Des chercheurs de l'université de Harvard viennent de mettre au point un transistor qui imite une synapse puisqu'il est capable d'apprendre. Ces recherches pourraient donner de nouvelles perspectives à l'intelligence artificielle.
Back in the dark ages of January, 2012, my colleague Alysia Santo wrote a thoughtful piece about how journalism schools were—or were not—equipping their students with the tools and know-how they need to protect their digital information...
“ Hace ya muchísimo tiempo, en el 2590 AP (Antes del PowerPoint) los griegos hablaban de los cinco cánones de la retórica: invención, organización, estilo, memoria y actuación. Hoy vamos a hablar de la memoria.”
I'm a big fan of music and use it a lot when working, but I had no idea about how it really affects our brains and bodies. Music is such a big part of our lives, and we react to it in many ways without even realizing.
Below is a graph of Computing on a logarithmic scale. It shows the power of computing at the Supercomputer, Desktop Computer and Mobile level. This is Moore’s Law in action – it states that the number of transistors doubles every 18 months.
Computers are Turing machines, which means that they all work the same fundamental way – as a series of operations. Computing power is just a measure of operations or calculations per second.
Ciberpsicología. La nueva sensibilidad que forjan tecnologías como Internet prepara culturalmente para la aparición de un nuevo tipo de máquinas: los robots sociales. El vínculo ya comenzó con los celulares.
Cornell engineers are helping humans and robots work together to find the best way to do a job, an approach called “coactive learning.”
“We give the robot a lot of flexibility in learning,” said Ashutosh Saxena, assistant professor of computer science. “We build on our previous work in teaching robots to plan their actions, then the user can give corrective feedback.”
Saxena’s research team will report their work at the Neural Information Processing Systems conference in Lake Tahoe, Calif., Dec. 5-8.
Modern industrial robots, like those on automobile assembly lines, have no brains, just memory. An operator programs the robot to move through the desired action; the robot can then repeat the exact same action every time a car goes by.
But off the assembly line, things get complicated: A personal robot working in a home has to handle tomatoes more gently than canned goods. If it needs to pick up and use a sharp kitchen knife, it should be smart enough to keep the blade away from humans.
Saxena’s team, led by Ph.D. student Ashesh Jain, set out to teach a robot to work on a supermarket checkout line, modifying a Baxter robot from Rethink Robotics in Boston, designed for assembly line work. It can be programmed by moving its arms through an action, but also offers a mode where a human can make adjustments while anaxctiinis in progress.
With over 7% of the population unemployed, the job market is very competitive. On average, 144 people apply for each entry-level position posted and 89 people for each professional level position. That’s a lot of work for recruitment teams, so...