elementalest

This. Its been around for over a decade and has all the features mentioned.

Isn't that whats happening to a certain extent with wasm?

What is the alternative?

If cheap labour is no longer possible/desirable, then near fully autonomous factories driven by next-gen AI and robotics becomes significantly more viable.

From Mozilla's point of view its probably that people might get confused between the old and new themes and wonder why all the highly customisable themes we use to have no longer work. So we have to have a new the colourways name so Mozilla can market the 'new' feature and sidestep the problem.

I don't think its about best practices, its about good design and communication. Even if we are just talking about PhD students, the majority of them are fresh graduates. They are no different than fresh grads in a company. Those grads work with experienced senior software engineers to guide them and provide design advice (not just best practices). Those engineers are often the ones writing the complex/difficult areas of code.

RSEs should not be writing code for students doing PhD level projects in my opinion

So should a mechanical engineer PhD be designing and making all their own robot parts? Or should the shop engineer help them? The few mechanical engineer PhD's in robotics I know made a few early prototype test parts themselves with help from the shop engineer, but the shop engineer made and even helped design most of it, especially the final prototype.

As you say, this is a great idea in principle. In reality I think that it's really difficult to make it work.

The point I'm making is that it does work and its proven to work very well (which is why the major industry labs do it). In my experience its Academia that doesn't like it. Anything which appears to take power/freedom away from scientists and gets in the road of their research is rejected. Though I think the core reason is (as other comments have mentioned), there is no incentive for Academia to make it work. The funny thing is that having a RSE working with them would actually help the scientists in the long run and allow them to focus more on the research because they wouldn't have to do everything themselves.

RSE's can and often absolutely should be involved at the PhD level. In my experience, collaboration between the scientist and engineer in the process of research iterations almost always produce better results. Each has insights the other may not, likely leading to better outcomes for the research, final product/tool and time taken.

The scientist just wants to focus on their research and once they have a barely working proof of concept, hand it over to the engineer to figure the rest out. The engineer wants a well specified design and prototype that they can lightly refactor to clean up, scale up and turn into a product/tool.

The reality is that approach makes it way harder for both, though most often harder for the engineer as they are generally at the end of the chain in Academia and have little power. For example, the code or spec from the scientist is often terrible, so the engineer needs to start from scratch and keep going back to the scientist to spec out the design as they were not involved at any stage prior. They may even find edge cases or flaws the scientist had not considered that are fundamentally problematic to turning it into a viable product/tool.

This is why the big corporate/industry research labs often have high level RSE that are involved in the research process and get their names in papers (they sometimes have PhD's themselves). They are not optimising for the scientists time, but for the companies resources

As I mentioned in my other comment, the gun related deaths halved 2 years after the gun laws [1]. Furthermore, in 1996, the gun deaths per capita were 2.84, the homicides were ~650 per capita. So of course you will barely see a difference with the homicide graph. The real difference is that there have been no mass shootings for 20 years.

So yes, it really is that simple and completely obvious.

[1] https://www.gunpolicy.org/firearms/compareyears/10/rate_of_a...

Yep, my mistake its 25 years, not 35. Though the difference doesn't negate the point that its been decades since a gun related massacre.

That linked source is for all massacres, most of which are not gun related and have < 6 deaths. Even if you include the 2002 Monash University shootings, its still 20 years.

If you look at [1], when the Australian gun laws came into effect, a year later the per capita number of gun related deaths halved. 25 years later and its halved again and the trend continues downwards. For reference the US numbers are here [2]. What is interesting is that when comparing the number of firearm possession per capita between the US and Australia, the US has roughly 10 times more guns [3]. Based on [1] and [2] the US has roughly 10 times the number of gun related deaths per capita. The reason why Australia has historically had less problems than the US with gun violence is that even at Australia's peak, it had 5 times fewer guns [4] than the US [5] did per capita.

[1] https://www.gunpolicy.org/firearms/compareyears/10/rate_of_a...

[2] https://www.gunpolicy.org/firearms/compareyears/194/rate_of_...

[3] https://www.gunpolicy.org/firearms/compare/10/rate_of_civili...

[4] https://www.gunpolicy.org/firearms/compareyears/10/rate_of_c...

[5] https://www.gunpolicy.org/firearms/compareyears/194/rate_of_...

Interesting. When compared to places like Australia, where guns are highly regulated and barely anyone owns a gun, such that there have been no mass shootings for 35 years, the solution really is obvious.

Decoders are notoriously harder to support than encoders due to the various internal formats and encoding/decoding options. Until it supports all the different formats (a lot of effort), it will only be able to play back a few videos.

By focusing on an encoder (at least initially) you can just support a subset of features that work well for you. Then focus on making a decoder that can at least play back videos from your encoder.

More people will find it useful to have an encoder that works all the time, rather than a decoder that only works on a subset of videos.

Then you get things like this: https://youtu.be/syiSYMPwFck

I get that the most direct way of learning is to make mistakes and learn from those. But there's an easier way too. Read books, talk to people, get the benefit of others experience without needing to make those same mistakes again.

We don't go about individually discovering why modular design is a good thing, or why at certain scales microservices are a better option. We do the research, talk to others, and figure out that the general consensus is a reasonable one that we can use.

I think we need to do a better job at explaining why something is a bad idea to junior developers. Learn to see things from their perspective, and communicate in a way that relates to their experience rather than ours.

Not everyone learns the same. Some people may learn significantly faster and/or more effectively if they are allowed to make mistakes - to see/experience the difference. I think this a good approach for simple problems. However, if the problem is highly complex and time consuming, its not as practical as the time cost to redo, as the work is too high. Thats where you do the research and reading. It requires a balance.

You misunderstand, I'm saying that if Telstra were properly separated right from the start (when the Howard government privatised it), the Rudd government could have easily gotten Telstra wholesale to do what Chorus in NZ is doing now. Most of Australia would probably have FTTP by now, or at least FTTN/HFC.

I do agree with the rest of your comment though.

When the Liberals privatised the government owned monopoly telco (now called Tesltra), they didn't properly structurally seperate it in the first place. The government, like NZ, could have gotten the wholesale part of Telstra to start upgrading network infrastructure. If they had done it properly the first time, we wouldn't be in this mess.

Yep, and try getting the government to pay the billions required to get public transport up to standard to be able to just provide adequate transport for the majority of people in those cities.

I worked for a BLDC company in their research division for a few years and there are many things that can still be improved. At the time we were working on reducing the size of motors without sacrificing torque or efficiency. This was particularly the case for industry motors where we developing a motor half the size of an older industry standard AC motor, but with the same power and 94% efficiency.

Size is where the majority of advancements for BLDC motors will come.

Due to the publication requirements/incentives, academia greatly favours those who take on short term low risk research that will likely result in a few quick easy papers. Furthermore, due to the limited positions available in academia, generally only those who are good at this will rise up in academia.

Getting to a point where you control your own research and have financial stability for research that could span 3+ years with very little output (paper wise) is something comparatively few academics achieve. Even fewer of those who have, did so by conducting longer term research. Most academics I know are just trying to produce as many papers per year as they can and do whatever research in their field they can do, to do it.

Unless I'm mistaken, if you're using smart pointers, the memory wont be freed until the destructor has executed its code. Use after free should only be an issue if you're using raw pointers.

Whilst I agree it is hard to consistently write safe/secure code in C for increasingly more complex code bases, and that C is no longer the best tool for the job in these cases (there are better tools/languages out there), I think the author unfairly lumps modern C++ (>C++11) in with C. Modern C++ has many of the tools necessary to mitigate many of the problems C (and <C++11) can encounter.

I do think Rust is a viable replacement for C, but not a replacement for modern C++, rather an alternative - at least for the foreseeable future.

Even when only part of a system/process can be automated and it looks like the rest is too hard to automate, doesn't mean there wont be ways around it, or ways to cheat. Just look at how automation in factories has developed. Sometimes all it takes is to change the process slightly.

In the case of your delivery example, a person is not necessarily required to drop off the package. A system could be setup where you can request a delivery time frame for your package (e.g. between 7-9pm). When the autonomous delivery van arrives, it parks outside your house and notifies you of its arrival. You go down, scan your card and the van dispenses your package. The van then goes off to its next delivery.

In the second last paragraph the author agrees what you argue in your comment is possible:

Finally, it’s conceivable that the ostensibly tranquil and low-turbulence economy is masking something more disruptive underneath the surface. Ryan Avent, the author of The Wealth of Humans, has thought about this question deeply and offered a plausible explanation. In his telling, automation has created an abundance of labor, including machine labor and human labor. Just as rising supply typically leads to falling prices, the oversupply of labor has put a downward pressure on wages. Companies, seeing that they have access to cheap labor in a slowly growing economy, invest less in new risky technology, which leads to less productivity growth. High employment, low productivity, low wage growth, and automation can all live together in the same story.

I think the term artificial intelligence is incorrect. What we're currently building is, IMO, artificial intellect.

The rest of your comment contradicts this statement.

Dictionary definition of intellect is "the faculty of reasoning and understanding objectively, especially with regard to abstract matters". Dictionary definition for intelligence is "the ability to acquire and apply knowledge and skills".

Current AI has great difficulty in abstract matters/thought, let alone understanding something beyond simply a series of learned patterns.

If we want to build intelligent machines, we have to understand the architectures of the mind.

We have intelligent machines now, many which outperform human capacity for specific tasks. If your talking about strong artificial intelligence, then I wouldn't necessarily disagree, but maybe it could go the other way. By developing strong AI, we can understand the architecture of the mind. Maybe strong AI can be developed with the intellect of a cat/dog, and that gives insight into the human mind.

We believe we're going to develop "artificial intelligence" by building massive computers and data centers. How absurd is that?

No one who is knowledgeable about AI actually believes this (based on your definition of AI).

Folks, to build intelligent machines, we have to build thinking machines and for this, we'll have to truly understand how the mind works and when we do this, I believe we'll be quite surprised.

You ask the question "what is a thought" above, then state we need to have thinking machines to make intelligent machines. One could argue machines today think, one could argue alphago 'thinks'. Using your definition of intelligence, we have AI today that meets your requirements. Wisdom is knowledge with good judgement and creativity is exploration with experimentation. There is plenty of academic work out there which covers all this.

One has to wonder if its actually just an AI doing web scraps looking for 'news' and posting a summary or just direct excerpts from the source. Then changing/adding a few things it knows are clickbait/headliners.

If this isn't being done, it seems like something that could potentially be achieved with current tech, if not now, then in the near future.

Maybe its not so much that nobody learns, but that its something that is generally best learned through experience. Its hard to self assess and self deception is easy. So society keeps repeating the same mistakes, even though those who have experienced and learned from it are actually talking about it.

To me it seems much more like a societal/systemic problem - one that will not be easy to fix, especially with the increasing inequality and rise of automation. The demand for achievement and lifestyle upheld by society as something worthwhile to strive for (for happiness, fulfilment, recognition etc), just perpetuates the cycle and will be become harder to attain.

What are those to think/do who did not reach what society taught them they should want and have to be happy and fulfilled? These people put the effort in, but get nothing back. They get burnt out and depressed and even though they later talk about it, others cant understand as they don't have perspective and/or don't think it will happen to them. They are too busy burning themselves out chasing the goal.

I don't think there is a solution that doesn't involve a radical shift in society and work/life balance.

Instead, preserving it to study and learn things about game development at that time would be far more valuable for the common good.

Given the game recently went free to play and many people still play it, its not surprising blizzard are not releasing the source. If the game had been dead for 5-10 years, then sure, they should probably release the source. Its still going strong and shows no signs of stopping in the next 5-10 years, especially now due to the remaster.

There are plenty of other games out there to learn from using the source, if that's your goal.

For goodness sake this thing is older than half of people on HN.

Are you saying that half of HN are younger than 19? I would have thought the average age on HN would be somewhere around 30. I would expect the average HN person was a kid or teenager when Starcraft was released.

I followed reference [2] and the highest voted answer (not the selected one) concludes:

I think the results speak for themselves and demonstrate unequivocally that LLVM is perfectly suitable for JIT compilation.

On windows I can chance the scroll speed so its one line per tick, on ubuntu its stuck at 3 lines per tick. I have a logitech 'spinny wheel' and this makes it very frustrating as the screen zooms by and I lose precision.

My experience with spideroak has overall been very poor as I discussed in a previous thread on HN [1]. I have since moved away from spideroak and am using duplicati [2]. Honestly, things have been much better since then. I have not had any issues, and whats more, duplicati is free and open source.

[1] https://news.ycombinator.com/item?id=13306745 [2] https://www.duplicati.com/

I'm just curios, disregarding performance aspects, what is there to like about w10 over, say w7? Two things that have put me off upgrading to w10 is the inconsistency of the UI, and the fact the user has less control over the system in a variety of ways.

Adaptation can take a while (particularly if its generational). Many things have to go right for it to happen smoothly. While society and people are adapting, there will likely be many workers who are unable/unwilling to re-skill to compete in other job markets. Many people will be without work as those markets will become highly competitive. They will also likely require years of university, increasing the economic load on society.

You seem to have a lot of faith in education systems in a capitalist environment. My own observations is that universities are just enrolling students in courses regardless of there being jobs available in those fields or not - as long as they are making a profit. I doubt governments can move fast enough to develop proper education systems to educate the population for modern day jobs.