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Joined 1 year ago
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Cake day: June 7th, 2023

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  • I think your job in your current form is likely in danger.

    SOTA Foundation Models like GPT4 and Gemini Ultra can write code, execute, and debug with special chain of thought prompting techniques, and large acale process verification on synthetic data and RL search for correct outputs will make this 10x better. The silver lining to this is that I expect this to require an absolute shit ton of compute to constantly generate LLM output hundreds of times for each internal prompt over multiple prompts, requiring immense compute and possibly taking longer than an ordinary software engineer to run. I suspect early full stack developer LLMs will mainly be used to do a few very tedious coding tasks and SWEs will be cheaper for a fair length of time.

    I expect it will be 2-3 years before this happens, so for that short period I expect workers to be “super-productive” by using LLMs in the coding process, but I expect the crossover point when the LLM becomes better is quite soon, perhaps in the next 5 years as compute requirements go down.


  • I suppose having worked with LLMs a whole bunch over the past year I have a better sense of what I meant by “automate high level tasks”.

    I’m talking about an assistant where, let’s say you need to edit a podcast video to add graphics and cut out dead space or mistakes that you corrected in the recording. You could tell the assistant to do that and it would open the video in Adobe Premiere pro, do the necessary tasks, then ask you to review it to check if it made mistakes.

    Or if you had an issue with a particular device, e.g. your display, the assistant would research the issue and perform the necessary steps to troubleshoot and fix the issue.

    These are currently hypothetical scenarios, but current GPT4 can already perform some of these tasks, and specifically training it to be a desktop assistant and to do more agentic tasks will make this a reality in a few years.

    It’s additionally already useful for reading and editing long documents and will only get better on this end. You can already use an LLM to query your documents and give you summaries or use them as instructions/research to aid in performing a task.


  • Current LLMs are manifestly different from Cortana (🤢) because they are actually somewhat intelligent. Microsoft’s copilot can do web search and perform basic tasks on the computer, and because of their exclusive contract with OpenAI they’re gonna have access to more advanced versions of GPT which will be able to do more high level control and automation on the desktop. It will 100% be useful for users to have this available, and I expect even Linux desktops will eventually add local LLM support (once consumer compute and the tech matures). It is not just glorified auto complete, it is actually fairly correlated with outputs of real human language cognition.

    The main issue for me is that they get all the data you input and mine it for better models without your explicit consent. This isn’t an area where open source can catch up without significant capital in favor of it, so we have to hope Meta, Mistral and government funded projects give us what we need to have a competitor.



  • coolin@beehaw.orgtoPrivacy@lemmy.ml*Permanently Deleted*
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    10 months ago

    “I use Signal to hide my data from the US government and big tech”

    “Wait, you seriously still use Reddit? Everyone switched to the Fediverse!”

    “Wow, can’t believe you use Apple! Android is so much better.”

    No one who isn’t terminally online understands what these statements mean. If you want people to use something else, don’t make it about privacy and choose something with fancy buttons and cool features that looks close enough to what they have. They do not care about privacy and are literally of the mindset “if I have nothing to hide I have nothing to fear”. They sleep well at night.






  • For the love of God please stop posting the same story about AI model collapse. This paper has been out since May, been discussed multiple times, and the scenario it presents is highly unrealistic.

    Training on the whole internet is known to produce shit model output, requiring humans to produce their own high quality datasets to feed to these models to yield high quality results. That is why we have techniques like fine-tuning, LoRAs and RLHF as well as countless datasets to feed to models.

    Yes, if a model for some reason was trained on the internet for several iterations, it would collapse and produce garbage. But the current frontier approach for datasets is for LLMs (e.g. GPT4) to produce high quality datasets and for new LLMs to train on that. This has been shown to work with Phi-1 (really good at writing Python code, trained on high quality textbook level content and GPT3.5) and Orca/OpenOrca (GPT-3.5 level model trained on millions of examples from GPT4 and GPT-3.5). Additionally, GPT4 has itself likely been trained on synthetic data and future iterations will train on more and more.

    Notably, by selecting a narrow range of outputs, instead of the whole range, we are able to avoid model collapse and in fact produce even better outputs.



  • I don’t know what type of chatbots these companies are using, but I’ve literally never had a good experience with them and it doesn’t make sense considering how advanced even something like OpenOrca 13B is (GPT-3.5 level) which can run on a single graphics card in some company server room. Most of the ones I’ve talked to are from some random AI startup that have cookie cutter preprogrammed text responses that feel less like LLMs and more like a flow chart and a rudimentary classifier to select an appropriate response. We have LLMs that can do the more complex human tasks of figuring out problems and suggesting solutions and that can query a company database to respond correctly, but we don’t use them.





  • I used to be on GrapheneOS, but the drama with the developer plus mainly not being able to put my university ID on the wallet, forced me back on stock Android.

    Besides Android, I use Google Play Store, YouTube, and Maps. For YouTube I’ve technically degoogled, using Invidious and NewPipe, but that’s obviously still using Google services.

    I really wish that digital payment didn’t rely on two proprietary services (Google Wallet and Apple Wallet). It would be so much easier for phone companies to ship privacy friendly versions of Android if there was a FOSS alternative directly integrated into AOSP. I also wish apps didn’t have to use Google service framework just to function, it seems stupid af. I don’t think this will ever improve, so I’ll probably end up on a true Linux phone whenever those catch up (2030 YEAR OF THE LINUX PHONE???)

    We also need open collaboration on mapping. There is the OpenStreetMaps and Overture maps from Linux foundation, but those aren’t really there yet unfortunately.



  • The natural next place for people to go to once they can’t block ads on YouTube’s website is to go to services that exploit the API to serve free content (NewPipe, Invidious, youtube-dl, etc.). If that happens at a large scale, YouTube might shut off its API just like Reddit did and we’ll end up in scenario where creators are forced to move to Peertube, and, given how costly hosting is for video streaming, it could be much worse than Reddit->Lemmy+KBin or Twitter->Mastodon. Then again, YouTube has survived enshittiffication for a long time, so we’ll have to wait and see.


  • FediSearch I guess is similar to your idea, though I think the goal would be to make a new and open search index specifically containing fediverse websites instead of just using Google. I also feel like the formatting should be more like Lemmy, with the particular post title and short description showing instead of the generic search UI.

    The idea of a fediverse search is really cool though. If things like news and academic papers ever got their own fediverse-connected service, I could see a FediSearch being a great alternative to the AI sludge of Google.


  • coolin@beehaw.orgtoAsklemmy@lemmy.mlDeleted
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    1 year ago

    I mean advanced AI aside, there are already browser extensions that you can pay for that have humans on the other end solving your Captcha. It’s pretty much impossible to stop it imo

    A long term solution would probably be a system similar to like public key/private key that is issued by a government or something to verify you’re a real person that you must provide to sign up for a site. We obviously don’t have the resources to do that 😐 and people are going to leak theirs starting day 1.

    Honestly, disregarding the dystopian nature of it all, I think Sam Altman’s worldcoin is a good idea at least for authentication because all you need to do is scan your iris to prove you are a person and you’re in easily. People could steal your eyes tho 💀 so it’s not foolproof. But in general biometric proof of personhood could be a way forward as well.