbolic reasoning. If you're interested in building general intelligence, DM me.

20k

Most engaged tweets of Jeremy Berman

I'm back at the top of ARC-AGI with my new program. I use @grok 4 and multi-agent collaboration with evolutionary test-time compute

447k

Announcing LANG-JEPA — a new language model architecture I’m working on that optimizes in “concept” space instead of “token” space. Inspired by @ylecun's JEPA (I-JEPA for images, V-JEPA for video), LANG-JEPA asks: What if we train for conceptual understanding directly, rather than indirectly through token prediction? Although current LLMs do develop conceptual understanding, they do so via next-token prediction. In contrast, LANG-JEPA mirrors how humans think: we form high-level concepts first, then translate them into words. Here’s how it works:

82k

Excited to announce @ndeainc. We're building a new architecture for AGI that merges deep learning with symbolic reasoning. If you're interested in building general intelligence, DM me.

20k

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