LLM

73 Articles

Welcome Your New AI (LEGO) Overlord

May 15, 2025 by 13 Comments

You’d think a paper from a science team from Carnegie Mellon would be short on fun. But the team behind LegoGPT would prove you wrong. The system allows you to enter prompt text and produce physically stable LEGO models. They’ve done more than just a paper. You can find a GitHub repo and a running demo, too.

The authors note that the automated generation of 3D shapes has been done. However, incorporating real physics constraints and planning the resulting shape in LEGO-sized chunks is the real topic of interest. The actual project is a set of training data that can transform text to shapes. The real work is done using one of the LLaMA models. The training involved converting Lego designs into tokens, just like a chatbot converts words into tokens.

There are a lot of parts involved in the creation of the designs. They convert meshes to LEGO in one step using 1×1, 1×2, 1×4, 1×6, 1×8, 2×2, 2×4, and 2×6 bricks. Then they evaluate the stability of the design. Finally, they render an image and ask GPT-4o to produce captions to go with the image.

The most interesting example is when they feed robot arms the designs and let them make the resulting design. From text to LEGO with no human intervention! Sounds like something from a bad movie.

We wonder if they added the more advanced LEGO sets, if we could ask for our own Turing machine?

An LLM For The Raspberry Pi

May 10, 2025 by 32 Comments

Microsoft’s latest Phi4 LLM has 14 billion parameters that require about 11 GB of storage. Can you run it on a Raspberry Pi? Get serious. However, the Phi4-mini-reasoning model is a cut-down version with “only” 3.8 billion parameters that requires 3.2 GB. That’s more realistic and, in a recent video, [Gary Explains] tells you how to add this LLM to your Raspberry Pi arsenal.

The version [Gary] uses has four-bit quantization and, as you might expect, the performance isn’t going to be stellar. If you are versed in all the LLM lingo, the quantization is the way weights are stored, and, in general, the more parameters a model uses, the more things it can figure out.

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AI Brings Play-by-Play Commentary To Pong

May 6, 2025 by 6 Comments

While most of us won’t ever play Wimbledon, we can play Pong. But it isn’t the same without the thrill of the sportscaster’s commentary during the game. Thanks to [Parth Parikh] and an LLM, you can now watch Pong matches with commentary during the game. You can see the very cool result in the video below — the game itself starts around the 2:50 mark. Sadly, you don’t get to play. It seems like it wouldn’t be that hard to wire yourself in with a little programming.

The game features multiple AI players and two announcers. There are 15 years of tournaments, including four majors, for a total of 60 events. In the 16th year, the two top players face off in the World Championship Final.

There are several interesting techniques here. For one, each action is logged as an event that generates metrics and is prioritized. If an important game event occurs, commentary pauses to announce that event and then picks back up where it left off.

We really want to see a one- or two-player human version of this. Please tell us if you take on that challenge. Even if you don’t write it, maybe the AI can write it for you.

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LLM Ported To The C64, Kinda

May 3, 2025 by 8 Comments

“If there’s one thing the Commodore 64 is missing, it’s a large language model,” is a phrase nobody has uttered on this Earth. Yet, you could run one, if you so desired, thanks to [ytm] and the Llama2.c64 project!

[ytm] did the hard work of porting the Llama 2 model to the most popular computer ever made. Of course, as you might expect, the ancient 8-bit machine doesn’t really have the stones to run an LLM on its own. You will need one rather significant upgrade, in the form of 2 MB additional RAM via a C64 REU.

Now, don’t get ahead of things—this is no wide-ranging ChatGPT clone. It’s not going to do your homework, counsel you on your failed marriage, or solve the geopolitical crisis in your local region. Instead, you’re getting the 260 K tinystories model, which is a tad more limited. In [ytm]’s words… “Imagine prompting a 3-year-old child with the beginning of a story — they will continue it to the best of their vocabulary and abilities.”

It might not be supremely capable, but there’s something fun about seeing such a model talking back on an old-school C64 display. If you’ve been hacking away at your own C64 projects, don’t hesitate to let us know. We certainly can’t get enough of them!

Thanks to [ytm] for the tip!

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Hackaday Links: April 27, 2025

April 27, 2025 by 14 Comments

Looks like the Simpsons had it right again, now that an Australian radio station has been caught using an AI-generated DJ for their midday slot. Station CADA, a Sydney-based broadcaster that’s part of the Australian Radio Network, revealed that “Workdays with Thy” isn’t actually hosted by a person; rather, “Thy” is a generative AI text-to-speech system that has been on the air since November. An actual employee of the ARN finance department was used for Thy’s voice model and her headshot, which adds a bit to the creepy factor.

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An illustration of two translucent blue hands knitting a DNA double helix of yellow, green, and red base pairs from three colors of yarn. Text in white to the left of the hands reads: "Evo 2 doesn't just copy existing DNA -- it creates truly new sequences not found in nature that scientists can test for useful properties."

LLMs Coming For A DNA Sequence Near You

April 24, 2025 by 16 Comments

While tools like CRISPR have blown the field of genome hacking wide open, being able to predict what will happen when you tinker with the code underlying the living things on our planet is still tricky. Researchers at Stanford hope their new Evo 2 DNA generative AI tool can help.

Trained on a dataset of over 100,000 organisms from bacteria to humans, the system can quickly determine what mutations contribute to certain diseases and what mutations are mostly harmless. An “area we are hopeful about is using Evo 2 for designing new genetic sequences with specific functions of interest.”

To that end, the system can also generate gene sequences from a starting prompt like any other LLM as well as cross-reference the results to see if the sequence already occurs in nature to aid in predicting what the sequence might do in real life. These synthetic sequences can then be made using CRISPR or similar techniques in the lab for testing. While the prospect of building our own Moya is exciting, we do wonder what possible negative consequences could come from this technology, despite the hand-wavy mention of not training the model on viruses to “to prevent Evo 2 from being used to create new or more dangerous diseases.”

We’ve got you covered if you need to get your own biohacking space setup for DNA gels or if you want to find out more about powering living computers using electricity. If you’re more curious about other interesting uses for machine learning, how about a dolphin translator or discovering better battery materials?

A black and blue swirl background with the logo of a blue dolphin over the word DolphinGemma with dolphin in white and Gemma in blue

DolphinGemma Seeks To Speak To Dolphins

April 24, 2025 by 43 Comments

Most people have wished for the ability to talk to other animals at some point, until they realized their cat would mostly insult them and ask for better service, but researchers are getting closer to a dolphin translator.

DolphinGemma is an upcoming LLM based on the recordings from the Wild Dolphin Project. Using the hours and hours of dolphin sounds recorded by researchers over the decades, the hope is that the LLM will allow us to communicate more effectively with the second most intelligent species on the planet.

The LLM is designed to run in the field on Google Pixel phones, due to it being based on Google’s in-house Gemini product, which is a bit less cumbersome than hauling a mainframe on a dive. The Wild Dolphin Project currently uses the Georgia Tech developed CHAT (Cetacean Hearing Augmentation Telemetry) device which has a Pixel 6 at its heart, but the newer system will be bumped up to a Pixel 9 to take advantage of all those shiny new AI processing advances. Hopefully, we’ll have a better chance of catching when they say, “So long and thanks for all the fish.”

If you’re curious about other mysterious languages being deciphered by LLMs, we have you covered.

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