guicho271828

The "largely" and "probably" are the mentions to the fact that there aren't yet legal cases concerning LLGPL. I am not an expert in law, but given that the journal is peer-reviewed, I will give some credit. https://www.ifosslr.org/index.php/ifosslr/about/editorialPol...

the article title is the name of the paper. "Lisping Copyleft: A Close Reading of the Lisp LGPL"

I was convinced by this paper by lawyers analysing LLGPL that LGPL is just enough.

https://ja.reddit.com/r/lisp/comments/9gjd0m/lisping_copylef...

Author here. IBM is currently focusing on the combination of machine learning and reasoning, also called neural-symbolic AI [1], to combine the best of both worlds (noise robustness and explainability, etc.). I am from Tokyo and will join MIT-IBM lab soon to perform this line of research.

I have been working on Latplan [AAAI-2018, 2,3,4,5,6], a neural-symbolic classical planning system that learns symbolic representations of noisy images and perform efficient symbolic planning in the latent space. Later, several other groups have started working in this field, like [7].

The problem with python is the lack of sequential execution speed, which is necessary for solving symbolic tasks, e.g. SAT solver, classical planning, theorem prover. At the same time, traditional languages like C++, typically used for writing solvers, are too inflexible to accommodate the workflow in machine learning. For a neural-symbolic task, personally, Lisp is best in this space (I don't try to repeat why, because there are plenty of articles on it.), with Julia being a contender.

I am also interested in adding the compile time type/shape checking on the deep learning code, since python debugging is painful (just a personal opinion -- not intending to start a war here).

By the way, I made the first prototype of this lib in 3 days, and am working on improving it for 3 month (for other ML projects).

[1] https://medium.com/@MITIBMLab/the-shared-history-and-vision-... [2] https://github.com/guicho271828/latplan [3] AAAI18 presentation at : https://asai-research-presentation.github.io/2018-2-5-aaai/ [4] AAAI18 paper : Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary, https://arxiv.org/abs/1705.00154 [5] Follow-up papers (ICAPS2019) : https://arxiv.org/abs/1903.11277 [6] Follow-up papers (ICAPS2019), extension to first order logic : https://arxiv.org/abs/1902.08093 [7] Learning Plannable Representations with Causal InfoGAN, https://arxiv.org/abs/1807.09341v1

bagof/setof/findall ARE indeed list comprehensions, aren't they

Sounds like Lisp Machine Lisp reborn.

First time reader. The definition of technology seems very narrow --- almost exclusive to the entertainment. I don't think e.g. an optimized GEMM on GPUs or SQL query would be covered in this article.

> we should sell automobiles without traction control

That is not a good example. Perfect traction control is beyond human limit even if the person in the driver's seat is maximally attentive.

So what's the correct code? I try my guess before reading the 30 page paper (I will add my comment after reading it)

My first guess: Normalize it. Find the largest exponent and divide all values with the exponent. This is a power-of-2 operation so would not lose any precision. Then divide all numbers by the length. Perform the same normalization again. Sum the numbers, then revert the exponent that was removed in the first step.

My second guess (backup plan): Use the interval arithmetic. I don't remember the specifics but I remember this is the safest form of floating point operations. But perhaps I should be careful about the performance penalty.

So .. like human brains that chose a particular president?

> Physiognomy gave concrete shape to liberalism’s dark secret: the sense that reasoning and discourse are only part of how society and politics function, and that just looking someone in the face can be more revealing than listening to what they say.

Wait, what?

Ended up spending 30 minutes of my life for reading https://en.wikipedia.org/wiki/Development_of_Duke_Nukem_Fore...

That sounds also related to the ABC hypothesis that a crazy Japanese mathematician published a multi-thousand-page paper on it. Hopefully this clears the thing up in the messed up paper?

Wait, from what is implied by the creator's tweet, this was the intended method for getting the secret?

CLOS can dispatch by value with eql specifier...

System 1 logos look very similar to the GitLab logo.

Common Lisp has readtables, so technically Lisp has been already syntax-independent. You can switch between ()s and []s, for example.

Few comes in my mind: iRobot[1], Grammarly, D-wave. I feel there is something in common but it is hard to describe.

[1] If you call iRobot is a venture company. It is actually 30 yrs old.

legitimate employment == full-time job I guess

27 years. The first famous "proof of concept" autonomous driving is Navlab (Thorpe, 1990). (Are there any prior projects?)

I'm on 1070 for DL tasks with the proprietary driver and it segfaults cinnamon every hours, probably when the acceleration for its graphic effects kicks in. It can be restarted though. I know it is due to the driver because every time the kernel gets updated cinnamon keeps failing to restart itself until I restart the entire system. This never happened before switching from Radeon.

> Structures, types, generics, etc, do cover a lot of what people actually want in practice...

For scientific computing, no. However it is very useful in other areas such as web, agents, gui, where you have many methods to combine in many ways and OOP really suits in.

Correct and useless programs are useless. Quite simple.

I saw a chart somewhere recently comparing the tweet length distributions between Japanese and other countries which basically says, there are less surge near the 140 char limit in JP than in other countries, and that should describe the reason why Twitter is still popular in JP while it's struggling in others: JP people are less frustrated by the char limit and thus experience a better UX.

My friend flew to London from Japan with Aeroflot. It was a connection flight and he had 4 flights in total (round trip included), and 3 of 4 flights were delayed for 3+ hours each.

I also experienced a 5 hour delay. The worst thing was not the length of the delay, but how they handled it... they gave us nearly zero information and most passengers were frustrated by the "expected departure time" on the screen constantly being updated with no explanation.

It is same in Japan.

I hope driving on the road will not be banned, but instead hope for the more strict law for a driver's license. Too many people pay not enough attention to driving, some may check emails, some may lack ethics, some may roadrage with ridiculous reasons, and so on. We are lucky that those people do not love driving and therefore are likely to welcome the introduction of autonomous cars. There would be an autonomous-only license in the future, bad drivers eliminated first (and shifted to autonomous cars).

I also believe realistically an abrupt change as a total ban on driving would not happen, and instead there will be a more gradual shift to the driverless society, which would only materialize at the time I become too old to drive. I am completely fine with it, by that time I would have enjoyed plenty of driving.

4. should make distinction between the one primarily used for recreation and one also used for e.g. commuting. Majority of cars are used purely for transportation and are expendable. Therefore it is reasonable to introduce a shift to electric because it has a higher impact. Track day cars are driven less miles, though slightly higher emission per mile, with smaller impact in total. It is as wasteful as operating a roller coaster in a Disneyland.

Most people don't care about what car they drive. For them driving a Prius is just fine. For petroheads driving a Prius is NOT fine. It feels as if Mac enthusiasts are forced to live forever with Windows XP, or Emacs/Vim users forced to write code with Notepad, or a mechanical keyboard user forced to live with a cheap membrane keyboard. It brings a huge disappointment to their life. For most people switching to a dull car means nothing, since they have been driving a dull car, which is not the case for them.

By the way, the more serious track day cars, without audio/AC/insurator, are painful and impossible to drive daily, in my personal experience. Especially the summer. One day I was dehydrated and could not shift properly.

This article deserves more attention.

OK, reversible updates. You need to somehow store the parent state information in order to backtrack. And the natural way to do this is to push the edge/diff info in the stack. By doing so you only have to maintain one state at a time, keeping the backtrack information compact. But when to backtrack? You surely use iterative deepening, otherwise it returns a suboptimal path or may not backtrack forever on the state space graph. You also want to prune the states? Use the sum of the depth and the heuristic lower bound. This is IDA＊. You can call a blind IDA＊ as IDDFS too, but I generally just call them IDA＊. A plain DFS is not viable in complex problems, so let's forget about it.

> choosing which node (next state) to expand next

I know this is "heuristic search", a broader class of algorithms which includes A＊ and IDA＊ and many more. But the core selling point of IDA＊ is not the "heuristic search", but its compact linear-space memory usage (thus fast) compared to A＊. So I did not suggested IDA＊ because of its heuristic search aspect.

For an efficient implementation, reversible updates are just natural and common in IDA＊. Below is an excerpt from [1]. I believe this is equivalent to what you call reversible state updates.

    * In-place Modification

    The main source of remaining overhead in the expansion function is
    the copy performed when generating each new successor (line 12 in Figure 1).
    Since IDA＊ only considers a single node for expansion at a time, and because
    our recursive implementation of depth-first search always backtracks to the
    parent before considering the next successor, it is possible to avoid copying entirely.
    We will use an optimization called in-place modification where the search 
    only uses a single state that is modified to generate each successor and
    reverted upon backtracking.

[1] Burns, E. A., Hatem, M., Leighton, M. J., & Ruml, W. (2012, July). "Implementing fast heuristic search code". In Fifth Annual Symposium on Combinatorial Search.