Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Ontogenetic hardware

M Sipper1, D Mange, A Stauffer

  • 1Logic Systems Laboratory, Swiss Federal Institute of Technology, Lausanne, Switzerland. moshe.sipper@di.epfl.ch

Bio Systems
|January 1, 1997
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Five fraction stereotactic radiotherapy after brain metastasectomy: a single-institution experience and literature review.

Journal of neuro-oncology·2021
Same author

Intraoperative high frequency ultrasound in intracerebral high-grade tumors.

Ultraschall in der Medizin (Stuttgart, Germany : 1980)·2012
Same author

Necessary conditions for density classification by cellular automata.

Physical review. E, Statistical, nonlinear, and soft matter physics·2001
Same author

Go forth and replicate.

Scientific American·2001
Same author

Evolutionary computation in medicine: an overview.

Artificial intelligence in medicine·2000
Same author

Design, observation, surprise! A test of emergence.

Artificial life·2000
Same journal

The Quantum-to-Classical Transducer: A Thermodynamic and Quantum Mechanical Framework for the Emergence of Bioenergetics.

Bio Systems·2026
Same journal

Forward-backward gene expression binarization for boolean state inference over a known regulatory network.

Bio Systems·2026
Same journal

Partial-Label Metric Ceilings for Evaluating Gene Regulatory Networks Inferred from Single-Cell Foundation Models.

Bio Systems·2026
Same journal

The impedance mismatch theory: A non-equilibrium thermodynamic framework for a shared energetic stress pathway in neurodegeneration.

Bio Systems·2026
Same journal

Immune signal-status misclassification: A theoretical framework for biological status assignment and failed status resolution.

Bio Systems·2026
Same journal

Contextuality, incompatibility, and intra-system entanglement of mental markers: From cognition and decision making to medicine.

Bio Systems·2026
See all related articles

Researchers developed bio-inspired ontogenetic hardware that mimics biological development. This artificial hardware exhibits self-replication, self-repair, and growth, opening possibilities for novel regenerative systems.

Area of Science:

  • Bio-inspired engineering
  • Artificial intelligence
  • Developmental biology

Background:

  • Ontogeny describes the development of an organism from a single cell.
  • Living organisms exhibit remarkable properties like self-replication, self-repair, and growth.
  • These biological principles have inspired the creation of artificial systems.

Purpose of the Study:

  • To explore the transposition of ontogenetic principles to integrated circuits.
  • To demonstrate that artificial objects can achieve life-like properties.
  • To introduce novel classes of ontogenetic hardware.

Main Methods:

  • Adopting cellular organization features from biological ontogeny.
  • Applying these features to integrated circuits on silicon.

Related Experiment Videos

  • Identifying and describing three classes of ontogenetic hardware: self-replicating, embryonic, and L-systems based (L-hardware).

    • Main Results:

    • Demonstrated that integrated circuits can exhibit self-replication, self-repair, and growth.
    • Presented hardware realizations for each of the three identified classes.
    • Discussed potential applications for these ontogenetic hardware systems.

    Conclusions:

    • Ontogenetic hardware can successfully emulate key properties of biological development.
    • Further research may lead to bio-inspired systems with advanced replicative, growth, and regenerative capabilities.
    • This work bridges developmental biology and artificial systems engineering.