Jfc that ai summary. Can we just fuck off with this ai bullshit usage already. Who asked for this? Just link the articles

I responded further down but the infrared equivalent to these are very useful and explicitly solve for the energy waste issue you describe. Infrared heaters can’t heat open air which means heat-energy is transferred right to solid surfaces. It is extremely efficient in areas with any amount of airflow as the heat isn’t able to be blown away as it’s radiating from the surfaces below the heater, not the heater or the air between.

Kinda both right, it heats surfaces the infrared energy emitted by the heater can make contact with. It won’t heat open air which makes it extremely useful in outside environments or anywhere with a potential for airflow. But yeah it does heat everything it does point at, just not the air in between. Really useful for heating furniture to heat the ambient area in addition to the people present.

lol I think that was exactly it, and it actually had a good long-term effect as I’ve noticed an increase of using actual footage/images from the topics being discussed when prior it was more stock image stuff. And also 100% with the phases. Gotta binge and purge that dopamine 😭😂

How so? Not doubting, I just hadn’t heard anything before.

His stuff is great, there was a short time where he was using some AI generated content but the backlash was so severe that only lasted a handful of episodes

Check out Simon Whistler and his team’s channels. Tons of informative stuff and I think they make a sizable portion of all YouTube content lol

https://www.simonwhistler.com/

Oh and now gas costs!

You’re not wrong and it sucks. I do put some hope that businesses will learn fairly quickly you simply can’t sell a product that doesn’t work, and relying on LLMs to build your product will always result in issues as that’s simply not what that technology was ever designed to do.

Where I’m worried is that people attach themselves to brands beyond a point of making it part of their personality so as some of these begin enshittifying their products with LLMs, the customers will simply keep paying for a worse product because the company can do no wrong.

How is it not yet understood. The models will repeat what they’ve been trained with. Nothing more, nothing less. Are they trained on only the solutions to these issues, no. They also are trained with code implementing these same issues so of course they will output them, unless instructed not to.

Developer jobs are just fine.

You’ve missed the point - I was responding to someone answering in an authoritative manner about something of which they were mis-informed. I posed a question someone in the space would immediately know. The disappointing part is simply pasting my question into any search engine or LLM would immediately have said “Temperature.”

This is a perfect example of how we’re using our brain less and less and simply relying on “something” else to answer it for us. Do your research. Learn and teach.

https://lemmy.world/comment/22464598

1. No. And I’ve lost my voice describing why this is the case - LLMs do not use training data in real time which is indicative of the fact that their reasoning chains are learned over many training epochs rather than something akin to a search engine which is parsing and aggregating results from direct sources. I wish I had a different answer but that is simply how the mathematics behind this kind of machine learning model work. The only way to properly manage it would be to limit and license the data appropriately during core model training, but that genie is out of the bottle.
2. We will eventually (soon hopefully) hit critical mass where the technology isn’t delivering value on the hardware it takes to run it. The limitations, like I detailed above, are core to the technology and are not something that we’re just around the corner from solving. Those are core limitations and a different technology will be needed to move the ball forward past what is essentially a calculator with words. When this happens, we’ll see a whiplash effect where a ton of (server) hardware hits the market from the small datacenters looking to capitalize on the current rush. It’ll cripple the market for new hardware, I’d expect, as they’re going to want to get that capital back ASAP as it’s a quickly deprecating asset if just sitting idle.
3. Similar to above, the current trajectory isn’t going to last. It’s going to hurt once the reality finally sets in for the economy.
4. Oh yes, and it’s already been there for years! Unfortunately, these applications are not the glamorous applications like a “Her”-style chat companion, but rather precise application of specific machine learning models for specific business needs. I.e. do you really need an LLM to upload a picture to ask what kind of cat is in the picture? NO! That’s what convolutional neural networks are for, or maybe some custom vision transformers. There are dozens of types of ML models that have clear applications and with fine tuning and proper process implementation, the models can produce production-ready results as any other means of solving this issue.

The core problem with this technology is the misuse/misunderstanding that:

1. AI does not yet exist. Full stop.
2. An LLM is just ONE TYPE of machine learning algorithm
3. An LLM does not possess the ability to understand OR interpret intent
4. An LLM CAN NOT THINK This is the point I can’t stress enough; the “thinking” models you see today are doing nothing much more than cramming additional data into it’s working context and hoping that this guides the inference to produce a higher-quality result. Once a model is loaded for inference (i.e. asking questions) it is a STATIC entity and does not change.

Thank you for coming to my autistic TED talk <3

Edit: Also, fantastic question and never apologize for wanting to learn; keep that hunger and run with it

I encourage you to do some additional research on LLMs and the underlying mathematical models before making statements on incorrect information

The answer to this question was Temperature. It’s one of the many hyperparameters available to the engineer loading the model. Begin with looking into the difference between hyperparameters and parameters, as they relate to LLMs.

I’m one of the contributors to the LIDA cognitive architecture. This is my space and I want to help people learn so we can begin to use this technology as was intended - not all this marketing wank.

So question then, what parameter controls deterministic results for an LLM?

Site auto plays their video WITH sound on page load. Absolutely not.

This is me. Game and story were great and I desperately wanted to finish it, but the combat just sucked the joy out of it. Wish there was some option to change it

I haven’t used Matrix before but after signing up and trying to join the room by address, it says it’s not found. I am using Element X on iOS.

And if I try using the link in this post, the app says an unknown error occurred when I try to add it.

So are we great yet? /s

This perspective makes me so incredibly depressed. This is where we’re at as a species. We will ultimately be our own destruction.