Moderator: Vincent Maret Panelists: Elaine Chen, Marine Gall, Erik Grab, Gilles Zancanaro
Culture is a potent force in shaping individual and group behavior, yet it has received relatively little attention in the context of financial risk management and the recent financial crisis. In this talk, Professor Lo will present a brief overview of the role of culture and ethics according to psychologists, sociologists, and economists, and then propose a specific framework for analyzing culture in the context of financial practices and institutions in which three questions are addressed: (1) What is culture?; (2) Does it matter?; and (3) Can it be changed?
Medicine presents a particular problem for creating artificial intelligence (AI), because the issues and tasks involved are surprisingly subjective. Valid and useful AI requires not only reliable, unbiased, and extensive data, but also objective definitions and intentions. Assistance is most needed in day-to-day complex decision-making that requires data synthesis and integration, tasks we now approach with clinical intuition. This process is generally accepted as representing the ‘art’ of medicine despite being riddled with cognitive biases and often based on large information gaps. Resolving the subjectivity of medicine with the objectivity required for digitization—and the secondary creation of AI—first involves resolution of a number of questions: What do we want to do? What do we need to do? What can we do?
Attempts to embed machine learning-based predictive models to make products smarter, faster, cheaper, and more personalized will dominate activity in the technology industry for the foreseeable future. Veeramachaneni and MIT researchers are proposing a paradigm shift from the current practice of creating machine learning models that requires months-long discovery, exploration and “feasibility report” generation, followed by re-engineering for deployment, in favor of a rapid 8 week long process of development, understanding, validation and deployment that can executed by developers or subject matter experts using reusable APIs.
If you're like most people, you probably believe that humans are the most intelligent animals on our planet. But there's another kind of entity that can be far smarter: groups of people. In this talk, Thomas Malone shows how groups of people working together in superminds -- like hierarchies, markets, democracies, and communities -- have been responsible for almost all human achievements in business, government, science, and beyond. Malone also shows how computers can help create more intelligent superminds simply by connecting humans to one another in a variety of ways. Artificially intelligent computers will also amplify the power of these superminds by doing increasingly complex kinds of thinking. By understanding how these collectively intelligent groups work, we can learn how to harness their genius to achieve our human goals.
This talk introduces a new generation of machine learning methods that provide state of the art performance and are very interpretable. Optimal classification (OCT) and regression (ORT) trees are introduced for prediction and prescription with and without hyperplanes. It will be shown that (a) Trees are very interpretable, (b) They can be calculated in large scale in practical times, and (c) In a large collection of real world data sets, they give comparable or better performance than random forests or boosted trees. Their prescriptive counterparts have a significant edge on interpretability and comparable or better performance than causal forests. These optimal trees with hyperplanes have at least as much modeling power as (feedforward, convolutional and recurrent) neural networks and comparable performance in a variety of real world data sets. Finally, a variety of optimal trees applications in financial services will be discussed.
This lecture will detail the creation of ultrasensitive sensors based on electronically active conjugated polymers (CPs) and carbon nanotubes (CNTs). Conceptually a single nano- or molecular-wire spanning between two electrodes would create an exceptional sensor if binding of a molecule of interest to it would block all electronic transport. Nanowire networks of CNTs modified chemically or in composites with polymers provide for a practical approximation to the single nanowire scheme. Creating chemiresistive and FET based sensors that have selectivity and accuracy requires the development of new methods. I will discuss covalent and non-covalent medication of CNTs with groups that impart selectivity for target analytes. This can involve reactions at the CNT sidewalls and rapping of the CNTs with CPs. Highly specific chemical processes orthogonal responses can be produced for mixtures of analytes through careful integration of chemical functionality. A prevailing problem in all chemiresistive schemes, which is seldom highlighted by researchers, is drift. This is intrinsic for systems that need to interface with their surroundings and changes in the position of ions of small changes in the organization of the CNTs relative to each other, the electrodes, or their surroundings can change the base resistance. I will detail different methods designed to lock the CNT networks in place. These novel compositions are also designed to accommodate functionality and I will demonstrate how we can use a diversity of transition metals to create selective responses to gases. We will also show that this scheme creates CNT networks that are robust enough for solution sensing and demonstrate chemiresistive based glucose sensing. I will also briefly discuss the successful use of CNT based gas sensors for the detection of ethylene and other gases relevant to agricultural and food production/storage/transportation and integrated systems that increase production, manage inventories, and minimize losses.
In June of this year, MIT will complete the construction of the MIT.nano, an 18,000 sq.m. facility in the middle of the campus for MIT’s nanotechnology-related activities. This facility is, in effect, an acknowledgement of the nanotech’s importance today. Within MIT.nano, SENSE.nano is its first Center of Excellence. The impetus for SENSE.nano is the recognition that novel sensors and sensing systems are bound to provide previously unimaginable insight into the condition of individuals, as well as the built and natural world, to positively impact people, machines, and environment. Advances in nano-sciences and nano-technologies, pursued by many researchers at MIT, now offer unprecedented opportunities to realize designs for, and at-scale manufacturing of, unique sensors and sensing systems, while leveraging data-science and IoT infrastructure.
Moderator: Scott Kirsner, Editor & Co-Founder, Innovation Leader Panelists:
Moderator: Leon Sandler, Executive Director, MIT Deshpande Center for Technological Innovation Panelists: