ThinkingNode - Reasoning Computing to handle Complex Knowledge instead of Big Data
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https://www.thinkingnode.com/ Humans are very good at solving problems and use two main cognitive approaches: Pattern Recognition (right brain) to perceive and Reasoning(left brain) to analyze. Unfortunately, we cannot scale our thinking to handle the ever-increasing volumes of both data and knowledge. Human-level cognition has become a bottleneck for humanity’s progress.
Today, the AI market is mainly based on companies that have been focusing on scaling Pattern Recognition using Machine Learning and the results have been impressive on how it has been possible to extract from Big Data new patterns based on correlations to build statistical predictive systems. However, in order to solve and to understand, and not just to predict the outputs for hard analytic problems, such as cancer therapies, immune system deficiencies, and medical diagnosis…, scaling reasoning is an absolute necessity 1) to process highly combinatorial Complex Knowledge, 2) to make sense of new knowledge that are continuously generated by both human experts and Machine Learning, and 3) to be able to infer new knowledge from existing knowledge, which is what human thinking does very well but we can only process 5-9 concepts at the same time. Reasoning Computing can provide the exponential thinking capability. Until now, Reasoning Computing systems have yet to see their "new surge" as neural networks have. |
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- Date: 13 Feb 2018
- Time: 06:30 PM to 08:30 PM
- All times are (GMT-08:00) US/Pacific
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- 10155 Pacific Heights Blvd,
- San Diego, California
- United States 92121
- Building: Qualcomm, Building AZ Multipurpose room A/B/C
- Starts 23 January 2018 06:00 PM
- Ends 13 February 2018 08:30 PM
- All times are (GMT-08:00) US/Pacific
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Speakers
Dr. Khai M Pham, PhD, MD, CEO, Thinkingnode
Thinking Node - Reasoning Computing to handle Complex Knowledge instead of Big Data
ttps://www.thinkingnode.com/
Humans use two main cognitive approaches to perceive and analyze problems: Pattern Recognition (left brain) and Problem Solving (right brain). In an age of ever-increasing volumes of both data and complex knowledge human cognition has become a bottleneck for humanity’s progress.
Interestingly, AI has two main schools based on the same complimentary cognitive approaches: Pattern Recognition (Data Mining/Machine Learning using Big Data) and Problem Solving (Reasoning Computing using Complex Knowledge). Today, AI companies have been focusing on Pattern Recognition systems and the results have been impressive. However, it is well known that these systems are “black boxes” and this is a major limitation when explanation is essential to justify the results and to improve upon a system. More importantly, solving the most challenging problems humanity is facing requires reasoning through combinations of Complex Knowledge where Big Data correlation analysis is not relevant or possible alone.
This is why, complementary to Pattern Recognition, Reasoning Computing is so needed and is the next big step for the AI market because it can solve problems where Pattern Recognition systems are not designed for or because it can process the output of these systems by combining knowledge contexts to provide meaningful results. Until now, Reasoning Computing systems have been in the deceptive phase for decades and have yet to see their “second surge” as neural networks have.
Biography:
A multi-disciplinary (Medicine and Artificial Intelligence +25 y) entrepreneur in Silicon Valley for 15 years, Dr. Khai Minh Pham is a serial entrepreneur and technology innovator.
In 1995 he pioneered Data Mining as the founder & CEO of DataMind, a leading data mining company using an Intelligent Agent Technology. Benchmarked by Andersen Consulting Research as the best technology in its field, it was used by major financial institutions, marketing centers, and medical manufacturers, and Bank of America acquired the patent in 2012. Later renamed RightPoint, DataMind was acquired in 2000 by E.piphany for US$400 Million, still one of the highest acquisitions for an AI-based company.
In 2000, Dr. Pham was a pioneer in social networking as the founder & CEO of Easyplanet, providing the first Community Browser (including video phone, favorites sharing, content. etc.) to help strong brands maintain their relationship with their customers, while harnessing data mining to push content and one-to-one ads. A major partnership was established in India as the first large scale pilot when the financial crash happened in 2008.
Today, with ThinkingNode, Dr. Pham is pioneering in Reasoning Computing. He believes that a breakthrough for humanity in solving major challenges is to overcome human linear reasoning to empower human thinking allowing us to apprehend highly complex systems.
Khai Minh holds an M.D. and a Ph.D. in AI both from University Pierre and Marie Curie in Paris. Author of several scientific papers, received international grants (DEC research labs), taught AI at LISH-CNRS (eq. of the NFS in US), received an entrepreneur award from BP bank, was on the committee of Silicon French (a Silicon Valley network), was speaker at DBF, is EIR/Mentor at CONNECT (notorious startup accelerator in San Diego), and part of the jury for the "2016 Most Innovative New Product Awards" in Life Science and Robotics.