Beyond the Hype: A Realistic Look at Large Language Models • Jodie Burchell • GOTO 2024

This presentation was recorded at GOTO Amsterdam 2024. #GOTOcon #GOTOams

Jodie Burchell - Data Scientist and Developer at JetBrains @jodieburchell

RESOURCES

ABSTRACT
If you've been remotely tuned in to the latest developments in large language models (LLMs), you've likely been inundated with news, ranging from claims that these models will replace numerous white-collar jobs to declarations of sentience and an impending AI apocalypse. At this stage, the hype surrounding these models has far surpassed the actual useful information available.

In this talk, we’ll cut through the noise and delve deep into the current applications, risks, and limitations of LLMs. We’ll start with early research endeavours aimed at creating an "artificial brain" and trace the path that has led us to today's sophisticated text models. Along the way, we'll address how these models have been mistaken for intelligent systems.

We’ll shed light on the actual requirements for developing true artificial general intelligence, and see how far LLMs are from this goal. We’ll end with a practical demonstration of how you can use LLMs in a way that plays to their strengths, by showing you how to build a system which leans into these models’ powerful natural language capabilities. [...]

TIMECODES
00:00 Intro
03:01 Where are we and how did we get here?
13:35 Are LLMs "intelligent"?
27:29 Using LLMs
42:29 Outro

Download slides and read the full abstract here:

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#LLM #LargeLanguageModel #LimitationsOfLLMs #GenAI #AI #GenerativeAI #CUDA #CommonCrawl #LSTMs #Kaggle #JodieBurchell

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[tigerjp]

Excellent talk. More than the USING LLMs section which was great, however quite a few would be familiar with given the massive focus on GenAI...it was the first 30 minutes that was really useful especially to our responsibility as technologists. Listening to the categorisation of intelligence and where current LLMs are set the context on where they should be used for and where they shouldn't e.g. fighting wars.

[prasad_yt]

Great presentation - concise and loaded.
Removal of the hype and capturing the essence .

[andrewprahst]

I like when she says "so"
I would be sad if Australia stopped existing

[apksriva]

woah .. ! brilliant talk. Very well constructed, I was immersed in the talk till the end.

[kehoste]

Excellent talk, thanks for recording and sharing!

[Anna-mcll]

Thank you very much for sharing this interesting and detailed presentation!

Kind regards,
Anna

[generischgesichtslosgeneri]

Don't call it hallucinating, it fabulates.

[InfiniteQuest]

Thank you. She's one of the few rational people left on Earth. You would not believe the type of hate speech pure rage angry arguing I get when I mention that a language model should be used for language, and if we want to do something else we should use whatever tool is suited to that task. How are we living in a time where people think this is a controversial idea?

[millax-evyz]

Excellent video...although i had to stop my mind from thinking about what would happen if i mixed Foster's and vic bitter together because of the accent. Thats my own neural net working against me

[Theodorus]

OK for folks that know something about the subject but a woefully inadequate introduction for those who may not

[pristine_joe]

Just thinking, LLMs have been a subject of research for the last few decades & is limited by the computing capacity our technology has thus far produced. Human intelligence is backed by training through evolution & has perfected the art of passing it down to the next generation through DNA, the community etc., . Could we be in the very early stages of trying to replicate our consciousness & maybe it may eventually emerge if we overcome the limitations we currently face 🐝🌻

[sblowes]

Wow, this is so off! AGI didn’t become ASI because it’s sexier, it’s a different class of AI. LLMs have a base level of reasoning properties already at the ChatGPT-4 level, and the _general consensus_ among current leading AI researchers is that we expect a higher level of reasoning once we multiply the size again.

[etunimenisukunimeni]

This is the best talk I've seen on any subject in months. Very well put together, super informative even in this short time. You can tell there would've been more where that came from, and the knowledge and experience of the speaker shows. No over/underhyping, just how, where and why LLMs work the way they do.

[TechTalksWeekly]

This is an excellent introduction to LLMs and Jodie is a brilliant speaker. That's why this talk has been featured in the last issue of Tech Talks Weekly newsletter 🎉
Congrats!

[StatMachLearn]

LSTM paper was published in 1997, rather than the 2007 stated in this presentation.

[dwiss]

This has been one of the best if not the best demonstration of what AI is actually capable of. Thank you for a great talk and most of all keeping it on a level that is understandable even for non-Gurus!

[seanendapower]

This is the clearest explanation of how this works I’ve come across

[mikemaldanado]

Chatgpt measured its performance in the Bar exam against a set of people that have taken and failed the exam at least once. Research show that people that have failed once have a high probability of failing again. ie. do not trust research funded results, independent research disproves a lot of the gpt claims. ex. independent research found that gpt3.5 gave better answers than 4.0 just not as fast. Thanks you for this "no hype" talk, it should be the norm when it comes to discussing LLM's.

[alaad]

Jodie, if you're reading this, you're amazing !

[ahmedeldeeb]

Good talk all in all, but I found the section on "are LLMs intelligent" to be less than coherent. The placement of current LLMs on the chart is completely subjective, and the classification of generalization levels relevant but wasn't really brought to bear. The method of generating a "skill program" is only a preferred way of designing a system and by no means the only way, so why bring it up?