In episode 9 of season 4 we talk about the Statement on Nature Machine Intelligence. We reached out to Nature for a statement on the statement and received the following:

“At Springer Nature we are very clear in our mission to advance discovery and help researchers share their work. Having an extensive, and growing, open access portfolio is one important way we do this but it is important to remember that while open access has been around for 20 years now it still only accounts for a small percentage of overall global research output with demand for subscription content remaining high. This is because the move to open access is complex, and for many, simply not a viable option.

Nature Machine Intelligence is a new subscription journal that aims to stimulate cross-disciplinary interactions, reach broad audiences and explore the impact that AI research has on other fields by publishing high-quality research, reviews and commentary on machine learning, robotics and AI. It involves substantial editorial development, offers high levels of author service and publishes informative, accessible content beyond primary research all of which requires considerable investment. At present, we believe that the fairest way of producing highly selective journals like this one and ensuring their long-term sustainability as a resource for the widest possible community, is to spread these costs among many readers — instead of having them borne by a few authors.   

 We also offer multiple open access options for AI authors. We already publish AI papers in Scientific Reports and Nature Communications, which are the largest open access journal in the world and the most cited open access journal respectively. We offer hybrid publishing options and are set to launch a new AI multidisciplinary, open access journal later this year.

We help all researchers to freely share their discoveries by encouraging preprint posting and data- and code-sharing and continue to extend access to all Nature journals in various ways, including our free SharedIt content-sharing initiative, which provides authors and subscribers with shareable links to view-only versions of published papers.”

We also get a chance to talk with Maithra Raghu from the Google Brain team about her work.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In episode eight of season four we review some recently published articles by Michael Jordan and Rodney Brooks (for more reading along these lines, Tom Dettriech is a great person to follow), we recommend some further reading, and talk with Arthur Gretton who was part of the team behind one of the Best Papers at NIPS 2017

For more reading we recommend Machine Learning Yearning, Talking Nets, The Mechanical Mind in History, and Colossus.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In episode seven of season four we chat about Ellis and the UK AI Sector Deal , we take a listener question about the next AI winter and if/when it is coming, plus we hear from Christina Colclough Director of Platform and Agency Workers, Digitalization and Trade UNI Global Union.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In episode six of season four we chat about AI and religion, we take a listener question about personal bias checking and we hear from Been Kim of Google Brain.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In episode five of season four we talk about the GDPR or as we like to think of it Good Data Practice Rules. (If you actually read it, you move to expert level!) We take a listener question about the power of approximate inference, and we hear from our guest Andrew Blake of The Alan Turing Institute.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In episode four of season four we talk more about natural an artificial intelligences and thinking about diversity in systems. Reading Can a Biologist Fix a Radio is a great paper around these ideas. We take a listener question about moving into machine learning after having advanced training in a different program. Our guest on this episode is our second second time guest Peter Donnelly, Professor of Statistical Science at the University of Oxford, Director of the Wellcome Trust Center for Human Genetics and a Fellow of the Royal Society. 

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In season four episode three of Talking Machines we chat about Neil’s recent thinking (definitely not work) on the core differences between natural intelligence and machine intelligence, he recently wrote blog post on the subject and in the fall of 2017 he gave a TedX talk about the topic. We also take a listener question about what maths you should take to get into building ML tools. Our guests this week are Moshe Vardi, Karen Ostrum George Distinguished Service Professor in Computational Engineering and Director of the Ken Kennedy Institute for Information Technology at Rice University and Margaret Levi Director of the Center for Advanced Study in the Behavioral Sciences(CASBS) at Stanford and Professor of Political Science, Stanford University, and Jere L. Bacharach Professor Emerita of International Studies in the Department of Political Science at the University of Washington. They co-organized a symposium put on by the American Academy of Arts and Sciences and the Royal Society about the future of work. We got a chance to speak to both of them about their work and the event.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In episode two of season four we're proud to bring you the second annual "Hosts of Talking Machine's Episode"! Ryan and Neil chat about Ali Rahimi's speech at NIPS-17, Kate Crawford's talk The Trouble with Bias, and much more.

We also get to hear a conversation with Ciira wa Maina, lecturer in the Department of Electrical and Electronic Engineering Dedan Kimathi University of Technology in Nyeri Kenya

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

On this episode of Talking Machines we take a break from our regular format to talk about the “code review of community culture” that the AI, ML, Stats and Computer Science fields in general need to undergo. 

In a blog post, that was put up shortly after NIPS, researcher Kristian Lum outlined several instances of sexual harassment and abuse of power. In her post she mentioned Brad Carlin and a person who she referred to as S. We learned in reporting done by Bloomberg that S was Steven Scott, who was at Google. 

As of this posing Carlin is under investigation and Scott has left Google after being suspended. 

Today we pause in our regular format to talk about how we, as a community, can change. 

Full disclosure: Neil and Katherine served as press chairs for NIPS 2017. They will hold the same post for ICML 2018 and NIPS 2018 and are working along with the other organizers of these events to effect change around these issues.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.

In episode ten of season three we talk about the rate of change (prompted by Tim Harford), take a listener question about the power of kernels, and talk with Peter Donnelly in his capacity with the Royal Society's Machine Learning Working Group about the work they've done on the public's views on AI and ML.

See omnystudio.com/listener for privacy information.

Hosted on Acast. See acast.com/privacy for more information.