Quantum computing has turned into a phrase that the tech industry will sprinkle on almost anything to help raise funds and generate sales. As a result, there is a tsunami of hype about what quantum computers are going to revolutionise. Join leading quantum computing specialist Scott Aaronson as he challenges the hype and tells us what is really going on.
AI can now imitate the great artists so well that we often can’t tell the difference. But imitation is not creation. Philosopher of aesthetics Derek Matravers argues that a painting without intention is not art at all. When we engage with a painting merely for its beauty, the maker’s identity might not matter. But art does more: it connects us to another mind, to an artist’s deliberate creation of meaning. A human artist stakes something on each decision; an AI stakes nothing, merely averaging out its training data. It might make some beautiful objects, but they are empty of the meaning that we seek in art.
Can AI produce art? The question is not as simple as it might seem. Certainly, AI has played a large part in the production of works of art. The Turkish-American artist, Refik Anadol, has won international acclaim for some spectacular pieces of visual art generated by AI. But was it Anadol who produced these using AI akin to Titian producing his paintings using a paintbrush? Or was it AI who produced these? If consciousness is necessary for creativity, and AI lacks consciousness, then AI lacks creativity. And if creativity is necessary to produce art, then AI could not have produced the works and those works still be art. These and other questions are generating a rich and interesting debate in universities and academic journals across the world.
Where one stands on these matters will depend on where one stands on the broader issues that structure the debate. There is no point in asking whether AI can produce art if one does not know what art is. The same might be true for other concepts that feature in the debate, such as intentions, creativity, meaning and so on. It also helps to know about how the various systems (in particular, the image-generating systems such as DALL-E, Midjourney, and Stable Diffusion) work. I am going to start at a rather more practical level. AI can produce works that have the appearance of works of art in all media. It can produce complex narrative works, complex musical works, and complex images. Judged purely on qualities associated with the medium (say, narrative, musical, or visual complexity) some of these works are above the quality most of us could achieve if we tried it ourselves.
You want to reprogram a cell to heal a disease, but you don’t know what instructions it has already received. Throughout their lives, cells constantly receive chemical signals from their environment that tell them what to do and what to become. If scientists want to manipulate these cells for medical treatments, they first need to decode their “signal history.” However, reading this history inside living, developing tissues has been incredibly difficult—until now. https://www.nature.com/articles/s41592-026-03213-8
To solve this, researchers created a clever two-step workaround. First, in the lab, they exposed human stem cells to thousands of different chemical signals, creating a massive “dictionary” of how cells physically react to specific instructions. Next, they trained an artificial intelligence program named IRIS to memorize this dictionary, teaching it to recognize the unique “fingerprints” that different signals leave behind on a cell.
Once IRIS was trained, the researchers let it act as a detective on real, living mouse embryos. By looking at the current state of the embryo’s single cells, IRIS successfully reconstructed their past. It figured out exactly which chemical signals the cells had experienced to become the specific types they are today, revealing hidden differences between seemingly identical cells and tracing the exact chemical journey cells take as they develop.
Ultimately, this breakthrough reveals that cells across different types share a common, universal language of chemical signals. By giving scientists a scalable, highly accurate tool to map out how cells communicate and develop in the living body, this technology paves the way for designing highly targeted medical therapies and precisely engineering cell behavior.
#machinelearning #cellfateengineering #ComputationalBiology #CellularReprogramming
IRIS learns conserved signaling representations from in vitro perturbation data to reconstruct signaling states and histories across diverse in vivo cellular contexts.
In 1972, Mercedes engineered a clever front-suspension geometry for the W116 to reduce nose-diving under heavy braking. A small engineering detail that helped…
NASA’s newest and largest flying laboratory is being prepped at NASA Langley.
Link: https://www.wavy.com/video/nasa-langl…
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Scientists have discovered that a potential new drug can reverse severe fatty liver disease in animal models by restoring gut health and blocking harmful substances from reaching the liver. The breakthrough could pave the way for new treatments for liver disease and potentially other serious conditions, including cardiovascular disease.
Prof. Moreira argues that reason cannot generate intrinsic value; it merely operates on existing human needs and emotional commitments. While reason can expose contradictions, refine desires, and structure society, it cannot logically compel anyone to care about existence, honesty, or reciprocity. True human value begins with felt needs—most fundamentally, the recognition of the “Other” and their inner life. Ultimately, reason and need must work together to build a pluralistic society where individuals can coexist without needing universal agreement on what makes life meaningful.
