A timestamped scouting report for outreach and monitoring: a top-200 AI KOL map on X with technical/semi-technical labels, plus a focused benchmark watchlist for AI models in drug discovery, biotechnology, chemistry, biology, and scientific agents.
Use the filter to isolate the more technical research/engineering/evals accounts for DDDBench/MMAI-style outreach.
Massive X-native reach; Grok/xAI announcements and AI platform narrative.
Technical rationale: xAI/Grok strategy and technical/product narratives, but mostly founder/platform distribution
OpenAI narrative-setter and frontier-model launch signal.
Technical rationale: Strategic lab and product framing rather than code-level posts
Long-form AI interviews bridging researchers, founders, and policy.
Technical rationale: Technical interviews, broad public audience
One of the highest signal technical AI explainers on X.
Technical rationale: Posts deep model intuition, training, code, and technical education
Major applied-AI educator and practitioner influence.
Technical rationale: Applied ML, data-centric AI, courses, technical practice
China/global AI strategy and commercialization voice.
Technical rationale: Strategic AI and commercialization, occasionally model/company technical context
High-authority AI-for-science and AGI lab voice.
Technical rationale: Science-AI, DeepMind research, AlphaFold/Gemini technical context
Major technical counterweight to LLM-scaling consensus.
Technical rationale: Research debates on world models, self-supervised learning, architectures
OpenAI product/research amplification.
Technical rationale: Demos and product/research amplification, less code-level
Rare posts carry frontier-lab/research weight.
Technical rationale: Foundational LLM researcher; rare but technical significance
New frontier-lab founder and ex-OpenAI CTO.
Technical rationale: Lab/product strategy from technical leadership background
AI search and consumer-AI distribution leader.
Technical rationale: AI search/product strategy with some model context
Major AI research and human-centered AI authority.
Technical rationale: Computer vision, spatial intelligence, AI healthcare/policy
Important benchmark/reasoning voice.
Technical rationale: Reasoning benchmarks, Keras, AGI critique, architecture debates
High-authority voice on deep learning and AI risk.
Technical rationale: Foundational deep-learning researcher
Claude/frontier AI strategy and safety framing.
Technical rationale: Frontier lab strategy/safety, not frequent code-level posting
Elite systems + ML research credibility.
Technical rationale: Systems ML, scaling, Gemini/Google research
Open-source AI distribution and community leader.
Technical rationale: Open-source model ecosystem/product strategy
Data, evals, and enterprise AI influence.
Technical rationale: AI data/evals/enterprise strategy
High-signal physical AGI and robotics commentator.
Technical rationale: Robotics, simulation, embodied agents, model systems
Important AI paper discovery/amplification account.
Technical rationale: Research-paper firehose; mostly aggregation
Hands-on LLM training and architecture education.
Technical rationale: Implementation-level LLM/ML tutorials
PyTorch ecosystem credibility.
Technical rationale: Open-source ML framework engineering
Widely cited technical explainer.
Technical rationale: Canonical technical essays on agents, RLHF, safety
Applied technical AI education and open models.
Technical rationale: Practical model training, pedagogy, open-source AI
Open-source AI and generative media commentary.
Technical rationale: Open model strategy and ecosystem commentary
AI R&D paper/news amplification.
Technical rationale: Technical research curation rather than original research
Developer-facing AI launch signal.
Technical rationale: API/model developer-relations updates
Top practical technical evaluator of LLM tools.
Technical rationale: Hands-on testing, code, model behavior, security
High-signal practitioner voice on AI evals.
Technical rationale: Evals, product quality, production LLM systems
Useful model-design and frontier-lab research signal.
Technical rationale: Frontier model design/research perspective
Foundational ML researcher.
Technical rationale: GANs and deep learning research
Major DeepMind technical leader.
Technical rationale: Gemini, AlphaCode, sequence models
High-credibility research voice.
Technical rationale: Deep learning and superintelligence research
Applied ML competition and tooling expert.
Technical rationale: Kaggle, AutoML, model-building practice
Large AI news distribution channel.
Technical rationale: News/tool curation, not usually technical depth
Broad technology/AI reach.
Technical rationale: Technology commentary and amplification
Large data/AI amplification account.
Technical rationale: Data science/AI curation; PhD background
Large B2B AI/data reach.
Technical rationale: Business/AI content and amplification
Influential AI ethics/accountability voice.
Technical rationale: AI accountability research and policy
Influential skeptical AI commentator.
Technical rationale: Critiques of deep learning and LLM limits
Important AI-economics KOL.
Technical rationale: AI productivity and economics research
Large AI tools/tutorial audience.
Technical rationale: Tool/use-case education, usually not deep technical
AI automation business influencer.
Technical rationale: Business automation/AI commentary
AI community amplification.
Technical rationale: AI/AGI commentary and community account
Broad enterprise AI reach.
Technical rationale: Business tech/AI thought leadership
Practical AI/data app educator.
Technical rationale: Python/data apps/LLM developer content
Technical-ish data science influencer.
Technical rationale: Data science and visualization content
Longstanding ML research figure.
Technical rationale: Deep learning history and research claims
AI tools distribution channel.
Technical rationale: AI tools/news aggregation
Major AI ethics scholar.
Technical rationale: Sociotechnical AI research and policy
AI startup/media reach.
Technical rationale: Investor/media commentary
Recognized ML academic voice.
Technical rationale: ML theory and AI commentary
Broad AI business audience.
Technical rationale: Business AI education
Important AI media voice.
Technical rationale: Investigative AI reporting
Large practical ML learning audience.
Technical rationale: Hands-on ML engineering and system design
Applied ML/Kaggle KOL.
Technical rationale: Data science/Kaggle/model-building
Large applied AI education audience.
Technical rationale: Practical LLM/RAG/agent explainers
Large AI/data reach.
Technical rationale: AI/data science curation and commentary
High-quality ML research voice.
Technical rationale: Deep learning research and education
Technical computer-vision KOL.
Technical rationale: Vision/imaging ML research
Practical ML engineering audience.
Technical rationale: End-to-end ML engineering education
AI developer education.
Technical rationale: Developer education and DeepMind-facing updates
Authoritative ML textbook/research voice.
Technical rationale: Bayesian ML, probabilistic modeling
Technical ML theory voice.
Technical rationale: Privacy, statistics, ML theory
Important efficient/open AI researcher.
Technical rationale: ML efficiency, multilingual/multimodal research
Foundational ML researcher.
Technical rationale: Core ML optimization and generative modeling
Strong ML educational voice.
Technical rationale: ML/LLM books and practical education
Rising technical AI research voice.
Technical rationale: Multimodal NLP, post-training, data, evals
Technical DeepMind/social-good voice.
Technical rationale: ML research and AI for social good
Technical ML/statistics KOL.
Technical rationale: Bayesian/statistical ML commentary
Technical ML academic.
Technical rationale: Bayesian/deep learning theory
Sharp technical ML critic.
Technical rationale: Optimization, ML systems, critical analysis
Senior ML research authority.
Technical rationale: Probabilistic ML and AI research leadership
Technical RL/agents researcher.
Technical rationale: Multi-agent RL and ML research
Important technical retrieval/embedding voice.
Technical rationale: Embeddings, retrieval, AI search
Hands-on ML builder.
Technical rationale: Open-source ML tooling
AI research interview/amplification channel.
Technical rationale: Technical AI podcast and ML commentary
Technical ML/statistics voice.
Technical rationale: Statistical ML intuition and methods
Turing laureate and major AI safety/research voice.
Technical rationale: Foundational deep-learning research
Core interpretability KOL.
Technical rationale: Mechanistic interpretability research
Technical robotics/HRI authority.
Technical rationale: Human-robot interaction and robotics
Major robotics/RL KOL.
Technical rationale: Robotics and reinforcement learning
AI-healthcare founder/research voice.
Technical rationale: AI in healthcare and biology entrepreneurship
High-signal robotics/learning researcher.
Technical rationale: Robotics, meta-learning, imitation learning
Top technical robotics/RL researcher.
Technical rationale: Deep RL and robot learning
Important technical interpretability voice.
Technical rationale: Explainability/interpretability research
Senior deep learning researcher.
Technical rationale: Deep learning research leadership
Technical NLP researcher.
Technical rationale: Neural machine translation, NLP, deep learning
Technical ML/science-AI voice.
Technical rationale: ML theory, generative science, Bayesian/deep learning
Technical and creative AI research voice.
Technical rationale: World models, generative systems, creative AI
Foundational sequence-model researcher.
Technical rationale: RNNs, sequence learning, deep learning
Senior technical Google AI researcher.
Technical rationale: AutoML and deep learning research
Senior AI/robotics authority.
Technical rationale: Planning, robotics, AI fundamentals
Major lab/product/policy voice.
Technical rationale: AI strategy, product, policy
Large business/AI network.
Technical rationale: AI entrepreneurship and investment
Frontier-lab leadership voice.
Technical rationale: Anthropic strategy and safety operations
Technical founder with model lineage.
Technical rationale: Transformer coauthor and enterprise LLM builder
Large enterprise AI channel.
Technical rationale: Enterprise AI/data platform narratives
AI compute platform narrative-setter.
Technical rationale: AI hardware/platform strategy
Technical educator and fast.ai cofounder.
Technical rationale: Practical ML and responsible AI education
Core open-source AI platform builder.
Technical rationale: Transformers/open-source AI engineering
Important open-source AI infra voice.
Technical rationale: Model hub/open-source platform engineering
AI compute/systems founder.
Technical rationale: AI hardware and systems entrepreneurship
Major AI investment voice.
Technical rationale: AI investment and market theses
Robotics/AI education pioneer.
Technical rationale: Robotics, autonomous vehicles, education
Broad innovation audience.
Technical rationale: AI futurism and entrepreneurship
Longstanding AI futurist voice.
Technical rationale: Singularity/AI future commentary
AI fairness and policy KOL.
Technical rationale: Algorithmic bias/accountability research
Important AI governance voice.
Technical rationale: Responsible AI and governance
Strong responsible-AI researcher.
Technical rationale: AI bias/eval/accountability research
Technical/public-interest AI voice.
Technical rationale: Algorithms and social-good AI research
Important policy/privacy voice.
Technical rationale: AI politics, privacy, surveillance critique
Public algorithmic-risk voice.
Technical rationale: Risk, fairness, automated decision-making
Important sociotechnical AI voice.
Technical rationale: Critical AI/search scholarship
Sociotechnical AI influence.
Technical rationale: Race, technology, AI society
Measured AI policy/technical newsletter voice.
Technical rationale: AI policy, capability trends, technical summaries
Technical and skeptical AI researcher.
Technical rationale: AI reasoning, analogy, cognitive science
Popular practical ML educator.
Technical rationale: Hands-on ML education
High-signal AI engineering voice.
Technical rationale: ML systems, AI engineering, evals
Technical data/AI product KOL.
Technical rationale: Data/AI product strategy and systems
Important AI auditing voice.
Technical rationale: Model auditing and accountability
Technical AI and policy critic.
Technical rationale: AI, fairness, privacy, crypto, accountability
High-signal practical technical educator.
Technical rationale: Practical ML education and tooling
Technical responsible-AI voice.
Technical rationale: AI energy, climate, responsible AI evaluation
Important policy/safety KOL.
Technical rationale: AI governance and frontier-lab policy
Top technical alignment researcher.
Technical rationale: Alignment, scalable oversight, RLHF
Core technical alignment voice.
Technical rationale: Technical AI alignment theory/evals
Senior AI institution builder.
Technical rationale: AI research, policy, entrepreneurship
Top LLM-evaluation researcher.
Technical rationale: Benchmarking, NLP, HELM/MedHELM
Technical NLP/agents researcher.
Technical rationale: Language grounding, agents, NLP research
Important eval/safety benchmark creator.
Technical rationale: Benchmarks, model risks, WMDP/MMLU-style evals
Technical theory/safety voice.
Technical rationale: Complexity theory, quantum, AI safety commentary
Top AI engineering community builder.
Technical rationale: Agents, RAG, evals, AI engineering stack
Practical AI builder influence.
Technical rationale: AI app demos and builder workflows
High-signal AI startup/model curator.
Technical rationale: Model release summaries and benchmark takes
High-engagement AI product/founder voice.
Technical rationale: AI capability/startup commentary
Major practical AI adoption voice.
Technical rationale: Empirical AI use and workplace experiments
Technical AI product/research voice.
Technical rationale: LLM internals, embeddings, AI-native UX
Strong AI interview/eval commentator.
Technical rationale: Model eval discussions, AI interviews
Top technical post-training/open-model voice.
Technical rationale: RLHF, post-training, open models
Research-paper amplification and education.
Technical rationale: Paper explainers and ML education
Raw research discovery channel.
Technical rationale: Primary research feed
AI paper discovery/amplification.
Technical rationale: Social layer for arXiv/papers
High-signal technical AI explainer.
Technical rationale: Paper breakdowns and Deep Learning Focus
Practical model builder.
Technical rationale: Small-model/VLM engineering
Primary OpenAI launch channel.
Technical rationale: Official launches and benchmark posts
Primary Anthropic launch channel.
Technical rationale: Claude releases and safety research
Major technical AI lab channel.
Technical rationale: Research releases, AlphaFold/Gemini science AI
Key open-model lab channel.
Technical rationale: Llama/open model research and product
European frontier model channel.
Technical rationale: Open/foundation model releases
High-impact open AI distribution.
Technical rationale: Model/dataset/leaderboard ecosystem
AI infrastructure narrative channel.
Technical rationale: GPU/platform launches and AI hardware
Enterprise LLM platform channel.
Technical rationale: Enterprise model releases and retrieval/RAG context
Consumer AI search channel.
Technical rationale: AI search product releases
Open AI infrastructure channel.
Technical rationale: Inference/fine-tuning/open model infra
xAI primary launch channel.
Technical rationale: Grok releases and xAI research
Important public model benchmark channel.
Technical rationale: Chatbot Arena / model rankings
Useful model market/API signal.
Technical rationale: Model availability and routing data
Model deployment ecosystem channel.
Technical rationale: Open model deployment and demos
MLOps and AI eval community.
Technical rationale: Experiment tracking, evals, ML tooling
Key AI agent/RAG developer channel.
Technical rationale: Agents, RAG, LangGraph, app tooling
Important AI engineering framework.
Technical rationale: RAG, retrieval, agents, data connectors
Technical AI infra channel.
Technical rationale: Serverless GPU/AI infra
Important scalable AI systems channel.
Technical rationale: Distributed ML/serving infrastructure
Evals/data infrastructure influence.
Technical rationale: Data, evals, enterprise AI
High-signal eval/benchmark channel.
Technical rationale: DrugDiscoveryBench and agent benchmarks
Important agent-eval methodology voice.
Technical rationale: Agent/R&D capability measurements
Government eval-framework voice.
Technical rationale: Inspect Evals and frontier-model evaluation
Bio/chem/cyber eval relevance.
Technical rationale: WMDP and risk evaluations
Methodology/benchmark analysis amplifier.
Technical rationale: Benchmark and compute trend analysis
Standards-setting benchmark channel.
Technical rationale: MLPerf, medical AI, benchmark working groups
Broad benchmark visibility channel.
Technical rationale: Paper/code/leaderboard discovery
Foundational drug-discovery benchmark ecosystem.
Technical rationale: TDC tasks/leaderboards/datasets
Direct DDDBench peer/partner target.
Technical rationale: Biomni, BiomniBench, DrugDiscoveryBench
High-signal biomedical-agent benchmark KOL.
Technical rationale: BiomniBench/Biomni; long-horizon bio tasks
Top scientific-agent benchmark target.
Technical rationale: LAB-Bench/BixBench/scientific-agent ecosystem
Relevant industry-standard DD benchmarking channel.
Technical rationale: Polaris benchmark/data platform
High-credibility DD benchmark evaluator.
Technical rationale: ADMET/blind challenges, benchmark validity
Community amplifier for open BioML benchmarks.
Technical rationale: BioML/ChemNLP community amplification
Strong AI-bio benchmark amplifier.
Technical rationale: Genomics, biosecurity, AI-bio eval commentary
Relevant chemistry benchmark group.
Technical rationale: ChemBench and chemistry/materials LLM evals
Strong chemistry/science-agent benchmark KOL.
Technical rationale: ChemCrow, PaperQA, chemistry agents
Chemistry model/eval KOL.
Technical rationale: RXN/ChemCrow/chemistry AI
Protein/structure benchmark channel.
Technical rationale: Chai-1/chai-lab structure benchmarks
Protein-design benchmark credibility network.
Technical rationale: Rosetta, CASP/CAPRI ecosystem
Benchmark/data community account.
Technical rationale: ChEMBL resource updates
Medical LLM benchmark KOL.
Technical rationale: Medmarks and medical AI evaluation
Generative AI model distribution channel.
Technical rationale: Open image/audio/model releases
Major creative AI model channel.
Technical rationale: Model/product releases, creative AI
Major generative video model channel.
Technical rationale: Video model/product releases
Creative model product channel.
Technical rationale: Dream Machine/video/3D model releases
Major AI coding tool channel.
Technical rationale: AI coding product and model integrations
Important coding-agent benchmark/product channel.
Technical rationale: Devin and coding-agent releases
AI coding/developer distribution channel.
Technical rationale: AI coding agents and cloud dev platform
Important AI coding product channel.
Technical rationale: Coding-agent/product releases
Primary technical OpenAI developer channel.
Technical rationale: API, model tiers, developer releases
Broad Google AI channel.
Technical rationale: Google AI releases and research/product links
Important enterprise data+AI platform channel.
Technical rationale: Lakehouse, MosaicML, model serving and enterprise AI infra
Technical model-training infrastructure voice.
Technical rationale: Open model training, LLM training systems and infra
This is the higher-priority watchlist for DDDBench/MMAI Gym style outreach. It mixes individual researchers, benchmark creators, lab/org accounts, and amplification channels.
LifeSciBench: 750 expert-authored tasks, 173 scientist contributors, 19,020 rubric criteria.
Relevance: Direct benchmark comparator and high-impact launch/amplification target.
Referenced in LifeSciBench launch ecosystem with OpenAI.
Relevance: Potential partner/peer for life-science task design and validation.
Named in LifeSciBench/Tacit Labs launch amplification.
Relevance: Likely useful individual contact around biology eval design.
Named in LifeSciBench/Tacit Labs launch amplification.
Relevance: Likely useful individual contact around life-science verification.
LAB-Bench and FutureHouse scientific-agent ecosystem; BixBench repo under Future-House.
Relevance: Top target for scientific-agent benchmark comparison/amplification.
DrugDiscoveryBench with Scale Labs; BiomniBench process-level evaluation.
Relevance: Direct DDDBench peer/benchmark partner and high-priority outreach target.
DrugDiscoveryBench: 82 early-stage DD tasks with expert rubrics and leaderboard.
Relevance: Direct benchmark comparison; useful for model-vs-harness narrative.
Scale blog and labs leaderboard for DrugDiscoveryBench.
Relevance: Enterprise-eval distribution channel.
Posted BiomniBench launch: process-level evaluation of agents on long-horizon biology tasks.
Relevance: Strong KOL for agentic biomedical benchmarks and scientific-agent systems.
TDC platform for AI-ready therapeutic datasets and leaderboards.
Relevance: Foundational benchmark ecosystem for DDDBench positioning.
TDC / Harvard-Stanford biomedical ML ecosystem.
Relevance: Senior benchmark and graph-ML amplifier.
PolarisHub benchmark/data platform for drug discovery.
Relevance: Highly relevant for industry-standard DD benchmarking.
OpenADMET/blind-challenge and benchmark-validity commentary.
Relevance: High-credibility evaluator/KOL for DD benchmark quality.
Community journal clubs and BioML paper amplification.
Relevance: Community amplifier for open BioML benchmarking.
Amplified BixBench and other AI-biology benchmark papers.
Relevance: Useful awareness channel for DDDBench/MMAI benchmark posts.
Genomics and biosecurity/AI benchmark commentary.
Relevance: Strong commentator/amplifier for AI-bio benchmark credibility.
ChemBench benchmark for chemistry reasoning and tool use.
Relevance: Relevant analog for chemistry/LLM eval methodology.
ChemCrow and scientific-agent evaluation work.
Relevance: Very strong chemistry/science-agent benchmark KOL.
ChemCrow / reaction prediction / chemistry AI work.
Relevance: Good benchmark reviewer and chemistry-agent evaluator.
Chai-1, chai-lab, structure prediction comparisons.
Relevance: Protein/structure benchmark comparison channel.
AlphaFold and Isomorphic science-AI narratives.
Relevance: Huge amplifier; benchmark framing authority.
Rosetta, CASP/CAPRI-related modeling ecosystem.
Relevance: Protein-design benchmark credibility network.
ChEMBL data/resource updates.
Relevance: Useful data/benchmark community account.
Benchmark and paper leaderboard distribution.
Relevance: Broad benchmark visibility channel.
Open Medical LLM Leaderboard; dataset/model benchmark hosting.
Relevance: High-impact hosting/amplification route for DDDBench/MMAI.
Stanford CRFM HELM and medical evaluation frameworks.
Relevance: Credible LLM-eval benchmark KOL.
Autonomous capability measurement and eval methodology.
Relevance: Useful for agent-eval methodology framing.
Inspect eval framework and frontier-model safety evaluations.
Relevance: Strong eval-framework/governance target.
WMDP benchmark and biorisk/chem risk evals.
Relevance: Relevant to bio/chem LLM evals; outreach should be careful and risk-aware.
Epoch benchmark tracking and AI trend analysis.
Relevance: Methodology/benchmark-analysis amplifier.
MLCommons medical/data working groups.
Relevance: Standards-setting outreach target.
Medmarks benchmark posts and GitHub project.
Relevance: Strong medical LLM benchmark KOL.
| # | Name | X handle | Followers | Technical | Category | Why / technical rationale |
|---|---|---|---|---|---|---|
| 1 | Elon Musk | @elonmusk | ~240.7M | Semi-technical | xAI / X platform | Massive X-native reach; Grok/xAI announcements and AI platform narrative. xAI/Grok strategy and technical/product narratives, but mostly founder/platform distribution |
| 2 | Sam Altman | @sama | ~5.4M | Semi-technical | OpenAI / frontier AI CEO | OpenAI narrative-setter and frontier-model launch signal. Strategic lab and product framing rather than code-level posts |
| 3 | Lex Fridman | @lexfridman | ~5.0M | Semi-technical | AI podcast / public discourse | Long-form AI interviews bridging researchers, founders, and policy. Technical interviews, broad public audience |
| 4 | Andrej Karpathy | @karpathy | ~3.2M | Technical | AI researcher / educator | One of the highest signal technical AI explainers on X. Posts deep model intuition, training, code, and technical education |
| 5 | Andrew Ng | @AndrewYNg | ~1.5–1.6M | Technical | AI education / applied ML | Major applied-AI educator and practitioner influence. Applied ML, data-centric AI, courses, technical practice |
| 6 | Kai-Fu Lee | @kaifulee | ~1.4M | Semi-technical | AI investor / 01.AI | China/global AI strategy and commercialization voice. Strategic AI and commercialization, occasionally model/company technical context |
| 7 | Demis Hassabis | @demishassabis | ~1.3M | Technical | Google DeepMind CEO | High-authority AI-for-science and AGI lab voice. Science-AI, DeepMind research, AlphaFold/Gemini technical context |
| 8 | Yann LeCun | @ylecun | ~0.94–1.2M | Technical | Meta AI / Turing laureate | Major technical counterweight to LLM-scaling consensus. Research debates on world models, self-supervised learning, architectures |
| 9 | Greg Brockman | @gdb | ~0.63–1.0M | Semi-technical | OpenAI cofounder/president | OpenAI product/research amplification. Demos and product/research amplification, less code-level |
| 10 | Ilya Sutskever | @ilyasut | ~760.9K | Technical | SSI / frontier research | Rare posts carry frontier-lab/research weight. Foundational LLM researcher; rare but technical significance |
| 11 | Mira Murati | @miramurati | ~742.1K | Semi-technical | Thinking Machines Lab | New frontier-lab founder and ex-OpenAI CTO. Lab/product strategy from technical leadership background |
| 12 | Aravind Srinivas | @AravSrinivas | ~800.6K | Semi-technical | Perplexity CEO | AI search and consumer-AI distribution leader. AI search/product strategy with some model context |
| 13 | Fei-Fei Li | @drfeifei | ~632–781K | Technical | World Labs / Stanford | Major AI research and human-centered AI authority. Computer vision, spatial intelligence, AI healthcare/policy |
| 14 | François Chollet | @fchollet | ~566–704K | Technical | Keras / ARC-AGI | Important benchmark/reasoning voice. Reasoning benchmarks, Keras, AGI critique, architecture debates |
| 15 | Geoffrey Hinton | @geoffreyhinton | ~489–618K | Technical | Deep learning pioneer | High-authority voice on deep learning and AI risk. Foundational deep-learning researcher |
| 16 | Dario Amodei | @DarioAmodei | ~478.6K | Semi-technical | Anthropic CEO | Claude/frontier AI strategy and safety framing. Frontier lab strategy/safety, not frequent code-level posting |
| 17 | Jeff Dean | @JeffDean | ~361–448K | Technical | Google DeepMind / Google Research | Elite systems + ML research credibility. Systems ML, scaling, Gemini/Google research |
| 18 | Clément Delangue | @ClementDelangue | ~452.1K | Semi-technical | Hugging Face CEO | Open-source AI distribution and community leader. Open-source model ecosystem/product strategy |
| 19 | Alexandr Wang | @alexandr_wang | ~541.7K | Semi-technical | Meta AI / Scale founder | Data, evals, and enterprise AI influence. AI data/evals/enterprise strategy |
| 20 | Jim Fan | @DrJimFan | ~435–486K | Technical | NVIDIA robotics / agents | High-signal physical AGI and robotics commentator. Robotics, simulation, embodied agents, model systems |
| 21 | AK | @_akhaliq | ~500.4K | Semi-technical | AI paper aggregator | Important AI paper discovery/amplification account. Research-paper firehose; mostly aggregation |
| 22 | Sebastian Raschka | @rasbt | ~476K | Technical | ML/LLM educator | Hands-on LLM training and architecture education. Implementation-level LLM/ML tutorials |
| 23 | Soumith Chintala | @soumithchintala | ~247–311K | Technical | PyTorch / Meta | PyTorch ecosystem credibility. Open-source ML framework engineering |
| 24 | Lilian Weng | @lilianweng | ~88–267K | Technical | AI research / agents / safety | Widely cited technical explainer. Canonical technical essays on agents, RLHF, safety |
| 25 | Jeremy Howard | @jeremyphoward | ~236–289K | Technical | fast.ai / Answer.AI | Applied technical AI education and open models. Practical model training, pedagogy, open-source AI |
| 26 | Emad Mostaque | @EMostaque | ~328.3K | Semi-technical | Stability AI founder | Open-source AI and generative media commentary. Open model strategy and ecosystem commentary |
| 27 | Lior / AlphaSignal | @AlphaSignalAI | ~80.4K | Semi-technical | AI R&D newsletter | AI R&D paper/news amplification. Technical research curation rather than original research |
| 28 | Logan Kilpatrick | @OfficialLoganK | ~339.2K | Semi-technical | Google AI Studio / devrel | Developer-facing AI launch signal. API/model developer-relations updates |
| 29 | Simon Willison | @simonw | ~154.5K | Technical | Developer / AI tooling analyst | Top practical technical evaluator of LLM tools. Hands-on testing, code, model behavior, security |
| 30 | Hamel Husain | @HamelHusain | n/a | Technical | AI evals / applied LLM systems | High-signal practitioner voice on AI evals. Evals, product quality, production LLM systems |
| 31 | Aidan McLaughlin | @aidan_mclau | ~47.8K | Technical | OpenAI research | Useful model-design and frontier-lab research signal. Frontier model design/research perspective |
| 32 | Ian Goodfellow | @goodfellow_ian | ~315.7K | Technical | Deep learning researcher | Foundational ML researcher. GANs and deep learning research |
| 33 | Oriol Vinyals | @oriolvinyalsml | ~182.4K | Technical | Google DeepMind research | Major DeepMind technical leader. Gemini, AlphaCode, sequence models |
| 34 | Nando de Freitas | @NandoDF | ~108.9K | Technical | Microsoft AI / ex-DeepMind | High-credibility research voice. Deep learning and superintelligence research |
| 35 | Abhishek Thakur | @abhi1thakur | ~83.1K | Technical | Kaggle / Hugging Face AutoTrain | Applied ML competition and tooling expert. Kaggle, AutoML, model-building practice |
| 36 | Rowan Cheung | @rowancheung | ~563.6K | Non-technical / media-business | AI newsletter / curator | Large AI news distribution channel. News/tool curation, not usually technical depth |
| 37 | Robert Scoble | @Scobleizer | ~536.6K | Non-technical / media-business | Tech futurist / AI commentator | Broad technology/AI reach. Technology commentary and amplification |
| 38 | Kirk Borne | @KirkDBorne | ~455.1K | Semi-technical | Data science / AI influencer | Large data/AI amplification account. Data science/AI curation; PhD background |
| 39 | Ronald van Loon | @Ronald_vanLoon | ~337.6K | Non-technical / media-business | AI/data influencer | Large B2B AI/data reach. Business/AI content and amplification |
| 40 | Timnit Gebru | @timnitGebru | ~162.1K | Semi-technical | AI ethics / DAIR | Influential AI ethics/accountability voice. AI accountability research and policy |
| 41 | Gary Marcus | @GaryMarcus | ~213.5K | Semi-technical | AI critic / cognitive scientist | Influential skeptical AI commentator. Critiques of deep learning and LLM limits |
| 42 | Erik Brynjolfsson | @erikbryn | ~210.2K | Semi-technical | AI economics / Stanford | Important AI-economics KOL. AI productivity and economics research |
| 43 | Paul Couvert | @itsPaulAi | ~191.1K | Non-technical / media-business | AI educator / tools | Large AI tools/tutorial audience. Tool/use-case education, usually not deep technical |
| 44 | Pascal Bornet | @pascal_bornet | ~158.1K | Non-technical / media-business | AI automation author | AI automation business influencer. Business automation/AI commentary |
| 45 | Vincent Boucher | @ceobillionaire | ~153.7K | Semi-technical | Montreal AI / AGI commentator | AI community amplification. AI/AGI commentary and community account |
| 46 | Bernard Marr | @bernardmarr | ~138.7K | Non-technical / media-business | Tech futurist / author | Broad enterprise AI reach. Business tech/AI thought leadership |
| 47 | Data Chaz | @DataChaz | ~114.1K | Semi-technical | Developer advocate / Streamlit | Practical AI/data app educator. Python/data apps/LLM developer content |
| 48 | Randy Olson | @randal_olson | ~110.7K | Semi-technical | Data science / visualization | Technical-ish data science influencer. Data science and visualization content |
| 49 | Jürgen Schmidhuber | @SchmidhuberAI | ~98.1K | Technical | AI researcher | Longstanding ML research figure. Deep learning history and research claims |
| 50 | AI Tool Report | @AIToolReport | ~85.2K | Non-technical / media-business | AI tools newsletter | AI tools distribution channel. AI tools/news aggregation |
| 51 | Kate Crawford | @katecrawford | ~82.3K | Semi-technical | AI ethics / policy researcher | Major AI ethics scholar. Sociotechnical AI research and policy |
| 52 | Nathan Lands | @nathanlands | ~77.3K | Non-technical / media-business | AI investor / podcast | AI startup/media reach. Investor/media commentary |
| 53 | Pedro Domingos | @pmddomingos | ~74.3K | Technical | ML professor / author | Recognized ML academic voice. ML theory and AI commentary |
| 54 | Allie Miller | @alliekmiller | ~71.7K | Non-technical / media-business | AI business speaker | Broad AI business audience. Business AI education |
| 55 | Karen Hao | @_karenhao | ~61.6K | Non-technical / media-business | AI journalist | Important AI media voice. Investigative AI reporting |
| 56 | Santiago Valdarrama | @svpino | ~383.3K | Technical | ML educator | Large practical ML learning audience. Hands-on ML engineering and system design |
| 57 | Bojan Tunguz | @tunguz | ~251.1K | Technical | ML engineer / Kaggle | Applied ML/Kaggle KOL. Data science/Kaggle/model-building |
| 58 | Akshay Pachaar | @akshay_pachaar | ~240K | Semi-technical | LLM/agents educator | Large applied AI education audience. Practical LLM/RAG/agent explainers |
| 59 | Ganapathi Pulipaka | @gp_pulipaka | ~153.2K | Semi-technical | AI/data science influencer | Large AI/data reach. AI/data science curation and commentary |
| 60 | Hugo Larochelle | @hugo_larochelle | ~115.9K | Technical | Google DeepMind researcher | High-quality ML research voice. Deep learning research and education |
| 61 | Peyman Milanfar | @docmilanfar | ~100.1K | Technical | Google computational imaging | Technical computer-vision KOL. Vision/imaging ML research |
| 62 | Dan Kornas | @dankornas | ~87.1K | Technical | ML engineer / educator | Practical ML engineering audience. End-to-end ML engineering education |
| 63 | Patrick Loeber | @patloeber | ~70.7K | Semi-technical | Google DeepMind devrel | AI developer education. Developer education and DeepMind-facing updates |
| 64 | Kevin Patrick Murphy | @sirbayes | ~64.7K | Technical | Google DeepMind researcher | Authoritative ML textbook/research voice. Bayesian ML, probabilistic modeling |
| 65 | Gautam Kamath | @thegautamkamath | ~59.7K | Technical | ML professor / Vector Institute | Technical ML theory voice. Privacy, statistics, ML theory |
| 66 | Sara Hooker | @sarahookr | ~53.3K | Technical | Cohere Labs / model efficiency | Important efficient/open AI researcher. ML efficiency, multilingual/multimodal research |
| 67 | Durk Kingma | @dpkingma | ~51.3K | Technical | Anthropic / VAE/Adam inventor | Foundational ML researcher. Core ML optimization and generative modeling |
| 68 | Andriy Burkov | @burkov | ~50.8K | Technical | ML author | Strong ML educational voice. ML/LLM books and practical education |
| 69 | Jean de Nyandwi | @Jeande_d | ~46.9K | Technical | CMU / NLP evals | Rising technical AI research voice. Multimodal NLP, post-training, data, evals |
| 70 | Shakir Mohamed | @shakir_za | ~41.7K | Technical | DeepMind researcher | Technical DeepMind/social-good voice. ML research and AI for social good |
| 71 | Ferenc Huszár | @fhuszar | ~37.9K | Technical | ML professor | Technical ML/statistics KOL. Bayesian/statistical ML commentary |
| 72 | Andrew Gordon Wilson | @andrewgwils | ~35.5K | Technical | ML professor | Technical ML academic. Bayesian/deep learning theory |
| 73 | Ben Recht | @beenwrekt | ~32.9K | Technical | Berkeley ML/control | Sharp technical ML critic. Optimization, ML systems, critical analysis |
| 74 | Zoubin Ghahramani | @ZoubinGhahrama1 | ~32.6K | Technical | Google DeepMind / Cambridge | Senior ML research authority. Probabilistic ML and AI research leadership |
| 75 | Jakob Foerster | @j_foerst | ~22.7K | Technical | Oxford/Meta ML researcher | Technical RL/agents researcher. Multi-agent RL and ML research |
| 76 | Nils Reimers | @Nils_Reimers | ~14.6K | Technical | Cohere / SBERT | Important technical retrieval/embedding voice. Embeddings, retrieval, AI search |
| 77 | Nathan Raw | @_nateraw | ~9.5K | Technical | ML hacker / Hugging Face alumnus | Hands-on ML builder. Open-source ML tooling |
| 78 | Tim Scarfe | @ecsquendor | ~8.7K | Semi-technical | ML Street Talk / ML engineer | AI research interview/amplification channel. Technical AI podcast and ML commentary |
| 79 | Alicia Curth | @AliciaCurth | ~4.7K | Technical | ML/statistics researcher | Technical ML/statistics voice. Statistical ML intuition and methods |
| 80 | Yoshua Bengio | @yoshuabengio | n/a | Technical | Deep learning pioneer | Turing laureate and major AI safety/research voice. Foundational deep-learning research |
| 81 | Chris Olah | @chrisolah | n/a | Technical | Anthropic / interpretability | Core interpretability KOL. Mechanistic interpretability research |
| 82 | Anca Dragan | @ancadragan | n/a | Technical | Berkeley robotics / HRI | Technical robotics/HRI authority. Human-robot interaction and robotics |
| 83 | Pieter Abbeel | @pabbeel | n/a | Technical | Berkeley robotics / Covariant | Major robotics/RL KOL. Robotics and reinforcement learning |
| 84 | Daphne Koller | @DaphneKoller | n/a | Semi-technical | AI healthcare / Coursera | AI-healthcare founder/research voice. AI in healthcare and biology entrepreneurship |
| 85 | Chelsea Finn | @chelseabfinn | n/a | Technical | Stanford robotics / meta-learning | High-signal robotics/learning researcher. Robotics, meta-learning, imitation learning |
| 86 | Sergey Levine | @svlevine | n/a | Technical | Berkeley robotics / RL | Top technical robotics/RL researcher. Deep RL and robot learning |
| 87 | Been Kim | @beenkim | n/a | Technical | Google interpretability | Important technical interpretability voice. Explainability/interpretability research |
| 88 | Samy Bengio | @samybengio | n/a | Technical | Apple / ex-Google Brain | Senior deep learning researcher. Deep learning research leadership |
| 89 | Kyunghyun Cho | @kchon2020 | n/a | Technical | NYU / NLP | Technical NLP researcher. Neural machine translation, NLP, deep learning |
| 90 | Max Welling | @wellingmax | n/a | Technical | CuspAI / ML professor | Technical ML/science-AI voice. ML theory, generative science, Bayesian/deep learning |
| 91 | David Ha | @hardmaru | n/a | Technical | AI researcher / generative systems | Technical and creative AI research voice. World models, generative systems, creative AI |
| 92 | Alex Graves | @alexjgraves | n/a | Technical | DeepMind researcher | Foundational sequence-model researcher. RNNs, sequence learning, deep learning |
| 93 | Quoc Le | @quocleix | n/a | Technical | Google Brain / AutoML | Senior technical Google AI researcher. AutoML and deep learning research |
| 94 | Leslie Kaelbling | @lpkaelbling | n/a | Technical | MIT AI/robotics | Senior AI/robotics authority. Planning, robotics, AI fundamentals |
| 95 | Mustafa Suleyman | @mustafasuleymn | n/a | Semi-technical | Microsoft AI / DeepMind cofounder | Major lab/product/policy voice. AI strategy, product, policy |
| 96 | Reid Hoffman | @reidhoffman | n/a | Non-technical / media-business | AI investor / author | Large business/AI network. AI entrepreneurship and investment |
| 97 | Daniela Amodei | @daniela_amodei | n/a | Semi-technical | Anthropic cofounder | Frontier-lab leadership voice. Anthropic strategy and safety operations |
| 98 | Aidan Gomez | @aidangomez | n/a | Technical | Cohere CEO / Transformer coauthor | Technical founder with model lineage. Transformer coauthor and enterprise LLM builder |
| 99 | Palantir | @PalantirTech | n/a | Semi-technical | AI/data platform company | Large enterprise AI channel. Enterprise AI/data platform narratives |
| 100 | Jensen Huang | @JensenHuang | n/a | Semi-technical | NVIDIA CEO | AI compute platform narrative-setter. AI hardware/platform strategy |
| 101 | Rachel Thomas | @math_rachel | n/a | Technical | fast.ai / AI education | Technical educator and fast.ai cofounder. Practical ML and responsible AI education |
| 102 | Thomas Wolf | @Thom_Wolf | n/a | Technical | Hugging Face cofounder | Core open-source AI platform builder. Transformers/open-source AI engineering |
| 103 | Julien Chaumond | @julien_c | n/a | Technical | Hugging Face CTO/cofounder | Important open-source AI infra voice. Model hub/open-source platform engineering |
| 104 | Naveen Rao | @NaveenGRao | n/a | Semi-technical | AI chips / Databricks | AI compute/systems founder. AI hardware and systems entrepreneurship |
| 105 | Vinod Khosla | @vkhosla | n/a | Non-technical / media-business | AI investor | Major AI investment voice. AI investment and market theses |
| 106 | Sebastian Thrun | @SebastianThrun | n/a | Technical | Udacity / robotics | Robotics/AI education pioneer. Robotics, autonomous vehicles, education |
| 107 | Peter Diamandis | @PeterDiamandis | n/a | Non-technical / media-business | Futurist / XPRIZE | Broad innovation audience. AI futurism and entrepreneurship |
| 108 | Ray Kurzweil | @raykurzweil | n/a | Semi-technical | AI futurist | Longstanding AI futurist voice. Singularity/AI future commentary |
| 109 | Joy Buolamwini | @jovialjoy | n/a | Semi-technical | Algorithmic Justice League | AI fairness and policy KOL. Algorithmic bias/accountability research |
| 110 | Rumman Chowdhury | @ruchowdh | n/a | Semi-technical | AI ethics / governance | Important AI governance voice. Responsible AI and governance |
| 111 | Abeba Birhane | @Abebab | n/a | Semi-technical | AI accountability researcher | Strong responsible-AI researcher. AI bias/eval/accountability research |
| 112 | Rediet Abebe | @red_abebe | n/a | Technical | AI for social good | Technical/public-interest AI voice. Algorithms and social-good AI research |
| 113 | Meredith Whittaker | @mer__edith | n/a | Non-technical / media-business | Signal / AI critic | Important policy/privacy voice. AI politics, privacy, surveillance critique |
| 114 | Cathy O’Neil | @mathbabedotorg | n/a | Semi-technical | Algorithmic accountability | Public algorithmic-risk voice. Risk, fairness, automated decision-making |
| 115 | Safiya Noble | @safiyanoble | n/a | Non-technical / media-business | AI/search equity scholar | Important sociotechnical AI voice. Critical AI/search scholarship |
| 116 | Ruha Benjamin | @ruha9 | n/a | Non-technical / media-business | Technology and society scholar | Sociotechnical AI influence. Race, technology, AI society |
| 117 | Jack Clark | @jackclarkSF | n/a | Semi-technical | Anthropic cofounder / Import AI | Measured AI policy/technical newsletter voice. AI policy, capability trends, technical summaries |
| 118 | Melanie Mitchell | @MelMitchell1 | n/a | Technical | Complexity / AI researcher | Technical and skeptical AI researcher. AI reasoning, analogy, cognitive science |
| 119 | Aurélien Géron | @aureliengeron | n/a | Technical | ML author | Popular practical ML educator. Hands-on ML education |
| 120 | Chip Huyen | @chipro | n/a | Technical | AI engineering author | High-signal AI engineering voice. ML systems, AI engineering, evals |
| 121 | Monica Rogati | @mrogati | n/a | Technical | Data science leader | Technical data/AI product KOL. Data/AI product strategy and systems |
| 122 | Inioluwa Deborah Raji | @rajiinio | n/a | Semi-technical | AI accountability researcher | Important AI auditing voice. Model auditing and accountability |
| 123 | Arvind Narayanan | @random_walker | n/a | Technical | Princeton AI/society | Technical AI and policy critic. AI, fairness, privacy, crypto, accountability |
| 124 | Vincent Warmerdam | @fishnets88 | n/a | Technical | Calmcode / ML tooling | High-signal practical technical educator. Practical ML education and tooling |
| 125 | Sasha Luccioni | @SashaMTL | n/a | Semi-technical | Hugging Face / AI climate | Technical responsible-AI voice. AI energy, climate, responsible AI evaluation |
| 126 | Miles Brundage | @Miles_Brundage | n/a | Semi-technical | AI policy/safety | Important policy/safety KOL. AI governance and frontier-lab policy |
| 127 | Jan Leike | @janleike | n/a | Technical | Anthropic / alignment | Top technical alignment researcher. Alignment, scalable oversight, RLHF |
| 128 | Paul Christiano | @paulc443 | n/a | Technical | Alignment Research Center | Core technical alignment voice. Technical AI alignment theory/evals |
| 129 | Oren Etzioni | @etzioni | n/a | Semi-technical | AI2 founder | Senior AI institution builder. AI research, policy, entrepreneurship |
| 130 | Percy Liang | @percyliang | ~106.5K | Technical | Stanford NLP / HELM | Top LLM-evaluation researcher. Benchmarking, NLP, HELM/MedHELM |
| 131 | Jacob Andreas | @jacobandreas | n/a | Technical | MIT NLP | Technical NLP/agents researcher. Language grounding, agents, NLP research |
| 132 | Dan Hendrycks | @DanHendrycks | n/a | Technical | Center for AI Safety | Important eval/safety benchmark creator. Benchmarks, model risks, WMDP/MMLU-style evals |
| 133 | Scott Aaronson | @scottaaronson | n/a | Technical | Theoretical CS / OpenAI alumnus | Technical theory/safety voice. Complexity theory, quantum, AI safety commentary |
| 134 | Swyx | @swyx | n/a | Technical | AI engineering / Latent Space | Top AI engineering community builder. Agents, RAG, evals, AI engineering stack |
| 135 | Mckay Wrigley | @mckaywrigley | n/a | Semi-technical | AI builder / Chatbot UI | Practical AI builder influence. AI app demos and builder workflows |
| 136 | Deedy Das | @deedydas | n/a | Semi-technical | AI investor / curator | High-signal AI startup/model curator. Model release summaries and benchmark takes |
| 137 | Bindu Reddy | @bindureddy | n/a | Semi-technical | Abacus AI CEO | High-engagement AI product/founder voice. AI capability/startup commentary |
| 138 | Ethan Mollick | @emollick | n/a | Semi-technical | Wharton professor / AI use cases | Major practical AI adoption voice. Empirical AI use and workplace experiments |
| 139 | Linus Lee | @thesephist | n/a | Technical | Notion AI researcher | Technical AI product/research voice. LLM internals, embeddings, AI-native UX |
| 140 | Nathan Labenz | @labenz | n/a | Semi-technical | Cognitive Revolution podcast | Strong AI interview/eval commentator. Model eval discussions, AI interviews |
| 141 | Nathan Lambert | @natolambert | n/a | Technical | AI2 / Interconnects | Top technical post-training/open-model voice. RLHF, post-training, open models |
| 142 | DAIR.AI | @DAIR_AI | n/a | Semi-technical | AI research education | Research-paper amplification and education. Paper explainers and ML education |
| 143 | arXiv | @arxiv_org | n/a | Technical | Research preprint platform | Raw research discovery channel. Primary research feed |
| 144 | AlphaXiv | @alphaxiv | n/a | Technical | Paper discovery platform | AI paper discovery/amplification. Social layer for arXiv/papers |
| 145 | Cameron Wolfe | @cwolferesearch | n/a | Technical | AI researcher / writer | High-signal technical AI explainer. Paper breakdowns and Deep Learning Focus |
| 146 | Vikhyat K. | @vikhyatk | n/a | Technical | Moondream / small VLMs | Practical model builder. Small-model/VLM engineering |
| 147 | OpenAI | @OpenAI | n/a | Semi-technical | Frontier AI lab | Primary OpenAI launch channel. Official launches and benchmark posts |
| 148 | Anthropic | @AnthropicAI | n/a | Semi-technical | Frontier AI lab | Primary Anthropic launch channel. Claude releases and safety research |
| 149 | Google DeepMind | @GoogleDeepMind | ~1.2M | Technical | Frontier AI/science lab | Major technical AI lab channel. Research releases, AlphaFold/Gemini science AI |
| 150 | Meta AI | @MetaAI | n/a | Technical | Open models / AI lab | Key open-model lab channel. Llama/open model research and product |
| 151 | Mistral AI | @MistralAI | n/a | Technical | Frontier/open model lab | European frontier model channel. Open/foundation model releases |
| 152 | Hugging Face | @huggingface | ~689K | Semi-technical | Open-source AI platform | High-impact open AI distribution. Model/dataset/leaderboard ecosystem |
| 153 | NVIDIA | @nvidia | n/a | Semi-technical | AI compute platform | AI infrastructure narrative channel. GPU/platform launches and AI hardware |
| 154 | Cohere | @cohere | n/a | Semi-technical | Enterprise LLM lab | Enterprise LLM platform channel. Enterprise model releases and retrieval/RAG context |
| 155 | Perplexity | @perplexity_ai | n/a | Semi-technical | AI search company | Consumer AI search channel. AI search product releases |
| 156 | Together AI | @togethercompute | n/a | Technical | Open model infra | Open AI infrastructure channel. Inference/fine-tuning/open model infra |
| 157 | xAI | @xai | n/a | Semi-technical | Frontier AI lab | xAI primary launch channel. Grok releases and xAI research |
| 158 | LM Arena | @lmarena_ai | n/a | Technical | Model leaderboard/evals | Important public model benchmark channel. Chatbot Arena / model rankings |
| 159 | OpenRouter | @OpenRouterAI | n/a | Semi-technical | Model routing/API platform | Useful model market/API signal. Model availability and routing data |
| 160 | Replicate | @replicate | n/a | Technical | Model hosting/API | Model deployment ecosystem channel. Open model deployment and demos |
| 161 | Weights & Biases | @weights_biases | n/a | Semi-technical | MLOps / evals | MLOps and AI eval community. Experiment tracking, evals, ML tooling |
| 162 | LangChain | @LangChainAI | n/a | Technical | LLM app framework | Key AI agent/RAG developer channel. Agents, RAG, LangGraph, app tooling |
| 163 | LlamaIndex | @llama_index | n/a | Technical | LLM data/RAG framework | Important AI engineering framework. RAG, retrieval, agents, data connectors |
| 164 | Modal | @modal_labs | n/a | Technical | AI compute platform | Technical AI infra channel. Serverless GPU/AI infra |
| 165 | Anyscale | @AnyscaleCompute | n/a | Technical | Ray / AI infra | Important scalable AI systems channel. Distributed ML/serving infrastructure |
| 166 | Scale AI | @scale_AI | n/a | Semi-technical | Data/evals platform | Evals/data infrastructure influence. Data, evals, enterprise AI |
| 167 | Scale Labs | @ScaleAILabs | n/a | Technical | AI evals / benchmarks | High-signal eval/benchmark channel. DrugDiscoveryBench and agent benchmarks |
| 168 | METR | @METR_Evals | ~25.2K | Technical | AI capability evals | Important agent-eval methodology voice. Agent/R&D capability measurements |
| 169 | UK AI Security Institute | @AISecurityInst | ~7.6K | Semi-technical | Model safety/evals | Government eval-framework voice. Inspect Evals and frontier-model evaluation |
| 170 | Center for AI Safety | @ai_risks | ~8.2K | Semi-technical | AI safety benchmarks | Bio/chem/cyber eval relevance. WMDP and risk evaluations |
| 171 | Epoch AI | @EpochAIResearch | ~45.7K | Semi-technical | AI trends/benchmarks | Methodology/benchmark analysis amplifier. Benchmark and compute trend analysis |
| 172 | MLCommons | @MLCommons | ~3.6K | Semi-technical | AI standards/benchmarks | Standards-setting benchmark channel. MLPerf, medical AI, benchmark working groups |
| 173 | Papers with Code | @paperswithcode | ~114.7K | Semi-technical | Benchmark leaderboard platform | Broad benchmark visibility channel. Paper/code/leaderboard discovery |
| 174 | Therapeutics Data Commons | @ProjectTDC | ~1.3K | Technical | Drug-discovery ML benchmarks | Foundational drug-discovery benchmark ecosystem. TDC tasks/leaderboards/datasets |
| 175 | Phylo | @phylo_bio | n/a | Technical | Biomedical agents / DrugDiscoveryBench | Direct DDDBench peer/partner target. Biomni, BiomniBench, DrugDiscoveryBench |
| 176 | Kexin Huang | @KexinHuang5 | n/a | Technical | Biomedical AI agents | High-signal biomedical-agent benchmark KOL. BiomniBench/Biomni; long-horizon bio tasks |
| 177 | FutureHouse | @FutureHouseSF | n/a | Technical | Scientific agents / LAB-Bench | Top scientific-agent benchmark target. LAB-Bench/BixBench/scientific-agent ecosystem |
| 178 | Valence Labs | @valence_ai | ~5.9K | Technical | Drug-discovery benchmarks | Relevant industry-standard DD benchmarking channel. Polaris benchmark/data platform |
| 179 | Pat Walters | @wpwalters | ~6.3K | Technical | Cheminformatics / benchmark critique | High-credibility DD benchmark evaluator. ADMET/blind challenges, benchmark validity |
| 180 | OpenBioML | @openbioml | ~4.1K | Technical | Open biology ML | Community amplifier for open BioML benchmarks. BioML/ChemNLP community amplification |
| 181 | Stephen Turner | @strnr | ~31.3K | Technical | Genomics / AIxBio commentary | Strong AI-bio benchmark amplifier. Genomics, biosecurity, AI-bio eval commentary |
| 182 | Jablonka Lab | @jablonkagroup | ~359 | Technical | ChemBench / chemistry AI | Relevant chemistry benchmark group. ChemBench and chemistry/materials LLM evals |
| 183 | Andrew White | @andrewwhite01 | n/a | Technical | ChemCrow / scientific agents | Strong chemistry/science-agent benchmark KOL. ChemCrow, PaperQA, chemistry agents |
| 184 | Philippe Schwaller | @pschwllr | n/a | Technical | Chemical language models | Chemistry model/eval KOL. RXN/ChemCrow/chemistry AI |
| 185 | Chai Discovery | @chaidiscovery | ~5.6K | Technical | Structure prediction | Protein/structure benchmark channel. Chai-1/chai-lab structure benchmarks |
| 186 | Rosetta Commons | @RosettaCommons | ~1.9K | Technical | Protein modeling/design | Protein-design benchmark credibility network. Rosetta, CASP/CAPRI ecosystem |
| 187 | ChEMBL Database | @ChEMBL | ~2.9K | Technical | Drug-discovery data | Benchmark/data community account. ChEMBL resource updates |
| 188 | Tanishq Abraham / MedARC | @iScienceLuvr | n/a | Technical | Medical LLM benchmarks | Medical LLM benchmark KOL. Medmarks and medical AI evaluation |
| 189 | Stability AI | @StabilityAI | n/a | Semi-technical | Open generative AI lab | Generative AI model distribution channel. Open image/audio/model releases |
| 190 | Midjourney | @midjourney | n/a | Non-technical / media-business | Generative image models | Major creative AI model channel. Model/product releases, creative AI |
| 191 | Runway | @runwayml | n/a | Semi-technical | Generative video AI | Major generative video model channel. Video model/product releases |
| 192 | Luma AI | @LumaLabsAI | n/a | Semi-technical | Generative video/3D | Creative model product channel. Dream Machine/video/3D model releases |
| 193 | Cursor | @cursor_ai | n/a | Technical | AI coding IDE | Major AI coding tool channel. AI coding product and model integrations |
| 194 | Cognition | @cognition_labs | n/a | Technical | AI software agents | Important coding-agent benchmark/product channel. Devin and coding-agent releases |
| 195 | Replit | @Replit | n/a | Semi-technical | AI coding platform | AI coding/developer distribution channel. AI coding agents and cloud dev platform |
| 196 | Windsurf | @windsurf_ai | n/a | Technical | AI coding IDE | Important AI coding product channel. Coding-agent/product releases |
| 197 | OpenAI Developers | @OpenAIDevs | n/a | Technical | OpenAI developer platform | Primary technical OpenAI developer channel. API, model tiers, developer releases |
| 198 | Google AI | @GoogleAI | n/a | Semi-technical | Google AI product/research | Broad Google AI channel. Google AI releases and research/product links |
| 199 | Databricks | @databricks | n/a | Semi-technical | Data/AI platform | Important enterprise data+AI platform channel. Lakehouse, MosaicML, model serving and enterprise AI infra |
| 200 | MosaicML | @MosaicML | n/a | Technical | Model training infrastructure | Technical model-training infrastructure voice. Open model training, LLM training systems and infra |
| # | Name | X handle | Followers | Benchmark/eval focus | Examples + relevance |
|---|---|---|---|---|---|
| 1 | OpenAI | @OpenAI | very large / n.a. | LifeSciBench; GeneBench-Pro; life-science model evaluation | LifeSciBench: 750 expert-authored tasks, 173 scientist contributors, 19,020 rubric criteria. Direct benchmark comparator and high-impact launch/amplification target. |
| 2 | Tacit Labs | @tacitlabsco | n/a | LifeSciBench partner / biology verification loop | Referenced in LifeSciBench launch ecosystem with OpenAI. Potential partner/peer for life-science task design and validation. |
| 3 | Nina Fitzpatrick | @ninklefitz | n/a | LifeSciBench / Tacit Labs | Named in LifeSciBench/Tacit Labs launch amplification. Likely useful individual contact around biology eval design. |
| 4 | Andrew Droste | @AmDroste | n/a | LifeSciBench / Tacit Labs | Named in LifeSciBench/Tacit Labs launch amplification. Likely useful individual contact around life-science verification. |
| 5 | FutureHouse | @FutureHouseSF | n/a | Biology/science agents, LAB-Bench, scientific task evaluation | LAB-Bench and FutureHouse scientific-agent ecosystem; BixBench repo under Future-House. Top target for scientific-agent benchmark comparison/amplification. |
| 6 | Phylo | @phylo_bio | n/a | Biomni, BiomniBench, DrugDiscoveryBench, biomedical agents | DrugDiscoveryBench with Scale Labs; BiomniBench process-level evaluation. Direct DDDBench peer/benchmark partner and high-priority outreach target. |
| 7 | Scale Labs | @ScaleAILabs | n/a | DrugDiscoveryBench and agent evals | DrugDiscoveryBench: 82 early-stage DD tasks with expert rubrics and leaderboard. Direct benchmark comparison; useful for model-vs-harness narrative. |
| 8 | Scale AI | @scale_AI | large / n.a. | AI data/evals; Scale Labs amplification | Scale blog and labs leaderboard for DrugDiscoveryBench. Enterprise-eval distribution channel. |
| 9 | Kexin Huang | @KexinHuang5 | n/a | Biomni, BiomniBench, AI agents for biomedical research | Posted BiomniBench launch: process-level evaluation of agents on long-horizon biology tasks. Strong KOL for agentic biomedical benchmarks and scientific-agent systems. |
| 10 | Therapeutics Data Commons | @ProjectTDC | ~1.3K | Drug-discovery ML datasets/tasks/leaderboards | TDC platform for AI-ready therapeutic datasets and leaderboards. Foundational benchmark ecosystem for DDDBench positioning. |
| 11 | Jure Leskovec | @jure | ~44.7K | TDC, graph ML, biomedical ML | TDC / Harvard-Stanford biomedical ML ecosystem. Senior benchmark and graph-ML amplifier. |
| 12 | Valence Labs | @valence_ai | ~5.9K | Polaris drug-discovery benchmark platform | PolarisHub benchmark/data platform for drug discovery. Highly relevant for industry-standard DD benchmarking. |
| 13 | Pat Walters | @wpwalters | ~6.3K | Cheminformatics benchmark critique, ADMET, blind challenges | OpenADMET/blind-challenge and benchmark-validity commentary. High-credibility evaluator/KOL for DD benchmark quality. |
| 14 | OpenBioML | @openbioml | ~4.1K | Open biology ML, ChemNLP, model-risk/eval discussion | Community journal clubs and BioML paper amplification. Community amplifier for open BioML benchmarking. |
| 15 | Biology+AI Daily | @BiologyAIDaily | n/a | AI-bio paper/benchmark amplification | Amplified BixBench and other AI-biology benchmark papers. Useful awareness channel for DDDBench/MMAI benchmark posts. |
| 16 | Stephen Turner | @strnr | ~31.3K | Genomics, computational biology, AIxBio commentary | Genomics and biosecurity/AI benchmark commentary. Strong commentator/amplifier for AI-bio benchmark credibility. |
| 17 | Jablonka Lab | @jablonkagroup | ~359 | ChemBench, chemistry/materials LLM evaluation | ChemBench benchmark for chemistry reasoning and tool use. Relevant analog for chemistry/LLM eval methodology. |
| 18 | Andrew White | @andrewwhite01 | n/a | ChemCrow, PaperQA, scientific agents, chemistry LLMs | ChemCrow and scientific-agent evaluation work. Very strong chemistry/science-agent benchmark KOL. |
| 19 | Philippe Schwaller | @pschwllr | n/a | Chemical language models, RXN, ChemCrow ecosystem | ChemCrow / reaction prediction / chemistry AI work. Good benchmark reviewer and chemistry-agent evaluator. |
| 20 | Chai Discovery | @chaidiscovery | ~5.6K | Biomolecular structure prediction benchmarks | Chai-1, chai-lab, structure prediction comparisons. Protein/structure benchmark comparison channel. |
| 21 | Google DeepMind | @GoogleDeepMind | ~1.2M | AlphaFold/CASP, Gemini science AI | AlphaFold and Isomorphic science-AI narratives. Huge amplifier; benchmark framing authority. |
| 22 | Rosetta Commons | @RosettaCommons | ~1.9K | Protein modeling/design benchmarks and community tools | Rosetta, CASP/CAPRI-related modeling ecosystem. Protein-design benchmark credibility network. |
| 23 | ChEMBL Database | @ChEMBL | ~2.9K | Drug-discovery data resource used in benchmarks | ChEMBL data/resource updates. Useful data/benchmark community account. |
| 24 | Papers with Code | @paperswithcode | ~114.7K | ML benchmark/leaderboard amplification | Benchmark and paper leaderboard distribution. Broad benchmark visibility channel. |
| 25 | Hugging Face | @huggingface | ~689K | Open leaderboards and model hubs | Open Medical LLM Leaderboard; dataset/model benchmark hosting. High-impact hosting/amplification route for DDDBench/MMAI. |
| 26 | Percy Liang / Stanford HELM | @percyliang | ~106.5K | HELM, MedHELM, holistic LLM evals | Stanford CRFM HELM and medical evaluation frameworks. Credible LLM-eval benchmark KOL. |
| 27 | METR | @METR_Evals | ~25.2K | Agent/R&D capability evals, time-horizon evals | Autonomous capability measurement and eval methodology. Useful for agent-eval methodology framing. |
| 28 | UK AI Security Institute | @AISecurityInst | ~7.6K | Inspect Evals; chem/bio/frontier model evals | Inspect eval framework and frontier-model safety evaluations. Strong eval-framework/governance target. |
| 29 | Center for AI Safety | @CAIS / @ai_risks | ~8.2K | WMDP bio/chem/cyber hazardous-knowledge benchmark | WMDP benchmark and biorisk/chem risk evals. Relevant to bio/chem LLM evals; outreach should be careful and risk-aware. |
| 30 | Epoch AI | @EpochAIResearch | ~45.7K | Benchmark datasets/trends and biorisk eval analysis | Epoch benchmark tracking and AI trend analysis. Methodology/benchmark-analysis amplifier. |
| 31 | MLCommons | @MLCommons | ~3.6K | Medical AI, safety, and science benchmark working groups | MLCommons medical/data working groups. Standards-setting outreach target. |
| 32 | Tanishq M. Abraham / MedARC | @iScienceLuvr | n/a | Medmarks medical LLM benchmark suite | Medmarks benchmark posts and GitHub project. Strong medical LLM benchmark KOL. |