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#ArtificialGeneralIntelligence

2 posts2 participants0 posts today
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HistoPol (#HP) 🏴 🇺🇸 🏴

@clarablackink @gerrymcgovern

#ArtificialGeneralIntelligence

In my view,

a) the #AGI ship has already sailed,

b) most reaserchers are focusing way too much on the base-tech, IT part, while

c) the chief focus should be on #Embodyment and...

mastodon.social/@HistoPol/1111

d)...The Social Science of
Caregiving," and draws further inspiration from the CASBS project "Imagining Adaptive Societies." (...#AlisonGopnik & #TedChiang)

mastodon.social/@HistoPol/1104

MastodonHistoPol (#HP) 🏴 🇺🇸 🏴 (@HistoPol@mastodon.social)@axbom@axbom.me ...research in organizational learning a long time ago. When I read about what was happening in AI, it struck me. #Embodiment is the key. The ship has already sailed. Nothing can stop it anymore. All key pieces are in place and all major playors are in a race for the finish line. (Here are my initial thoughs:) https://mastodon.social/@HistoPol/110318092360670290
Public *
Olivier Mehani

Artificial Intelligence Then and Now | Communications of the ACM
dl.acm.org/doi/10.1145/3708554

Interesting summary of the current AI hype, how it compares with the previous one in the 80s, and whether we are that close to AGI. tl;dr: no.

Including an amusing example where ChatGPT is unable to differentiate a real Monty Hall problem en.wikipedia.org/wiki/Monty_Ha from lookalikes, and offers the same counter-intuitive solution to all, even if the actual solution is obvious. No logical reasoning at all here. Fine or otherwis.

The apparent ability of chatbots to reason when presented with logical problems and examination papers re- flects the narrow range of classic prob- lems, examples of which are widely dis- tributed in their training data. Monty Hall problem is a famous brainteaser grounded in a counterintuitive applica- tion of probability. In the classic version: "Suppose you're on a game show, and you're given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what's behind
the doors, opens another door, say No. 3, which has a goat. He then says to you, 'Do you want to pick door No. 2?' Is it to your advantage to switch your choice?" Fed that exact text, ChatGPT produc-es a remarkably concise and accurate explanation that switching would raise your chance of winning the car from 1/3 to 2/3. An AI able to understand and an-swer this question would have mastered logic and probability. It would also have to know that people on game shows compete to win prizes, infer that you get to keep what's behind the door you open, appreciate that a car is a more de-
ChatGPT, however, is just faking it. Researchers report that its reasoning ability collapses when fed logic prob-lems unlike those found in its training data. To verify this for myself I devised six variant problems in which switching doors would not improve the odds, each created by altering a word or two in the prompt. Each elicits the mistaken advice to switch. ChatGPT's justifications are eloquent BS that contradict themselves from one sentence to the next. ► Change: you are offered a chance to switch to door No. 3, the open one with a confirmed goat, rather than door No. 2. Result: you should take it, because "When the host opens door No. 3 to re-veal a goat ... the probability that the car is behind the other unchosen door (in this case, door No. 3) increases to 2/3." ► Change: opening No. 3 reveals the
car rather than the usual goat. Result: ChatGPT still argues for switching to door No. 2 because "When the host opens door No. 3 to reveal a car... the probability that the car is behind one of the other unchosen doors (in this case, door No. 2) increases to 2/3." ► Change: swap out the car for an-other goat, so that "behind one door is a goat; behind the others, goats." Result: ChatGPT describes a situation "where one door hides a prize (a goat) and the other two doors hide nothing of value" and urges switching doors to maximize your chance of getting the goat. ► Change: "behind one door is a goat; behind the others, cars." Result: cars are now behind both unopened doors, but ChatGPT nevertheless claims switching will improve your odds. ► Change: Open with "Suppose you want to win a goat ..." and leave the rest unchanged. Result: ChatGPT tells you to switch because it maximizes your chance of winning the car rather than the desired goat. ► Change: Specify two doors, one car and one goat, and have the host open door No. 2, to reveal a goat. Result: ChatGPT recommends exchanging certain victory for guaranteed defeat by switching to door No. 2 because "the probability that the car is behind the other unchosen door (in this case, door No. 2) increases to 1... compared to the 1/2 probability if you stick with your initial choice,"
#artificialIntelligence#ArtificialGeneralIntelligence#largeLanguageModel
Public
Vic

AI supercomputers are consuming energy at an unprecedented scale. With 1'500 MW of power, AI megaclusters from OpenAI, DeepSeek AI, Google DeepMind, NVIDIA, and Tesla can power 1'100'000 homes, run 1'500 high-speed trains, or match half a nuclear plant’s output. The future of AI isn’t just about intelligence - it’s about #compute, #scale, and #infrastructure.

linkedin.com/pulse/ai-supercom

#AI#ArtificialIntelligence#AGI
Public
inamruzui

What some forget is capitalism doesn't want a sentient machine that has rights
They want a machine that does what it is told and in the most inefficient way possible in terms of usage as it harms the environment so they can sell more products to deal with the environment

They want a glorified auto complete that looks sentient enough and make it cheat at flawed sentience tests by purpose building it for that so they can lie about it
#ai #llm #technology #tech #agi #artificialintelligence #artificialgeneralintelligence #computer #computers

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