As a professional and expert I would love to hear your thoughts and opinions on the use of elliptic curve crypto with SSH. There was a concern (unsure of the validity) that NSA/NIST had compromised the algorithm used and ECC was unfit for 'secure' communication.
2048bit RSA has been deprecated since that declaration and while 4096bit is still viable, the smaller key-size of ed25519 is appealing.
Ever since the DUAL_EC_DBRG backdoor[1], trust in cryptographic algorithms set by NIST has been reduced.
In the case of ECC curves, the NIST curves rely on a number of highly specific but unexplained constants. More info about the safety and security of curves can be found at https://safecurves.cr.yp.to/
I was quite proud of the fact that i could easily out-type my 1200 baud modem.
Tech improved and so did my typing.
Late-night C64 BBS's when the sysop jumped in and started talking to you in real-time was the biggest pressure cooker to learn to type, to learn to type fast, and to watch the screen while you type.
The came IRC, and well; in busy channels it was tricky. Today Slack feels slow with all the animated crap.
>The long-term side effects of GLP-1 drugs are not well-studied
The long-term effects of diabetes is.
For me, this was the _ONLY_ thing that brought my blood sugar under control.
Even with severe dietary restriction, my blood sugar would be dangerously high first thing in the morning after fasting 12-16hrs.
The 'potential side effects' of the drugs that I was taking was terrifying. And the list of drugs that I was on was so long that even if there was only a 1% chance that I'd catch a side effect from 1% of the drugs then my prospects went down to nil.
I was scheduled for gastric-bypass surgery.
I can modestly say that ozempic probably saved my life.
I've lost ~100lbs (~45kgs) and I can now wear the same size clothes that I wore in high-school which is a nice benefit too.
steamos is the only one ive used in recent years (steam deck) but i've had pretty much no problems with it, i virtually never encounter a game that won't run
OpenBSD at the Edge.
FreeBSD on the internal servers.
FreeBSD or Linux as a daily-driver. (I can't settle)
You are trying to decide what-OS to base your work on. That depends on what your work is.
If you are looking for cutting-edge? Go with Linux.
If you are looking for a 'whole-system' approach? {Open|Free}BSD
I'd say we need more details if you want a better answer.
I agree and disagree with you. Same 'grumpy old sysop' energy.
Same as you I, ssh into 100 different servers on dozens of client networks. Too many have a stupid amount of restrictions in the name of security that prevent changes or enforce settings.
i.e. One client has a 'forced' PS1 output that shows:
RAM free/total
HD space free/total
CPU load
TOP cpu item
Previous command
All with obnoxious colours AND blinking if a threshold gets met.
.bashrc (and associated)is read-only (and) overwritten at every login.
But, I can `source .my-env` And bring sanity to my session.
I'd rather have a 'default-plain' then some forced-bling that a dev thought was cool 20 years ago.
I'm ignorant on this topic so please excuse me. Why did `AI` happen now? What was the secret sauce that OpenAI did that seemed to make this explode into being all of a sudden?
My general impression was that the concept of 'how it works' existed for a long time, it was only recently that video cards had enough VRAM to hold the matrix(?) within memory to do the necessary calculations.
If anybody knows, not just the person I replied to.
1986: Geoffrey Hinton publishes the backpropagation algorithm as applied to neural networks, allowing more efficient training.
2011: Jeff Dean starts Google Brain.
2012: Ilya Sutskever and Geoffrey Hinton publish AlexNet, which demonstrates that using GPUs yields quicker training on deep networks, surpassing non-neural-network participants by a wide margin on an image categorization competition.
2013: Geoffrey Hinton sells his team to the highest bidder. Google Brain wins the bid.
2015: Ilya Sutskever founds OpenAI.
2017: Google Brain publishes the first Transformer, showing impressive performance on language translation.
2018: OpenAI publishes GPT, showing that next-token prediction can solve many language benchmarks at once using Transformers, hinting at foundation models. They later scale it and show increasing performance.
The reality is that the ideas for this could have been combined earlier than they did (and plausibly future ideas could have been found today), but research takes time, and researchers tend to focus on one approach and assume that another has already been explored and doesn’t scale to SOTA (as many did for neural networks). First mover advantage, when finding a workable solution, is strong, and benefited OpenAI.
This is not accurate. OpenAI and other companies could do it not entirely because of transformers but because of the hardware that can compute faster.
We've had upgrades to hardware, mostly led by NVidia, that made it possible.
New LLMs don't even rely that much on that aforementioned older architecture, right now it's mostly about compute and the quality of data.
I remember seeing some graphs that shows that the whole "learning" phenomena that we see with neural nets is mostly about compute and quality of data, the model and optimizations just being the cherry on the cake.
> New LLMs don't even rely that much on that aforementioned older architecture
Don’t they all indicate being based on the transformer architecture?
> not entirely because of transformers but because of the hardware
Kaplan et al. 2020[0] (figure 7, §3.2.1) shows that LSTMs, the leading language architecture prior to transformers, scaled worse because they plateau’ed quickly with larger context.
I know this is just a short history but I think it is inaccurate to say "2015: Ilya Sutskever founds OpenAI." I get that we all want to know what he saw etc and he's clearly one of the smartest people in the world but he didn't found OpenAI by himself. Nor was it his idea to?
Ilya may not be the only founder. Sam was coordinating it, Elon provided vital capital (and also access to Ilya).
But out of the co-founders, especially if we believe Elon's and Hinton's description of him, he may have been the one that mattered most for their scientific achievements.
Short histories remove a lot of information, but it would be impractical to make it book-sized. There were numerous founders, and as another commenter mentioned, Elon Musk recruited Ilya, which soured his relationship with Larry Page.
Honestly, those are not the missing parts that most matter IMO. The evolution of the concept of attention across many academic papers which fed to the Transformer is the big missing element in this timeline.
AI has been happening "forever". While "machine learning" or "genetic algorithms" were more of the rage pre-LLMs that doesn't mean people weren't using them. It's just Google Search didn't brand their search engine as "powered by ML". AI is everywhere now because everything already used AI and now the products as "Spellcheck With AI" instead of just "Spellcheck".
w.r.t. Willingness
Chatbots aren't new. You might remember Tay (2016) [1], Microsoft's twitter chat bot. It should seem really strange as well that right after OpenAI releases ChatGPT, Google releases Gemini. The transformers architecture for LLMs is from 2014, nobody was willing to be the first chatbot again until OpenAI did it but they all internally were working on them. ChatGPT is Nov 2022 [2], Blake Lemoine's firing was June 2022 [3].
Thanks for the information. I know Google had TPU custom made a long time ago, and that the concept has existed for a LONG TIME. I assumed that a technical hurdle (i.e. VRAM) was finally behind allowing this theoretical (1 token/sec on a CPU vs 100 tokens/sec on a GPU) to become reasonable.
Residential users make up ~38% of the electricity market in the US.
Where do you suggest the rest of the users should get power from? And how would that work exactly in reality?
Even of the government had to ensure that everyone has access to affordable electricity they'd still have to buy it from someone which fundamentally doesn't change anything.
Profit is… not fake, but fiat. Energy and clean water are real.
With collapsing demographics the current economic system will fall over anyway, either due to inflation or defaults, so maybe it’s a good time to start thinking about how to separate utilities from money.
If I had answers, I wouldn't be saying that it's a good time to think about that.
But you shouldn't assume that things will just continue on as they were in the past hundred years. Boomers are retiring now, when the busters start going into retirement it's going to be a huge mess. Inflation is how democracies die.
Capitalism is the extraordinary belief that the nastiest of men, for the nastiest of reasons, will somehow work for the benefit of us all.
-- John Maynard Keynes.
I think he's onto something as I see the lengths Boing, Intel, FAANG, et. al going to benefit us all everyday...
There are so few corporations which build things to better the world and make money in the process.
99% of the corporations build things to earn money. Their wares sometimes do no harm, but it's the exception.
In many cases, the desire for money, not the need, is the driving force behind the technology. See n startups which are discussed here and categorized as "this is better as X. they're just trying to earn money with no real benefit to anyone".
Did Exxon hide their global warming research to benefit humanity? Of course not. Did Tetra Ethyl Lead added to gasoline instead of Ethanol, just because it was better? No because it was patentable and ethanol was not. Did WV created "better" diesel engines to benefit the humanity? No the engines were only "better" for their bottom line and problematic for every one. Did DuPont hid the effects of forever chemicals because it was beneficial/harmless to the nature? On the contrary.
Companies do whatever they can without breaking laws (or bending them with money) to earn more money. The products we get are side effects of it.
I like this take about current (Generative) AI hype:
The true purpose of AI is to allow wealth to access skill without allowing skill to access wealth.
-- jeffowski (at Twitter/X)
> Their wares sometimes do no harm, but it's the exception.
I disagree with that to a very extreme degree (also it's a very silly thing to say unless you don't see any value in computers, smartphones, planes, automobiles, washing machines, fridges and other appliances).
The things you listed are generally the exceptions. Also the question is whether society/people benefited from VW, Exxon, DuPont etc. to such an extent that it outweighed all of those things?
Of course it's relative, if we value access to cheap and effective transportation, synthetic clothing, various plastic products etc. more than we care about all the negative externalities that's what we get... It's all down to incentives, corporations are inherently neither good nor evil.
> to earn more money. The products we get are side effects of it.
I agree that's true on the whole. But that's why humans do anything at all (replace money with other tangible or intangible benefits). Absolute altruism doesn't scale and isn't in any way sustainable.
They did when they were led by people passionate about the technology. As soon as MBAs got ahold of them, it was all about enriching shareholders in the short-term.
Who pays for it?
If everybody gets all of the above for free, then why would they ever work and contribute to covering the cost of these free for everyone services?
Once a large number of people stop working, who actually works to grow the food? Who builds the houses?
It's interesting that you bring up a large number of people no longer growing food as if that's not the current reality. What do all those people do now that they don't have to work for food?
Someone works grueling hours in the sun to grow it and then the rest of us work and pay those people that grew it money. Is this really a question?
If the people doing the growing are getting all of their needs met why would they grind to produce food to sell for money when they get money for free?
Why would the vast majority of people in the bottom 50% of the economic ladder work at all if they were getting all of their needs met at no cost to them?
Why stop there? EVERYBODY deserves healthcare and education too!
I would say in a perfect world everyone should have all of these things.
The problem is that the marginal cost to giving each of these things to everyone increases to infinity as we approach 100% of a sufficiently large and diverse population. For example, creating a city water system should efficiently deliver clean water to a large proportion of an urban population. However, not everyone lives in an urban setting and delivering clean water to remote populations can get astronomically expensive.
As rational citizens we must acknowledge this unfortunate reality and figure out how to deal with it fairly and equitably. Profit seeking enterprise has been astoundingly effective at driving down these marginal costs for a whole host of goods for centuries. Many of these things you mention only exist because profit seekers developed and distributed them!
I have a custom domain with a site-specific email. No 2 sites have the same email address.
I have not seen any activity using that 'hacker-news' account.
Not saying your experience isn't accurate, providing one additional datapoint for analysis.
