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Posted on 09/23/2026 9:39:51 PM PDT by SeekAndFind
For years, we've been asking whether artificial intelligence can write like us, draw like us, code like us, or eventually replace us. Anthropic just gave us a more interesting question: Can AI notice something in nature that human scientists have been staring past?
On Wednesday, Anthropic announced that its Claude AI had identified what researchers believe is previously unrecognized biological system hidden in the DNA of bacteriophages, viruses that infect bacteria. The system contains a reverse transcriptase, a nearby partner gene, and a long array of repeating DNA sequences. Anthropic calls it ART, short for array-associated reverse transcriptases.
From Anthropic:
Today, we’re sharing early results from one of our first research programs, in which Claude autonomously discovered a novel enzyme system that is associated with an array of DNA repeats, a pattern reminiscent of CRISPR. Although we don’t yet know its function, the system that Claude discovered has a set of characteristics that have only ever been found together in a handful of other systems, all of which are programmable and perform operations like cutting, copying, and pasting DNA. Beyond CRISPR, which has already transformed science and medicine, several other such systems are now in development as promising tools.
The system that Claude found is based on a reverse transcriptase (RT), enzymes that copy RNA into DNA. While this underlying RT, found in a jumbo phage, had been identified in previous studies, Claude appears to be the first to notice the system’s defining features—an associated array of non-coding DNA sequences and an additional accessory protein of unknown function.
The enzyme itself wasn't unknown. Scientists had already catalogued the reverse transcriptase. What humans apparently missed was the larger pattern surrounding it. Claude noticed that these pieces occurred together... /p>
(Excerpt) Read more at pjmedia.com ...
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The issue here is that LLMs (Large Language Models) from the first examples to the latest, all suffer from the same limitations. They have improved in some ways but the basics have remained the same.
Quoting from Google's most advanced Gemini model itself, “An LLM only sounds self-aware because it has ingested millions of human conversations discussing self-awareness, allowing it to mathematically predict what a self-aware response should look like. It is a highly convincing mirror, not a mind.”
If I had not spent a great deal of time working with a wide variety of artificial intelligence models it would not be so obvious to me that they all have similar limitations at this point in time. Large language models are very useful tools in many ways, but they are a complete dead end when it comes to achieving true human like intelligence. $Billions have been spent developing them over the past few years all over the world and true progress toward actual intelligence has been stalled for an extended period of time. Evolutionary progress has been made to improve their output, but the entire concept has been flawed from the beginning by a ceiling that cannot be broken through without an entirely new concept that will necessarily have to be built from the ground up.
Terminator was not a documentary. It is fantasy that has captured the imaginations of people in our society who have no firsthand experience working with AI tools.
Trump says he’s renaming AI to ‘super intelligence’
Washington Post ^ | 09/22/2026 | By Violet Jira
Posted on 9/22/2026, 7:48:36 PM by Responsibility2nd
So, AI developing from the human brain, to be smarter . . .
proves evolution.
We need a new chart of the amoeba leaving the sea and then growing legs and walking, etc., and growing a brain, and spewing electrons and getting smarter and better.
RE: So, AI developing from the human brain, to be smarter . . . proves evolution.
Not sure if it does. After all AI was CREATED by intelligent beings (i.e. humans ).
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