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CFChelsea Finn, Stanford professor, co-founder Physical Intelligence

Top 100 IA · Stati Uniti

Chelsea Finn

Stanford Stati Uniti

Punteggio
71270 oggi
Posizione
80/198 ↓3
in 90 giorni
+350+4,8%

Chelsea Finn è Professore Associato di Informatica e Ingegneria Elettrica alla Stanford University e co-fondatrice di Physical Intelligence. È specializzata in intelligenza artificiale, robotica e machine learning, e condivide frequentemente risultati di ricerca, benchmark e applicazioni pratiche di sistemi robotici. I suoi contenuti includono analisi dettagliate sulle prestazioni dei modelli di IA, attività robotiche e risorse educative come video di lezioni e interventi a workshop.

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Dati al 25 ott 2026.

I numeri grezzi · ultimi 90 giorni

Visualizzazioni mediane
42,8K
per post
Interazioni mediane
435
per post
Post
10
in 90 giorni
Follower
129,3K
tutti i social nel punteggio

Cosa determina il punteggio

Percentili 0 – 100 rispetto a tutti i creator monitorati.

  • Portata · 30%86

    Visualizzazioni medie per post su 90 giorni

  • Engagement · 30%70

    Reazioni medie per post

  • Audience · 30%75

    Follower totali, rapportati alla popolazione

  • Costanza · 10%63

    Ritmo di pubblicazione (25 post / 90 g = 100)

Social

129,3K follower in totale

SocialFollowerPunteggio
X@chelseabfinn105,9K8277t2
LinkedIn@cbfinn23,3K2599t9

Ultimi 30 giorni

I migliori post di Finn

  1. The Pi API is officially in beta! 🤖 Many people have already been using it to fine-tune π models for their robots -- below are a few We’re hoping to expand testing significantly. Let us know if you are interested! Bl…
    X · 13 gg fa#1
    CFChelsea Finn, Stanford professor, co-founder Physical IntelligenceChelsea Finn

    The Pi API is officially in beta! 🤖 Many people have already been using it to fine-tune π models for their robots -- below are a few We’re hoping to expand testing significantly. Let us know if you are interested! Bl…

    29,1K visualizzazioni582 interazioni

  2. X · 17 gg fa#2
    As robots become more reliable, DAgger becomes far less efficient. eg 90% success means the person spends >90% of the time passively watching the robot Key idea: failures come from similar initial states & we c…
    CFChelsea Finn, Stanford professor, co-founder Physical IntelligenceChelsea Finn

    38,5K visualizzazioni398 interazioni

  3. X · 22 gg fa#3
    Scientific discovery is one of the most exciting applications of LLMs, but we lack data & evals on the scientific process. ScholarCatalyst captures which prior papers can advance new research on a problem, rather …
    CFChelsea Finn, Stanford professor, co-founder Physical IntelligenceChelsea Finn

    28,6K visualizzazioni344 interazioni

  4. How do we scale up the context of LLMs? Agentic search scales to arbitrarily large amounts of info, but can easily miss relevant info. Idea💡: Optimize organization of info for downstream utility. Leads to 30+% gains …
    X · 5 gg fa#4
    CFChelsea Finn, Stanford professor, co-founder Physical IntelligenceChelsea Finn

    How do we scale up the context of LLMs? Agentic search scales to arbitrarily large amounts of info, but can easily miss relevant info. Idea💡: Optimize organization of info for downstream utility. Leads to 30+% gains …

    24K visualizzazioni340 interazioni

  5. X · l’altro ieri#5
    Generative value classifiers are a new parametrization of Q-functions that don't require action conditioning. We think these may combine gracefully with large, pre-trained policies and learn/generalize better from a r…
    CFChelsea Finn, Stanford professor, co-founder Physical IntelligenceChelsea Finn

    18,2K visualizzazioni312 interazioni

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