Singularity

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The original was posted on /r/singularity by /u/posipanrh on 2024-01-10 01:41:20+00:00.

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The original was posted on /r/singularity by /u/seas2699 on 2024-01-09 22:27:21+00:00.

My dream of having extra robotic bench hands is getting closer. For only a few hundred dollars….. would you add one you your work bench?

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The original was posted on /r/singularity by /u/seas2699 on 2024-01-09 22:27:21+00:00.

My dream of having extra robotic bench hands is getting closer. For only a few hundred dollars….. would you add one you your work bench?

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The original was posted on /r/singularity by /u/posipanrh on 2024-01-09 22:24:33+00:00.

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The original was posted on /r/singularity by /u/posipanrh on 2024-01-09 22:24:33+00:00.

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The original was posted on /r/singularity by /u/Uchihaboy316 on 2024-01-09 21:53:35+00:00.

Original Title: Life span increases in mice when specific brain cells are activated. The brain cells communicate with fat tissue to produce cellular fuel, which counteracts effects of aging. The mice were also more active and looked younger — with thicker and shinier coats — at later ages.

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The original was posted on /r/singularity by /u/Uchihaboy316 on 2024-01-09 21:53:35+00:00.

Original Title: Life span increases in mice when specific brain cells are activated. The brain cells communicate with fat tissue to produce cellular fuel, which counteracts effects of aging. The mice were also more active and looked younger — with thicker and shinier coats — at later ages.

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The original was posted on /r/singularity by /u/pocolai on 2024-01-09 21:36:11+00:00.

Alan Turing proposed the test in the paper "computer machinery and intelligence" from 1950. he called it "the imitation game".

however, the test is just a detail, it is used as a simple example to a much bigger point he was trying to make.

the main goal of the paper is to argue philosophically that "intelligence" and "counsciousness" of a being are properties that can only be assessed internally by the being itself and assumed externally from it's behavior.

from a part of the paper: "According to the most extreme form of this view the only way by which one could be sure that a machine thinks is to be the machine and to feel oneself thinking. (...) Instead of arguing continually over this point it is usual to have the polite convention that everyone thinks."

so this is why he proposed the test. it was just a way to try to say this in a more objective way, but the details of the test are not that relevant.

here's the paper so you can read the paper for yourselves. most of the text is fairly tractable:

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The original was posted on /r/singularity by /u/pocolai on 2024-01-09 21:36:11+00:00.

Alan Turing proposed the test in the paper "computer machinery and intelligence" from 1950. he called it "the imitation game".

however, the test is just a detail, it is used as a simple example to a much bigger point he was trying to make.

the main goal of the paper is to argue philosophically that "intelligence" and "counsciousness" of a being are properties that can only be assessed internally by the being itself and assumed externally from it's behavior.

from a part of the paper: "According to the most extreme form of this view the only way by which one could be sure that a machine thinks is to be the machine and to feel oneself thinking. (...) Instead of arguing continually over this point it is usual to have the polite convention that everyone thinks."

so this is why he proposed the test. it was just a way to try to say this in a more objective way, but the details of the test are not that relevant.

here's the paper so you can read the paper for yourselves. most of the text is fairly tractable:

This is an automated archive.

The original was posted on /r/singularity by /u/TalkaboutJoudy on 2024-01-09 21:35:51+00:00.

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The original was posted on /r/singularity by /u/TalkaboutJoudy on 2024-01-09 21:35:51+00:00.

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The original was posted on /r/singularity by /u/IluvBsissa on 2024-01-09 21:18:48+00:00.

In a new paper, “Physics-enhanced deep surrogates for partial differential equations,” published in December in Nature Machine Intelligence, a new method is proposed for developing data-driven surrogate models for complex physical systems in such fields as mechanics, optics, thermal transport, fluid dynamics, physical chemistry, and climate models.

The paper was authored by MIT’s professor of applied mathematics Steven G. Johnson along with Payel Das and Youssef Mroueh of the MIT-IBM Watson AI Lab and IBM Research; Chris Rackauckas of Julia Lab; and Raphaël Pestourie, a former MIT postdoc who is now at Georgia Tech. The authors call their method "physics-enhanced deep surrogate" (PEDS), which combines a low-fidelity, explainable physics simulator with a neural network generator. The neural network generator is trained end-to-end to match the output of the high-fidelity numerical solver.

“My aspiration is to replace the inefficient process of trial and error with systematic, computer-aided simulation and optimization,” says Pestourie. “Recent breakthroughs in AI like the large language model of ChatGPT rely on hundreds of billions of parameters and require vast amounts of resources to train and evaluate. In contrast, PEDS is affordable to all because it is incredibly efficient in computing resources and has a very low barrier in terms of infrastructure needed to use it.”

In the article, they show that PEDS surrogates can be up to three times more accurate than an ensemble of feedforward neural networks with limited data (approximately 1,000 training points), and reduce the training data needed by at least a factor of 100 to achieve a target error of 5 percent. Developed using the MIT-designed Julia programming language, this scientific machine-learning method is thus efficient in both computing and data.

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The original was posted on /r/singularity by /u/IluvBsissa on 2024-01-09 21:18:48+00:00.

In a new paper, “Physics-enhanced deep surrogates for partial differential equations,” published in December in Nature Machine Intelligence, a new method is proposed for developing data-driven surrogate models for complex physical systems in such fields as mechanics, optics, thermal transport, fluid dynamics, physical chemistry, and climate models.

The paper was authored by MIT’s professor of applied mathematics Steven G. Johnson along with Payel Das and Youssef Mroueh of the MIT-IBM Watson AI Lab and IBM Research; Chris Rackauckas of Julia Lab; and Raphaël Pestourie, a former MIT postdoc who is now at Georgia Tech. The authors call their method "physics-enhanced deep surrogate" (PEDS), which combines a low-fidelity, explainable physics simulator with a neural network generator. The neural network generator is trained end-to-end to match the output of the high-fidelity numerical solver.

“My aspiration is to replace the inefficient process of trial and error with systematic, computer-aided simulation and optimization,” says Pestourie. “Recent breakthroughs in AI like the large language model of ChatGPT rely on hundreds of billions of parameters and require vast amounts of resources to train and evaluate. In contrast, PEDS is affordable to all because it is incredibly efficient in computing resources and has a very low barrier in terms of infrastructure needed to use it.”

In the article, they show that PEDS surrogates can be up to three times more accurate than an ensemble of feedforward neural networks with limited data (approximately 1,000 training points), and reduce the training data needed by at least a factor of 100 to achieve a target error of 5 percent. Developed using the MIT-designed Julia programming language, this scientific machine-learning method is thus efficient in both computing and data.

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The original was posted on /r/singularity by /u/Zestyclose_West5265 on 2024-01-09 20:55:24+00:00.

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The original was posted on /r/singularity by /u/abidallico on 2024-01-09 17:05:43+00:00.

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The original was posted on /r/singularity by /u/Zestyclose_West5265 on 2024-01-09 20:55:24+00:00.

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The original was posted on /r/singularity by /u/abidallico on 2024-01-09 17:05:43+00:00.

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The original was posted on /r/singularity by /u/ImInTheAudience on 2024-01-09 16:26:58+00:00.

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The original was posted on /r/singularity by /u/ImInTheAudience on 2024-01-09 16:26:58+00:00.

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The original was posted on /r/singularity by /u/cissybicuck on 2024-01-09 20:29:53+00:00.

Anyone interested? We're going to try to do this working from home, on zero budget, getting AI to do as much of the work as possible.

What sort of movie would you want to help create? I would like something character-driven, with good dialogue. Something animated, but not overly cartoonish or uncanny. Maybe 90 minutes? It might take us a while to make it, and we should plan a development schedule with the idea of better technologies emerging baked-in. It'll be a matter of passion, timing, and lucky guesses.

We can release it for torrent download with a customer-chosen price tag, free if they want it for free. All proceeds will go directly into funding the next movie. Maybe we can start a tiny film production studio.

My qualifications: I have an MBA, wrote for publication in school, was an NCO in the Army, and have all kinds of time.

If you're interested, comment here or send me a direct message.

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The original was posted on /r/singularity by /u/glencoe2000 on 2024-01-09 20:20:20+00:00.

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The original was posted on /r/singularity by /u/stievstigma on 2024-01-09 20:17:41+00:00.

Despite having decades to consider digital resurrection, my mind is still blown after watching this new hour long special from the late great George Carlin. It is genuinely very funny (and that’s coming from a comedian).

What really struck me about the special are the moments where he breaks the 4th wall to wonder out loud about his digital existence and even dedicates a whole bit on “what the fuck am I?”.

I’d like to know what the community thinks, preferably after watching the full hour, about digital Carlin’s assertions about A.I. and digital immortality.

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The original was posted on /r/singularity by /u/Altruistic-Skill8667 on 2024-01-09 19:42:51+00:00.

I am looking for a list of PAID professions where replacement by AI is nonsensical, even if AI would be outperforming the corresponding human. Here are some for now I could come up with, so you see that there actually are some:

Athletes / professional players: intrinsically about human performance

Some artists: I believe some rich collectors will still pay a premium for “human made objects”, as they are artifacts with unique imperfections that showcase human ability similar to what athletes showcase.

Priests: Even if AI understands the Bible better and gives better speeches, I believe some people still will pay a premium for services like weddings and funerals due to respect for the dead person or their symbolic meaning.

Many CEOs / company owners: by the sheer fact that WE want to decide what AI does and not the other way round.

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The original was posted on /r/singularity by /u/Altruistic-Skill8667 on 2024-01-09 19:42:51+00:00.

I am looking for a list of PAID professions where replacement by AI is nonsensical, even if AI would be outperforming the corresponding human. Here are some for now I could come up with, so you see that there actually are some:

Athletes / professional players: intrinsically about human performance

Some artists: I believe some rich collectors will still pay a premium for “human made objects”, as they are artifacts with unique imperfections that showcase human ability similar to what athletes showcase.

Priests: Even if AI understands the Bible better and gives better speeches, I believe some people still will pay a premium for services like weddings and funerals due to respect for the dead person or their symbolic meaning.

Many CEOs / company owners: by the sheer fact that WE want to decide what AI does and not the other way round.

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The original was posted on /r/singularity by /u/Sprengmeister_NK on 2024-01-09 19:10:45+00:00.

Paper:

Code:

Abstract:

State Space Models (SSMs) have become serious contenders in the field of sequential modeling, challenging the dominance of Transformers. At the same time, Mixture of Experts (MoE) has significantly improved Transformer-based LLMs, including recent state-of-the-art open-source models. We propose that to unlock the potential of SSMs for scaling, they should be combined with MoE. We showcase this on Mamba, a recent SSM-based model that achieves remarkable, Transformer-like performance. Our model, MoE-Mamba, outperforms both Mamba and Transformer-MoE. In particular, MoE-Mamba reaches the same performance as Mamba in 2.2x less training steps while preserving the inference performance gains of Mamba against the Transformer.