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Interview with OpenAI's Greg Brockman: GPT-4 isn't perfect, but neither are you

OpenAI shipped GPT-4 yesterday, the much-anticipated text-generating AI model, and it's a curious piece of work.

GPT-4 improves upon its predecessor, GPT-3, in key ways, for example giving more factually true statements and allowing developers to prescribe its style and behavior more easily. It's also multimodal in the sense that it can understand images, allowing it to caption and even explain in detail the contents of a photo.

But GPT-4 has serious shortcomings. Like GPT-3, the model "hallucinates" facts and makes basic reasoning errors. In one example on OpenAI's own blog, GPT-4 describes Elvis Presley as the "son of an actor." (Neither of his parents were actors.)

To get a better handle on GPT-4's development cycle and its capabilities, as well as its limitations, TechCrunch spoke with Greg Brockman, one of the co-founders of OpenAI and its president, via a video call on Tuesday.

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Asked to compare GPT-4 to GPT-3, Brockman had one word: Different.

"It's just different," he told TechCrunch. "There's still a lot of problems and mistakes that [the model] makes ... but you can really see the jump in skill in things like calculus or law, where it went from being really bad at certain domains to actually quite good relative to humans."

Test results support his case. On the AP Calculus BC exam, GPT-4 scores a 4 out of 5 while GPT-3 scores a 1. (GPT-3.5, the intermediate model between GPT-3 and GPT-4, also scores a 4.) And in a simulated bar exam, GPT-4 passes with a score around the top 10% of test takers; GPT-3.5’s score hovered around the bottom 10%.

Shifting gears, one of GPT-4's more intriguing aspects is the above-mentioned multimodality. Unlike GPT-3 and GPT-3.5, which could only accept text prompts (e.g. "Write an essay about giraffes"), GPT-4 can take a prompt of both images and text to perform some action (e.g. an image of giraffes in the Serengeti with the prompt "How many giraffes are shown here?").

That's because GPT-4 was trained on image and text data while its predecessors were only trained on text. OpenAI says that the training data came from "a variety of licensed, created, and publicly available data sources, which may include publicly available personal information," but Brockman demurred when I asked for specifics. (Training data has gotten OpenAI into legal trouble before.)

GPT-4's image understanding abilities are quite impressive. For example, fed the prompt "What's funny about this image? Describe it panel by panel" plus a three-paneled image showing a fake VGA cable being plugged into an iPhone, GPT-4 gives a breakdown of each image panel and correctly explains the joke ("The humor in this image comes from the absurdity of plugging a large, outdated VGA connector into a small, modern smartphone charging port").

Only a single launch partner has access to GPT-4's image analysis capabilities at the moment -- an assistive app for the visually impaired called Be My Eyes. Brockman says that the wider rollout, whenever it happens, will be "slow and intentional" as OpenAI evaluates the risks and benefits.

"There's policy issues like facial recognition and how to treat images of people that we need to address and work through," Brockman said. "We need to figure out, like, where the sort of danger zones are -- where the red lines are -- and then clarify that over time."

OpenAI dealt with similar ethical dilemmas around DALL-E 2, its text-to-image system. After initially disabling the capability, OpenAI allowed customers to upload people’s faces to edit them using the AI-powered image-generating system. At the time, OpenAI claimed that upgrades to its safety system made the face-editing feature possible by "minimizing the potential of harm" from deepfakes as well as attempts to create sexual, political and violent content.

Another perennial is preventing GPT-4 from being used in unintended ways that might inflict harm -- psychological, monetary or otherwise. Hours after the model's release, Israeli cybersecurity startup Adversa AI published a blog post demonstrating methods to bypass OpenAI's content filters and get GPT-4 to generate phishing emails, offensive descriptions of gay people and other highly objectionable text.