A Brand for social justice
In 2020, brands did something they’d never done before: They spoke up about race.
The goal is to make computers learn the way humans do
Teaching computers to learn the way we do is widely considered an important step toward better artificial intelligence, but it's hard to achieve without a good understanding of how we think. With that premise in mind, a new $US12 million effort launched on Wednesday with aims to "reverse-engineer" the human brain.
Led by Tai Sing Lee, a professor in Carnegie Mellon University's Computer Science Department and the Center for the Neural Basis of Cognition (CNBC), the five-year project seeks to unlock the secrets of neural circuitry and the brain's learning methods. Ultimately, the goal is to improve neural networks, the computational models often used for AI in applications including self-driving cars, automated trading, and facial and speech recognition.
"Today's neural nets use algorithms that were essentially developed in the early 1980s," Lee said. "Powerful as they are, they still aren't nearly as efficient or powerful as those used by the human brain."
A computer might need to be shown thousands of labeled examples in order to learn to recognize an object, for example, while a human would require only a handful.
Trying to figure out why that's so will use a technique called two-photon calcium imaging microscopy. Researchers will record the signaling of tens of thousands of individual neurons in mice as they process visual information.
"By incorporating molecular sensors to monitor neural activity in combination with sophisticated optical methods, it is now possible to simultaneously track the neural dynamics of most, if not all, of the neurons within a brain region," said team member Sandra Kuhlman, assistant professor of biological sciences at Carnegie Mellon and the CNBC.
A massive data set will result, offering a detailed picture of how neurons in one region of the visual cortex behave, she added.
The project is funded by the Intelligence Advanced Research Projects Activity (IARPA) through its Machine Intelligence from Cortical Networks (MICrONS) research program, which is working to advance President Obama's BRAIN Initiative.
The CMU-led team will collaborate with other related projects and make multiple vast databases publicly available for research groups all over the world.
"The hope is that this knowledge will lead to the development of a new generation of machine-learning algorithms that will allow AI machines to learn without supervision and from a few examples, which are hallmarks of human intelligence," Lee said.
Another IARPA-funded project launched recently at Harvard shares a similar goal.
In this latest episode of our conversations over a cuppa with CMO, we catch up with the delightful Pip Arthur, Microsoft Australia's chief marketing officer and communications director, to talk about thinking differently, delivering on B2B connection in the crisis, brand purpose and marketing transformation.
In 2020, brands did something they’d never done before: They spoke up about race.
‘Business as unusual’ is a term my organisation has adopted to describe the professional aftermath of COVID-19 and the rest of the tragic events this year. Social distancing, perspex screens at counters and masks in all manner of situations have introduced us to a world we were never familiar with. But, as we keep being reminded, this is the new normal. This is the world we created. Yet we also have the opportunity to create something else.
In times of uncertainty, people gravitate towards the familiar. How can businesses capitalise on this to overcome the recessionary conditions brought on by COVID? Craig Flanders explains.
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