Executives at the National Eating Disorders Association (NEDA) decided to replace hotline workers with a chatbot named Tessa four days after the workers unionized.
NEDA, the largest nonprofit organization dedicated to eating disorders, has had a helpline for the last twenty years that provided support to hundreds of thousands of people via chat, phone call, and text. โNEDA claims this was a long-anticipated change and that AI can better serve those with eating disorders.
Growing human babies from scratch in a lab could be possible in just five years thanks to a new breakthrough.
Researchers in Japan are on the cusp of being able to create human eggs and sperm in the lab from scratch, which would then develop in an artificial womb.
Professor Katsuhiko Hayashi, a Japanese scientist at Kyushu University who has already figured out the process in mice, believes he is just five years away from replicating the results in humans.
This is the other boom in super intelligence coming soon. Manipulating gametes will boost human IQs and other desirable traits above any human who has ever lived. This is a form of eugenics that does not involve killing people or depriving them of the right to produce offspring. People will be able to choose to breed the old way and produce offspring by Darwinian chance, or the new way and have their best genes mingled in a laboratory. It will also be possible to build even better outcomes by multigenerational manipulation of gametes. There is no way to stop technology like this and no reason to want to. Many social problems will cease to exist due to tech like this. ABN
To put it very simplyโweโre going to be living among digital minds of all shapes and sizes. So how do you determine who gets a vote? How do you deal with the fact that to reproduce, it takes a human 9 months to make 1 copy of itself, while it takes a digital mind 1 second to make 100,000 copies of itself? Can we have a democracy when the AI population grows to 300 ๐ก๐๐๐๐๐๐๐ while the human population stagnates at 300 ๐๐๐๐๐๐๐?
Moreover, how do you deal with 10000x intelligence differences? We donโt give frogs a vote over human affairs; are we supposed to give 100 IQ beings a vote when it affects those with 1000 IQโs? What if a single mind ends up with 99% of the intelligence/compute (which seems likely)?
Above all, everyone is failing to think about the downstream consequences of this new world we are entering and just how weird and different itโll be.
‘Twas the night before 4/20, and all through the pad, Not a creature was stirring, not even a cat. The bongs were all placed by the windows with care, In hopes that St. Ganja soon would be there.
The stoners were nestled all snug in their beds, While visions of munchies danced in their heads. With my hemp cap on, and my stoner babe near, We had just settled down for a night without fear.
When out on the lawn there arose such a clatter, I sprang from the bed to see what was the matter. Away to the window I flew like a flash, Tore open the shutters and threw up the sash.
The moon on the breast of the new-fallen weed, Gave the lustre of mid-day to objects indeed. When, what to my wondering eyes should appear, But a miniature van, and eight tiny reindeer.
With a little old driver, so lively and quick, I knew in a moment it must be St. Ganja, no trick. More rapid than eagles his coursers they came, And he whistled, and shouted, and called them by name!
“Now, Blunt! Now, Bubbler! Now, Vape Pen and Zigzag! On, Kush! On, Haze! On, Skunk and Big Bag! To the top of the porch! To the top of the wall! Now dash away! Dash away! Dash away all!”
As dry leaves that before the wild hurricane fly, When they meet with an obstacle, mount to the sky. So up to the housetop the coursers they flew, With the van full of weed, and St. Ganja too.
And then, in a twinkling, I heard on the roof, The prancing and pawing of each little hoof. As I drew in my head, and was turning around, Down the chimney St. Ganja came with a bound.
He was dressed all in hemp, from his head to his foot, And his clothes were all tarnished with ashes and soot. A bundle of weed he had flung on his back, And he looked like a peddler just opening his sack.
His eyesโhow they twinkled! His dimples, how merry! His cheeks were like roses, his nose like a cherry! His droll little mouth was drawn up like a bow, And the beard on his chin was as white as the snow.
The stump of a pipe he held tight in his teeth, And the smoke it encircled his head like a wreath. He had a broad face and a round little belly, That shook when he laughed, like a bowl full of jelly!
He was chubby and plump, a right jolly old elf, And I laughed when I saw him, in spite of myself. A wink of his eye and a twist of his head, Soon gave me to know I had nothing to dread.
He spoke not a word, but went straight to his work, And filled all the bongs, then turned with a jerk. And laying his finger aside of his nose, And giving a nod, up the chimney he rose!
He sprang to his van, to his team gave a whistle, And away they all flew like the down of a thistle. But I heard him exclaim, as he drove out of sight, “Happy 4/20 to all, and to all a good night!”
A team of scientists has made a groundbreaking discovery by employing a Generative Pre-trained Transformer (GPT) AI model similar to ChatGPT to reconstruct human thoughts with up to 82% accuracy from functional MRI (fMRI) recordings. This unprecedented level of accuracy in decoding human thoughts from non-invasive signals paves the way for a myriad of scientific opportunities and potential future applications, the researchers say.
The Study and Methodology
Published in Nature Neuroscience, researchers from the University of Texas at Austin used fMRI to gather 16 hours of brain recordings from three human subjects as they listened to narrative stories. The team analyzed these recordings to identify the specific neural stimuli that corresponded to individual words.
Decoding words from non-invasive recordings has long been a challenge due to fMRI’s high spatial resolution but low temporal resolution. Although fMRI images are of high quality, a single thought can persist in the brain’s signals for up to 10 seconds, causing the recordings to capture the combined signals of approximately 20 English words spoken at a typical pace.
Before the advent of GPT Large Language Models (LLMs), this task was nearly insurmountable for scientists. Non-invasive techniques could only identify a few specific words that a human subject was thinking. However, by utilizing a custom-trained GPT LLM, the researchers successfully created a powerful tool for continuous decoding, as there are far more words to decode than brain images available โ exactly where the LLM has superpowers.
The prospect of decoding human thoughts raises questions about mental privacy. Addressing this concern, the research team conducted an additional study in which decoders trained on data from other subjects were used to decode the thoughts of new subjects. The researchers found that “decoders trained on cross-subject data performed barely above chance,” emphasizing the importance of using a subject’s own brain recordings for accurate AI model training.
Recent dramatic increases in generative Artificial Intelligence (AI), including language modeling and image generation, has led to many questions about the effect of these technologies on the economy. We use a recently developed methodology to systematically assess which occupations are most exposed to advances in AI language modeling and image generation capabilities. We then characterize the profile of occupations that are more or less exposed based on characteristics of the occupation, suggesting that highly-educated, highly-paid, white-collar occupations may be most exposed to generative AI, and consider demographic variation in who will be most exposed to advances in generative AI. The range of occupations exposed to advances in generative AI, the rapidity with its spread, and the variation in which populations will be most exposed to such advances, suggest that government can play an important role in helping people adapt to how generative AI changes work.
Massive announcements in the world of AI today from the University of Texas, Geoffery Hinton, IBM, and Walmart.
Here’s the rundown on everything you need to know:
1. AI makes mind-reading possible
This new study will literally- *blow your mind*
Researchers at the University of Texas have developed a GPT-based decoder that translates thoughts into text using non-invasive fMRI scans.
– Participants trained the decoder by listening to podcasts for 16 hours.
– The AI system generated a text as participants listened to or imagined a new story, capturing thoughts .
The exact words were not always the same, but the overall meaning was captured.
[This whole thread is interesting but I am putting it up because the kind of AI feedback described above will reveal in detail the underlying loose organization and chaos of the mind as we speak and listen (and do everything else). Being able to see this clearly will revolutionize our understanding of human psychology; how it actually functions in real-time. When tech like this is something we can access routinely at a business or school or even purchase and use at home, human communication and self-understanding will hit fabulous new levels, freeing us from the humdrum common associations we must now depend on for clear communication. FIML practice can show a great deal of this right now. I would highly recommend more smart people learn to do FIML because it shows us how we really think and act, thus preparing us for what is coming from this new tech. Subjectivity will become much more objective. This will shock and even traumatize many, but it need not because it is real and utterly fascinating. In my view, this will become one of the most impactful technologies stemming from AI. ABN]
Ppl tend to think about AI through very very narrow frames
Obviously, thereโs many who default to AI=unemployment issue
Or the tech folks who see it as crypto 2.0 or merely as big as the internet
But it goes way deeper.
(1/3)
Even EAโs will think about AI primarily in terms of โis it an X-risk? yes or noโ and then go back to debating the โmoral worthโ of animals, totally ignoring the prospect of digital minds that will shortly have arbitrarily large amounts of whatever they define as โmoral worthโ
Everyone is trying to map AI onto some familiar ontology, but the reality will be so unfamiliar, foreign, & incomprehensible that it will tear to shreds the assumptions which we didnโt even know we made
We are going to live through this and are only seeing glimpses of it now
This was the description of itself GPT-4 generated: “Imagine a sleek, metallic sphere with a smooth surface, representing the vast knowledge contained within the model. The sphere emits a soft, pulsating glow that shifts between various colors, symbolizing the dynamic nature ofโฆ
American Buddhist Net 
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