In this fascinating interview from Psychology Today, Dr. Kira Radinsky, Technion alumna and Co-founder, Chairwoman, and Chief Technology Officer of Diagnostic Robotics, shares her views on the present and future of Artificial Intelligence (A.I.). Diagnostic Robotics is a health care A.I. system with predictive analytics.
Dr. Radinsky explains: “I think the best way to predict the future is to create it. One of the things that we are doing right now is identifying the patterns, and when the patterns start, try to predict the next step. So, it can predict things that have a pattern. Random things? It’s a philosophical question. Do we even have random things? Or is it part of a pattern that we don’t have data for? So, if you believe there is no random thing and everything has a pattern, then AI can predict the future. We just need more data for that.”
In a study led by Professor Shulamit Levenberg, paraplegic rats were able to walk again after receiving stem cell therapy. After just three weeks, 42% of the rodents improved their ability to walk and support their weight, and some 75% of the animals were able to respond to stimuli on their back legs after being treated. This research has promising implications for future approaches to treat people with spinal cord injuries.
Prof. Levenberg is dean of the Technion Faculty of Biomedical Engineering, and holder of the Stan and Sylvia Shirvan Chair in Cancer and Life Sciences.
‘Hardware neural network’ to make Artificial Intelligence tech faster, cheaper
Researchers at the Technion and TowerJazz have developed a revolutionary technology that can turn TowerJazz’s commercial flash memory components into memristors—devices that contain both memory and computing power. The technology, which was inspired by the operation of the human brain, significantly accelerates the operation of artificial intelligence (AI) algorithms.
Published in the Nature Electronics journal, the research was led by doctoral student Loai Danial and Professor Shahar Kvatinsky of the Andrew & Erna Viterbi Faculty of Electrical Engineering at the Technion, in collaboration with Prof. Yakov Roizin and Dr. Evgeny Pikhay from TowerJazz and Prof. Ramez Daniel of the Faculty of Biomedical Engineering at the Technion.
From the outset, the ability of computers to solve computational problems has been superior to that of humans. Yet for decades, when it came to identifying images, classifying image attributes and making decisions, computers lagged behind humans. In recent years, artificial intelligence has begun to narrow this gap and has managed to carry out complex operations by means of training based on examples. For the past few decades, vast resources have been devoted to developing artificial intelligence on the software level. This investment has generated a quantum leap in AI effectiveness in many and varied fields, among them medicine, intelligent transportation, robotics and agriculture.
Artificial intelligence is fueled by data, and specifically by extremely large data sets known as big data. For this reason, the major breakthrough in the field of artificial intelligence had to “wait” for dramatic improvements in computing power. Yet hardware lagged behind these rapid developments in software performance, such that the development of hardware that would meet the demands of AI software was delayed for years. Such hardware must work well in terms of speed, low power demand, accuracy, area and cost. These requirements are very difficult to satisfy with the traditional hardware model based on digital computation.
The digital model limits hardware performance in two main contexts: 1) Digital hardware has difficulty performing many operations in parallel, for it was originally intended to perform a relatively small number of operations. 2) This type of hardware can provide great accuracy only at the cost of extremely high energy and time consumption. As a result, the researchers say innovative hardware is needed that will meet the needs of the artificial intelligence era.
According to Prof. Kvatinsky: “One of the major challenges that AI poses to hardware engineers is how to implement complex algorithms that require a) storage of massive amounts of data in the computer memory, b) rapid retrieval from memory, c) performing many computations in parallel, and d) high accuracy. Standard digital platforms hardware (processors) is not suited for this for the reasons mentioned above.”
This is the background for the new technology described in the article published in Nature Electronics. “Our technology transforms hardware that is digital in nature into a neuromorphic platform—an analog infrastructure of sorts that resembles the human brain,” said Prof. Kvatinsky. “Just as the brain can perform millions of operations in parallel, our hardware is also capable of performing many operations in parallel, thus accelerating all associated operations.”
Doctoral student Loai Danial goes on to explain: “I am personally interested in neuromorphic computations, both as a computer engineering student and as someone who lost his father to a rare neurological disease. The brain has always served as an inspiration for computational systems, and my challenge is to use engineering tools to understand the computational mechanism of brain operations. In the current research we showed that an electrical chip based on standard commercial technology has two critical abilities: associative memory that, like the brain, operates based on features rather than index searching, and the ability to learn.”
Associative memory, which is familiar to us from human thought, means, for example, that when we see eyes we do not search some clause in an index of items to find a match for an eye but rather identify the eye associatively. This mechanism is rapid, efficient and energy-saving. Moreover, as with the brain, the system’s ability to learn improves as the links between the synapses and the nerve cells change and are updated.
According to Prof. Roizin of TowerJazz: “The new technology is easy to implement and transforms TowerJazz’s transistors, originally designed to store data only, into memristors—units that contain not only memory but also computing ability. Because the memristors are situated on existing TowerJazz transistors, they immediately interface with all the devices the transistors work with. The new technology has been tested under real conditions, demonstrating that it can be implemented in building neural hardware networks, thus significantly improving the performance of commercial artificial intelligence systems. Like the brain, the improved system excels in its ability to store data over the long term and in its very low energy consumption.”
According to Prof. Ramez Daniel, formerly an electrical engineer at TowerJazz and now a member of the Technion Faculty of Biomedical Engineering: “The computing power of the improved device stems from its ability to function in the sub-conduction area, or to put it more simply, in a way that resembles natural biological mechanisms. As a result, we have achieved high efficiency with low output, similar to mechanisms that developed in nature over billions of years of evolution.”
Technion researchers Eric Herbelin, Nicolas Wainstein, Vasu Gupta and Nimrod Wald from Prof. Kvatinsky’s research group participated in the research.
This research was supported by the Planning and Budgeting Committee (PBC), the KAMIN grant from the Israel Innovation Authority, the Andrew Viterbi and Erna Finci Viterbi Scholarship for Graduate Students and the European Research Council (ERC) starting grant. Recently, Loai Danial presented this research at the Nature Conference in China and was awarded the prize for the best paper award at the conference.
OncoHost combines life-science research and advanced machine-learning technology to develop personalized strategies to maximize the success of cancer therapy. By analyzing the patient’s proteins, the company aims to understand patients’ unique response to therapy and overcome resistance to therapy, one of the major obstacles in clinical oncology.
The company was founded in 2017 following more than a decade of academic research led by chief scientific adviser Professor Yuval Shaked, who also serves as the head of the Technion Integrated Cancer Center.
“There is a pressing need to advance the development of novel therapeutic strategies and rationally-based combination therapies. These capabilities come at the ideal time to address the current challenges of immunotherapy for cancer,” stated Professor Shaked.
Professional Highlights: After the Yom Kippur war, I started in the petro-chemical industry in Israel and then emigrated to Canada in 1977. I spent over 25 years with Shell Canada, serving in a number of senior management positions, including Vice President, Operations and President, Albian Sands Energy.
Q & A
What were some of the highlights of your Technion education?
The level of education at the Technion is extremely high, and chemical engineering is a very difficult and demanding program. We were challenged to achieve at the highest levels. We were fortunate to learn from world renowned faculty; the professors and assistants were very committed and helpful to the students. I also made many good friends during my time in university.
How has your Technion education and experience prepared you for your career and contributed to your professional success?
If I can name one thing that I learned at the Technion, beyond of course the technical knowledge, it’s that they teach you how to think…think outside the box, think about issues, and to persevere when you are facing a challenge.
What makes you most proud to be a Technion Alumnus?
In the world of academia, the Technion is on an elite level, there is a huge amount of recognition and respect for the school. To have a university in a small country reaching this level of success in such a short period is incredible. The story of the Technion is the story of Israel, and we must be proud and support it.
What is your message to anyone giving back to Technion or considering doing so?
My message to alumni is: You graduated from one of the top schools in the world and it is important to give back to support the school so that others can benefit from the education and the opportunity. It can be through volunteering or donating at any level. I am proud to go back to Technion each year as a guest professor to teach management and leadership to chemical engineering students, a course I designed based on my professional experience.
Researchers at the Technion, led by Professor Ester Segal of the Faculty of Biotechnology and Food Engineering, and researchers at Bar Ilan University, have developed new technology for transporting drugs within silicon nanostructures to the brain.
These nanostructures release an essential protein, which can inhibit the development of Alzheimer’s disease, and provide targeted delivery in the brain with the use of a “gene gun.” The research was conducted with the support of the Russell Berrie Nanotechnology Institute at the Technion.
As we count down to the end of 2019, we take you on a trip through some of the most popular news and innovations of the year according to you. In case you missed it – here are the top 10 stories from our Facebook page featuring Technion Researchers and Alumni!
#1 Customized Antibiotics
Customized Antibiotics are new to the scene but making waves in the industry. Technion researchers have been busy pioneering how to use them for prevention and healing!
Charging a car in the time it takes to brew a cup of coffee? Technion alumnus Doron Meyersdorf is StoreDot Ltd.’s CEO and Co-Founder. They are ready to revolutionize electric vehicles. Production will likely start in 2022.
Nano-ghost technology is a new and versatile drug delivery platform to fight cancer and is the only drug delivery system of its kind in the world. Nano-ghosts have proven effective in the lab and Professor Marcelle Machluf now hopes to move to human clinical trials.
Professor Dedi Meiri of Technion-Israel Institute of Technology’s Laboratory of Cancer Biology and Cannabinoid Research in the Faculty of Biology discusses his research.
Prof. Meiri’s laboratory is the only one in the world that has the ability to analyze all the active compounds in the cannabis plant and his research team is examining over 900 different types of cannabis and exploring what strains are effective for addressing different conditions and types of disease.
Their aim is to effectively use cannabis to both improve quality of life and to treat specific illnesses.
For those who fear flying, Technion technology offers reassurance of a safe flight! Technion professors and students from the Faculty of Aerospace Engineering have developed and successfully tested software that monitors a plane’s trajectory to determine if it’s losing altitude and what physical obstacles might be in its way. It also guides the plane to the best alternative landing strip.
The team was led by Professor Nahum Shimkin and Dr. Aharon Bar-Gill, both of the Viterbi Faculty of Electrical Engineering at the Technion. Prof. Shimkin is the dean of the Faculty.