Portfolios are always a hot topic in career Q&As and the conversation design community, and for good reason! A portfolio is a great way to highlight your writing and design skills, but with a little creativity, they can speak to so much more than just a prototype. I put together my top considerations and must-have skills for your own portfolio, to ensure that it speaks for you, and that your ideal audience will understand your work and what you're most passionate about when it comes to conversation design. Later in this post, Brielle Nickoloff and I review four portfolios from real conversation designers! This is the most obvious and most important thing to highlight in your portfolio.

In today's music industry, the separation between digital and analogue is almost impossible to determine. At the most basic level, the majority of today's music is crafted using highly intelligent software. However, at the cutting edge of AI and the music industry, innovators are continuously pushing the boundaries of human/machine collaboration in musical creation as well as business. One such innovator is Vernica Serjilus, professionally as Verphoria, an American singer, record producer, songwriter, entrepreneur, and the Founder and CEO of Hierarchy Music. Hierarchy Music is a global music company that connects musicians globally with Grammy Award-winning, multi-platinum music services. At the crux of Hierarchy Music's operations is data AI and back-end exposure which allow us to bring exposure to new artists, or existing artists and their brands, utilizing both Hierarchy Music and Hierarchy Media's back-end network.

WIRE)--WekaIO (Weka), the fastest-growing data platform for artificial intelligence/machine learning (AI/ML), life sciences research, enterprise technical computing, and high-performance data analytics (HPDA), today announced that it has been named a finalist in The Business Intelligence Group's inaugural Artificial Intelligence Excellence Awards program. The Artificial Intelligence Excellence Awards recognizes those organizations and products that are truly unique and making an impact on the market. Weka's Limitless Data Platform is built on a shareable, scalable, and distributed file storage system (WekaFS). Designed to help future-ready clients' data centers and enable digital transformation, the breakthrough WekaFS solution was architected to leverage the performance benefits of flash, high-speed networking, and compute acceleration technologies (like GPUs) whether the data resides on-premises, in the public cloud, or as a hybrid model. WekaFS stands out as a leading solution because it gives clients the leverage to get more value out of their compute resources, providing a full enterprise-grade solution with advanced security and full cloud integration.

Annie Brown is the founder of Lips, an AI enabled social commerce platform for women and LGBTQ creators.

Last week, Google Research held an online workshop on the conceptual understanding of deep learning. The workshop, which featured presentations by award-winning computer scientists and neuroscientists, discussed how new findings in deep learning and neuroscience can help create better artificial intelligence systems. While all the presentations and discussions were worth watching (and I might revisit them again in the coming weeks), one, in particular, stood out for me: A talk on word representations in the brain by Christos Papadimitriou, professor of computer science at the University of Columbia. In his presentation, Papadimitriou, a recipient of the Gödel Prize and Knuth Prize, discussed how our growing understanding of information-processing mechanisms in the brain might help create algorithms that are more robust in understanding and engaging in conversations. Papadimitriou presented a simple and efficient model that explains how different areas of the brain inter-communicate to solve cognitive problems.

The surveillance-state dystopia portrayed in George Orwell's 1984 could "come to pass in 2024" if governments don't do enough to protect the public against artificial intelligence (AI), Microsoft president Brad Smith warned in an interview for the BBC's investigative documentary series Panorama. During the interview, Smith warned of China's increasing AI prowess and the fact that we may be caught up in a losing race with the technology itself. "If we don't enact the laws that will protect the public in the future, we are going to find the technology racing ahead, and it's going to be very difficult to catch up," Smith stated. Many of the world's brightest minds have warned of the perils of artificial intelligence. In 2017, astrophysicist Stephen Hawking stated his fear that "AI may replace humans altogether."

Last week, Google Research held an online workshop on the conceptual understanding of deep learning. The workshop, which featured presentations by award-winning computer scientists and neuroscientists, discussed how new findings in deep learning and neuroscience can help create better artificial intelligence systems. While all the presentations and discussions were worth watching (and I might revisit them again in the coming weeks), one, in particular, stood out for me: A talk on word representations in the brain by Christos Papadimitriou, professor of computer science at the University of Columbia. In his presentation, Papadimitriou, a recipient of the Gödel Prize and Knuth Prize, discussed how our growing understanding of information-processing mechanisms in the brain might help create algorithms that are more robust in understanding and engaging in conversations. Papadimitriou presented a simple and efficient model that explains how different areas of the brain inter-communicate to solve cognitive problems.

Best listening experience is on Chrome, Firefox or Safari. A lot of corporate research effort goes into artificial intelligence and machine learning. But do the top tech companies' investments coincide with national priorities for competitiveness and scientific leadership? That's what Georgetown University's Center for Security and Emerging Technology set out to discover. Research fellow Tim Hwang joined Federal Drive with Tom Temin for the findings.

So maybe you can make it more tangible. But that's the understanding I have. Where do you really see digital twins driving value in terms of day-to-day decisions for executives who really need to steer the company?

Towards AI is a community that discusses artificial intelligence, data science, data visualization, deep learning, machine learning, NLP, computer vision, related news, robotics, self-driving cars, programming, technology, and more! Considering various factors such as the research areas, research focus, courses offered, duration of the program, location of the university, honors, awards, and job prospects, we came up with the best universities to help prospective students choose. This article is most suited for individuals who would like to pursue a Ph.D. with a focus on machine learning and need some guidance on their decision-making. For the list of the universities, please jump at the end of the article. Note: The universities mentioned below are in no particular order.