Despite the widespread adoption of endoscopic devices for several cancer screening procedures, manual control of these devices still remains challenging for clinicians, leading to several critical issues such as increased workload, fatigue, and distractions. To address these issues, in this paper, we introduce the design and development of an intuitive, modular, and easily installable mechatronic framework. This framework includes (i) a novel nested collet-chuck gripping mechanism that can readily be integrated and assembled with the existing endoscopic devices and control their bending degrees-of-freedom (DoFs); (ii) a feeder mechanism that can control the insertion/retraction DoF of a colonoscope, and (iii) a complementary and intuitive user interface that enables simultaneous control of all DoFs during the procedure. To analyze the design of the proposed mechanisms, we also introduce a mathematical modeling approach and a design space for optimal selection of the parameters involved in the design of gripping and feeder mechanisms. Our simulation and experimental studies thoroughly demonstrate the performance of the proposed mathematical modeling and robotic framework.

New York-based software startup Alkymi recently raised $5 million in a seed round to help financial institutions and other enterprise clients automate back-office workflow. The company, part of INV Fintech's current startup class, calls its automation solution Data Inbox, and uses machine learning that can be applied to various parts of everyday operations, including finance, human resources, sales and IT. For example, by leveraging Alkymi's Data Inbox, a bank could automatically extract and structure data from emails and documents sent by a business client applying for a loan, thus avoiding the need to process that documentation manually. The AI solution works with the enterprise's email platform, file-organization application and document-sharing application used on the job. Alkymi's standard API then connects the data in the applications and emails to the Data Inbox. According to Harald Collet, Cofounder and CEO of Alkymi, businesses struggle to manage data and documents, which is often a repetitive task that gets in the way of higher value tasks.

Every week, my team at Invector Labs publishes a newsletter that covers the most recent developments in AI research and technology. You can find this week's issue below. You can sign up for it below. Francois Collet is a well-known name in the artificial intelligence(AI) community. A scientist in Google's AI unit, Mr. Collet rose to prominence with the creation of Keras, one of the most popular deep learning frameworks in the market.

Every once in a while, you encounter a research paper that is so simple and yet profound and brilliant that makes you wish you would have written it yourself. That's how I felt when I read Francois Collet's On the Measure of Intelligence. The paper resonated with me not only because it confronts some of the key philosophical and technical challenges about artificial intelligence(AI) systems that I have been spending some time on but also because it does so in such an elegant way that is hard to argue with. Mr. Collet's thesis is remarkably simple: for AI systems to reach its potential, we need quantitative and actionable methods that measure intelligence in a way that shows similarities with human cognition. Mr. Collet's thesis might seem contradictory given the recent achievements of AI systems.