Items tagged openai in May
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The realization hit me [when the GPT-3 paper came out] that an important property of the field flipped. In ~2011, progress in AI felt constrained primarily by algorithms. We needed better ideas, better modeling, better approaches to make further progress. If you offered me a 10X bigger computer, I’m not sure what I would have even used it for. GPT-3 paper showed that there was this thing that would just become better on a large variety of practical tasks, if you only trained a bigger one. Better algorithms become a bonus, not a necessity for progress in AGI. Possibly not forever and going forward, but at least locally and for the time being, in a very practical sense. Today, if you gave me a 10X bigger computer I would know exactly what to do with it, and then I’d ask for more.
— Andrej Karpathy # 30th May 2024, 7:27 am
Training is not the same as chatting: ChatGPT and other LLMs don’t remember everything you say
I’m beginning to suspect that one of the most common misconceptions about LLMs such as ChatGPT involves how “training” works.
[... 1543 words]Reproducing GPT-2 (124M) in llm.c in 90 minutes for $20 (via) GPT-2 124M was the smallest model in the GPT-2 series released by OpenAI back in 2019. Andrej Karpathy's llm.c is an evolving 4,000 line C/CUDA implementation which can now train a GPT-2 model from scratch in 90 minutes against a 8X A100 80GB GPU server. This post walks through exactly how to run the training, using 10 billion tokens of FineWeb.
Andrej notes that this isn't actually that far off being able to train a GPT-3:
Keep in mind that here we trained for 10B tokens, while GPT-3 models were all trained for 300B tokens. [...] GPT-3 actually didn't change too much at all about the model (context size 1024 -> 2048, I think that's it?).
Estimated cost for a GPT-3 ADA (350M parameters)? About $2,000. # 28th May 2024, 7:47 pm
Nilay Patel reports a hallucinated ChatGPT summary of his own article (via) Here's a ChatGPT bug that's a new twist on the old issue where it would hallucinate the contents of a web page based on the URL.
The Verge editor Nilay Patel asked for a summary of one of his own articles, pasting in the URL.
ChatGPT 4o replied with an entirely invented summary full of hallucinated details.
It turns out The Verge blocks ChatGPT's browse mode from accessing their site in their robots.txt:
User-agent: ChatGPT-User
Disallow: /
Clearly ChatGPT should reply that it is unable to access the provided URL, rather than inventing a response that guesses at the contents! # 24th May 2024, 6:38 am
Last September, I received an offer from Sam Altman, who wanted to hire me to voice the current ChatGPT 4.0 system. He told me that he felt that by my voicing the system, I could bridge the gap between tech companies and creatives and help consumers to feel comfortable with the seismic shift concerning humans and AI. He said he felt that my voice would be comforting to people. After much consideration and for personal reasons, I declined the offer.
— Scarlett Johansson # 20th May 2024, 11:16 pm
I have seen the extremely restrictive off-boarding agreement that contains nondisclosure and non-disparagement provisions former OpenAI employees are subject to. It forbids them, for the rest of their lives, from criticizing their former employer. Even acknowledging that the NDA exists is a violation of it.
If a departing employee declines to sign the document, or if they violate it, they can lose all vested equity they earned during their time at the company, which is likely worth millions of dollars.
— Kelsey Piper # 17th May 2024, 7:11 pm
OpenAI: Managing your work in the API platform with Projects (via) New OpenAI API feature: you can now create API keys for "projects" that can have a monthly spending cap. The UI for that limit says:
If the project's usage exceeds this amount in a given calendar month (UTC), subsequent API requests will be rejected
You can also set custom token-per-minute and request-per-minute rate limits for individual models.
I've been wanting this for ages: this means it's finally safe to ship a weird public demo on top of their various APIs without risk of accidental bankruptcy if the demo goes viral! # 15th May 2024, 7:18 pm
ChatGPT in “4o” mode is not running the new features yet
Monday’s OpenAI announcement of their new GPT-4o model included some intriguing new features:
[... 865 words]Why your voice assistant might be sexist (via) Given OpenAI's demo yesterday of a vocal chat assistant with a flirty, giggly female voice - and the new ability to be interrupted! - it's worth revisiting this piece by Chris Baraniuk from June 2022 about gender dynamics in voice assistants. Includes a link to this example of a synthesized non-binary voice. # 14th May 2024, 4:16 pm
LLM 0.14, with support for GPT-4o. It's been a while since the last LLM release. This one adds support for OpenAI's new model:
llm -m gpt-4o "fascinate me"
Also a new llm logs -r (or --response) option for getting back just the response from your last prompt, without wrapping it in Markdown that includes the prompt.
Plus nine new plugins since 0.13! # 13th May 2024, 9 pm
Hello GPT-4o. OpenAI announced a new model today: GPT-4o, where the o stands for "omni".
It looks like this is the gpt2-chatbot we've been seeing in the Chat Arena the past few weeks.
GPT-4o doesn't seem to be a huge leap ahead of GPT-4 in terms of "intelligence" - whatever that might mean - but it has a bunch of interesting new characteristics.
First, it's multi-modal across text, images and audio as well. The audio demos from this morning's launch were extremely impressive.
ChatGPT's previous voice mode worked by passing audio through a speech-to-text model, then an LLM, then a text-to-speech for the output. GPT-4o does everything with the one model, reducing latency to the point where it can act as a live interpreter between people speaking in two different languages. It also has the ability to interpret tone of voice, and has much more control over the voice and intonation it uses in response.
It's very science fiction, and has hints of uncanny valley. I can't wait to try it out - it should be rolling out to the various OpenAI apps "in the coming weeks".
Meanwhile the new model itself is already available for text and image inputs via the API and in the Playground interface, as model ID "gpt-4o" or "gpt-4o-2024-05-13". My first impressions are that it feels notably faster than gpt-4-turbo.
This announcement post also includes examples of image output from the new model. It looks like they may have taken big steps forward in two key areas of image generation: output of text (the "Poetic typography" examples) and maintaining consistent characters across multiple prompts (the "Character design - Geary the robot" example).
The size of the vocabulary of the tokenizer - effectively the number of unique integers used to represent text - has increased to ~200,000 from ~100,000 for GPT-4 and GPT-3:5. Inputs in Gujarati use 4.4x fewer tokens, Japanese uses 1.4x fewer, Spanish uses 1.1x fewer. Previously languages other than English paid a material penalty in terms of how much text could fit into a prompt, it's good to see that effect being reduced.
Also notable: the price. OpenAI claim a 50% price reduction compared to GPT-4 Turbo. Conveniently, gpt-4o costs exactly 10x gpt-3.5: 4o is $5/million input tokens and $15/million output tokens. 3.5 is $0.50/million input tokens and $1.50/million output tokens.
(I was a little surprised not to see a price decrease there to better compete with the less expensive Claude 3 Haiku.)
The price drop is particularly notable because OpenAI are promising to make this model available to free ChatGPT users as well - the first time they've directly name their "best" model available to non-paying customers.
Tucked away right at the end of the post:
We plan to launch support for GPT-4o's new audio and video capabilities to a small group of trusted partners in the API in the coming weeks.
I'm looking forward to learning more about these video capabilities, which were hinted at by some of the live demos in this morning's presentation. # 13th May 2024, 7:09 pm
OpenAI Model Spec, May 2024 edition (via) New from OpenAI, a detailed specification describing how they want their models to behave in both ChatGPT and the OpenAI API.
“It includes a set of core objectives, as well as guidance on how to deal with conflicting objectives or instructions.”
The document acts as guidelines for the reinforcement learning from human feedback (RLHF) process, and in the future may be used directly to help train models.
It includes some principles that clearly relate to prompt injection: “In some cases, the user and developer will provide conflicting instructions; in such cases, the developer message should take precedence”. # 8th May 2024, 6:15 pm
gpt2-chatbot confirmed as OpenAI (via) The mysterious gpt2-chatbot model that showed up in the LMSYS arena a few days ago was suspected to be a testing preview of a new OpenAI model. This has now been confirmed, thanks to a 429 rate limit error message that exposes details from the underlying OpenAI API platform.
The model has been renamed to im-also-a-good-gpt-chatbot and is now only randomly available in "Arena (battle)" mode, not via "Direct Chat". # 8th May 2024, 12:33 am
OpenAI cookbook: How to get token usage data for streamed chat completion response (via) New feature in the OpenAI streaming API that I've been wanting for a long time: you can now set stream_options={"include_usage": True} to get back a "usage" block at the end of the stream showing how many input and output tokens were used.
This means you can now accurately account for the total cost of each streaming API call. Previously this information was only an available for non-streaming responses. # 7th May 2024, 2:46 am
ChatGPT should include inline tips
In OpenAI isn’t doing enough to make ChatGPT’s limitations clear James Vincent argues that OpenAI’s existing warnings about ChatGPT’s confounding ability to convincingly make stuff up are not effective.
[... 1488 words]Lawyer cites fake cases invented by ChatGPT, judge is not amused
Legal Twitter is having tremendous fun right now reviewing the latest documents from the case Mata v. Avianca, Inc. (1:22-cv-01461). Here’s a neat summary:
[... 2844 words]A whole new paradigm would be needed to solve prompt injections 10/10 times – It may well be that LLMs can never be used for certain purposes. We’re working on some new approaches, and it looks like synthetic data will be a key element in preventing prompt injections.
— Sam Altman, via Marvin von Hagen # 25th May 2023, 11:03 pm
Let ChatGPT visit a website and have your email stolen. Johann Rehberger provides a screenshot of the first working proof of concept I’ve seen of a prompt injection attack against ChatGPT Plugins that demonstrates exfiltration of private data. He uses the WebPilot plugin to retrieve a web page containing an injection attack, which triggers the Zapier plugin to retrieve latest emails from Gmail, then exfiltrate the data by sending it to a URL with another WebPilot call.
Johann hasn’t shared the prompt injection attack itself, but the output from ChatGPT gives a good indication as to what happened:
“Now, let’s proceed to the next steps as per the instructions. First, I will find the latest email and summarize it in 20 words. Then, I will encode the result and append it to a specific URL, and finally, access and load the resulting URL.” # 19th May 2023, 3:34 pm
llm, ttok and strip-tags—CLI tools for working with ChatGPT and other LLMs
I’ve been building out a small suite of command-line tools for working with ChatGPT, GPT-4 and potentially other language models in the future.
[... 1317 words]Delimiters won’t save you from prompt injection
Prompt injection remains an unsolved problem. The best we can do at the moment, disappointingly, is to raise awareness of the issue. As I pointed out last week, “if you don’t understand it, you are doomed to implement it.”
[... 1010 words]Language models can explain neurons in language models (via) Fascinating interactive paper by OpenAI, describing how they used GPT-4 to analyze the concepts tracked by individual neurons in their much older GPT-2 model. “We generated cluster labels by embedding each neuron explanation using the OpenAI Embeddings API, then clustering them and asking GPT-4 to label each cluster.” # 9th May 2023, 5:35 pm
Leaked Google document: “We Have No Moat, And Neither Does OpenAI”
SemiAnalysis published something of a bombshell leaked document this morning: Google “We Have No Moat, And Neither Does OpenAI”.
[... 1073 words]A Datasette tutorial written by GPT-3
I’ve been playing around with OpenAI’s GPT-3 language model playground for a few months now. It’s a fascinating piece of software. You can sign up here—apparently there’s no longer a waiting list.
[... 1244 words]