Ronen, a 16-year veteran at IBM Research in Haifa, Israel, focuses on the stumbles of chatbots. Their efforts extend from work process automation to the design of ever more intelligent chatbots to the discovery of new, more effective antibiotics. March 9, 2020 | Written by: IBM Research Editorial Staff. Every once in awhile an idea comes along that’s so good it makes you wonder why it took so long for someone to think of it. IBM researchers have developed a series of quantum algorithms that show how entanglement can improve AI classification accuracy. A global team of researchers from MIT, National Taiwan University and the MIT-IBM Watson AI Lab want to change that. IBM and AMD have signed a multi-year joint development agreement to enhance and extend the security and Artificial Intelligence (AI) offerings of both companies. She zeros in on incidents where bots get confused and hand a query over to a human. The field looked promising for over a decade, with the US government in the 1960s pouring billions into symbolic AI research. Deep learning may have revolutionized AI – boosting progress in computer vision and natural language processing and impacting nearly every industry. In their experiment they described using HEIDL to improve AI’s ability to interpret the dense legal language found in contracts. It’s a dual job that involves education of human beings as well as machines. Yunyao enrolled in Tsinghua University in Beijing, where she ranked at the top of her class and received a dual undergraduate degree in automation and economics. At IBM Research’s recent “The Path to More Flexible AI” virtual roundtable, a panel of MIT and IBM experts discussed some of the biggest obstacles they face in developing artificial intelligence that can perform optimally in real-world situations. “I’m a full-time working mom,” Ronen says. Each component -- such as the pastry -- requires a specific set of instructions. IBM and MIT researchers find a new way to prevent deep learning hacks. Positive experiences with mentors in school and as a young professional have inspired Yunyao to take on that role for a new generation of women computer scientists. Yunyao is leading a group investigating how to apply this approach to help AI better interact with people through natural language. With IBM researchers interest AI and security, they were determined to create such an attack as part of its countermeasure research. Put the power of AI in your command line with Command Line AI (CLAI). Led by Ji Lin – a PhD student in Professor Song Han’s lab at MIT’s Electrical Engineering & Computer Science (EECS) – their recent study could help put more AI into a microcontroller than ever before. “She left her job as a teacher and sacrificed to raise us.” Backed by her supportive family, Agarwal went to university in New Delhi and later received her master’s in computer science from the Indraprastha Institute of Information Technology (IIT Dehli). IBM unleashes AI on two space problems: How to map all the junk in Earth's orbit, and how to put more up there Open-source projects aim to give researchers, startups a helping hand. But even deep learning isn’t immune to hacking. As she sees it, her job is to advance this educational process for AI. The IBM 702: a computer used by the first generation of AI researchers. IBM-MIT launch new AI challenge to push the limits of object recognition models, Coders worldwide help computers understand natural language, IBM and MIT researchers find a new way to prevent deep learning hacks, The potential benefits of AI for breast cancer detection, Moving Beyond the Lab: IBM Research Powers Pipeline of AI Advances for the Enterprise. The WWN partners with senior management, human resources and other diversity network groups to promote programs in mentoring, networking, diversity, knowledge sharing and recruiting. D eep learning may have revolutionized AI — boosting progress in computer vision and natural language processing and impacting nearly every industry. Deep learning may have revolutionized AI – boosting progress in computer vision and natural language processing and impacting nearly every industry. Every time one of them falters—failing to understand a question or botching an answer—Ronnen sees a teaching opportunity. Customers are able to get quick answers without waiting on help lines, and human agents are able to devote more time to more complex questions. “That’s the beauty of [having a] human in the loop.”. Katyanna Quach Fri 2 Oct 2020 // 13:45 UTC. What are the steps that they’re taking, and how complicated are they?” It’s through this process, she hopes, that she will contribute to AI systems that give back to society. We're building tools to help you ensure that it is. Try your hand at testing the … “We don’t just want predictions from AI, we want to see if a model can explain why something is, or isn’t, going to work,” adds Payel, who has published more than 40 peer-reviewed articles and is an adjunct associate professor in Columbia University’s Department of Applied Physics and Applied Mathematics (APAM). “Now, I want to share my experience with other people, and help give young researchers some visibility into their own future,” she says. Some of her other Natural Language Processing (NLP) research is aimed at helping train expansive AI systems using unstructured data, “a service that hasn’t been available to enterprises in a scalable manner,” she says. How do you increase the chance of scientific success? The Open Source python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence. All four of these researchers are women—a constituency that has helped lead IBM Research in the crucial task of removing or mitigating bias from AI algorithms—a key for fairness and gender equity. The AI Fairness 360 toolkit (AIF360) is an open source software toolkit that can help detect and remove bias in machine learning models. Applying trained models to new challenges requires an immense amount of new data training, and time. IBM and MIT to pursue joint research in artificial intelligence, establish new MIT-IBM Watson AI Lab 09/07/2017 - MIT News IBM and MIT are building a 100-person artificial intelligence research lab and business incubator Growing up in Kolkata—the capital of the Indian state of West Bengal—the idea of girls pursuing any career, much less one in math or science, was not widely accepted. She specializes in AI. The more efficient method, however, is to engineer the system itself to learn from the human, and adjust automatically. The MIT-IBM Watson AI Lab membership program is forging a new model for R&D. The HEIDL (Human-in-the-loop linguistic Expressions wIth Deep Learning) model they introduced last year proposes to bring expert humans into the AI loop twice: first to label training data, then to analyze and improve AI models. “We have to identify who are the actors involved,” she says “There’s a finite set of them. IBM has maintained a research laboratory in Switzerland since 1956. Trust and security should be baked into
the core of any AI we put out into the world. In short, AI must have fluid intelligence—
and that's exactly what AI research teams are building. IBM’s customers, Ronen says, use Watson Assistant to improve service. “That motivated me because, in a sense, she had to compromise her career because of her family.” Fortunately, Payel had no shortage of support from her immediate family, in particular her parents and an uncle who taught chemistry. In 2017, she joined IBM Research in New Delhi. “In that sense,” she says, “the human is teaching the bot.”. The second paper is the first work describing a methodology to create AI documentation and explicitly includes FactSheet consumers and producers in FactSheet requirements gathering. IBM noted that its Spectrum Computing team, based out of Canada Lab, has contributed “significantly” to Oríon’s code base. As AI becomes more prominent, so do fears that the technology will put people out of work. “There are a lot of things that data alone cannot tell you or that are more easily learned by asking someone,” says Yunyao, a Principal Research Staff Member and Senior Research Manager for Scalable Knowledge Intelligence. Her interest in seeing rapid, more tangible results from research led her to IBM Research in 2007. “Fortunately, as a student I found a wonderful mentor—Mary Fernandez, a researcher at AT&T Research. IBM Research papers accepted to NeurIPS 2020, Verifiably Safe Exploration for End-to-End Reinforcement Learning, Accurate deep neural network inference using computational phase-change memory, Towards a Homomorphic Machine Learning Big Data Pipeline for the Financial Services Sector. Yunyao and her colleagues are working to advance last year’s research by better automating data labeling and improving HEIDL’s ability to interpret words not included in training dictionaries. The system will grow more robust, she says, as it processes the feedback and adjusts its predictions. “I owe my career to my mother,” she says. At the same time, they identify steps in the process that can be automated. A team of researchers from IBM and Pfizer have designed an AI model that uses small samples of language data (obtained from clinical verbal cognitive tests) to help predict with 71 percent accuracy the eventual onset of Alzheimer's disease within healthy people. They have three children. IBM’s human-in-the-loop research investigates how best to combine human and machine intelligence to train, tune and test AI models. IBM Research – Zurich is one of IBM's 12 global research labs. Train a verifiably safe drone for dynamic environments. Her specialty was the exploding field of social search and social network analysis. Researchers from IBM and AMD are working on projects around confidential computing in the Cloud and accelerating their machine learning capabilities. By Larry Greenemeier. Gopalakrishnan, along with other IBM researchers Naigang Wang, Jungwook Choi, Daniel Brand, and Chia-Yu Chen, achieved an AI milestone by introducing the … One of her favorites books growing up was Jules Verne’s Around the World in Eighty Days. During IBM’s virtual AI Summit this week, the company announced updates across its Watson family of products in the areas of language, explainability, and workplace automation. COVID-19 knows no borders and has resulted in around 75,896 deaths as of writing. In addition to her work for social good, Agarwal develops AI systems for business processes. Both IBM Research’s offices in Kenya and South Africa and Google’s AI lab in Ghana share the same mission as their parent organizations: to pursue fundamental and cutting-edge research. Working with a non-profit called EmancipAction, she is developing a system to analyze resumes, questionnaires and video interviews to pinpoint the most promising candidates to be trained as counselors for trafficking victims. “We are developing machine learning algorithms that can combine learning from not only data, but also from physics principles, in order to design new materials and drugs,” says Payel, a Research Staff Scientist and Manager of Trusting AI research. For Inbal Ronen, mistakes are opportunities. She stayed there early in her career, working at several startups. She and her team zero in on these bottlenecks, studying the various tasks involved. IBM’s AI Fact Sheets is one of those ideas. NLP essentially helps machines to read and write, and thus learn to learn and share information and knowledge with people.”, Yunyao Li, Principal Research Staff Member and Senior Research Manager for Scalable Knowledge Intelligence, IBM Research, with her son. This post is presented by The Watson Women’s Network, a community of technical staff, primarily based at the T.J. Watson Research Center, that seeks to encourage a workplace environment that advances the professional effectiveness, individual growth, recognition, and advancement of all women at IBM Research. Researchers are using AI to predict Alzheimer's disease seven years before clinical diagnosis. Yunyao has benefitted from several mentors at IBM, as well, including Almaden researcher Rajasekar Krishnamurthy, former IBM Fellow Shivakumar Vaithyanathan and Laura Haas, who retired from IBM Research in 2017 after 36 years. CLAI helps you navigate the command line more efficiently, removing roadblocks and finding missing dependencies. 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