This is whats wrong with articles. You can never know the motive behind them. There’s no way this article is actually written organically and the big corps aren’t paying them to write this. There should be some regulation stopping this. Basically any company with money can now spread their own propoganda.
It’s not just this, you search about anything on google, any subjects there’s hundreds like this. You search if eggs are good you get hundreds saying how they’re great for you and if search if eggs are bad you get another hundred. It’s becoming impossible to be able to sort from good and bad articles. Even the research behind them many times can be paid by the corps. This is not good. There has to be a mechanism that changes this.
I wonder what kinda data they will get cause most people who code and do heavy stuff I think are on mac/Linux so I wonder how good the data they gather be you know? Mostly moms and dads using their computers wrong this is what I imagine my head is the data they gather, like maybe 50-60% of it lol and heavy users with good data are nowhere to be found
> What the hell is the "wrong" way to use a computer?
Searching for your bank's website rather than bookmarking it, and entering your credentials into the phishing site that's the top result.
Installing Anydesk or something for the "nice gentleman who called me from Microsoft to tell me my warranty had expired and he needed gift cards to pay for it."
Those are the two most obvious ones I can think of. There's a multi-billion dollar "industry" separating especially older people from their money using computers.
Frankly if you've even been around computers for 50+ years and haven't encountered the many and varied ridiculous ways people can use them "wrong," I have to wonder whether you've ever had to deal with regular people using them in the real world at all.
Eh, I'm a pretty advanced user by any mean, and I still search for my banks website a non-trivial amount of time. I have a bookmark, but it's honestly just as fast to do it that way
Is not wrong because it is slower. It is wrong because it is a security problem. A typo in your search or a phisher who managed to SEO their results above the genuine one, and you end up on a malicious site identical except for a hard to spot detail in the URL. You enter your username and password, and probably even helpfully do the 2FA dance for them to let them drain your account.
Actually I loved it. I dont think they have any grounds to sue. Its different and close enough. Also they wouldn’t sue a project on github, if they do they show their faces its worse for them. Also many forks will happen and they have to sue many. Worst case you change the name of the repo. Thats the power of open source ;)
Yuzu’s downfall was not the repo, it was their Discord. They were sharing DRM cracking keys on there and getting paid $30K/month on Patreon. It’s the same reason most emulators require you to bring your own BIOS.
Thank you so much for posting this and ofc the creators. My brother and I were in a debate and this just proved my point. Feels real good to see it. Cant wait to try it ;)
I think the problem with it is more about how it’s emphasizing hardware physical attributes of the device but apple is mostly about the culture and the feeling in their past ads. When u buy an iphone u know ur not getting the best hardware but you but it for the culture and the feelings it gives you no?
Well after the XZ attack, I was thinking how common this can be. Good to know that at least im not the only one and others inside the community are wondering about this. I hope someone is smart or lucky enough to find a solution to at least be able to lessen the impact of these attacks. I still wonder how many more of these are there, and my question is because of these attacks, isn’t open source more prone to these compared to closed sourced software? Usually the argument for open source is because everyone can read the code, its less vulnerable but now because everyone can write the code and have big incentives to do malicious stuff, doesn’t it make open source worse?
Many open source projects just don't get enough attention for the 'many eyes' benefit of OSS to occur. Many projects are neglected and poorly maintained, with little participation from the users.
I don't think OSS is particularly special though. If a state actor threw cash around they could find folks at many big companies to do their bidding. In my experience, commercial software reviews are susceptible to the same sorts of attacks as those listed in the article("please review my change ASAP because it needs to go into the next release before the deadline!").
I don't know what to do about this. You could subject approved submitters to better background checks. You can improve automated threat detection and code analysis. You can switch to safer-by-default languages that make backdoors and malicious behavior more obvious.
I wonder if the same issue exists in other engineering fields? Has anyone ever bribed an engineer to make a bridge or a water supply less robust?
Ah, misunderstood, you mean something like a sneaky sabotage? Hm, don't recall any, the payoff seems to be too small and unpredictable? But I think there were cases of "poisoning" the design of some weapons
The problem is, we don't know. I've seen PRs that could be curious students, or it could be a first try to see if we are paying attention. It's really easy these days to produce a halfway decent looking PR for someone in their first year of uni and my worry is that an increased volume of low to medium quality contributions will lead to maintainer fatigue. Depending on the project, that may be the point where pressure can be applied to share maintainership.
I agree with you somewhat. You are correct unless they have a much better GPT model that have not released for whatever reason. They are a year ahead than competitors and GPT4 is pretty old now. I find it hard to believe they don’t have much more capable models now. We Will see though
The polish of OpenAI stuff when released has been quite mature since gpt4 or even 3.5.
They are no doubt sitting on ultra polished stuff. When you are the tip of the arrow though and the cutting edge itself it might not be as efficient but does it ever show you things you can’t unsee.
When OpenAI can launch a video thing a day after because it’s ready to go. I am less and less skeptical e dry time they ship because the quality of the first version isn’t sliding back wards even in different areas like video.
Maybe releasing it is strategic, or releasing it also requires supporting it infrastructure wise and then some. That might be a challenge.
My feeling is the next model of an k between may have massive efficiency and performance improvements without having to go quantum with brute forcing it.
Meanwhile others who are following what OpenAI has done seem to be able to optimize it and make it more efficient whether it’s open source or otherwise.
Both are doing important work and I'm not sure I want to see it as a one winner take all game.
The way AI vendors are responding suddenly to another’s launch feels like they are always ready to launch and continue to add functionality to it that could also ship.
It reminds me of when Google spent a billion dollars advertising bing had a billion pages indexed. Google stayed quiet. Then when the money was spent by Microsoft, Google simply added a zero or two to their search page, when they used to list how many pages they have indexed. They were just sitting on it already done, announcing it when it’s to their benefit.
Also, what will the effect of open models be on the LLM provider industry? What effect will Meta’s scorched earth policy of killing markets by releasing very good open models have?
I use LLMs constantly, but no longer in a commercial environment (I am retired except for writing books, performing personal research projects, and small consulting tasks). I now usually turn first to local models for most things: ellama+Emacs is good enough for me to mostly stop using GPT-4+Emacs or GitHub Copilot, the latest open 7B, 8B, 30B models running on my Mac seem sufficient for most of the NLP and data manipulating things I do.
However, it is also fantastic to have long context Gemini, OpenAI APIs, Claude, etc. available when needed or just to experiment with.
GPT-4 is not a single model. The GPT-4 that was released initially a year ago is way worse in benchmarks than the newest versions of it and the original version has been beat by quite a lot of other models by this point.
The newest version of GPT-4 is probably still overall the best model currently, but it is only a few months old, and the picture depends a lot on what benchmarks you are looking at.
E.g. for what we are doing at our company (document processing, etc.) Claude-3 Opus and Gemini-1.5 Pro are currently the better models. The newest GPT-4 even performed worse than a previous version.
So to me it def. seems like the gap is getting smaller. Of course, OpenAI could be coming out with GPT-5 next week and it could be vastly better than all other current models.
There's wide speculation that what will be branded as either GPT-4.5 or GPT-5 has finished pretraining now and is undergoing internal testing for a fairly near-term release.
My speculation is that internally they have much stronger models like Q* but they won’t be able to release them to public even if they want to for lack of compute and safety and other reasons they see probably…
> My speculation is that internally they have much stronger models like Q*
People used to speculate the same about Google. Everyone hypes up their “secret, too powerful to release” models. Remember the dude who was convinced that there was a sentient AI in the machine? The light of actual public release tends to expose a lot of the hype.
That would be a reasonable assumption if OpenAI did not already have an established track record of repeatedly re-defining our fundamental expectations of what technology can do.
GPT-4 was already completed and secretly being tested on Bing users in India in mid-2022 (there were even Microsoft forum posts asking about the funny chatbot). Even after heavy quantization and the alignment tax GPT-4 is still the bar to beat. It's been two years and their funding has increased over 10x since then.
Short of a fundamental Hard Problem that they cannot overcome, their internal bleeding edge models can reasonably be assumed to possess significantly greater capabilities.
Honestly I'm pretty puzzled by this mystical fog that hangs over OpenAIs skunkworks projects - don't people leave for other jobs/go to conferences etc.?
I'm surprised that nobody call tell what they infact do or do not have.
With hundreds of billions on the line for the founders and a whole lot of likely unvested stock options for the employees, it doesnt seem like anyone wants to open up about whats actually going on day to day.
I'm not saying Claude 3 and Gemini are better than GPT4 in every aspect, but those two models can at least perform addition on arbitrarily long numbers, meanwhile GPT4 struggles.
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