SoulGuardian55

SoulGuardian55 t1_jdh9576 wrote

Some people will still believe that AI should not be given the diagnosis of patients. Because no matter how it improves and develops, "mistakes will creep into it, or there will be from beginning, costing patients lives."

I put forward a counter question to this thesis: "If it does not fit, then what is better? Human doctors also make mistakes more than once, which costs people their lives."

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SoulGuardian55 OP t1_j73se3x wrote

Love to speculate about exponential growth and future developments, but the current progress gives too much fuel for discussion alone. Narrow AI systems and their advances are what brought my attention more closely since late 2010's.

And make some check about these words in the post. They came mostly from youngest person (like I said before), and he is a social worker by education.

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SoulGuardian55 OP t1_j6z5mra wrote

>That is the silliest point of them all, with respect to the people you were talking to. First of all it can be said of many technologies, just think of space travel and the amazing discoveries it brought even indirectly. But even simpler: we haven't been doing that good in the last 40 000 years. Besides, that sounds a lot like an appeal to nature fallacy

Try to emphasize about that point. In another thread I mentioned three people (and their age) who engaged a topic with me. Such words (from 2nd point) came from youngest of them, who's 22.

The second person, which is 23, is a medical student, he's doubtful about complete handling to AI such work as art, but agrees that it's a powerful tool that enhances artists, writers and etc and can give them a lot of help. Out of three he seems most revelant and opened to topic. Of course, he excited about developments of biomedical AI.

The last one is an engineer, 28, just not so engaged in topic about AI and was brought to it partially after appearance of Generative AI and ChatGPT. But also sees potential in that technology.

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SoulGuardian55 OP t1_j6wvwhg wrote

>but use them to improve (e.g. you ask ChatGPT to improve your essay and you learn how to write better).

# Such thought I used in argument with one of them, but he tried to counter it like that: "Do you really think students shall use such systems, even if they are be "education type" to improve themselves? I highly doubtful that's shall be the case."

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SoulGuardian55 OP t1_iyeilnd wrote

"Wormholes — wrinkles in the fabric of spacetime that connect two disparate locations — may seem like the stuff of science fiction. But whether or not they exist in reality, studying these hypothetical objects could be the key to making concrete the tantalizing link between information and matter that has bedeviled physicists for decades.

Surprisingly, a quantum computer is an ideal platform to investigate this connection. The trick is to use a correspondence called AdS/CFT, which establishes an equivalence between a theory that describes gravity and spacetime (and wormholes) in a fictional world with a special geometry (AdS) to a quantum theory that does not contain gravity at all (CFT).

In “Traversable wormhole dynamics on a quantum processor”, published in Nature today, we report on a collaboration with researchers at Caltech, Harvard, MIT, and Fermilab to simulate the CFT on the Google Sycamore processor. By studying this quantum theory on the processor, we are able to leverage the AdS/CFT correspondence to probe the dynamics of a quantum system equivalent to a wormhole in a model of gravity. The Google Sycamore processor is among the first to have the fidelity needed to carry out this experiment."

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SoulGuardian55 OP t1_iy4xgqn wrote

"Scientists have developed an artificial intelligence algorithm capable of predicting the structure and properties of more than 31 million materials that do not yet exist.

The AI tool, named M3GNet, could lead to the discovery of new materials with exceptional properties, according to the team from the University of California San Diego who created it.

M3GNet was able to populate a vast database of yet-to-be-synthesized materials instantaneously, which the engineers are already using in their hunt for more energy-dense electrodes for lithium-ion batteries used in everything from smartphones to electric cars.

The matterverse.ai database and the M3GNet algorithm could potentially expand the exploration space for materials by orders of magnitude.

UC San Diego nanoengineering professor Shyue Ping Ong described M3GNet as “an AlphaFold for materials”, referring to the breakthrough AI algorithm built by Google’s DeepMind that can predict protein structures.

“Similar to proteins, we need to know the structure of a material to predict its properties,” said Professor Ong.

“We truly believe that the M3GNet architecture is a transformative tool that can greatly expand our ability to explore new material chemistries and structures.”"

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