This is getting really crazy... I wonder if a discussion about this topic with both of them is possible. Something where all the evidence is presented and discussed. While I feel like there is a lot of damning evidence I feel like we mostly hear about the Schmidhuber side of things on this subreddit. I would like to hear what Bengio et al. have to say for themselves.

In general, the hyperparams are related - if you perturb one hyperparam, you need to perturb some other hyperparams also to get satisfactory results. Some people do a random search on their hyperparam grid but if one hyperparam is very sensitive to changes in the other hyperparams, then the search will be more difficult. Personally, I've had OK results using Cyclic Learning Rate together with batchnorm and only have 3 values for the max-learning-rate hyperparam in my hyperparam grid. However, you probably won't find many papers on CLR because its efficacy and the details of the right way to use it is probably quite problem-specific and there's very little theory behind it even by deep-learning standards.

The AI Index Report tracks, collates, distills, and visualizes data relating to artificial intelligence. Its mission is to provide unbiased, rigorously-vetted data for policymakers, researchers, executives, journalists, and the general public to develop intuitions about the complex field of AI. Expanding annually, the Report endeavors to include data on AI development from communities around the globe.

"This paper is all about reconstructing a 3D point cloud from single depth map for Anthropomorphic body part (Human Feet).

AX Semantics an artificial intelligence (AI)-powered, natural language generation (NLG) company said it could create AI-produced content in more than 110 languages. The Stuttgart-based company which launched in the US today, 12 December 2019 already works with hundreds of customers, including several Fortune 500 companies such as Deloitte for BSS reporting, Porsche and Nestlé. The demand for digital content continues to rise. And technology like AI is considered to be instrumental in helping companies keep pace. The global NLG market size is expected to reach $1,150.9

As far as Bing is concerned, they have announced that their production is starting to use machine learning.

In the latest version of Ortoma Treatment Solution, OTS 4, Ortoma has introduced support of Artificial Intelligence. The system drastically reduces the time needed for pre-operatively planning of a hip implant in 3D, which has created a big interest for the company's unique solution. Performance has been a focus area during the development of the latest version of Ortoma Treatment Solution (OTS). With OTS 4, an automatic AI-analysis, which forms the basis for the pre-operative planning, is made. The analysis does not take more than about 30 seconds and includes a suggestion for suitable implant and its optimized position.

Apple has acquired a startup in the UK that develops technology designed to improve smartphone photography. According to a new report from Bloomberg, Apple has acquired Spectral Edge for an undisclosed sum. Spectral Edge uses machine learning to "make smartphone pictures crisper, with more accurate colors." This works primarily by taking an infrared image and blending it with a standard photo. "Spectral Edge combines patented Image Fusion tech with Deep Learning to reveal more of the color, detail and clarity in any image," the company explained in its pitch.

The world's most prestigious machine learning conference wraps up in Vancouver this weekend.