Brains, minds and machines

Brains, minds and machines Computational vision     

                                                                                                                                                                                                                                                              Biological

The foundation of intelligence – the way the brain produces intelligent behavior and just how we might be able to replicate intelligence in machines – is perhaps the finest condition in science. To resolve it, we will have to know how human intelligence emerges from computations in neural circuits, with rigor sufficient to breed similar intelligent behavior in machines. Success within this endeavor ultimately will enable us to know ourselves better, to create smarter machines, and possibly even going to make ourselves smarter. Today’s AI technologies, for example Watson and Siri, are impressive, however their domain specificity and reliance upon vast figures of labeled examples are apparent limitations couple of view this as brain-like or human intelligence. The synergistic mixture of cognitive science, neurobiology, engineering, mathematics, and information technology supports the promise to construct a lot more robust and complicated algorithms implemented in intelligent machines. The aim of this program would be to help create a community of leaders that’s equally knowledgeable in neuroscience, cognitive science, and information technology and can lead the introduction of true biologically inspired AI.

The category discussions covers a variety of topics, including:

  • Neuroscience: neurons and models
  • Computational vision
  • Brains, minds and machines Memory     

    Social cognition     

    Inverse problems

  • Biological vision
  • Machine learning
  • Bayesian inference
  • Planning and motor control
  • Memory
  • Social cognition
  • Inverse problems & well-posedness
  • Audition and speech processing
  • Natural language processing

These discussions is going to be complemented within the first week by MathCamps and NeuroCamps, to refresh the required background. Through the course, students will take part in workshops and tutorials to achieve hands-on knowledge about these topics.

Core presentations will be presented jointly by neuroscientists, cognitive scientists, and computer scientists. Lectures is going to be adopted by afternoons of computational labs, with a lot more evening research workshops. To strengthen the theme of collaboration between (information technology + math) and (neuroscience + cognitive science), exercises and projects frequently is going to be performed in teams that combine students with backgrounds.

The program will culminate with student presentations of the projects. These projects supply the chance for college students to operate carefully using the resident faculty, to build up ideas that outgrow the lectures and workshops, and also to connect these ideas with problems in the students’ own research in their home institutions.

This program aims to mix-educate computer engineers and neuroscientists it’s suitable for graduated pupils, postdocs, and faculty in information technology or neuroscience. Students are envisioned having a powerful background in a single discipline (for example neurobiology, physics, engineering, and mathematics). Our goal would be to get the science and also the technology of intelligence and also to help train a brand new generation of scientists which will leverage the progress in neuroscience, cognitive science, and information technology.

Resourse: http://mbl.edu/education/courses/brains-minds-and-machines/

Lecture 0: Tomaso Poggio – Introduction to Brains, Minds, and Machines


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