In the next five years, autonomous vehicle technology may finally blossom and enter our lives. The first applications of intelligent self-driving vehicles may embark on highways, campuses, and warehouses. Bottlecap-size consumer drones may roam around, filming the next big hit video on social media. What are some of the technical challenges and technological enablers? How will the new technology impact new products, markets, businesses, and ultimately our lives? Professor Sertac Karaman's research is enabling new ways of designing autonomous vehicles with the help of rigorous, mathematical thinking that leads to valuable insights.
CATALOG The world will generate 160 zettabytes of data in 2025. That’s more bytes than there are stars in the observable universe. Conventional storage media like flash-drives and hard-drives do not have the longevity, data density, or cost efficiency to meet the global demand. CATALOG is building the world’s first DNA-based platform for massive digital data storage.
Interpretable AI The company is bringing interpretability to machine learning and artificial intelligence and was co-founded by Professor Dimitris Bertsimas of MIT Sloan School of Management’s Operations Research Center (ORC).
Osaro Advanced imaging AI for robotics that can identify objects others cannot.
Digital Health mobile apps and connected medical devices are rapidly changing how patients learn, monitor, diagnose and treat disease. Even in these early days of the digital transformation of healthcare, connected medical devices and digital services are winning reimbursement as “digiceuticals” by payors and insurers. However, the critical need going forward is how to measure, compare and prove these new tools and digital biomarkers are safe, effective and valuable at scale, not just in the USA but globally, across geographies, cultures and health systems.
As a strategy to save the cost of expensive substrates in semiconductor processing, the technique called “layer-transfer” has been developed. In order to achieve real cost-reduction via the “layer-transfer”, the following needs to be insured: (1) Reusability of the expensive substrate, (2) Minimal substrate refurbishment step after the layer release, (3) Fast release rate, and (4) Precise control of a released interface. Although a number of layer transfer methods have been developed including chemical lift-off, optical lift-off, and mechanical lift-off, none of those three methods fully satisfies conditions listed above. In this talk, we will discuss our recent development in a “graphene-based layer-transfer” process that could fully satisfy the above requirements, where epitaxial graphene can serve as a universal seed layer to grow single-crystalline GaN, III-V, II-VI and IV semiconductor films and a release layer that allows precise and repeatable release at the graphene surface. We will further discuss about cost-effective, defect-free heterointergration of semiconductors using graphene-based layer transfers.
Lastly, I will introduce our new research activities in developing advanced RRAM devices. Resistive switching devices have attracted tremendous attention due to their high endurance, sub-nanosecond switching, long retention, scalability, low power consumption, and CMOS compatibility. RRAMs have also emerged as a promising candidate for non-Von Neumann computing architectures based on neuromorphic and machine learning systems to deal with “big data” problems such as pattern recognition from large amounts of data sets. However, currently reported RRAM devices have not shown uniform switching behaviors across the devices with high on-off ratio which holds up commercialization of RRAM-based data storages as well as demonstration of large-scale neuromorphic functions. Recently, we redesigned RRAM devices and this new device structure exhibits most of functions required for large-array memories and neuromorphic computing, which are (1) excellent retention with high endurance, (2) excellent device uniformity, (3) high on/off current ratio, and (4) current suppression in low voltage regime. I will discuss about the characterization results of this new RRAM device.
Platform firms are coming and will impact you in ways that you cannot control. The successful business models of the last generation are no longer sufficient and corporations must adapt to the multi-sided markets that are the hallmark of the platform business model. How quickly an industry adapts to and utilizes platforms depends on regulation, cost, and risk. Join Geoff Parker to explore why platform firms are a threat, how they will affect your business, and how you can transform your business model to compete.