Though the brain is a very slow machine, its capabilities exceed typical state-of-the-art, ultrafast artificial intelligence algorithms; hence, a revolution in deep learning must emerge, as experimentally and theoretically demonstrated by physicists
Machine learning, introduced 70 years ago, is based on evidence of the dynamics of learning in our brain. Using the speed of modern computers and large data sets, deep learning algorithms have recently produced results comparable to those of human experts in various applicable fields, but with different characteristics that are distant from current knowledge of learning in neuroscience.
Using advanced experiments on neuronal cultures and large scale simulations, a group of scientists at Bar-Ilan University in Israel has demonstrated a new type of ultrafast artifical intelligence algorithms — based on the very slow brain dynamics — which outperform learning rates achieved to date by state-of-the-art learning algorithms.
In an article published today in the journal Scientific Reports, the researchers rebuild the bridge between neuroscience and advanced artificial intelligence algorithms that has been left virtually useless for almost 70 years.
“The current scientific and technological viewpoint is that neurobiology and machine learning are two distinct disciplines that advanced independently,” said the study’s lead author, Prof. Ido Kanter, of Bar-Ilan University’s Department of Physics and Gonda (Goldschmied) Multidisciplinary Brain Research Center. “The absence of expectedly reciprocal influence is puzzling.”
“The number of neurons in a brain is less than the number of bits in a typical disc size of modern personal computers, and the computational speed of the brain is like the second hand on a clock, even slower than the first computer invented over 70 years ago,” he continued. “In addition, the brain’s learning rules are very complicated and remote from the principles of learning steps in current artificial intelligence algorithms,” added Prof. Kanter, whose research team includes Herut Uzan, Shira Sardi, Amir Goldental and Roni Vardi.
Brain dynamics do not comply with a well-defined clock synchronized for all nerve cells, since the biological scheme has to cope with asynchronous inputs, as physical reality develops. “When looking ahead one immediately observes a frame with multiple objects. For instance, while driving one observes cars, pedestrian crossings, and road signs, and can easily identify their temporal ordering and relative positions,” said Prof. Kanter. “Biological hardware (learning rules) is designed to deal with asynchronous inputs and refine their relative information.” In contrast, traditional artifical intelligence algorithms are based on synchronous inputs, hence the relative timing of different inputs constituting the same frame is typically ignored.
The new study demonstrates that ultrafast learning rates are surprisingly identical for small and large networks. Hence, say the researchers, “the disadvantage of the complicated brain’s learning scheme is actually an advantage”. Another important finding is that learning can occur without learning steps through self-adaptation according to asynchronous inputs. This type of learning-without-learning occurs in the dendrites, several terminals of each neuron, as was recently experimentally observed. In addition, network dynamics under dendritic learning are governed by weak weights which were previously deemed insignificant.
The idea of efficient deep learning algorithms based on the very slow brain’s dynamics offers an opportunity to implement a new class of advanced artificial intelligence based on fast computers. It calls for the reinitiation of the bridge from neurobiology to artifical intelligence and, as the research group concludes, “Insights of fundamental principles of our brain have to be once again at the center of future artificial intelligence”.
Learn more: The brain inspires a new type of artificial intelligence
The Latest on: Ultrafast artifical intelligence
[google_news title=”” keyword=”ultrafast artifical intelligence” num_posts=”10″ blurb_length=”0″ show_thumb=”left”]
via Google News
The Latest on: Ultrafast artifical intelligence
- Revolutionary AI device utilizes few-molecule reservoir computing for blood glucose predictionon April 26, 2024 at 10:15 am
A collaborative research team from NIMS and Tokyo University of Science has successfully developed a cutting-edge artificial intelligence (AI) device that executes brain-like information processing ...
- Smart technologies take center stage at Beijing auto showon April 25, 2024 at 1:21 pm
A product launch event for Ji Yue Automobile at the Beijing International Automotive Exhibition on April 25 Photo: Zhang Yiyi/GT. Smart technologies in the auto industry chain are ...
- A collaborative ecosystemon April 23, 2024 at 6:00 am
In high-energy physics, the relationship can be symbiotic: Industry gives researchers access to the best computing resources, while researchers give industry huge amounts of clean data for testing new ...
- Huawei and partners join forces to create a smarter and greener Singaporeon April 22, 2024 at 6:00 pm
SINGAPORE: Governments worldwide are turning to Artificial Intelligence (AI) to boost their economies. Singapore, for... The post Huawei and partners join forces to create a smarter and greener Singap ...
- Huawei empowers partners to help realise a smarter and greener Singaporeon April 22, 2024 at 1:00 am
Huawei and its partners are paving the way to enhance industrial intelligence and sustainability in Singapore.
- 2 AI Stocks That Could See Faster Growth Than NVIDIAon April 19, 2024 at 4:38 am
No stock in the S&P 500 has seen recent growth at levels approaching NVIDIA (Nasdaq: NVDA). Last quarter the company saw sales growth of 265% while profits soared an absurd 769%. Yet, a recent ...
- Business Tech Roundup: Google Workspace Gets A $10 AI Optionon April 14, 2024 at 4:00 am
Plus: Samsung will transfer data faster, Apple has a great new laptop and Jamie Dimon says AI is going to change the world.
- Ultrafast Camera Captures 156 Trillion Frames Per Secondon April 5, 2024 at 5:00 pm
INRS’s Énergie Matériaux Télécommunications Research Centre has developed a new ultrafast camera system that can capture ... disruptive technology and trends including Space, Robotics, Artificial ...
- Transporting spin information at the speed of lighton April 2, 2024 at 4:59 pm
It will also greatly benefit development of various advanced technologies on Earth, such as optical quantum communication and computation, neuromorphic computing for artificial intelligence, ultrafast ...
- Forget Nvidia: Billionaires Are Selling It and Buying These 2 Hypergrowth Artificial Intelligence (AI) Stocks Insteadon March 31, 2024 at 9:41 pm
Artificial intelligence (AI ... Though estimates vary, Nvidia's ultra-fast GPUs might account for 90% (or more) of the GPUs deployed in AI-accelerated data centers this year.
via Bing News