skysight-inc/HackerNews huggingface dataset:
I think OKC was just a catch-and-kill by Match. When they bought them, little of substance changed afterwards, and it's just slowly decaying. Shame.
Jeesh, don't bring this up, you're apt to get ten people arguing about the X,Y problem instead, and why you should or shouldn't to 10 other things, rather than ask the user if they are on a legacy system where they can't make major changes.
USA is not going to go to war with China over Taiwan. Instead it will just pick up and move "Taiwan" to USA.
Consider calling in:
https://www.youtube.com/watch?v=k3J8FYKZ52w
You can have GPT4 inspect its own errors and make corrections- I'm sure self-reflection works better this time than GPT3.5
Maybe a combination? Even simple beamforming/stereo would be helpful to help display the speaker's location. For example, the "speaker 1" tag could appear on the left, center, or right of the display to give a spatial clue where they are located.
TerraPower which is funded by Bill Gates.
After asking him what gpt-4 is and comparing gpt-3.5 to gpt-4 he gave me a straight answer to the question "Is bing chat using gpt-4?" which was yes
> I heard

where?
Thank you, I will check them out, I think I just googled VPS and went with the top results.
>but the people still yearn to be abused

Reminds me of Agent Smith's PoV from the Matrix, that humans define their existence through suffering. The first version of the matrix had everyone living in paradise and made the system unstable as humans couldn't accept it and would try to wake up from it, dying in the process. Once they introduced misery, humans accepted the programming. Yeah, it's a fantasy movie, but it has great symbolisms that rings true.
You are incorrect and it's really time for this misinformation to die out before it perpetuates misuse from misunderstanding model capabilities.

The Othello GPT research from Harvard months ago demonstrated that even a simple GPT model is capable of building world representations from which it reasons outputs. This makes intuitive sense if you understand the training, as where possible having reversed an abstraction in the NN is going to perform better than simply extrapolating predictively from the data.

Not only is GPT-4 more robust at logic puzzles its predecessor failed, I've seen it solve unique riddles outside any training data and the paper has explicit examples of critical reasoning, especially in the appendix.

It is extremely unlikely given the Harvard research and the size of the training data and NN that there isn't some degree of specialized critical reasoning which has developed in the NN.

The emerging challenge for researchers moving forward is to get better insight into the black box and where these capabilities have developed and where it's still falling into just a fancy Markov chain.

But comments like yours reflect an increasingly obsolete and yet increasingly popular misinformation online around the way they operate. So someone reading your comment might not think to do things like what the Bing team added with providing an internal monologue for reasoning, or guiding it towards extended chain of thought reasoning, because they would be engaging with the models thinking it's only frequency based context relative to the training set that matters.

If you haven't engaged with emerging research from the past year, you may want to brush up on your reading.
What was their revenue though?
Hope it wasn't keeping its payroll money in SVB.
Introduction to AWS Container Services
it definitely learns algorithms
GPT-3.5 for me also didn't answer the question, and also gave me a MUCH longer response. I guess score a win for GPT-4.
Will be. Wind is the future of American energy. Every year it pulls farther ahead.
But what if one doesn't trust the security of docker?
Maybe a different analogy will make my point better. Compare rocket technology with jet engine technology. Both continued to progress across a vaguely comparable time period, but at no point was one a substitute for the other except in some highly specialized (mostly military-related) cases. It is very clear that language models are very good at something. But are they, to use the analogy, the rocket engine or the jet engine?
The problem is even if it has this capability, how do you get it to consistently demonstrate this ability?

It could have a dozen internal reasoning networks but it doesn't use them when you want to.
Depositors received a benefit beyond previously promised insurance and benefits. Calling it a bailout or not is based on one's personal biases or semantics.
I think its wrong to speak about Reddit as a whole. There a lot of small moderated communities where you can discuss anything without "noise". Just ignore most popular sabs.

Yay, someone downvoted me just like on a reddit!
As opposed to the doctor who has glassed with a HUD that is guiding him through the surgery, or a robot that the surgeon is guiding in VR?
True! We are using FHE to perform PIR. The underlying scheme we use is a real homomorphic encryption scheme (Regev + GSW), but yeah, we explicitly do not support performing arbitrary computation on encrypted data. As it turns out, that's still quite slow - the Google FHE C++ transpiler still takes seconds to do 32-bit arithmetic operations. Our PIR system is able to achieve much more practical speed + communication overheads.
nope. royce rolls SMR, Toshiba. Pretty much everybody invests in it.

There are others in US, but NuScale is the closest to a product.
Well, this is nice but in reality useless. You can run Linux on ancient Apple devices such as 2009 iMac but not really on anything newer.

I want to have modern peripherals and experience such as 4k display, USB-C, reasonably fast wifi/bluetooth. I don't really have a need for CD-ROM, firewire and IR port...

And believe me, I tried to run Linux on 2018/2019 MBP. Apple really really tries to makes that as painful as possible. Most of the things are behind T2 (including keyboard for example) and since there is virtually no documentation you have to rely on reverse engineering efforts of few talented individuals. Also there are things that just plain don't work such as resuming from sleep (the graphics MUX gets all confused and the driver will not re-configure it for some reason) etc... Basically nice for playing around, not good enough for running as a main device.
Capitalism disallows private and public collusion beyond what is necessary to ensure public goods, defined by those gods which are nonexcludable and nonrivalous.
> The way in which this kind of error deviates from what a human would do is generally trivial

That's not even remotely true and if you've worked with these technologies at all you'd know that. For example, as I previously mentioned, humans don't typically make up complete fiction out of whole cloth and present it as fact unless those humans possess some sort of mental illness.

> The only real difference is that you’re imputing a particular kind of intention to the ai

No, in fact I'm imputing the precise opposite. These AIs have no intention because they have no comprehension or intelligence.

The result is that when they generate false information, it can be unexpected and unpredictable.

If I'm talking to a human I can make some reasonable inferences about what they might get wrong, where their biases lie, etc.

Machines fail in surprising, unexpected, and often subtle ways that make them difficult for humans to predict.
There isn't an obvious unsupervised problem to train medical imaging with.

What's the medical imaging equivalent to "predict the next word"?
By what metric? For most stuff 3.5 is better in my experience. Assuming you are trying to complete an actual task rather than have fun.
GPT-4 has a knowledge cutoff from 2001. Bing can talk about current events.
Generative AI isn't the answer to all your business needs
You would first have to define cognition. These terms often get thrown around. Is an approximation of a certain thing cognition? Only in the loosest of ways I think.
Wrong advice.

If you want to be leveled up fast in a FAANG, you should start in one. I know of 4+ YOE people jumping one level per year, they are an exception but the argument is, it is faster if you are born into the culture, rather than if you adopt it.
>The basic idea is that the switch activates only sometimes, and only after a delay, making the action indirect and uncertain. Several Orthodox poskim have ruled as thus makes the device permissible for general consumer use.[5][6] Others, however, have reached the opposite conclusion.[2]

Wow. Well, loopholes are loopholes I guess.
A lot of them are truly awful greedy and individualistic people. The SVB collapse is just unmasking how truly influential (to the negative side) they can also be. Zero sympathy for them.
FastGPT: Faster than PyTorch in 300 lines of Fortran
Uh, it’s not following instructions, you’re altering you’re prompts until it finds the combination you expect to see…
There are plenty of other startups and established players pursuing NRC approvals for other reactor types. Here's [1] a list put of reactors that the DoE is working on (together with private partners)

[1] https://www.energy.gov/ne/articles/infographic-advanced-reac...
I never said it wasn't - I know people who work in those facilities, and it takes a massive emotional toll. I'm just suggesting that the scientists who don't deal with their own animals aren't doing it because they're callous - it's because we need people who will do it right, and with minimal suffering to the animal.
If automation can make tax code easier to be in compliance with, does this imply a reduced cost of increasing complexity and special exceptions in the tax code?
This way the model would also be able to generate images, I would also be curious how they handle images with different aspect ratios (and maybe resolution so it can read well on papers).
TBH, even in the last few months you've been able to get comparable comp packages at the high end of senior and staff levels at public unicorns. G is no longer particularly competitive comp-wise.

I suspect the issue was that FAANG was massively overpaying junior talent fresh out of school (and hiring leetcoders without any engineering background) and now they're correcting.
they haven't given any sign that they will limit the access. They have given signs that they are capitalists & are ready to do a lot to make money, like not putting a list of authors on the GPT4 paper & not write anything about the model architecture or training process
I have. It wasn't great, but it worked, and that was years ago. Is that the reason, though? tRPC generates a nicer client when targeting the browser?
This is a particular alignment issue. People are used to people spouting bullshit all the time, as long as it's aligned to what we are used to. Take religion for example. People tend to be very confident around the unknowable there.

It is scary in the sense that people love following confident sounding authoritarians, so maybe AI will be our next world leader.
> What is stopping our adversaries from developing malicious AI models and unleashing them on us?

That fear is a big part of OpenAI’s reasoning behind not open sourcing their models. So in the immediate terms I’d say malicious uses are limited by its locked down nature. Of course, that’ll eventually end. The key research that makes this possible is open and eventually access will be democratized.

My personal take, which I know is controversial, is that by locking down these models, but still making them available over a GUI/API, the world can better prepare itself for the eventual AI onslaught. Just raising awareness that the tech has reached this level is helpful. Still not sure how we’ll deal with it when the bad actors come though.
Who knows / cares? Their product is the stock itself that was then sold to the acquirer.

The show Silicon Valley has a great parody of this fact: https://www.youtube.com/watch?v=YZFTaEenaHM
Python-based compiler achieves orders-of-magnitude speedups
Disagree. Imo, you should be at a FAANG company at least once. I liked all the jobs and internships I took and a few of them are arguably better than FAANG (hft/unicorns), but when it came time to interview for other places, I had a much harder time getting past resume screens vs my friends who were from a FAANG company.

Imo having a FAANG company on your resume provides flexibility. Also, FAANG jobs are just nice. You have a lot of creature comforts that will make your first few years out of college much easier (Good 401k matching, liquid stock, good benefits, plenty of locations to chose from, wide selection of teams, free food, etc). Ive been at "good" companies without many of these benefits, and while the work is interesting, your quality of life suffers greatly.

Also eng talent is generally pretty good at FAANG from what I can tell. You have a lot of really senior people showing you the ropes, vs a startup which may be led by younger people who may be smart, but lack experience.

If you are dead set on some career path that doesn't require you to be at a FAANG company (i.e you got a job somewhere and you are satisfied with being there for a while), then sure it may not matter, but for a general SWE, the flexibility, resume value, and scope going to a FAANG company gives you is very valuable.

Note: I am using "FAANG" here to mean FAANG + Similar adjacent companies. Think Uber, Microsoft, Airbnb, Datadog, etc.
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We are currently looking for an IoT engineer (Electrical/Mechanical) and will have a few more jobs up soon for Software and Data Science. Feel free to drop a message to david.hagan@quant-aq.com with any questions.
That's ridiculous. DL makes some really bafflingly stupid choices that make its product near-useless for serious study.
Nah, this is the second part of the industrial revolution. First part replaced and augmented physical abilities so instead of making things by hand we automated away a large portion of the work but not all of it. This is augmentation and automation for intelligence. Yes, a lot of what we currently do "by mind" will be automated but these systems have their limitations. It's still going to be crazy though, imagine what it was like to be the town blacksmith when they first heard of a steam hammer. Nowadays we have very few blacksmiths but we have a lot of people designing parts that will be made on a CNC. What is the role of the human once the labour of clicking away at a mouse hunched over a screen to produce a part is automated? Now we just discuss the end product with the AI, look through some renderings, ask for different versions, ask it to run simulations, tell it to send the file to the CNC? Now that anyone can "design" a part or a whole product by talking to an AI what kind of new jobs does that entail? There might be a big demand for computer controlled production of one off designs. What kind of incredible inventions and wonders can we create now that we can basically conjure our thoughts into existence? There's going to be a whole cross-disciplinary science of combining various areas of human knowledge into new things. Too bad Disney already coined Imagineer.
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Goldman Sachs bought SVB's bond portfolio, lender says
What would a benchmark even look like?

Does it make useful code? Does it make the same code?

Or more strictly on something like latency and cost?
What's the license for Redpanda? I couldn't find anything but maybe it's because I'm on mobile.
I don't understand how in the near future this will not remove designers, developers, and especially lawyers and marketers from the workforce.
Help me out to conceptualize the future use cases.
How about the more "impactful" implementation in creating a version of social index in which the "A.I." will be the Agency?
1) No clue

2) Yes, I know people with start dates in the fall at F and A (the fruit, not the river), and it looks like they intend to honor those offers.
The /r/sandiego subreddit, for instance, is controlled by a weirdo who masquerades as two moderators and who will shadowban you for merely participating in the subreddit created to escape his control(/r/sandiegan).
This is a non sequitur if ever I've seen one. The board of directors has the specific ability to fire the leadership of the company, that's where they get their influence and power.
Or, go to work at a large company (my company has nearly 100,000 employees) that is not a FAANG company. No bs leetcode interviews, much better work-life balance (I maybe put in 30 hours a week and have enough vacation stored up that I could potentially take off 5 months right now), I've never met an asshole engineer or manager, etc.
it makes shit up still
> Every time the FDIC has stepped in like this they have made all depositors whole.

This is a false assertion. Usually depositors end up losing some of their money above the insurance limits-- only not doing so if the amount of remaining assets proves sufficient to pay the liabilities.
You mean like the cloud?
Why would we believe that, though? Why bother with the extra layer of indirection, through an environment we know even less about?

Then there's the fact that life appeared on earth almost as soon as it was possible for it to exist. Either it was easy and formed really quickly on Earth, or space is/was so full of it that earth got contaminated almost immediately... which still implies life is common and easy. Panspermia just doesn't help.
If it’s a rate limit, give it a progress bar. Currently people just see “ Please check again in a few days.”

From what I can tell, people are at 10+ days with no clarity as to what’s going on. With Reddit down, I can only sort of see some of the posts from google results. There’s some mentions on Twitter too, starting almost two weeks ago.

10 days is more than a few.
Can GPT be used for something like feeding it a 2000 page PDF of pure text(not english) and ask questions about its contents?
It still makes up stuff.
VMware charges people per GB RAM attached to a VM. Selling on-prem software on consumption is very much possible. It's closed source software, so as long as they require 443 outbound to tick consumption that'd work.
What's the American plan for baseline energy generation?
Sure, but at the end of the day, a bunch of these startups withdrew large amounts of money successfully. Claims that you can't do that are simply false, at best conditionally true.
Those countries are pretty far from achieving big S Socialism.
Asking a LLM trained on the internet, full of computer specialists blogging and posting data non-stop for decades to perform something that can be found in a textbook is like asking a human to flex a muscle.
Two thoughts:

1) Vet techs have been some of the kindest, most patient people I have met. They are humans, which means some of them are nasty, but between the compassion fatigue, the relatively low pay for the amount of training, etc., I don't think "nastiness" is selected for.

2) Difficulty hiring is one. Difficulty firing is another, if they're at a state university. But there is a national shortage of these types of technicians, and it's not a job that can't get done.
Presumably, if you give it identical prompts you get identical answers?
As taken from the cover page of the July, 2018 edition of AARP Weekly.
I'm not using new Bing until the Edge requirement is gone. I have no interest in Edge. It is unfortunate MS is playing that tacky game of requiring/pushing an unrelated product just so you can try another product. I highly doubt there is a technical reason Bing can only operate in Edge.
This site was created by a SV tech billionaire and it's owned by a startup incubator. It was originally called "Startup News." The "Hacker" in "Hacker" news refers to hacking capitalism. This is literally the axis mundi for those people.
> has the drawback of older tech like X11.

Not everyone considers that a drawback.
This seems really cool for a company that has enough surface area of software where chances are somebody has already built the thing you need and instead of building a copy yourself, you can integrate with the existing system
Based on experience with the kids drawings I’ve seen, I’d say getting the right number of fingers is definitely the rare thing up to a certain age, but specifically drawing 7, probably not that common I guess.
Yeah, very unusual. Purpleteam is usually over some prod or prod-like environment.

I think they want you to put this in your purpleteam lab not as your actual defensive stack.

Might work for some folks but imo, the logging/detection/alerting part should alway be your actual prod stack but you can simulate attacks in a lab environment. What I have seen in the industry at large is a lot of purpleteam excercises are done in production, a red team excercise blended with a blue team investigation and response.
Lemmy doesn't seem to offer anything to me. It probably offers something tangible to certain groups with opinions that are not well represented elsewhere.

The fact that it's federated under the hood is not a feature that would matter for most people, at least as far as I can see. If it meant that I can easily move my conversation elsewhere then yea I can see that, but I really can't, and it only further divides my comments across yet another silo.

Would be happy to be corrected if I'm wrong about my impression.
With this example, a human can examine the implementation of the doesHalt function to determine what it will return for the input, and thus whether the program will halt.

Note: whatever algorithm is implemented in the doesHalt function will contain a bug for at least some inputs, since it's trying to generalize something that is non-algorithmic.

In principle no algorithm can be created to determine if an arbitrary program will halt, since whatever it is could be implemented in a function which the program calls (with itself as the input) and then does the opposite thing.
I think it is important to know, as a user, how things roughly work. Now we don't know how they fixed previous flaws or what the drawbacks are.
There are several missing words from your sentences that make it very difficult to understand them.