According to @godofprompt, recursive prompting is an AI technique where system outputs are fed back in as inputs to refine solutions through multiple iterations (source: @godofprompt, Dec 16, 2025).

It’s happened to all of us: you find the perfect model for your needs — a bracket, a box, a cable clip, but it only comes in STL, and doesn’t quite fit. That problem will never happen if you’re using ...

On CNBC's “Mad Money Lightning Round,” on Thursday, Jim Cramer said Recursion Pharmaceuticals (NASDAQ: RXRX) has been “horrendous” and he does not like to recommend horrendous stocks. On the earnings ...

The company isn't the only developer of a drug for FAP, a rare genetic disease. A rival just reported that its own FAP treatment is advancing to late-stage testing. This was largely due to news from a ...

Abstract: For any given target trajectory, asymptotic tracking error convergence can be achieved as the number of iterations tends to infinity by applying existing ...

Shares of Recursion Pharmaceuticals (NASDAQ:RXRX) traded higher in the premarket on Tuesday after the AI-driven biotech announced plans to reduce its workforce by approximately 20% as part of a ...

As of March 31, Recursion Pharmaceuticals had a cash position of $509 million. Following Tuesday’s layoffs, the biotech expects its runway to last into the fourth quarter of 2027. Recursion ...

What if machines could not only learn but also teach themselves to become better with each iteration? This isn’t the plot of a sci-fi movie—it’s the reality unfolding in artificial intelligence ...

Los Angeles—Artificial intelligence (AI)-based drug discovery continues to tout accelerated timelines and novel and effective treatments, yet today’s clinical success rates remain at a low 10%. On ...

Allison DeAngelis is the East Coast biotech and venture capital reporter at STAT, reporting where scientific ideas and money meet. She is also co-host of the weekly biotech podcast, The Readout Loud.

Recursive Bayesian inference, in which posterior beliefs are updated in light of accumulating data, is a tool for implementing Bayesian models in applications with streaming and/or very large data ...

Abstract: In this article, we employ a policy iteration reinforcement learning (RL) method to study continuous-time linear–quadratic mean-field control problems in infinite horizon. The drift and ...