I recently learned that my go-to park in Berlin, Gleisdreieck Park, was supposed to become an Autobahn in the second half of the last century. Protests have stopped it finally in the 90s [1]. Nowadays, Berlin is enlarging the Autobahn eventually leading to the removal of night clubs and nature. Why is the protest so small this time?
No one mentioning Facebook? Them forcing you to use the messenger app to be able to communicate on the mobile is using the same strategy. I have to use a different browser and use desktop mode to see messages. Writing then becomes horrible too. Not using fb messenger at all anymore an complain to people who text me on there.
The concept of a major depressive disorder exists. There are common symptoms and likely causes such as childhood trauma. Can we be certain it is a unanimous mental disorder? No, it might as well be several different disorders we haven't understood yet. But isn't that similar for most mental disorders?
If we eliminate king from the result list I would assume it's plural is removed as well. Bummer, that would mean the latent space algebra in this example has no effect whatsoever..
What happens if you get the latent space of king, do no algebra and return the outcome with king being excluded? In case it's queen, then the author is correct and these examples are highly misleading. In case it's something like prince, Lord or ruler of the seven kingdoms the latent space algebra would be suitable imho.
Also, if we think about it in terms of decision manifolds, it seems the distance between queen and king is too large for the simple - man + woman to have an effect. Why not scale that substraction, so it leads to a change in predicted class without removing king? But of course finding a justifiable weight would be hard..
I'm doing a PhD in Berlin, living in Kreuzberg and I can tell you far from all of the programmers that I know want to live here!
What makes Kreuzberg attractive for startups and a Google campus is that it's central and perfectly connected infrastructurewise. Most other regions like Schöneberg, parts of Friedrichshain, Prenzlauer Berg and maybe Moabit, are all harder to reach from some other regions, even though more start-up employees live there. You can see on the maps of rental e-scooters like Coup how during the day there is a lot of activity towards Kreuzberg whereas after work the district is basically empty of their scooters. Imho kreuzberg is too dirty for most startupers. I guess they don't want to see the heroin junkies of Kotti when they do their grocery shopping.
In general I liked the sentiment of the activists against placing a Campus in Kreuzberg. Nevertheless I didn't like much of their public attitude ("bullets for google") and some arguments seemed superficial ("other Google campuses have increased rents" idk about the causality and factor here). I wouldve liked a Google campus in Schöneberg for example, just as I liked the Google campus in Madrid. In Madrid it offered a nice environment for work, some interesting talks and I didn't feel like it was in an artsy district that suddenly gentrified and turned hip. This could've added something to Berlin, but meddling with the activist scene in Kreuzberg was a poor choice.
I have not read a single economist.com article in the last couple of months but the paywall tells me I've reached my limit. How badly can your paywall be implemented? This is I guess the most disencouraging thing from me getting a paid subscription.
Charité Berlin | Berlin, Germany | PhD Candidate in machine learning applied on neuroscience | Full-Time
Interested in doing a PhD in machine learning for healthcare? We are offering a PhD position at Charité Berlin.
German is not required!
______________________________________________________________
Deep Learning in clinical neuroimaging
PhD scholarship (starting October/November 2018, initially for 2 years; Promotionsstipendium II at Charité)
At the Berlin Center for Advanced Neuroimaging and Bernstein Center for Computational Neuroscience (Charité), we are looking for a motivated and highly talented PhD student for various research questions within the interdisciplinary field of deep learning and clinical neuroimaging. In particular, we employ convolutional neural networks for finding new representations from neuroimaging data in order to predict disease conversion and future clinical disability in neurological as well as psychiatric diseases. Whereas previous disease decoding approaches mostly relied on expert-based extraction of features in combination with standard classification algorithms and thus strongly depend on the choice of data representation, convolutional networks are capable of learning hierarchical information directly from raw imaging data. By this, they have a great potential for finding unexpected and latent data characteristics and might perform as a real “second reader”. A major focus will be on visualization techniques to make the learned content of convolutional neural networks visible.
Requirements for the PhD student:
- Very good degree in computer science, mathematics, physics, psychology, computational neuroscience or related subject.
- Very good programming skills (e.g. Python)
- Experience in machine learning
- Good writing and communication skills (in English)
Please send your application (motivation+CV) in one pdf-file (in English or German) to:
Dr. Kerstin Ritter
Berlin Center for Advanced Neuroimaging,
Bernstein-Zentrum für Computational Neuroscience
Charité - Universitätsmedizin Berlin
Sauerbruchweg 4, Charitéplatz 1, 10117 Berlin
Email: [email protected]
Great, intuitive explanations with a nice mix of code and formulas. Only I found the GIFs to be very annoying while reading, especially as they do not add to the content.
I was happily surprised the other day when the IBM debater was presented and there was no mention of it being Watson anywhere on their website. They really need to stop with this personification.
It's not the case. A year or two ago some of my friends who work at IBM couldn't tell me themselves what Watson really is. As of today I understand Watson as everything from IBM that can be related to AI, I.e. it includes IoT as well because the data could be used by AI.
I'm starting to think we have the need of something like the ICAN for facial recognition (FR), promoting the regulation of FR worldwide. There a little valid systems where FR is truly helpful. Most of todays applications are around things like "access control" and "tag your friends here", i.e. banalities which are either unnecessary or can be solved with simpler tech.
On the other hand the risks are incredible, FR in combination with AR systems could completely eradicate privacy. Autocratic governments could use it for a new levels of surveillance. Military usage could perfect the use of autonomous weapons etc.
It's just not worth it and should be internationally outlawed. Just like A-bombs and chemical warfare.
Here is a paper from Bosch in that direction, it uses a second network to classify examples as adversarials: https://arxiv.org/abs/1702.04267
Using a fail safe network is hard because adversarial examples usually have a high accuracy at a false class. So using an accuracy threshold in the main network wouldn't work. Using a network as described in the paper and then a different kind of classifier might be worth trying. But it has also been shown that adversarial examples can transfer to different kind of models (don't know if random forests have been tried as well).
I can recommend the book 'What money can'take buy' by Micheal Sandel. He has many more examples where using a fee actually resulted in an increase in the undesired behaviour.
[1] German only: https://de.wikipedia.org/wiki/Park_am_Gleisdreieck