A wooden doll with a long nose that has nothing to do with Disney

Bavarian Court Tells Gemini It Can’t Be A Real Boy Until It Tells The Truth

June 14, 2026 by Tyler August 63 Comments

Does anyone like Google’s AI summaries? If so, they weren’t on the Judge’s bench in a specific Bavarian courtroom recently, where it was ruled that yes, Google is liable for the hallucinations of its search engine AI.

This was a civil case brought by a pair of Munich companies, both of whom were wrongfully slandered by LLM hallucinations. Google took the position that this information must have existed somewhere, and like presenting links to libelous websites — something they have no obligation to avoid — they should not be held accountable for what the summary at the top of the search results says.

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Is A CS Degree DOA Thanks To LLMs? IEEE Says TBD.

June 14, 2026 by Tyler August 63 Comments

The ongoing AI apocalypse is hitting prices for high-end components from RAM to GPUs to storage hard, which is bad enough when you have a job to try and budget for those now-pricier items — but what if you don’t? Once upon a time, it might have been good advice to tell a jobless friend to “learn to code,” but is that still true in the era of AI? [Brian Jenney], writing for IEEE Spectrum, says the death of the CS degree has been vastly exaggerated, but your take might differ. Let’s look at the numbers.

Unemployment is higher amongst new Computer Science grads than ever: in the US, it’s at 6.1%, while 7.5% of Computer Engineering graduates are on the dole. That’s a record high, and while various EU countries have their own numbers, they all have one thing in common: they’ve all shot up like a rocket in the past few years. In the USA, Philosophy grads report only 3% unemployment. Let that sink in: the folks you used to bully as being the most useless on campus are twice as likely to get a job as you would be if you were in school today.

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Mesa Project Adds Code Comprehension Requirement After AI Slop Incident

October 1, 2025 by Maya Posch 31 Comments

Recently [Faith Ekstrand] announced on Mastodon that Mesa was updating its contributor guide. This follows a recent AI slop incident where someone submitted a massive patch to the Mesa project with the claim that this would improve performance ‘by a few percent’. The catch? The entire patch was generated by ChatGPT, with the submitter becoming somewhat irate when the very patient Mesa developers tried to explain that they’d happily look at the issue after the submitter had condensed the purported ‘improvement’ into a bite-sized patch.

The entire saga is summarized in a recent video by [Brodie Robertson] which highlights both how incredibly friendly the Mesa developers are, and how the use of ChatGPT and kin has made some people with zero programming skills apparently believe that they can now contribute code to OSS projects. Unsurprisingly, the Mesa developers were unable to disabuse this particular individual from that notion, but the diff to the Mesa contributor guide by [Timur Kristóf] should make abundantly clear that someone playing Telephone between a chatbot and OSS project developers is neither desirable nor helpful.

That said, [Brodie] also highlights a recent post by [Daniel Stenberg] of Curl fame, who thanked [Joshua Rogers] for contributing a massive list of potential issues that were found using ‘AI-assisted tools’, as detailed in this blog post by [Joshua]. An important point here is that these ‘AI tools’ are not LLM-based chatbots, but rather tweaked existing tools like static code analyzers with more smarts bolted on. They’re purpose-made tools that still require you to know what you’re doing, but they can be a real asset to a developer, and a heck of a lot more useful to a project like Curl than getting sent fake bug reports by a confabulating chatbot as has happened previously.

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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 Navarre Bartz 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?

All You Need For Artificial Intelligence Is A Commodore 64

November 3, 2024 by Maya Posch 50 Comments

Artificial intelligence has always been around us, with [Timothy J. O’Malley]’s 1985 book on AI projects for the Commodore 64 being one example of this. With AI defined as being the theory and development of systems that can perform tasks that normally requiring human intelligence (e.g. visual perception, speech recognition, decision-making), this book is a good introduction to the many ways that computer systems for decades now have been able to learn, make decisions and in general become more human-like. Even if there’s no electronic personality behind the actions.

In the book’s first chapter, [Timothy] isn’t afraid to toss in some opinions about the true nature of intelligence and thinking. Starting with the concept that intelligence is based around storing information and being able to derive meaning from connections between stored pieces of information, the idea of a basic AI as one would use in a game for the computer opponent arises. A number of ways of implementing such an AI is explored in the first and subsequent chapters, using Towers of Hanoi, chess, Nim and other games.

After this we look at natural language processing – referencing ELIZA as an example – followed by heuristics, pattern recognition and AI for robotics. Although much of this may seem outdated in this modern age of LLMs and neural networks, it’s important to realize that much of what we consider ‘bleeding edge’ today has its roots in AI research performed in the 1950s and 1960s. As [Timothy] rightfully states in the final chapter, there is no real limit to how far you can push this type of AI as long as you have more hardware and storage to throw at the problem. This is where we now got datacenters full of GPU-equipped systems churning through vector space calculations for the sake of today’s LLM & diffusion model take on ‘AI’.

Using a Commodore 64 to demonstrate the (lack of) validity of claims is not a new one, with recently a group of researchers using one of these breadbin marvels to run an Ising model with a tensor network and outperforming IBM’s quantum processor. As they say, just because it’s new and shiny doesn’t necessarily mean that it is actually better.

Mitre Wants The Feds To Play In Its Sandbox

May 7, 2024 by Al Williams 18 Comments

If you haven’t worked with the US government, you might not know Mitre, a non-profit government research organization. Formed in 1958 by the U.S. Air Force as a company to guide the SAGE computer, they are often research experts who oversee government contracts or evaluate proposals. Now they are building a $20 millon “AI Sandbox” for the Federal government to build AI prototypes.

Partnered with NVidia, the sandbox will use an NVidia GDX SuperPOD system capable of an exaFLOP of 8-bit AI computation. Mitre reports this will increase their compute power for AI by two orders of magnitude.

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AI Pet Door Rejects Dead Mice

January 9, 2024 by Kristina Panos 32 Comments

If you have pet with a little access door to the outside world, and that pet happens to be a cat, you’re likely on the receiving end of all kinds of lifeless little lagniappes. Don’t worry, it’s CES season out in Las Vegas and a company called Flappie has the solution — an AI-powered cat door that rejects dead mice and other would-be offerings.

It works about like you might expect — there’s a motion sensor and a night-vision camera on the exterior side of the door. Using Flappie’s “unique and proprietary” dataset, the door distinguishes between Tom and Jerry and keeps out unwanted guests with more than 90% accuracy. To do this, Flappie collected video of a lot of cats and prey in a variety of lighting conditions. There’s even a chip detection system that will reject all other cats.

Thankfully, it’s not all automation. The prey detection system can be turned off entirely, and there are manual switches on the inside for locking and unlocking the door at will. You don’t even have to hook it up to the Internet, it seems.

Americans will have to wait a while, as the company is rolling out the door in Switzerland and Germany first. No word on when the US launch will take place, but interested parties can expect to pay around $399.

Of course, this problem can be solved without AI as long as you’re willing to review the situation and unlock the door yourself.