ryeguy_24

I keep going back to the debate with myself. Do I give my now-young kids 500K in an ETF in 14 years or do I send them to college? And the debate is not about how they will spend it (I can hold on to it too), it’s about whether to spend the money or just pass on the wealth to them. People have given me tons of reasons why college is good for them - independence, etc etc. I can find a way to give them independence without spending 500k. I haven’t settled the debate but articles like this are not helping the college path.

Funny. He foreshadowed this in a recent interview. Saying that he may fall out of touch with evolving approaches and if any of the frontier labs would have him, he’d be interested.

https://youtu.be/kwSVtQ7dziU?t=47m50s

Ha, same. I absolutely love everything about my MacBook Pro.

Could you share more detail on how the AI layer is used? Is it an LLM?

Does anyone know of any HR departments actually using LLMs for scoring, selection, extraction, classification or any real use cases? I'm curious to hear about it and how they are using it.

Oh my gosh, this really brought me back. Haven't played that game in 30 years. What a great use of AI. Thanks for the trip down memory lane.

Curious on why you think this. Any data points that led you to this?

I rarely bookmark things but just did. For some reason, I never get this data concisely from Google search and always look for it. Nice job.

How many proprietary use cases truly need pre-training or even fine-tuning as opposed to RAG approach? And at what point does it make sense to pre-train/fine tune? Curious.

I still use AirPods for listening but if I’m ever taking a call, I always use EarPods (USB-C). The microphone quality is multiple times better and that’s important to me. Especially for work. It only took me a few times to hear other people will AirPods to be tainted. It just seems unprofessional now because of how bad it sounds.

Mostly same story. Tinkered for hours with Windows 3.1 floppy disks. Reinstalling OS’s all the time because I’d break stuff or I’d just want a fresh slate. I loved pushing the boundaries. In my 30’s I slowed down with the tinkering because of life (kids, work). I thought I lost the ability to tinker. But recently at 42, I bought a MacBook for the sole purpose of tinkering on the couch at the end of the day (basically after being on computer the whole day, I didn’t want to be in office anymore). And slowly, it’s coming back. I’m playing with new things, learning about Neural Networks, learning about Softare Defined Radio, installing tons of random libraries and tools to test that out. It’s coming back. Keep pushing on it and hopefully it returns for you too!

Has anyone tried to use a laptop at night? It’s pretty hard without lit keys. Maybe this one has some super reflective letters so that the screen lights them up.

What expense app are you building? I really want an app that helps me categorize transactions for budgeting purposes. Any recommendations?

My advice is a little different. It’s make the life of your boss insanely easy. Similar in nature to post but slightly different optimization function. Don’t over communicate, communicate just the right amount. Anticipate questions. Don’t create any friction for them and be really helpful. Some of my people will anticipate things and be proactive. I love that and I constantly push to get them promoted.

When I read the publications (the ACM magazine), I swear sometimes the content feels LLM generated. Does anyone else get that impression? In general, I'm not very impressed with the content (I'm used to WIRED, btw).

The way I think of it (might be wrong) but basically a model that has similar sensors to humans (eyes, ears) and has action-oriented outputs with some objective function (a goal to optimize against). I think autopilot is the closest to world models in that they have eyes, they have ability to interact with the world (go different directions) and see the response.

This is a very smart idea. I couldn't turn my Ring Alarm off and I was on the same Wifi connection as the system. In retrospect, it would be quite smart to switch over to local network.

Does anyone have this mystical report?

:) I mean, you always by a faster car. My interest is in the ability to enhance the voice quality of the uber-portable AirPods using AI.

Exactly. This was my point. Televisions can upconvert from 720p to 4k. In the same sense, the machine learning model would fill in the waveform and mimic a high powered mic. It can do this at the connection point (iPhone / computer).

Isn’t there a whole bunch of dependency here related to prompting and methodology that would significantly impact overall performance? My gut instinct is that there are many many ways to architect this around the LLMs and each might yield different levels of accuracy. What do others think?

Edit: In reading more, I guess this is meant to be a dumb benchmark to monitor through time. Maybe that’s the aim here instead of viability as an auto close tool.

Agree. Also, with respect to training, what is the goal that we are maximizing? LLMs are easy, predicting the next word and we have lots of training data. But what are we training for in real world? Modeling the next spatial photograph to predict things that will happen next? It’s not intuitive to me what that objective function would be in spatial intelligence.

100% agree. There is no reason for employees to be loyal to a company. LLM building is not some religious work. It’s machine learning on big data. Always do what is best for you because companies don’t act like loyal humans, they act like large organizations that aren’t always fair or rationale or logical in their decisions.

Rhetorical question man. I meant who spends time on this stuff.

How in the world did someone find this? The fact that things like this are found is a really an interesting revelation about the collective productivity of the humans race on the planet - all pushing the boundaries of knowledge in everything that we know. There is a scientist in the basement somewhere spending his/her whole life on researching a very small part of the world and maybe it will result in a spectacular finding. Go human race.

Would Microsoft have to comply with this also? Most enterprise users are acquiring LLM services through Microsoft's instance of the models in Azure? (i.e. data is not going to Open AI but enterprise gets to use Open AI models)

I’ve seen so much content on the Internet dedicated to how hard Git is to understand the moment you get beyond basic functionality. Is Git the problem or is meant to be used only after months of training and practice? Seems silly to have any software take so long to learn and comprehend.

Your article starts off with a grand proclamation that isn't true in most cases. Then you talk about how anyone can prompt an LLM. Most of HN already knows that engineers aren't needed to prompt an LLM. Then you state:

"By allowing non-technical people and domain experts to use English as the programming language, AI blurs the line between specification and implementation."

This is a non sequitur. You are saying that some PMs can update the prompts for an AI application. But it does not follow that AI can now specify and implement software. If you are talking about specifically "LLM Applications that just pre-prompt a model can be updated by a PM instead of an engineer". Then yes, that I would agree with. But you've extrapolated this wildly and close out with marketing for your tool.

Agree.

I mean...maybe. The title should be "Engineers are not needed for prompting LLMs"? Yes, LLMs can write code. But I don't think they are at the level yet to build and maintain complex and high-stakes systems with a few prompts.