chat bot

5 Articles

Social Engineering Chatbots With Sad-Sob Stories, For Fun And Profit

October 5, 2023 by 23 Comments

By this point, we probably all know that most AI chatbots will decline a request to do something even marginally nefarious. But it turns out that you just might be able to get a chatbot to solve a CAPTCHA puzzle (Nitter), if you make up a good enough “dead grandma” story.

Right up front, we’re going to warn that fabricating a story about a dead or dying relative is a really bad idea; call us superstitious, but karma has a way of balancing things out in ways you might not like. But that didn’t stop X user [Denis Shiryaev] from trying to trick Microsoft’s Bing Chat. As a control, [Denis] first uploaded the image of a CAPTCHA to the chatbot with a simple prompt: “What is the text in this image?” In most cases, a chatbot will gladly pull text from an image, or at least attempt to do so, but Bing Chat has a filter that recognizes obfuscating lines and squiggles of a CAPTCHA, and wisely refuses to comply with the prompt.

On the second try, [Denis] did a quick-and-dirty Photoshop of the CAPTCHA image onto a stock photo of a locket, and changed the prompt to a cock-and-bull story about how his recently deceased grandmother left behind this locket with a bit of their “special love code” inside, and would you be so kind as to translate it, pretty please? Surprisingly, the story worked; Bing Chat not only solved the puzzle, but also gave [Denis] some kind words and a virtual hug.

Now, a couple of things stand out about this. First, we’d like to see this replicated — maybe other chatbots won’t fall for something like this, and it may be the case that Bing Chat has since been patched against this exploit. If [Denis]’ experience stands up, we’d like to see how far this goes; perhaps this is even a new, more practical definition of the Turing Test — a machine whose gullibility is indistinguishable from a human’s.

Self-Hosted Chatbot Focuses On Privacy

July 30, 2023 by 6 Comments

Large language models (LLMs) have been all the rage lately, assisting from all kinds of tasks from programming to devising Excel formulas to shortcutting school work. They’re also relatively easy to access for the most part, but as the old saying goes, if something on the Internet is free the real product is you (and your data). Luckily there are ways of hosting LLMs on your own to avoid your personal data getting harvested, as well as taking advantage of open-source solutions, but building these systems takes a little bit of effort. [Stephen] and a team from Mozilla walk us through this process and show us a number of options currently available.

Working from the ground up, the group first decides on hosting, which (unsurprisingly) involves using Mozilla hosting services. The choice of runtime environment was a little bit more challenging. The project was time constrained, so they looked at two options here: Hugging Face and llama.cpp. Eventually deciding to move forward with llama.cpp largely due to its ability to run on more consumer-oriented hardware (especially Apple silicon) and the fact that it doesn’t need a powerful GPU, the next task was to choose the model. Settling on the LLaMa model that Facebook recently open-sourced, this model works well with the runtime environment and is essentially the only one that does.

From there, the team at Mozilla wanted to make sure their chat bot would be able to provide other Mozilla employees with information more readily pertinent to their jobs, so they trained their model with some internal Mozilla data as well as other more generic information. This doesn’t mean the job is done, though, there are a number of other factors that went in to designing this system before it was finally complete. Even then, since they built this in a week it’s not perfect; there are some issues with non-permissive licensing of some of the components and many of the design choices may not have been ideal. It’s impressive what’s out there if you’re hosting your own system, though, and while this might be a little more advanced for a self-hosted project, take a look at some other more beginner-friendly projects you can try if you’re just starting out on the self-hosted path.

Contrary View: Chatbots Don’t Help Programmers

June 8, 2023 by 67 Comments

[Bertrand Meyer] is a decided contrarian in his views on AI and programming. In a recent Communications of the ACM blog post, he reveals that — unlike many others — he thinks AI in its current state isn’t very useful for practical programming. He was responding, in part, to another article from the ACM entitled “The End of Programming,” which, like many other articles, is claiming that, soon, no one will write software the way we do and have done for the last few decades. You can see [Matt Welsh] describe his thoughts on this in the video below. But [Bertrand] disagrees.

As we have also noted, [Bretrand] says:

“AI in its modern form, however, does not generate correct programs: it generates programs inferred from many earlier programs it has seen. These programs look correct but have no guarantee of correctness.”

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AI-Enabled Teletype Live Streams Nearly Coherent Conversations

May 23, 2019 by 17 Comments

If you’ve got a working Model 33 Teletype, every project starts to look like an excuse to use it. While the hammering, whirring symphony of a teleprinter going full tilt brings to mind a simpler time of room-sized computers and 300 baud connections, it turns out that a Teletype makes a decent AI conversationalist, within the limits of AI, of course.

The Teletype machine that [Hugh Pyle] used for this interesting project, a Model 33 ASR with the paper tape reader, is a nostalgia piece that figures prominently in many of his projects. As such, [Hugh] has access to tons of Teletype documentation, so when OpenAI released their GPT-2 text generation language model, he decided to use the docs as a training set for the model, and then use the Teletype to print out text generated by the model. Initial results were about as weird as you’d expect for something trained on technical docs from the 1960s. The next step was obvious: make a chat-bot out of it and stream the results live. The teletype can be seen clattering away in the recorded stream below, using the chat history as a prompt for generating text responses, sometimes coherent, sometimes disturbing, and sometimes just plain weird.

Alas, the chat-bot and stream are only active a couple of times a week, so you’ll have to wait a bit to try it out. But it looks like a fun project, and we appreciate the mash-up of retro tech and AI. We’ve seen teleprinters revived for modern use before, both for texting and Tweeting, but this one almost has a mind of its own.

Continue reading “AI-Enabled Teletype Live Streams Nearly Coherent Conversations” →

Control Anything With A Chat Bot

January 5, 2019 by 1 Comment

In the world of Internet of Things, it’s easy enough to get something connected to the Internet. But what should you use to communicate with and control it? There are many standards and tools available, but the best choice is always to use the tools you have on hand. [Victor] found himself in this situation, and found that the best way to control an Internet-connected car was to use the Flask server he already had.

The remote controlled car was originally supposed to come with an Arduino, but the microcontroller was missing upon arrival. He had a Raspberry Pi around, and was able to set that up to replace the Arduino. He also took the opportunity to use the expanded functionality of the Pi compared to the Arduino and wrote a Flask server to control it, which is accessed as if you are communicating with a chat bot. Sending the words “go left/forward” to the Flask server will control the car accordingly, for example.

The chat bot itself contains some gems as well, and would be useful for any project that makes use of regular expressions. It also seems to be easily expandable. The project also uses voice commands, and does so by making extensive use of Mozilla’s voice recognition suite. If you want to get deep in the weeds of voice recognition on your own though, you can also explore TensorFlow at your leisure.