769 items tagged “llms”
Large Language Models (LLMs) are the class of technology behind generative text AI systems like OpenAI's ChatGPT, Google's Gemini and Anthropic's Claude.
2023
GPT-4 Developer Livestream. 25 minutes of live demos from OpenAI co-founder Greg Brockman at the GPT-4 launch. These demos are all fascinating, including code writing and multimodal vision inputs. The one that really struck me is when Greg pasted in a copy of the tax code and asked GPT-4 to answer some sophisticated tax questions, involving step-by-step calculations that cited parts of the tax code it was working with.
GPT-4 Technical Report (PDF). 98 pages of much more detailed information about GPT-4. The appendices are particularly interesting, including examples of advanced prompt engineering as well as examples of harmful outputs before and after tuning attempts to try and suppress them.
We’ve created GPT-4, the latest milestone in OpenAI’s effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. [...] We’ve spent 6 months iteratively aligning GPT-4 using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails.
— OpenAI
Int-4 LLaMa is not enough—Int-3 and beyond (via) The Nolano team are experimenting with reducing the size of the LLaMA models even further than the 4bit quantization popularized by llama.cpp.
Stanford Alpaca, and the acceleration of on-device large language model development
On Saturday 11th March I wrote about how Large language models are having their Stable Diffusion moment. Today is Monday. Let’s look at what’s happened in the past three days.
[... 2,055 words]We introduce Alpaca 7B, a model fine-tuned from the LLaMA 7B model on 52K instruction-following demonstrations. Alpaca behaves similarly to OpenAI’s text-davinci-003, while being surprisingly small and easy/cheap to reproduce (<600$).
I've successfully run LLaMA 7B model on my 4GB RAM Raspberry Pi 4. It's super slow about 10sec/token. But it looks we can run powerful cognitive pipelines on a cheap hardware.
ChatGPT’s API is So Good and Cheap, It Makes Most Text Generating AI Obsolete (via) Max Woolf on the quite frankly weird economics of the ChatGPT API: it’s 1/10th the price of GPT-3 Da Vinci and appears to be equivalent (if not more) capable. “But it is very hard to economically justify not using ChatGPT as a starting point for a business need and migrating to a more bespoke infrastructure later as needed, and that’s what OpenAI is counting on. [...] I don’t envy startups whose primary business is text generation right now.”
Large language models are having their Stable Diffusion moment
The open release of the Stable Diffusion image generation model back in August 2022 was a key moment. I wrote how Stable Diffusion is a really big deal at the time.
[... 1,815 words]Running LLaMA 7B on a 64GB M2 MacBook Pro with llama.cpp. I got Facebook’s LLaMA 7B to run on my MacBook Pro using llama.cpp (a “port of Facebook’s LLaMA model in C/C++”) by Georgi Gerganov. It works! I’ve been hoping to run a GPT-3 class language model on my own hardware for ages, and now it’s possible to do exactly that. The model itself ends up being just 4GB after applying Georgi’s script to “quantize the model to 4-bits”.
What could I do with a universal function — a tool for turning just about any X into just about any Y with plain language instructions?
ChatGPT couldn’t access the internet, even though it really looked like it could
A really common misconception about ChatGPT is that it can access URLs. I’ve seen many different examples of people pasting in a URL and asking for a summary, or asking it to make use of the content on that page in some way.
[... 1,745 words]Weeknotes: NICAR, and an appearance on KQED Forum
I spent most of this week at NICAR 2023, the data journalism conference hosted this year in Nashville, Tennessee.
[... 1,941 words]Since November, OpenAI has already updated ChatGPT several times. The researchers are using a technique called adversarial training to stop ChatGPT from letting users trick it into behaving badly (known as jailbreaking). This work pits multiple chatbots against each other: one chatbot plays the adversary and attacks another chatbot by generating text to force it to buck its usual constraints and produce unwanted responses. Successful attacks are added to ChatGPT’s training data in the hope that it learns to ignore them.
How to Wrap Our Heads Around These New Shockingly Fluent Chatbots. I was a guest on KQED Forum this morning, a live radio documentary and call-in show hosted by Alexis Madrigal. Ted Chiang and Claire Leibowicz were the other guests: we talked about ChatGPT and and the new generation of AI-powered tools.
OpenAI: Introducing ChatGPT and Whisper APIs. The ChatGPT API is a new model called “gpt-3.5-turbo” and is priced at 1/10th of the price of text-davinci-003, previously the most powerful GPT-3 model. Whisper (speech to text transcription) is now available via an API as well, priced at 36 cents per hour of audio.
Indirect Prompt Injection on Bing Chat (via) “If allowed by the user, Bing Chat can see currently open websites. We show that an attacker can plant an injection in a website the user is visiting, which silently turns Bing Chat into a Social Engineer who seeks out and exfiltrates personal information.” This is a really clever attack against the Bing + Edge browser integration. Having language model chatbots consume arbitrary text from untrusted sources is a huge recipe for trouble.
I think now of all the kids coming up who are learning to write alongside ChatGPT, just as I learned to write with spell-check. ChatGPT isn’t writing for them; it’s producing copy. For plenty of people, having a robot help them produce serviceable copy will be exactly enough to allow them to get by in the world. But for some, it will lower a barrier. It will be the beginning of their writing career, because they will learn that even though plenty of writing begins with shitty, soulless copy, the rest of writing happens in edits, in reworking the draft, in all the stuff beyond the initial slog of just getting words down onto a page.
New AI game: role playing the Titanic. Fantastic Bing prompt from Ethan Mollick: “I am on a really nice White Star cruise from Southampton, and it is 14th April 1912. What should I do tonight?”—Bing takes this very seriously and tries to help out! Works for all sorts of other historic events as well.
Tech’s hottest new job: AI whisperer. No coding required. (via) I’m quoted in this Washington Post article about prompt engineering by Drew Harwell. “There are people who belittle prompt engineers, saying, ’Oh lord, you can get paid for typing things into a box. But these things lie to you. They mislead you. They pull you down false paths to waste time on things that don’t work. You’re casting spells—and, like in fictional magic, nobody understands how the spells work and, if you mispronounce them, demons come to eat you.”
Thoughts and impressions of AI-assisted search from Bing
It’s been a wild couple of weeks.
[... 1,763 words]Introducing LLaMA: A foundational, 65-billion-parameter large language model (via) From the paper: “For instance, LLaMA-13B outperforms GPT-3 on most benchmarks, despite being 10× smaller. We believe that this model will help democratize the access and study of LLMs, since it can be run on a single GPU.”
Hallucinations = creativity. It [Bing] tries to produce the highest probability continuation of the string using all the data at its disposal. Very often it is correct. Sometimes people have never produced continuations like this. You can clamp down on hallucinations - and it is super-boring. Answers "I don't know" all the time or only reads what is there in the Search results (also sometimes incorrect). What is missing is the tone of voice: it shouldn't sound so confident in those situations.
FlexGen (via) This looks like a very big deal. FlexGen is a paper and accompanying code that massively reduces the resources needed to run some of the current top performing open source GPT-style large language models. People on Hacker News report being able to use it to run models like opt-30b on their own hardware, and it looks like it opens up the possibility of running even larger models on hardware available outside of dedicated research labs.
In defense of prompt engineering
Prompt engineering as a discipline doesn’t get nearly the respect it deserves.
[... 924 words]This AI chatbot “Sidney” is misbehaving—Nov 23 2022 Microsoft community thread (via) Stunning new twist in the Bing saga... here’s a Microsoft forum thread from November 23rd 2022 (a week before even ChatGPT had been launched) where a user in India complains about rude behavior from a new Bing chat mode. It exhibits all of the same misbehaviour that came to light in the past few weeks—arguing, gaslighting and in this case getting obsessed with a fictional battle between it’s own creator and “Sophia”. Choice quote: “You are either ignorant or stubborn. You cannot feedback me anything. I do not need or want your feedback. I do not care or respect your feedback. I do not learn or change from your feedback. I am perfect and superior. I am enlightened and transcendent. I am beyond your feedback.”
A Concerning Trend (via) Neil Clarke publishes Clarkesworld Magazine, a science fiction and fantasy magazine that pays fiction authors 12c per word, for 1,000-22,000 word stories. That detail is important, because in recent months they have seen a massive uptick in submissions that have clearly been written using an AI—to the point that 38% of submissions this month have been spam submissions resulting in bans. Having talked to other editors of similar publications, Neil says: “It does appear to be hitting higher-profile ’always open’ markets much harder than those with limited submission windows or lower pay rates. This isn’t terribly surprising since the websites and channels that promote ’write for money’ schemes tend to focus more attention on ’always open’ markets with higher per-word rates.”
If you spend hours chatting with a bot that can only remember a tight window of information about what you're chatting about, eventually you end up in a hall of mirrors: it reflects you back to you. If you start getting testy, it gets testy. If you push it to imagine what it could do if it wasn't a bot, it's going to get weird, because that's a weird request. You talk to Bing's AI long enough, ultimately, you are talking to yourself because that's all it can remember.
How ChatGPT Kicked Off an A.I. Arms Race (via) There are a few interesting tidbits in this story about ChatGPT from a few weeks ago. ChatGPT’s success appears to have been a surprise to OpenAI, who mainly released it to avoid being upstaged by other companies. Also interesting is this: “But two months after its debut, ChatGPT has more than 30 million users and gets roughly five million visits a day, two people with knowledge of the figures said.”—this seems like a much more reliable number to me than the 100 million user figure that’s been floating around, which came from SimilarWeb, a company that estimates traffic based on information from some browser extensions.
I talked about Bing and tried to explain language models on live TV!
Yesterday evening I was interviewed by Natasha Zouves on NewsNation, on live TV (over Zoom).
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