Data & AI - Elisify: Financial data on demand - Forge.AI: Unstructured text to data for machine learning - Nara Logics: AI for product recommendation and decision support - Posh: Conversation AI for customer service & helpdesk - Profit Isle: Data analytics to accelerate profit
Security & Platform Tech - Duality: Homomorphic encryption of data - Canopy: Personalization without losing data privacy - Silverthread: Improving software health and economics - CATALOG: DNA for data storage & computation - Tamr: Data unification powered by human-guided machine learning
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 talk (with apologies to David Letterman) will present the top ten big data mistakes witnessed in the last decade or so. These range from “not planning to move everything to the cloud” to “believing that a data lake will solve all your problems.” Also included is an eleventh blunder, which effectively means “working for a company that is not focused on avoiding these blunders.”
In the early days of the Internet, technical innovation shaped its future. Today, issues of economics, market dynamics, incentives, and some fundamental aspects of networked systems shape the future. This talk will summarize eleven forces that are shaping the future of the Internet, and make an argument that we are at a point of inflection in the character of the Internet, as profound as the change in the 1990’s when the Internet was commercialized.
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We are entering a new world of very effective, but very expensive, drug treatments for rare disease. How should society think about pricing these treatments? Are there financial models that can help spread the costs and make them more affordable? And what does this suggest for a new role for government-financed Research and Development?
The nano age is upon us. With nanoscale advancements we are reimagining health and life sciences, energy, computing, information technology, manufacturing, and quantum science. Nano is not a specific technology. It does not belong to a particular industry or discipline, it is, rather, a revolutionary way of understanding and working with matter, and it is the key to launching the next innovation age…the nano age.
SMEs are the backbone of most economies and employ approximately 60 percent of the working population in OECD countries. However, these businesses often struggle the most to access financing, oftentimes, relying on friends and family to help them flourish and thrive by lending money when others do not. We have created Trust·u to offer a solution to this. Trust·u is an internal venturing effort from BBVA, positioned to address innovation opportunities in an agile manner by mimicking startups. We utilize a digital platform to enable rapid on-boarding and underwriting, combining social elements with financial data, to grant small businesses access to financing based on a new risk assessment model, which takes full advantage of ML techniques and new data sources.
Redefining Small Business Lending through ML and Social Physics.
This lecture will detail the creation of ultrasensitive sensors based on electronically active conjugated polymers (CPs) and carbon nanotubes (CNTs). A central concept that 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. The use of molecular electronic circuits to give signal gain is not limited to electrical transport and CP-based fluorescent sensors can provide ultratrace detection of chemical vapors via amplification resulting from exciton migration. Nanowire networks of CNTs provide for a practical approximation to the single nanowire scheme. These methods include abrasion deposition and selectivity is generated by covalent and/or non-covalent binding selectors/receptors to the carbon nanotubes. Sensors for a variety of materials and cross-reactive sensor arrays will be described. The use of carbon nanotube based gas sensors for the detection of ethylene and other gases relevant to agricultural and food production/storage/transportation are being specifically targeted and can be used to create systems that increase production, manage inventories, and minimize losses.
The impetus for the SENSE.nano is the recognition that novel sensors and sensing system are bound to provide previously unimaginable insight into the condition of individuals, as well as built and natural world, to positively impact people, machines, and environment. Advances in nano-sciences and nano-technologies, pursued by many 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.