Artificial Intelligence (AI) is set to transform how we develop future protein foods, by identifying less resource-intensive plant crop varieties, and the most productive ways to farm them and turn them into new products.
Category: robotics/AI
A 9.4-mm untethered flying robot achieves controllable flights, such as hovering, collision survival, and route adjustment.
This article isn’t about whether AI is conscious. It’s about how it behaves—or, more precisely, how it performs something that resembles thinking within a completely different geometric, structural, and temporal reality. It’s a phenomenon we’ve yet to fully name, but we can begin to describe it—not as a function of symbolic logic or linear deduction, but as something more amorphous, more dynamic. Something I call the fluid architecture of cognitive possibility.
Traditional human thought is sequential. We move from premise to conclusion, symbol to symbol, with language as the scaffolding of cognition. We think in lines. We reason in steps. And it feels good—there’s comfort in the clarity of structure, in the rhythm of deduction.
But LLMs don’t think that way.
A new large language model framework teaches LLMs to use an optimization solving algorithm to resolve complex, multistep planning tasks. With the LLMFP framework, someone can input a natural language description of their problem and receive a plan to reach their desired goal.
Study finds that AI fundamentally lacks the human capability to make creative mental connections, raising warning signs for how we deploy AI tools.
The European Center for Medium-Range Weather Forecasts (ECMWF) has fully operationalized its AI Forecasting System (AIFS), achieving up to 20% greater accuracy than traditional methods, particularly in tropical cyclone tracking.
Large language models (LLMs) show promise in tackling planning problems, but there’s a balance between flexibility and complexity. While LLMs can act as zero-shot planners, they struggle with complex tasks involving multiple constraints or long-term goals.
Many frameworks that address these challenges require task-specific preparation, such as tailored examples and predefined validators, which limits their ability to adapt to different tasks.
Too often, the disconnect between a company’s IT department and its business teams slows progress and leads to missed opportunities. In the fast-moving pharmaceutical industry, that can mean the difference between success and losing out to a rival.
Commuters in downtown Barcelona have been able to ride the bus for free this week. There’s just one catch: this mini-bus has no one at the wheel.
The bus pulls away from the stop with its passengers on its own, brakes before changing lanes and eases down one of Barcelona’s most fashionable boulevards.
Renault is testing a new driverless mini-bus in Barcelona this week. The autonomous vehicle is running on a 2.2-km (1.3-mile) circular route with four stops in the center of the Spanish city. Adventurous commuters can jump on free of charge.
Make no mistake about it, there is a lot of money being spent on generative AI in 2025.