Position Description: Lenovo is venturing out into many new emerging businesses to position for growth into the future. We are looking to hire an Engineering Manager for the ML/AI Development team based out of Lenovo's Morrisville, NC HQ. We're looking for highly motivated individuals with passion for software development management to drive the next generation in technology, including information retrieval, data management, distributed computing, large-scale system design, and data storage, artificial intelligence; the list goes on and is growing every day. You will help build learning algorithms leveraging data sets consisting of user actions, collected from millions of PCs and other computing devices, per day to model, analyze, and predict user behaviors. While some of our algorithms run on client devices, others require large clusters on our cloud infrastructure.

These days you'll be hard-pressed to find someone who hasn't interrogated Siri (or Alexa), enjoyed the movie Netflix suggested, or fallen victim to purchasing that additional item Amazon recommended--all of which are only possible due to artificial intelligence. AI has been a field of study as far back as the 1950s, but advances have skyrocketed in recent years. These days AI is everywhere and has increasingly become part of all of our everyday lives. Thanks to AI, once tedious tasks are now simple, single-click activities. And as technology becomes even more pervasive, it will only continue to impact our personal and professional lives.

India's higher education sector has supplied some of the world's best talent. The CEOs of some of the biggest Fortune 500 companies--Microsoft, Google, Mastercard, and Adobe--are a product of the Indian higher education system. The landscape has also expanded over the past decade--from 436 universities in 2009–10 to 903 in 2017–18 and from 26,000 colleges to over 39,000.1 Student enrolment, at 36.6 million, is the third-largest in the world, next to China and the United States.2 Besides, India is already in the middle of the "demographic dividend" with a surge in its younger and working-age population, which is estimated to become the world's largest by 2030.3 India is expected to account for about 20 percent of the total young talent pool supplied by the non–Organisation for Economic Cooperation and Development (OECD) G-20 countries.4

Newswise -- According to a release issued earlier this month by the Los Alamos National Laboratory (LANL), researchers have developed a machine learning approach called transfer learning that lets them model novel materials by learning from data collected about millions of other compounds. The new approach can be applied to new molecules in milliseconds, enabling research into a far greater number of compounds over much longer timescales. The new technique, called ANI-1ccx potential, promises to advance the capabilities of researchers in many fields and improve the accuracy of machine learning-based potentials in future studies of metal alloys and detonation physics. "Our quantum mechanical calculations to create ANI-1ccx potential were conducted over two years with time split on the Comet supercomputer at the San Diego Supercomputer Center and the Badger supercomputer at LANL," said Olexandr Isayev, paper author and a pharmacy professor at the University of North Carolina at Chapel Hill. "We chose these two supercomputers to train our neural networks as there are few machines that can run these – due to the high memory and core requirements."

Automated Machine Learning (AutoML) has received significant interest recently. We believe that the right automation would bring significant value and dramatically shorten time-to-value for data science teams. Databricks is automating the Data Science and Machine Learning process through a combination of product offerings, partnerships, and custom solutions. This talk will focus on how Databricks can help automate hyperparameter tuning. For both traditional Machine Learning and modern Deep Learning, tuning hyperparameters can dramatically increase model performance and improve training times.

Yesterday we showed you that we embrace the #future #mobility. Today I would like to invite you to a free training on Operide, our micro-mobility fleet management application based on #ai! So you can make sure that you provide a more balanced distribution of #eBikes or even #eScooters! Operide, our #ai driven shared micro-mobility fleet management application, optimises the rebalancing process so that more assets (bikes/scooters) are available to the end-user.

Justin Boutilier uses optimization and machine learning to improve healthcare access, delivery and quality, particularly in low- and middle-income settings. As a second-year PhD student at the University of Toronto, Justin Boutilier spent four weeks in Dhaka, Bangladesh, investigating ways to curb ambulance response times in the bustling capital of a developing country. He quickly got a firsthand look at the scope of the challenge: The roughly 10-mile trip from his hotel to meetings in the city took about three hours. "You could walk faster," he says, "but there's no sidewalk, so it's kind of dangerous." Boutilier, who has joined the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison as an assistant professor, uses optimization and machine learning to improve healthcare access, delivery and quality, particularly in low- and middle-income settings.

That student with the heart of the world was born, My data burns the same stars in a window. No human would ever mistake these lines for award-winning verse. If they're a bit fanciful and lack coherence, that's because they were composed by a computer algorithm trained on more than 20 million words of 19th century poetry. The seed word in this case was "student." The resulting word salad makes it clear that as powerful as AI is, it still can't create like a human.

Workforce development has changed dramatically over the last few years. Challenges on how to tackle the future of work and related ethical issues abound. For example, how should companies help older workers transition to new ways of doing their jobs? How can they address the needs of a new generation of employees who care less about work-life balance, and more about work-life integration? And how can HR leverage emerging technologies and artificial intelligence (AI) to better meet employees' needs and help them wade through the overwhelming amount of data available to get answers to their specific problems? Emily He, Senior Vice President of Human Capital Management at Oracle, has been giving all these questions a lot of thought. Watch the video as she shares her insight into the future of work, talent management, and incorporating enterprise software and AI to help humanize the office environment. According to Emily, the concept of humanizing work means helping employees be the best they can be while connecting with the company's value. For companies, it also means understanding how their customers engage with the software they use in a conversational way, using, say, voice or text. She sees AI taking shape in enterprise software, freeing up time for workers to do more creative, strategic activities. Emily also talks about the challenges for HR in helping workers to deal with the automation of their old jobs and to acquire new skill sets in order to transition to new job functions. On the flip side, it also means adapting to the way new employees engage with technology in their lives and incorporating new styles of work into the company's environment. Overall, she believes HR sits at the intersection of technology, humanity, and work, and enjoys a unique position to use technology to deliver a better employee experience.

Less than a year ago, leaders in the advancement industry recognized that artificial intelligence (AI) technology was beginning to revolutionize the way fundraising worked. This group was committed to shaping AI's role in the advancement industry so that transformative innovation would happen in a transparent fashion, that AI would result in a positive impact on philanthropic efforts and social good, and that widespread adoption would be accessible to all nonprofit organizations. The 16-member group called itself the AI in Advancement Advisory Council (AAAC) and Gravyty, the first and leading AI company focused solely on social good, is proud to be the catalyst that brought this group together. This positive impact is the mission of the AAAC. "Gravyty is doing much more than bringing AI to advancement. They are creating the necessary dialogue between universities to help draft a language that will ensure that this type of technology is applied in an equitable manner."