yorak

Sorry to dissapoint you and the few other curious ones, this was some 10 years ago and such details such as name of the company have fell of from my overfilled brain long ago. While the person who told me the story is a reputable fellow I must admit they still are a secondhand source. Being a finn I tend to trust people and take their word on it and, hence, do not recall doing my research to factcheck.

Still, it _is_ a good story, and plausible based on what I saw to be the state of the industry back then. Your run of the mill last-mile courier services were really badly organized, from the mathematics and optimization side as simple as they get, and ability to build a robust optimization transportation management system would've given serious competitive edge.

(edit: removed repeated words)

Geoffrey, thanks for sharing your story with us. OR sure is a weird niche. Good enough algorithms for solving these problems have existed for decades1, but we still see low adoption and your 95% estimate of the companies not optimizing their operations rings true.

Similarly to you, I spent a short while trying to sell VRP optimization with an API business model, and what dawned on me was that most companies do not have the necessary in-house expertise to integrate optimization into their existing tools even if the API is well-designed. There also really seems not to be any urgency to do that and most logistics companies just offload their inefficiencies onto their customers. Your routes are not effective? No problem, just bill more.

Some years ago I heard about a Swedish team of optimization experts who got so fed up with selling optimization to unwilling transportation companies that they founded their own—just to mop the floor with their ineffective competition. :D

I agree that ease of use is key here. In my PhD dissertation, I tried to address the issue by adding self-adaptivity within transportation management systems, mostly through automatic parameter tuning and algorithm selection. Such approaches remove some amount of fiddling when the optimization tool is adapted to a new optimization problem. Worth a look, perhaps, if you're interested.

Many thanks again for the interesting article and all the best with Timefold.

1) E.g., already by the '90s, we had quite capable algorithms for the VRP. I have open-sourced a library of classical VRP algorithms called VeRyPy, containing simple and not-so-simple heuristic algorithms. It has enjoyed modest success among VRP researchers and practitioners. Nowhere near the success of OptaPlanner, but also, the purpose is different—OptaPlanner is production-ready, whereas VeRyPy is more geared towards education and research purposes.

At least to me the argument does not hold water. My fear is that humans being human, simulation of a coral reef imaginary or future holodeck-like experiences will not save the actual coral reefs. They might even hasten their demise (as less people are interested of the "ugly" reality of the reefs). The tech is cool, but the environment angle, at least here, feels as an afterthought.

I agree and have been saying for a while that an AI you control and run (be it on your own hardware or on a rented one) will be the Linux of this generation. There is no other way to retain the freedom of information processing.

Nice. The resulting graphics style reminds me of a Short Hike, which is a family friendly bite sized 3D adventure and exploration game. I'm not affiliated in any way, just enjoyed the game with my kid. It has a nice balance of story, challenges, and some platformer action. https://ashorthike.com/

Edit: IIRC the shader a Short Hike used was discussed in the GDC talk by the game's author: https://www.youtube.com/watch?v=ZW8gWgpptI8

I blame being an operations researcher for always (pessimistically) first and foremost seeing how the system can be gamed. You have to think very very carefully what the objective function is and which kind of undesired solutions need to be forbidden using the constraints.

Yes, rather than exchange rate, I'd be more worried about corvids carrying trash from the landfill to exchange it to food. Or, in case of cigarette stubs, emptying well contained ashtrays to the tables and floors only to get to those valuable stubs.

Aka. the Chinese room argument. However, I'm not so sure us people are little more than just pattern matching machines. When I start to talk (or write, as I'm doing now), the words kind of just flow out. I can make the argument, that I understand the "real" world, but do I really?

What is most impressive here, which I think other commentators of the thread have not pointed out, is its ability to have an inner dialogue (monologue?) with itself in this sample. For me, that property of the generated text (or should I write, thought process) gave the chills. Now, given this, AGI seems to be quite a few steps closer indeed.

This is an interesting and promising take on the problem. Despite being introduced already in the 60'ies, the optimization of delivery routes is still not used as widely as it should. I'd argue that this is mostly due to the complexities and challenges inherent in adapting such optimization technology to solve real world delivery route planning tasks, and, on the other hand, the high cost and low availability of operations researchers with relevant software engineering background.

In my recent PhD dissertation I tried to address the challenges from a different angle: I proposed using machine learning to predict the most suitable heuristic algorithm and its parameter values for a specific logistics planning problem. This way the developer or the user does not need to worry about the details of the optimization solver. The book is freely available for download from: https://jyx.jyu.fi/handle/123456789/65790

I've personally not seen this happen. Instead, I've seen many oversold ML/AI tools that offer no advantages over using open and freely available tooling that the data scientist (with or without PhD) is already familiar with. I know this must be frustrating to ML solution vendors, but as with any product, the value proposition has to be there and easy to see for the domain expert. And the value has to be great because the downside is the vendor lock-in of the proprietary solution. Hence, ask yourself: given a green field real world ML project, would you use your tool (with the the same learning algorithms, data manipulation methods etc. under the surface as everybody else), or resort to using some battle proven free and open stack.

Very true, my mind immediately wandered to thinking about Random Forests https://en.wikipedia.org/wiki/Random_forest

From how I see it the conflict is not technical but ideological. Or, in technical terms, what is the objective?: for Forrester and Collins this seemed to be increasing the economical growth of the city and managing KPI (crime, poverty etc.). Baker on the other hand considers also human dignity and our responsibility of keeping a fellow human fed, under a roof, and safe and does not ignore the externalities of the decisions.

In an utopia scenario you own the digital assistant. It is based on open source (even if deployed to cloud ) and you carefully curate the data sources is has access to.

In a dystopia version megacorporations own and control the digital assistant and can decide what information it feeds to you. It will become the marketer you trust, which has a significant influence on the decisions you do.

There is this trick among us operations researchers I'd like to share: even if one is able to perfectly model the peculiarities of a given application and get the optimal solution, it should not be the only output. Instead, one should put forward several good alternatives which the stakeholders can then discuss and become proponents for.

Nobody likes the scruffy operations researcher who awkwardly tells decision makers what to do in the form of an optimal solution, because this takes the power away from them. However, if one presents several good, preferably nearly optimal but different to each other, solutions between which the decision can be made freely, you have a better chance to make a change to better.

It is true that such problems /can/ be solved via mathematical linear programming (for those coming outside math circles, please note that the term programming here has nothing to do with coding) and this is how they are usually presented in academia. However, in practice, it is not something one would be advised to do. Usually, the complexities of the real world routing and scheduling make it impossible to solve these models of practical size. Therefore, numerous heuristic and metaheuristic algorithms have been proposed and are usually used in practical applications. These usually are sound familiar to those that have some experience with "old" AI: genetic algorithms, ant colony systems, simulated annealing, and even neural networks have been succesfully applied to provide "good enough" solutions to these problems.

Bus routing is just a variant of the vehicle routing problem (VRP), which itself is a generalization of traveling salesman problem (TSP) but with multiple salespersons doing the traveling.

There is an Excel sheet for solving such problems, and if one wishes to go further, the basic heuristic and metaheuristic algorithms are not that hard to implement either. http://people.bath.ac.uk/ge277/index.php/vrp-spreadsheet-sol...

With these keywords you are welcome to fall into this rabbit hole as deep as you wish. I promise to greet you on my way up (currently finishing my PhD on the topic).

Before the development of Voxel Quest (https://www.voxelquest.com/) was stopped it had shadows and animated agents. However, I'm not knowledgeable enough on game renderers to estimate which kind of technique was used nor what are its limitations.

Ah, perhaps in the other corners of the world, but in Finland we do not play such "games". That is, if you invite someone over by 17 pm, it might mean by 18 pm, or might not. Here, if you invite someone at 17 pm, whatever the cause, that is the target one should be aiming for. Some think of our culture as too direct or blunt, but in my mind ambiguity and misunderstandings are a root cause of much misery. :)

Like they did it in the 90'ies? Have an actual button on the key that you need to press to open the doors and authenticate. Same goes for starting the car, if you want to offer the "feature" of remote start/stop.

Thanks. I already have an use case in mind for this kind of transpiler, therefore I asked. I've toyed with Rapydscript a bit but the things mentioned in this thread and in the documentation, such as relative simpilicity, traspilation (is that even a word?) that retains the pythonic code structure, flexible use of Javascript libraries etc., tempt me to try also Transcrypt. Looking forward to it.

Does anyone have insight on how does this compare to Rapydscript (http://www.rapydscript.com/)?

There is also superresolution methods that in practice make the "enhance"-feature possible. The information from the same objects in successive frames, eg. from a security camera feed, are composited into a single frame of higher resolution than the originals. This can even be done for a single image (see. Glasner et al. "Super-resolution from a single image." Computer Vision, 2009 ICCV 2009. IEEE.).

If machine learning is brought into play it gets even more interesting. See eg. waifu2x, the anime video upscaler based on Deep Convolutional Neural Networks. Basically it is a neural net, that has been shown A LOT of anime, and it can therefore creatively(?) fill in the created pixels when upscaling.

I have no idea how advanced this kind of ML boosted "enhance" technology can get in the future, and it might even get a little scary: imagine an observer with the experience of million lives spent looking blurry images in poor lighting. It might get surprisingly good at that...

Somebody here at HN suggested using Zim wiki a while ago http://zim-wiki.org/

I've been using it ever since. It stores data in plain text files (dokuwiki markup) and in addition the folder structure is mirrored in the note hierarchy. Zim is open, cross-platform, can include Latex-formula, and is extendable with plugins written in Python. I really also like that it is a proper desktop application instead of some webapp that changes UX every now and then, usually to worse, and that is dependent on network connection. After learning the keyboard shortcuts it is really a pleasure to use. Five stars * * * * *

I keep my Zim notebooks (separate NB's for Work and Personal things) in Dropbox for easy syncing between two desktops. Other Win7 and other Ubuntu.

edit: Added mention to Latex, as it might be of interest in this crowd.

I just purhcased the finnish version of the book and the status says it is shipped. Perhaps I should have waited until it is in my hands? :)

Or then it is like the case with youngsters and mp3s, where the studies have found that they actually prefer the "sound" of compressed music - with compression artifacts and all. If a hifi enthusiast (~tunesmith) would say that uncompressed music sounds better, you wouldn't shoot his argument down by saying that improved fidelity and dynamics just allow you to hear the music was recorded and postprocessed in a studio.

What I'm trying to say with this mp3 analogue is that it is very much a matter of habit and preference. Technically lower quality video does not lead to better immersion if it is not something you have learnt to expect.

I did, a year and a half ago. I decided upon FX-8320, as for me, more cores was better. In my PhD I'm doing automatic parameter tuning of optimization algorithms, and I thought it would be handy to have as many cores as possible also back home (the actual runs are of course run on a monstrous computation server somewhere in the basement of the university). To have 8 separate cores has proven to be handy every once in a while. Just yesterday I did some parameter tuning on a machine vision side project.

Back then the difference in bang-per-buck was even more striking than it is now: http://paulisageek.com/compare/cpu/

Also, by choosing AMD I avoided the minefield of missing virtualization and overclocking support of some mid level Intel models.

Greg Anderson [1] from the Arcticstartup summed it up nicely: "My Summer Car ... is better described as bored Finnish guy in the 90's simulator."

[1] http://arcticstartup.com/2015/04/14/my-summer-car-looks-like...

The idea of digital assistant does not require it to be tied to any specific device. It can live in the cloud and follow you anywhere the entrypoint being any device you are using (and you are logged on). Think of Jarvis from the Iron man movies. If I understood the aim of the VIV correctly, they are trying to do this by not tying the service to any given platform but being this platform. This is what makes it so powerful and intriguing (and scary if you do not have the control of the assistant).

I've been pondering about this for some time and even more after the introduction of Siri, Google Now, and others. I've come to the conclusion that in the near future (artificially) intelligent personal digital assistants will become THE way majority of people will interact with the digital world. It will of course depend on how good and how quickly the assistants evolve, but the potential in productivity gains and transforming the way we live is too big opportunity to be missed. Imagine having a (real) person that would take care of simplifying and helping you with your digital and real life (calendar, meetings, notes, email, flights and other travel, anniversaries, even small research tasks like buy this or that etc.). It would help you immensely by saving time on the fluff of our daily lives and by allowing you to focus on what you deem important.

Therefore I think one of the most important open source projects of the next decade will be to build such a learning intelligent personal digital assistant. A Linux of our generation if you will.. Otherwise this opportunity will be lost to advertisers and others that have interest in steering movements and behavior of the masses. Does anyone know if such an FOSS initiative already exists?