Discover and read the best of Twitter Threads about #LLMs

Most recents (24)

I remember when I got into the beta user list for GPT-3.0, and interacting with it became my daily hobby.

Fast forward three years and your stance on large language models can make or break your company's stock price!

Business adoption is imminent. 🧵👇🏻 #llms Image
I’m super excited about the emerging tool stack that helps to deploy and scale real-world LLM solutions.

I made a YouTube video about a big-picture overview of four tools from the emerging LLM developer stack that lets you build advanced LLM apps 👇🏻
YouTube video link:
Read 11 tweets
In addition to the wonderful personal experiences, #EAMT2023 was also a professional highlight for me that has really inspired me and reassured me that my work is useful and appreciated. A bragging-thread 👇 cc @EAMT_2023 @lt3ugent @SignONEU Image
🎉 I presented MATEO, a tool for effortless #MT evaluation! It received an overwhelming response from researchers, users, and industry, validating my belief that improving accessibility to #opensource #evaluation methods fills a need. Check it out here: lt3.ugent.be/mateo/
The project funding (thank you @EAMTee and @CLARINERIC!) is ending this month but I've had the pleasure to talk to many engaging people to keep the project alive in an #openscience manner for the foreseeable future. All contributions and ideas are welcome! github.com/BramVanroy/mat…
Read 9 tweets
📯 Please RT!
✨ A Message To The #AICommunity

📣 I can't stress this enough: #LLMs are designed to reflect and amplify what we feed them. They're like kids, or psychedelics. (My friend @NeseLSD co-authored a superb paper on #psychedelics as non-specific amplifiers I will post… twitter.com/i/web/status/1… Image
1️⃣ Okay, so! My first point in response to all of the fear-mongering and doomsaying in the tech world right now — beyond the obvious, which is that there's an inherent conflict in hastily bringing forth tools you fear and maybe that's worth some personal reflection, because it's… twitter.com/i/web/status/1…
♻️ Side Note: I plan on writing all of this up into a more thorough and well-formatted article with an extensive bibliography, but for the time being I want to drop a couple of relevant tweets that serendipitously came up in my feed today.

Here's one from from @speakerjohnash,… twitter.com/i/web/status/1…
Read 4 tweets
New colab!

@LangChainAI 🤝 @elastic

LangChain is a cutting-edge library to make large language models (LLMs) more usable and versatile.

In synergy with ElasticSearch, this powerful duo opens new doors in application development and search applications.

Let's dive in 🧵

#AI
LangChain is a toolbox providing a standard interface for LLMs & facilitating their integration with other tools.

It makes developing applications like chatbots, decision-making agents, and more, easier by blending LLMs with other computations & knowledge bases.
Who's it for?

@LangChainAI is perfect for developers looking to harness the potential of LLMs to build transformative applications.

From question-answering apps to intelligent agents, the scope of possibilities with LangChain is immense.
Read 8 tweets
#dts23 is about to begin! Excited to be here! My name on a badge against ...
Image
Ready for a welcome address from @dccahalane, group CMO @dogpatchlabs #dts23
Read 199 tweets
Last week, we discussed techniques to speed up the training speed of large language models🔥💨

How about saving memory during inference? 🧠💾 Check out int8 & int4 quantization, which is supported in Lit-LLama 👉github.com/Lightning-AI/l…

🧵1/3

#LLMs #ML #DeepLearning Image
How does int8 quantization work? 🤔

It's a 2-part procedure with
1) using 8bit quantization
2) 16-bit matmuls for outlier feature dimensions

Check out the LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale paper for details arxiv.org/abs/2208.07339

🧵2/3
And how about int4? 🤔

It's a one-shot weight quantization method based on approximate second-order information⚙️📉

For more details, see GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers: 📚🔍 arxiv.org/abs/2210.17323

🧵3/3
Read 3 tweets
.@CohereAI now has an LLM University where you can learn about #LLMs! 🔥

> docs.cohere.com/docs/llmu Image
Here's the intro video from @CohereAI

@CohereAI Also check out their announcement tweet for more details:

Read 3 tweets
Welcome to day 2 of the 5th World Chatbots & Voice Summit, hosted the the beautiful city of #Berlin

I'll be keeping this thread going to cover all the presentations and learnings of the day.

As co-chair, I'll be looking after the chatbot track, today.

#chatbotvoice2023
First up, Alin from @SapienceS2P

Talking about how to deliver value and a competitive edge through customised chatbot solutions

SapienceS2P is an #SAP procurement consultancy Image
Taking us through their #procurement chatbot, Sapience Satori, which can integrate with #ChatGPT, most SAP APIs and also communication channels - #teams #slack #whatsapp
Read 75 tweets
Welcome to #chatbotvoice2023 from Berlin.

I'm throwing up some tidbits around #conversationalai live from the 5th World Chatbots & Voice Summit from Berlin.
First up, Christoph from @GetCyara

We're talking testing and assuring quality in #conversationalai Image
Testing is an impossible manual task and it needs to be automated. Done wrong, it can cost heavily. So it is a huge, but important challenge. Image
Read 83 tweets
#LLMs like GPT-4 are stuck in time — they only understand the world as it exists within their training data...

This causes issues when we need up-to-date info or interaction with specific datasets — here's how we fix that

pinecone.io/learn/langchai…
🔍📚 Retrieval augmentation uses an external knowledge base as a "window" into the world — we explore how to implement this for LLMs using @LangChainAI, reducing hallucinations and keeping info up to date
📖🔧 To give LLMs relevant source knowledge, we create a knowledge base:
- We start with a dataset (e.g., a subset of Wikipedia)
- Split it into chunks
- Generate embeddings (numerical representations) of the "human meaning" behind each chunk
Read 6 tweets
🧵
Czy SZTUCZNA INTELIGENCJA jest szkodliwa?

Pod względem językowym - NA PEWNO!

Czy termin “sztuczna inteligencja” faktycznie oddaje to co robi:
- uczenie maszynowe
- sieci neuronowe
- deep learning?

#ai #etyka #język #filozofia #ChatGPT #LLMs #sztuczna #inteligencja
1/40+👇 Image
2/ CO AUTOR MIAŁ NA MYŚLI

Termin “sztuczna inteligencja” powstał w 1956 podczas konferencji w Darmouth - założycielskiego zlotu dla tej gałęzi nauki. Autorem był John McCarthy, wówczas 29-letni wykładowca. Darmouth Conference proposa...
3/ Już w trakcie konferencji pojawił się pierwszy sprzeciw.

Dwóch uczestników, A.Newell i H.Simon uważali, że bardziej precyzyjne będzie określenie "systemy złożonego przetwarzania informacji" (complex information processing).

Wygrała “sztuczna inteligencja” Darmouth Conference 1956, F...
Read 44 tweets
Here are seven of the best #AI podcasts you can find online, many of which have recently covered #ChatGPT and #LLMs!

A thread 🧵 ↓
#1 `Tech Won’t Save Us` (@techwontsaveus)

A podcast hosted by Paris Marx (@parismarx) that explores the intersection of technology, capitalism, and the environment.

🎙️ techwontsave.us Image
#2 `The Data Exchange Podcast`

A podcast series that explores the latest trends, techniques, and tools in the world of data science, machine learning, and AI.

The podcast is hosted by Ben Lorica (@bigdata), Chief Data Scientist at O'Reilly Media.

🎙️ thedataexchange.media Image
Read 9 tweets
A recent paper titled "Sparks of Artificial General Intelligence: Early experiments with GPT-4", published by Microsoft Research makes for very interesting reading. I have gone through the entire report and it IS TL;DR. Here is my summary of the same #GPT4 #AGI #LLMs 1/n Image
But before that, let's take a brief detour into what intelligence actually means. One of the definitions is that intelligence is a multifaceted and complex cognitive ability that involves the capacity to understand, learn, reason, solve problems, adapt to new situations, 2/n
think critically, and apply knowledge to different domains. But what does it mean to say that an artificial intelligence system is intelligent?
From the paper:
3/n Image
Read 24 tweets
So @TheEconomist tells me now that #LLMs can do planning and reasoning after all. Obviously our own dismal experience of their planning performance (c.f. the 🧵 at ) must be a clear outlier.. 🙄 Thank goodness I pay big bucks for my subscription.. 1/ Image
Interestingly, I was just telling someone today how several of the papers on "LLMs for Task Planning by Prompting" are rife with the Clever Hans effect (c.f. en.wikipedia.org/wiki/Clever_Ha… ). I guess I will have to do a thread.. 2/ Image
(While we should all be used to #LLM hype-expertise in the press by now, this particular case was prickly as it is my cocky son who airily pointed this article out to me at dinner with barely concealed delight.. 😡 ) 3/
Read 5 tweets
I used @predictionguard (paired with @LangChainAI)to evaluate 27 Large Language Models (LLMs) for text generation and automatically select a best/fallback model for use in some generative #AI applications.

A thread 🧵
Some general thoughts:

-> No surprise in the top performer (@OpenAI GPT-3.5), but...

-> 3 of @CohereAI models show up, including the runner up.

-> Surprised to see XLNet, a model that I can pull down from @huggingface, performs better than some of the popular #LLMs
Regarding the evaluation, the process works as follows:

1. You upload some examples of the model input/ output behavior that you expect.

2. @predictionguard concurrently runs these examples through a bunch of SOTA models on the backend
Read 7 tweets
Slides to to engage clinical + informatics communities across multiple forums.

For the two people who have not already heard about and tried using #ChatGPT, over 100 million other people already have. The fastest growing internet application in history. #MedAI Image
Good or bad, ready or not, these tools are out there and are being used in all imaginable and some unimaginable ways.
Even LAST quarter, Stanford students are using ChatGPT on the class assignments, including straight up submitting ChatGPT generated answers without any edits. Image
Overly simplified breakdown on how these systems work. Auto-complete on steroids. How to guess the next word you enter? Learning parameters on how often those words have appeared together in prior examples. Image
Read 24 tweets
⚡️Breaking news from the EU & #GDPR land: the Italian Data Protection Authority #GarantePrivacy issued an order today against OpenAI, effectively blocking #ChatGPT in Italy (ordering it not to use personal data of Italians). Here is a deep dive into the short order - 1/
What did the Italian DPA #GarantePrivacy found problematic with ChatGPT4?
- Lack of transparency
- Absence of a lawful ground for processing
- Not respecting accuracy
- Lack of age verification
- Overall breach of Data Protection by Design
Why for each? A short explainer:
2/
A) Lack of transparency

Pursuant verification, the #GarantePrivacy found that no information is provided to users of the service, nor generally to people whose data have been collected by OpenAI & processed through the ChatGPT service.
=> a breach of Art. 13 #GDPR
3/
Read 19 tweets
#ChatGPT #AI performance on *open-ended, free-response,* clinical reasoning exams intended for human medical trainees. #LLMs are passing medical licensing exams, but artificial multiple choice designs do not reflect realistic clinical reasoning.
medrxiv.org/content/10.110…
From describing diagnostic schema, generating differential diagnoses and problem lists, to suggesting and interpreting tests, ChatGPT is already demonstrating the surprising ability to often reach a 70% passing threshold on multiple cases.
For simple recall style questions ("describe the typical symptoms of a patient with heart failure,") it will knock those questions out of the park, while showing wide variability and struggling with deeper analytical questions.
Read 5 tweets
Oghma Infinium
by #ChatGPT and Matt Yudysky
#OghmaInfinium
INTRODUCTION
The pursuit of knowledge and understanding has been a driving force in human history, shaping cultures, societies, and civilizations. Throughout the ages, people have sought to uncover the mysteries of the universe and their place within it.
Read 68 tweets
🧵 "#Possibility Architectures: Exploring Human #Communication with Generative #AI"

Today's SFI Seminar with ExFac Simon DeDeo @LaboratoryMinds (@CarnegieMellon), streaming now:
"A key feature of this is talk is that we make sense of what each other are saying IN PART by what they say, but ALSO by what we expect of them."
"Language transmits info against a background of expectations – syntactic, semantic, and this larger cultural spectrum. It's not just the choices of make but [how] we set ourselves up to make later choices."

@LaboratoryMinds re: work led by @clairebergey:
Read 15 tweets
#LLMs are powerful, but can they make existing GUIs interactable with language? Last summer at @GoogleAI, we found that LLMs can perform diverse language-based mobile UI tasks using few-shot prompting. Exciting implications for future interaction design! #chi2023 Thread 🧵 Image
🧠 Key Takeaway: Using LLMs, designers/researchers can quickly implement and test *various* language-based UI interactions. In contrast, traditional ML pipelines require expensive data collection and model training for a *single* interaction capability.

Learn more about it👇
To adapt LLMs to mobile UIs, we designed prompting techniques and an algorithm to convert the view hierarchy data in Android to the HTML syntax, which is well-represented in LLMs’ training data. Image
Read 13 tweets
Wanna build the next ChatGPT?

Here's a 6 month learning plan for AI large language models (LLMs) from scratch.

(thread)
1. Familiarize yourself with basic machine learning concepts and Python programming.

Books:

1.1. Introduction to Machine Learning with Python by Andreas Müller and Sarah Guido

1.2. Python Machine Learning by @rasbt
2. Learn about natural language processing (NLP) and its applications.

Books:

2.1. Speech and Language Processing by Daniel Jurafsky and James H. Martin

2.2. Natural Language Processing with Python by Steven Bird, Ewan Klein, and Edward Loper
Read 8 tweets
40 Deep #SEO Insights for 2023:

-In 2022, I told to focus on Natural Language Generation, and it happened.
-In 2023, F-O-C-U-S on "Information Density, Richness, and Unique Added Value" with Microsemantics.

I call the collection of these, "Information Responsiveness".

1/40 🧵.
1. PageRank Increases its Prominence for Weighting Sources

Reason: #AI and automation will bloat the web, and the real authority signals will come from PageRank, and Exogenous Factors.

The expert-like AI content and real expertise are differentiated with historical consistency.
2. Indexing and relevance thresholds will increase.

Reason: A bloated web creates the need for unique value to be added to the web with real-world expertise and organizational signals. The knowledge domain terms, or #PageRank, will be important in the future of a web source.
Read 45 tweets
1/ #ChatGPT is closing out 2022 with a bang, but what’s next? 💥

@OpenAI’s #GPT4 is set to be the first big #AI thing in 2023.

So here are some bold, optimistic, yet sensible predictions from me, @vivek7ue and @rajhans_samdani ... 👀
2/ Biggest model size for GPT-4 will be 1T parameters. Up 6x.

Not 100T parameters like some AI hypers are claiming ().2/ Biggest model size for GPT-4 will be 1T parameters. Up 6x Image
3/ The reason is simple: instruction fine tuning achieves same quality with 100x smaller models.
arxiv.org/pdf/2203.02155… Image
Read 16 tweets

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