Did you miss these 2 AI stories? A *Real* LLM-crafted Breakthrough + Continual Learning Blocked?

Okay, I'm going to be honest. AI companies have a set amount of computing power. And at the moment, they are spending more of it on scaling up money-making stuff like browsers and video shorts than on scaling up frontier performance and IQ points. Hence the feeling among some of a slowdown in progress and no hard feelings.

You got to make the investors some money. But as that maxes out, the story will shortly hopefully return to ramping up Frontier Intelligence. For example, when Gemini 3 comes out from Google DeepMind, expected in the next 2 months, but none of what I just said means that pretty juicy things aren't happening with our current language model horsepower. So, I'm going to start with a novelty produced by a baby LLM.

Then I'll get to a revealing remark from a top OpenAI researcher and end with some interesting bits that I found throughout this week. Let's start with a language model so often decrieded for their hallucinations, but one that actually is pushing science forward by learning the language of biology. Yes, the model does have a dodgy name, C2S scale, but it was able to generate a novel hypothesis for a drug to aid in cancer treatment. What I'm going to try and do is simplify the simplification of this 29page paper.

So here we go. When I say we have a language model that generated a novel hypothesis for a drug to aid in cancer treatment, what I mean is it was a drug candidate that was not in the literature for being able to help in this way. This model by the way was based largely on the openw weightights Gemma 2 architecture from Google released over a year ago. Gemma 3 has come out since.

Gemma 4 is due any time. So it's not the latest Gemma by any stretch. But anyway, this language model was given special doggy training. You can think of it.

Reinforcement learning rewards for accurately predicting how cells would react to drugs, especially regarding interferon. I know what you're thinking. But why would we do that though? Well, it's to make cold cancer tumors hot.

In other words, to make them detectable by the immune system. Wait, so hold on. This is an LLM that can speak biology. Yes.

And English, too. Like, you could probably likely still chat to this ...