Wolverine Gives Your Python Scripts The Ability To Self-Heal

April 9, 2023 by Donald Papp 38 Comments

[BioBootloader] combined Python and a hefty dose of of AI for a fascinating proof of concept: self-healing Python scripts. He shows things working in a video, embedded below the break, but we’ll also describe what happens right here.

The demo Python script is a simple calculator that works from the command line, and [BioBootloader] introduces a few bugs to it. He misspells a variable used as a return value, and deletes the subtract_numbers(a, b) function entirely. Running this script by itself simply crashes, but using Wolverine on it has a very different outcome.

In a short time, error messages are analyzed, changes proposed, those same changes applied, and the script re-run.

Wolverine is a wrapper that runs the buggy script, captures any error messages, then sends those errors to GPT-4 to ask it what it thinks went wrong with the code. In the demo, GPT-4 correctly identifies the two bugs (even though only one of them directly led to the crash) but that’s not all! Wolverine actually applies the proposed changes to the buggy script, and re-runs it. This time around there is still an error… because GPT-4’s previous changes included an out of scope return statement. No problem, because Wolverine once again consults with GPT-4, creates and formats a change, applies it, and re-runs the modified script. This time the script runs successfully and Wolverine’s work is done.

LLMs (Large Language Models) like GPT-4 are “programmed” in natural language, and these instructions are referred to as prompts. A large chunk of what Wolverine does is thanks to a carefully-written prompt, and you can read it here to gain some insight into the process. Don’t forget to watch the video demonstration just below if you want to see it all in action.

While AI coding capabilities definitely have their limitations, some of the questions it raises are becoming more urgent. Heck, consider that GPT-4 is barely even four weeks old at this writing.

Continue reading “Wolverine Gives Your Python Scripts The Ability To Self-Heal” →

ChatGPT Powers A Different Kind Of Logic Analyzer

April 6, 2023 by Dan Maloney 17 Comments

If you’re hoping that this AI-powered logic analyzer will help you quickly debug that wonky digital circuit on your bench with the magic of AI, we’re sorry to disappoint you. But if you’re in luck if you’re in the market for something to help you detect logical fallacies someone spouts in conversation. With the magic of AI, of course.

First, a quick review: logic fallacies are errors in reasoning that lead to the wrong conclusions from a set of observations. Enumerating the kinds of fallacies has become a bit of a cottage industry in this age of fake news and misinformation, to the extent that many of the common fallacies have catchy names like “Texas Sharpshooter” or “No True Scotsman”. Each fallacy has its own set of characteristics, and while it can be easy to pick some of them out, analyzing speech and finding them all is a tough job.

Continue reading “ChatGPT Powers A Different Kind Of Logic Analyzer” →

How Much Programming Can ChatGPT Really Do?

March 25, 2023 by Bryan Cockfield 50 Comments

By now we’ve all seen articles where the entire copy has been written by ChatGPT. It’s essentially a trope of its own at this point, so we will start out by assuring you that this article is being written by a human. AI tools do seem poised to be extremely disruptive to certain industries, though, but this doesn’t necessarily have to be a bad thing as long as they continue to be viewed as tools, rather than direct replacements. ChatGPT can be used to assist in plenty of tasks, and can help augment processes like programming (rather than becoming the programmer itself), and this article shows a few examples of what it might be used for.

AI comments are better than nothing…probably.

While it can write some programs on its own, in some cases quite capably, for specialized or complex tasks it might not be quite up to the challenge yet. It will often appear extremely confident in its solutions even if it’s providing poor or false information, though, but that doesn’t mean it can’t or shouldn’t be used at all.

The article goes over a few of the ways it can function more as an assistant than a programmer, including generating filler content for something like an SQL database, converting data from one format to another, converting programs from one language to another, and even help with a program’s debugging process.

Some other things that ChatGPT can be used for that we’ve been able to come up with include asking for recommendations for libraries we didn’t know existed, as well as asking for music recommendations to play in the background while working. Tools like these are extremely impressive, and while they likely aren’t taking over anyone’s job right now, that might not always be the case.

Modifying Artwork With Glaze To Interfere With Art Generating Algorithms

March 20, 2023 by Maya Posch 48 Comments

With the rise of machine-generated art we have also seen a major discussion begin about the ethics of using existing, human-made art to train these art models. Their defenders will often claim that the original art cannot be reproduced by the generator, but this is belied by the fact that one possible query to these generators is to produce art in the style of a specific artist. This is where feature extraction comes into play, and the Glaze tool as a potential obfuscation tool.

Developed by researchers at the University of Chicago, the theory behind this tool is covered in their preprint paper. The essential concept is that an artist can pick a target ‘cloak style’, which is used by Glaze to calculate specific perturbations which are added to the original image. These perturbations are not easily detected by the human eye, but will be picked up by the feature extraction algorithms of current machine-generated art models. Continue reading “Modifying Artwork With Glaze To Interfere With Art Generating Algorithms” →

The Singularity Isn’t Here… Yet

March 17, 2023 by Jenny List 112 Comments

So, GPT-4 is out, and it’s all over for us meatbags. Hype has reached fever pitch, here in the latest and greatest of AI chatbots we finally have something that can surpass us. The singularity has happened, and personally I welcome our new AI overlords.

Hang on a minute though, I smell a rat, and it comes in defining just what intelligence is. In my time I’ve hung out with a lot of very bright people, as well as a lot of not-so-bright people who nonetheless think they’re very clever simply because they have a bunch of qualifications and diplomas. Sadly the experience hasn’t bestowed God-like intelligence on me, but it has given me a handle on the difference between intelligence and knowledge.

My premise is that we humans are conditioned by our education system to equate learning with intelligence, mostly because we have flaky CPUs and worse memory, and that makes learning something a bit of an effort. Thus when we see an AI, a machine that can learn everything because it has a decent CPU and memory, we’re conditioned to think of it as intelligent because that’s what our schools train us to do. In fact it seems intelligent to us not because it’s thinking of new stuff, but merely through knowing stuff we don’t because we haven’t had the time or capacity to learn it.

Growing up and making my earlier career around a major university I’ve seen this in action so many times, people who master one skill, rote-learning the school textbook or the university tutor’s pet views and theories, and barfing them up all over the exam paper to get their amazing qualifications. On paper they’re the cream of the crop, and while it’s true they’re not thick, they’re rarely the special clever people they think they are. People with truly above-average intelligence exist, but in smaller numbers, and their occurrence is not a 1:1 mapping with holders of advanced university degrees.

Even the examples touted of GPT’s brilliance tend to reinforce this. It can do the bar exam or the SAT test, thus we’re told it’s as intelligent as a school-age kid or a lawyer. Both of those qualifications follow our educational system’s flawed premise that education equates to intelligence, so as a machine that’s learned all the facts it follows my point above about learning by rote. The machine has simply barfed up what it has learned the answers are onto the exam paper. Is that intelligence? Is a search engine intelligent?

This is not to say that tools such as GPT-4 are not amazing creations that have a lot of potential to do good things aside from filling up the internet with superficially readable spam. Everyone should have a play with them and investigate their potential, and from that will no doubt come some very interesting things. Just don’t confuse them with real people, because sometimes meatbags can surprise you.

AI And Savvy Marketing Create Dubious Moon Photos

March 13, 2023 by Bryan Cockfield 48 Comments

Taking a high-resolution photo of the moon is a surprisingly difficult task. Not only is a long enough lens required, but the camera typically needs to be mounted on a tracking system of some kind, as the moon moves too fast for the long exposure times needed. That’s why plenty were skeptical of Samsung’s claims that their latest smart phone cameras could actually photograph this celestial body with any degree of detail. It turns out that this skepticism might be warranted.

Samsung’s marketing department is claiming that this phone is using artificial intelligence to improve photos, which should quickly raise a red flag for anyone technically minded. [ibreakphotos] wanted to put this to the test rather than speculate, so a high-resolution image of the moon was modified in such a way that most of the fine detail of the image was lost. Displaying this image on a monitor, standing across the room, and using the smartphone in question reveals details in the image that can’t possibly be there.

The image that accompanies this post shows the two images side-by-side for those skeptical of these claims, but from what we can tell it looks like this is essentially an AI system copy-pasting the moon into images it thinks are of the moon itself. The AI also seems to need something more moon-like than a ping pong ball to trigger the detail overlay too, as other tests appear to debunk a more simplified overlay theory. It seems like using this system, though, is doing about the same thing that this AI camera does to take pictures of various common objects.

ChatGPT, Bing, And The Upcoming Security Apocalypse

March 4, 2023 by Elliot Williams 46 Comments

Most security professionals will tell you that it’s a lot easier to attack code systems than it is to defend them, and that this is especially true for large systems. The white hat’s job is to secure each and every point of contact, while the black hat’s goal is to find just one that’s insecure.

Whether black hat or white hat, it also helps a lot to know how the system works and exactly what it’s doing. When you’ve got the source code, either because it’s open-source, or because you’re working inside the company that makes the software, you’ve got a huge advantage both in finding bugs and in fixing them. In the case of closed-source software, the white hats arguably have the offsetting advantage that they at least can see the source code, and peek inside the black box, while the attackers cannot.

Still, if you look at the number of security issues raised weekly, it’s clear that even in the case of closed-source software, where the defenders should have the largest advantage, that offense is a lot easier than defense.

So now put yourself in the shoes of the poor folks who are going to try to secure large language models like ChatGPT, the new Bing, or Google’s soon-to-be-released Bard. They don’t understand their machines. Of course they know how the work inside, in the sense of cross multiplying tensors and updating weights based on training sets and so on. But because the billions of internal parameters interact in incomprehensible ways, almost all researchers refer to large language models’ inner workings as a black box.

And they haven’t even begun to consider security yet. They’re still worried about how to construct obscure background prompts that prevent their machines from spewing hate speech or pornographic novels. But as soon as the machines start doing something more interesting than just providing you plain text, the black hats will take notice, and someone will have to figure out defense.

Indeed, this week, we saw the first real shot across the bow: a hack to make Bing direct users to arbitrary (bad) webpages. The Bing hack requires the user to already be on a compromised website, so it’s maybe not very threatening, but it points out a possible real security difference between Bing and ChatGPT: Bing gives you links to follow, and that makes it a juicy target.

We’re right on the edge of a new security landscape, because even the white hats are facing a black box in the AI. So far, what ChatGPT and Codex and other large language models are doing is trivially secure – putting out plain text – but Bing is taking the first dangerous steps into doing something more useful, both for users and black hats. Given the ease with which people have undone OpenAI’s attempts to keep ChatGPT in its comfort zone, my guess is that the white hats will have their hands full, and the black-box nature of the model deprives them of their best hope. Buckle your seatbelts.