orbifold

I followed the SICP book cover to cover, when I was 17 and I remember it being a mind blowing experience.

In might be computable in principle but not in practice for a long time, similar to how it is possible to simulate all molecules of air in one cubic meter (neglecting quantum effects), but not actually feasible in practice. Any argument for computability all needs an argument why a "coarse graining" or "effective model" of the underlying physical system exists.

In the case of transistors that is because all that matters are binary stable states, which reliably abstract over the complicated device physics. In the case of biological cells and neurons in the brain it is much less obvious what the reliable abstraction is. Right now a lot points towards "it is just a bunch of linear algebra and lots of data", but especially when we come to things like memory, online and few shot learning, the answer becomes far less obvious.

Hammer is just a driver for tools that cost >100k to license. And that doesn't include access to memory compilers, which you would also need.

There is open source software, a good overview is on http://opencircuitdesign.com/qflow/index.html.

They have Norman Jouppi, he apparently was involved in the TPU design.

Well to be more accurate I saw a moderator claim that any comment that mentions it gets flagged to him and even if he allows the comment, it will reappear in the moderation queue.

Yup and they censor any mention of thedonald.win which is a clone of the subreddit.

Also good luck getting 1B converted to dollars without a major head-ache. I feel like 1B in bitcoin is as bad if not even worse than 1B in cash. It isn't super useful in that form.

Most of that verification infrastructure is tied to proprietary tooling in some way or another. In the case of IBM they have a lot of in house EDA tooling that they aren't willing to release or even talk about much. They extended vhdl with "aspect oriented programming" to implement their approach to verification. Most of the other verification tooling for verilog (now system verilog) started as proprietary extensions by some vendor (Intel, Synopsis, ...) and then made it into the system verilog standard. None of those verification parts of system verilog have an open source compiler that supports them.

The good news is that at least the simulation part has improved massively over the last few years. For synthesizable system verilog you have https://www.veripool.org/wiki/verilator, which allows you to compile to C++ and then you can implement any verification methodology you like from scratch in C++ :). I did that for parts of an in-house POWER based processor and it isn't actually as bad as it sounds. You also have the option to use DPI-C and interface with a C++ test-driver that way. We managed to do extensive Hardware and Software (full hardware abstraction layer + instruction compiler + FPGA + ASIC) co-simulation for an accelerator we build, although using proprietary tools because we had Xilinx IP and VHDL involved. Verilator is also used as a backend for Chisel.

For vhdl there is https://github.com/ghdl/ghdl.

All of the Ukraine color revolutions were clearly US / CIA / foreign intelligence agency backed (https://www.theguardian.com/world/2004/nov/26/ukraine.usa). Both the EU, Germany and the US had their favourite political operatives in the fight. Various NGOs including German ones paid protestors daily stipends to continue protesting on Maidan, provided them with food and other assistance.

There is no question that the irregular forces in Ukraine received military equipment from Germany, US and other sources. There is videos documenting that. Part of the anti-russian forces were literal neo-nazis, complete with insignia used during world war 2. The Vice magazine war reporting (Russian Roulette in Ukraine) documents both of these statements.

Klay and Clay sound similar?

Fake it until you raise 1 billion and then sell your company for 1 billion?

Objects in OCaml are structurally typed as well.

One of the few dangerous bike accidents I had involved a eBike. They should require a license to operate, their acceleration and breaking is far less predictable than normal bicycles and 15 year old kids should not be allowed to operate them.

Because sometimes it is better to keep a large number of people occupied with one specific goal instead of trying to convince them to do something else. This ultimately boils down to people, most of them are very smart and capable and could do any number of other things, but basically want to work on fundamental particle physics. You couldn't easily convince them to build a telescope instead (a totally different set of people finds that fascinating) or any of the other things you listed. Besides there are (smaller) collaborations that work on all of these other things you mentioned as well.

Furthermore there is good motivation to keep nuclear / particle physics research as centrally organised as possible because the people working on it would be equally capable of producing nuclear weapons. For example a good number of the people working with CERN in France sit right across the Institute that developed their nuclear weapons.

While it is one project it also is an umbrella to fund a large number of smaller projects. Whole institutes were funded and build in part to develop detector components for the LHC. A project like this gives everyone a common goal and pushes technology development in sectors that are critical to Europe's high tech economy. It also has consequences for the IT sector in Europe. Before cloud companies had to deal with PetaBytes of data, scientists at CERN and elsewhere developed techniques for filtering, storing and analysing this data with sophisticated statistical tools (and machine learning). You can easily scale your analysis run to thousands of machines all over the world and transparently get access to the huge experiment datastore.

There is no other scientific field in Europe that has developed a similar level of sophistication and scale. The initial idea behind the Human Brain Project was to build a similar infrastructure for Neuroscience research. But instead of the cooperation in Particle Physics it resulted in fierce opposition, out of fear that funding would be shifted away from national funding agencies and independent researchers and doubts over the ambitious goals of the project. If you think about it a project like CERN, that successfully contributed to understanding of the fundamental forces of nature is in some ways much more ambitious than a centralised program to understand the Human brain.

But the latter got badly derailed multiple times simply because the participants did not have the single minded will, focus and consensus that the Particle Physics community has been able to maintain for almost 70 years now.

Well these centralised resources are books. There are high quality (almost standard) books for most subjects. Want to learn Analysis at a Graduate level? Pick one of the popular books Rudin (for example) and work through it. Same goes for Quantum Field Theory (Peskin & Schroeder, Zee, Srednicki,...) and tons of other subjects.

The lectures are often only a guided tour through one of those books (at least at the undergraduate and early graduate level). In many ways lectures are still la huge advantage of course because most of these books are too long to be useful (I still have some guilt when I think about how little I absorbed of the 500+ pages experimental condensed matter book we used). Often the exercises then cover things that were not explicitly explained in the lecture but can be worked out with the help of the book.

I think you have a fundamentally wrong conception of what it takes to learn advanced concepts. In most cases you can't autograde or award points for everything, it also isn't what University education should be about. It is sad enough that during the Bologna reforms in Europe University education was "industrialised" as much as possible (ECTS points, core modules, etc.).

In the best case a University education in a STEM field will lead you pretty quickly (within 3-5 years) to do research in a lab that does cutting edge work. Most of that lab work can't be distributed or done online, nor can any of the preparatory lab courses in small groups with constant supervision (which are a large part of Physics, Chemistry, Biology, Medicine degrees). Even in subjects such as math and computer science a huge part is exercises that are graded and then discussed in small groups of 10-20 people. This wouldn't easily translate to an online experience either.

Universities like Cambridge even offer 1:1 supervision in Math and Physics, this can be totally awesome and is non-replaceable by video chat or online forums.

I think it is relatively obvious that the popularity of the Dalai is partially the result of a CIA psy-op (https://en.m.wikipedia.org/wiki/CIA_Tibetan_program)

It is interesting how different countries and cultures deal with the same challenge. Streets were pretty empty and shops were closed for maybe a month here in Germany. Now (almost) everything is open again, the streets are full. Unemployment rose somewhat but not catastrophically. The images and videos we get from the US feel apocalyptical in contrast.

The technical term for these is "thirst trap" ( https://www.urbandictionary.com/define.php?term=Thirst%20Tra...).

pipenv felt like it took forever to complete simple tasks. I briefly used it for a small project and quickly realized that it was a mistake. I now just use conda environment.yml and a requirements.txt, those two cover most bases I feel like.

The Standard Model was formulated in the 70s.

There is a very real sense in which working in mathematics can be suffering. I feel like any research mathematician sooner or later has that feeling. Because you will be confronted with your limitations and weaknesses eventually. So I think this a shared experience that is the implicitly understood background of his answer. What I took away from Thurstons answer was a way to deal with that suffering. I eventually decided that I did not really want to continue in a research mathematics direction, but for a while his answer really inspired me.

Checkout Lean, the lead developer also started Z3 . Lean 3 is implemented in C++ and apparently is much faster than Coq. They are in the process of implementing Lean 4, which will feature native code generation and might become one of the first practical dependently typed programming languages.

Germany now has 20 million retirees that just got a raise of 3.5%-4.5% in their pensions . Already 1/4 of the population expects to be paid by a dwindling and ageing workforce. Before long 1 adult will have to pay for 4 retirees (in Denmark). This isn't a problem that will lead to military conflict necessarily, but (almost) for sure to a collapse of social safety nets by mid century.

Luckily it is also not terribly important what those intellectuals think. The large majority of academics are not engaged in these games, but working on serious science like theoretical physics, mathematics, biology and politely ignore them. Also in case you are not aware, there already is https://en.wikipedia.org/wiki/Post-postmodernism, I'm sure they will come up with Post-post-postmodernism soon enough.

I think there basically was a crisis in philosophy, most sane and interesting perspectives had already been explored. Western Europa had almost self-destructed in the first half 20th century. France, Great Britain lost almost all of the rest of their empires right when post modernism developed. Many intellectuals were permanently high on one substance or another.

It isn't super surprising that someone like Lacan, who wrote incomprehensible gibberish, laced with spurious references to advanced concepts from pure mathematics like algebraic topology, became an idol in such a climate.

Basically I think it is time to recognise that baby boomer philosophers produced tons of intellectual garbage. They have been in positions of power in the philosophy and social science departments for the last few decades. Their "Marsch durch die Institutionen" (march through the institutions) is complete. Turns out they were far less competent and talented overall than the people they rebelled against.

The second one is the attack that spread all the way to a basement HPC cluster in the Physics Institute at LMU Munich, the IP addresses listed are indicators to look for that your system might be compromised, not the victims of the attack.

Well there were two incidents (https://csirt.egi.eu/academic-data-centers-abused-for-crypto...) one of which had "unknown purpose". It had the real effect of disrupting the majority of the super computing infrastructure in Switzerland and Germany for almost two weeks now. The attacks originated from China (Shanghai Jiao Tong University and CSTNET).