The MIT Stephen A. Schwarzman College of Computing announced its first two named professorships, beginning July 1, to Frédo Durand and Samuel Madden in the Department of Electrical Engineering and Computer Science (EECS). These named positions recognize the outstanding achievements and future potential of their academic careers. "I'm thrilled to acknowledge Frédo and Sam for their outstanding contributions in research and education. These named professorships recognize them for their extraordinary achievements," says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing. Frédo Durand, a professor of computer science and engineering in EECS, has been named the inaugural Amar Bose Professor of Computing.

Chris Wallace, host of "Fox News Sunday," took the online cognitive test President Donald Trump said he aced and wasn't impressed with its difficulty. Wallace interviewed Trump on his show Sunday. The wide ranging discussion mostly covered COVID-19. It also touched on the bestselling book by his niece, Dr. Mary L. Trump; his late father, Fred; the economy; Joe Biden; Biden's alleged vow to defund the police; and Biden's alleged cognitive problems. During the interview, Trump said he wanted Joe Biden to take the "Montreal Cognitive Assessment" (MoCA) test he took in 2018 and which his doctors said he "aced."

In a podcast, "Does Revelation Talk About Artificial Intelligence?", he discusses with Robert J. Marks, director of the Walter Bradley Institute, the title question: "Can AI replace the need for belief in God?" Robert J. Marks (right): Let's talk about the theological implications of AI. You have a reputation, not only as a mathematician, but a Christian apologist. And I wanted to go into some of the apologetics that you gave in the book and how it relates to some of the modern perceptions of artificial intelligence. Generally, how will technical advances affect the way in which people, either believers or non-believers, think of God? John Lennox: Well, sometimes technological development has a very positive effect because if, like myself, you believe that God is the intelligence behind the universe, that he's made human beings in his image, so that we are to a certain extent creative and we can produce this technology. Then the existence of the technology and the need for science itself is evidence that there is a God behind it all. So that is a positive development.

Organizers of the 37th International Conference on Machine Learning (ICML) have announced their Outstanding Paper awards, recognizing papers from the current conference that are "strong representatives of solid theoretical and empirical work in our field." A total of 1,088 papers out of 4,990 submissions made it to the prestigious machine learning conference. The acceptance rate of 21.8 percent is slightly lower than 2019's 22.6 percent (774 accepted papers from 3,424 submissions), and it seems likely the drastic increase in submissions helped contribute to this. Authors: Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya Institutions: NVIDIA Research, Stanford University, Bar Ilan University Abstract: Learning from unordered sets is a fundamental learning setup, recently attracting increasing attention. Research in this area has focused on the case where elements of the set are represented by feature vectors, and far less emphasis has been given to the common case where set elements themselves adhere to their own symmetries.

I recently started a new newsletter focus on AI education. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. One of the challenging elements of any deep learning solution is to understand the knowledge and decisions made by deep neural networks. While the interpretation of decisions made by a neural networks has always been difficult, the issue has become a nightmare with the raise of deep learning and the proliferation of large scale neural networks that operate with multi-dimensional datasets.

Since edge device failures (i.e., anomalies) seriously affect the production of industrial products in Industrial IoT (IIoT), accurately and timely detecting anomalies is becoming increasingly important. Furthermore, data collected by the edge device may contain the user's private data, which is challenging the current detection approaches as user privacy is calling for the public concern in recent years. With this focus, this paper proposes a new communication-efficient on-device federated learning (FL)-based deep anomaly detection framework for sensing time-series data in IIoT. Specifically, we first introduce a FL framework to enable decentralized edge devices to collaboratively train an anomaly detection model, which can improve its generalization ability. Second, we propose an Attention Mechanism-based Convolutional Neural Network-Long Short Term Memory (AMCNN-LSTM) model to accurately detect anomalies. The AMCNN-LSTM model uses attention mechanism-based CNN units to capture important fine-grained features, thereby preventing memory loss and gradient dispersion problems. Furthermore, this model retains the advantages of LSTM unit in predicting time series data. Third, to adapt the proposed framework to the timeliness of industrial anomaly detection, we propose a gradient compression mechanism based on Top-\textit{k} selection to improve communication efficiency. Extensive experiment studies on four real-world datasets demonstrate that the proposed framework can accurately and timely detect anomalies and also reduce the communication overhead by 50\% compared to the federated learning framework that does not use a gradient compression scheme.

Businesses and developers making conversational AI experiences should start with the understanding that you're going to have to use unsupervised learning to scale, said Prem Natarajan, Amazon head of product and VP of Alexa AI and NLP. He spoke with Barak Turovsky, Google AI director of product for the NLU team, at VentureBeat's Transform 2020 AI conference today as part of a conversation about future trends for AI assistants. Natarajan called unsupervised learning for language models an important trend for AI assistants and an essential part of creating conversational AI that works for everyone. "Don't wait for the unsupervised learning realization to come to you yet again. Start from the understanding that you're going to have to use unsupervised learning at some level of scale," he said.

RSS 2020 was held virtually this year, from the RSS Pioneers Workshop on July 11 to the Paper Awards and Farewell on July 16. Many talks are now available online, including 103 accepted papers, each presented as an online Spotlight Talk on the RSS Youtube channel, and of course the plenaries and much of the workshop content as well. We've tried to link here to all of the goodness from RSS 2020. The RSS Keynote on July 15 was delivered by Josh Tenenbaum, Professor of Computational Cognitive Science at MIT in the Department of Brain and Cognitive Sciences, CSAIL. Titled "It's all in your head: Intuitive physics, planning, and problem-solving in brains, minds and machines".

Businesses and developers making conversational AI experiences should start with the understanding that you're going to have to use unsupervised learning to scale, said Prem Natarajan, Amazon head of product and VP of Alexa AI and NLP. He spoke with Barak Turovsky, Google AI director of product for the NLU team, at VentureBeat's Transform 2020 AI conference today as part of a conversation about future trends for AI assistants. Natarajan called unsupervised learning for language models an important trend for AI assistants and an essential part of creating conversational AI that works for everyone. "Don't wait for the unsupervised learning realization to come to you yet again. Start from the understanding that you're going to have to use unsupervised learning at some level of scale," he said.

There was lots going on at the virtual ICML conference this week. The event was bookended by tutorials and workshops, with the invited talks and poster sessions happening mid-week. There were also numerous opportunities to get involved in socials, and a chance to have a say on the format for future editions at the Town Hall meeting. Here is a selection of tweets from attendees and organisers. At #ICML2020, join us at 1am (AOE) July 15 for the invited talk by Brenna Argall on "Human and Machine Learning for Assistive Autonomy", followed by live Q&A and panel discussion afterwards with Aude Billard, @EmmaBrunskill @FinaleDoshi.