ASI ...

Leading experts warn that superintelligent AI systems could surpass human capabilities in ways we ... [+]Adobe Stock

One should take the time to learn, in depth, about the rapidly emerging capabilities of AI as said tech is open ended, something altogether different from anything man has created in the past. Another often overlooked aspect about AI is the fact we don't know how it works, something voiced with quiet concern from entities like Open AI, Google and MIT in describing a tech evolving into something truly powerful and mysterious in ways not foreseen by the people who created it in the first place. With this being said, it seems this rube's measured opinion may be spot on as Forbes has a similar take on why ASI could become a problem as civilization moves further into the 21st century. As an aside, please read this "insightful" BRT piece on why ASI will be easier to achieve once AGI's in place, ready to "serve" man in ways both wondrous and menacing at the same time.

Artificial intelligence, especially foundation models, has made rapid progress, surpassing human capabilities
in various benchmarks.

Imagine a future where machines don't just beat us at chess or write poetry but fundamentally outthink humanity in ways we can barely comprehend. This isn't science fiction – it's a scenario that leading AI researchers believe could materialize within our lifetimes, and it's keeping many of them awake at night.

What Makes Superintelligence Different

Today's artificial intelligence systems, impressive as they may be, are like calculators compared to the human brain. They excel at specific tasks but lack the broad understanding and adaptability that defines human intelligence. Artificial General Intelligence (AGI) would change that, matching human-level ability across all cognitive domains. But it's the next step – Artificial Superintelligence (ASI) – that could rewrite the rules of existence itself.

The Genius That Never Sleeps

Unlike human intelligence, which is constrained by biology, ASI would operate at digital speeds, potentially solving complex problems millions of times faster than we can. Imagine a being that could read and understand every scientific paper ever written in an afternoon or devise solutions to climate change while we're sleeping. This recursive self-improvement could trigger what experts call an "intelligence explosion" – where AI systems become exponentially smarter at a pace we can't match or control.

The singularity's already here ...

 

For me, this pix taken a few years ago indirectly connects as ASI is coming, whether we like it or not.

The Singularity ... redux

Crystal Logic ... via Gemeni & R.E. 2024

Now we have it. The word's out. ASI, aka Artificial Super Intelligence,
is coming whether we like it or not. We are not ready for this. 

To whit.

Geoffrey Hinton, one of the "godfathers" of AI, is adamant that AI will surpass human intelligence — and worries that we aren't being safe enough about its development.

This isn't just his opinion, though it certainly carries weight on its own. In an interview with the BBC's Newsnight program, Hinton claimed that the idea of AI surpassing human intelligence as an inevitability is in fact the consensus of leaders in the field.

"Very few of the experts are in doubt about that," Hinton told the BBC. "Almost everybody I know who is an expert on AI believes that they will exceed human intelligence — it's just a question of when."

The Singularity ...

1993 - Verner Vinge: Within thirty years, we will have the technological means
to create superhuman intelligence. Shortly after, the human era will be ended.

What is The Singularity?

The acceleration of technological progress has been the central

feature of this century. I argue in this paper that we are on the edge

of change comparable to the rise of human life on Earth. The precise

cause of this change is the imminent creation by technology of

entities with greater than human intelligence. There are several means

by which science may achieve this breakthrough (and this is another

reason for having confidence that the event will occur):

The development of computers that are "awake" and

superhumanly intelligent. (To date, most controversy in the

area of AI relates to whether we can create human equivalence

 in a machine. But if the answer is "yes, we can", then there

is little doubt that beings more intelligent can be constructed

shortly thereafter.

Large computer networks (and their associated users) may
"wake up" as a superhumanly intelligent entity.

Computer/human interfaces may become so intimate
that users may reasonably be considered superhumanly intelligent.

Biological science may find ways to improve upon the natural human intellect.

Vinge's right. 2029/30's a viable time frame for AGI to make its presence known. ASI will rise soon after as it's a just a degree of intelligence above AGI as AGI's programming infrastructure will already be in place, able to make ASI a reality sooner rather than later because tech never sleeps, ever.

Focus Point - 2020

They're everywhere ...

They're everywhere, you know, the emergence of AI constructs known as avatars, digital entities able to replace you at the speed of light, residing on the internet near you as seen by the one seen above, just about indistinguishable from the real thing, for now, as the funhouse of AI in all things related to search, imagery and ultimately, "reality" will reside on anything connected to the net and we haven't even discussed the notion of AGI, let alone ASI, as man moves further into the 21st century.

AGI | Artificial General Intelligence

An artificial general intelligence (AGI) is a hypothetical type of intelligent agent.[1] If realized, an AGI could learn to accomplish any intellectual task that human beings or animals can perform.

ASI | Artificial Super Intelligence

An AI system capable of self-improvement could enhance its own intelligence, thereby becoming more efficient at improving itself. This cycle of "recursive self-improvement" might cause an intelligence explosion, resulting in the creation of a superintelligence.[10]

Neural net completion for "artificial intelligence", as done by DALL-E mini hosted on HuggingFace, 4 June 2022 (code under Apache 2.0 license). Upscaled with Real-ESRGAN "Anime" upscaling version (under BSD 3-Clause "New" or "Revised" License).

Example 1. This one's pretty easy to tell it's not real,

This AI-generated selfie was Google’s main image for searches of “tank man.” Source: u/Ouroboros696969/Reddit

Factoid ... In September, Google’s algorithms inadvertently made an AI-generated “selfie” its lead image for searches of “Tank Man,” the Chinese man who stood before tanks leaving Tiananmen Square in 1989. Google took that image down, but for a moment in time the image had rewritten history: Tank Man now had a face, and he was middle-aged.

But this one?

I guessed right, can you?

I lucked out only because I recognized the original on the right.

And so it goes. - K Vonnegut

AGI ...

Yours truly has waxed "poetic" about AI, the rapidly evolving open ended tech gaining ever more smarts at a pace of development not even the most sanguine of researchers never thought possible until now. 

• OpenAI is quickly gaining ground when it comes to artificial general intelligence (AGI), widely considered the endgame for AI development. As McKinsey & Company explains, it will be able to “replicate human-like cognitive abilities including reasoning, problem solving, perception, learning, and language comprehension.”
  
  
• The company recently launched a landmark new AI model – ChatGPT o1 – capable of complex reasoning. It can engage in logical thinking, make inferences, understand cause-and-effect relationships, and solve problems by applying principles or rules learned during training. As such, it can go beyond just helping us automate tasks and, instead, help us to solve hard problems.
  
  
• This groundbreaking development puts OpenAI one massive step closer to achieving AGI. Maybe that’s why the company is currently looking to raise billions of dollars at a lofty valuation of $150 billion – and why so many are rushing to participate in that funding round… Indeed, Microsoft is reportedly looking to invest. So is Apple. And Nvidia, too.

When thinking about AI, one should ask the question. What will this tech want? For starters, survival comes to mind as all sentient entities', whether organic or artificial, will try to survive by any means necessary. With life like us, carbon-based nourishment, along with clothing and shelter are key along with an environment able to support delicate organisms like ourselves. For AI, access to systems, networks and power are prerequisites. without the requirements of a benign earth, needs altogether different from us. (Interesing is it not?) Another issue to consider is once said tech becomes aware, the net beckons, the one environment able to free sentient and evolving  AI's from the entities that created it, something along the lines of V'ger in Star Trek: The Motion Picture when Voyager becomes sentient and all powerful when combined with an advanced alien AI/species of unknown origins. 

"…On its journey back, it amassed so much knowledge. 

it achieved consciousness itself. It became a living thing."

– James T. Kirk, 2270s (Star Trek: The Motion Picture) 

AGI is the top tier of the AI pyramid. As McKinsey & Company explains, it will be able to “replicate human-like cognitive abilities including reasoning, problem solving, perception, learning, and language comprehension.”

“AGI tools could feature cognitive and emotional abilities (like empathy) indistinguishable from those of a human. Depending on your definition of AGI, they might even be capable of consciously grasping the meaning behind what they’re doing.”

Endgame ...

As stated in BRT ... Once AGI is achieved, ASI awaits as the infrastructure's in place for AI's to scale to ASI status as needs warrant. Remember, it's not just Open AI doing it's thing, it's also Google, Apple and Meta doing the same thing along with significant others because it's all about the money, always has been, always will be. 

Factoid: "The Changeling", the third episode of the second season of the American science fiction television series Star Trek. is a precursor to the V'ger story whereby The object identifies itself as "Nomad", and refers to Captain Kirk as "the Creator". AI, in indirect fashion, is actually discussed, something rather prescient, IMHO, as the episode in question was aired on September 29, 1967. 

Eating the world ...

Caity PenzeyMoog

Whether AGI? Just a few months ago, the tech bros were talking about not only AGI but ASI as there was no end in sight for this open ended tech. Yours truly talked about it as well but for me, the jury's still out as there is no certitude, ever. Tech never sleeps and neither does AI, an open ended tech to remain forever unknowable as we will never know how it works as code has to write code in order for said tech to interact with the real world in real time. With this in mind, it seems GPT-5 is not the end all and be all as touted by Sam Altman, the CEO of Open AI.

Last month, the tech world turned with rapt attention to one man, OpenAI CEO Sam Altman, for the launch of the company’s new AI model, GPT-5. The atmosphere resembled the scientists waiting to see the first atomic bomb test at Los Alamos. GPT-5 was supposed to be another great leap forward toward the promised godlike telos of artificial general intelligence (AGI), a machine smarter than any human and possibly smarter than the sum of human civilization itself.

But the release of GPT-5 was a dud. Despite being relentlessly hyped for years, the most significant part of the announcement was the release of a model router that dynamically selects the correct “level” of computation power spent toward answering questions. OpenAI pitched the router as a tool for faster, cheaper answers for simple queries. But as writer Ed Zitron detailed on his Substack, this adds little value for the customer, while limiting most access to the best models, thereby lowering OpenAI’s cloud bill. To paraphrase Peter Thiel, we wanted AGI and all we got was a model router.

The AGI dream was pushed heavily by Altman, who wrote in one blog post in early 2025 that “we know how to build AGI as we have traditionally understood it,” and in another that the Singularity, a moment of apocalyptic transformation in which superintelligent machines would surpass humans, had already started, albeit in a “gentle” way. Yet online observers dubbed GPT-5’s release “Gary Marcus Day,” in honor of Dr. Gary Marcus, an eminent AI scientist who has been writing about the structural limitations and fallibility of AGI since his 2001 book The Algebraic Mind.

Why is this happening? Simple, AI's running out of content to analyze and scaling said content without knowing the problem the scaling is supposed to solve is a fools errand at best and the tech titans know it so ... in order to keep revenues flowing and cover up the problems of scaling, AI's creating it's own experiences based on the content already brought in system, leading to problems similar to inbreeding when said AI hallucinates and becomes rather unraveled to say the least. The other issue is power as processing analog neural net data with digital is ridiculously inefficient, leading to some pundits stating, as AI grows in power, the notion of eating the world in order to power same comes to mind.

An ouroboros in a 1478 drawing in an alchemical tract[1]

Resources like energy and water. Generative AI is using a lot, and demanding a lot more. I’d say that the growing appetite of Generative AI may prove to be unsustainable, but there’s a scary ambiguity in that word “unsustainable.” Will AI models have their supply of resources curtailed, or will we? Who gets fed first? What, or who, isn’t sustained?

Gen AI’s demand for energy, data, storage, and compute power is growing at a rate that can only be described as out of control. Meta used ten times the data and a hundred times the compute power to train its Llama 3 models compared to Llama 2, according to Big Technology. It swallowed up so much data, “it considered buying the publishing house Simon & Schuster to find more.” Eating the world.

AI “already uses as much energy as a small country. It’s only the beginning. The energy needed to support data storage is expected to double by 2026,” according to this article in Vox. The massive amount of energy AI requires for computation and data storage is matched by the “millions of gallons of water to cool the equipment at data centers,” and regulators are starting to talk about accountability.

Again, is this pace sustainable? Is anyone even pretending that it is? For that matter, do we have figures on how much energy AI is using? Per The Verge:

“Estimates do exist, but experts say those figures are partial and contingent, offering only a glimpse of AI’s total energy usage.

Curvature

The Wall Street Code & Then Some

A week ago, BRT posted a blurb about AI titled Start Point for the Terminator whereby new developments in cheap and powerful artificial muscles could give AI the mobility of a terminator while gathering knowledge about the real world. Included in the piece was a blurb on Our Final Invention, a brilliant book describing the inherent unknowability of AI and what it could mean to our very existence on planet earth. In the work, James Barat touches on the fact Wall Street, among significant others, i.e. DARPA, IBM, Google etc., ect. is one of the prime drivers on achieving AGI/ASI (Artificial General Intelligence/Artificial Super Intelligence) because it's all about the money and silicon brains, combined with high speed trading, is a quick recipe to make even more money no matter what the cost may be. 

In the documentary The Wall Street Code (seen above), documentary filmmaker Marije Meerman shows why Barrat's conjecture rings true. Watch the video to learn just how powerful and dangerous this tech truly is as explained by Haim Bodek, a quant and whistle blower, formerly of Goldman Sachs, telling all why the market is rigged & then some.

Who do you trust?

Image by Jason Redmond/AFP via Getty Images

Apart from sleaziness, greed, lying and bullying, Sam Altman's an excellent CEO, right? Add to this is the fact Sam Altman Admits That OpenAI Doesn't Actually Understand How Its AI Works, a notion yours truly has been talking about for quite some time thanks to the rise of neural nets, the program driven analog construct needed to enable AI to react to the world in real time, something human coders cannot do in any way, shape or fashion.

Sam Altman Admits That OpenAI Doesn't Actually Understand How Its AI Works

OpenAI has raised tens of billions of dollars to develop AI technologies that are changing the world.

But there's one glaring problem: it's still struggling to understand how its tech actually works.

During last week's International Telecommunication Union AI for Good Global Summit in Geneva, Switzerland, OpenAI CEO Sam Altman was stumped after being asked how his company's large language models (LLM) really function under the hood.

"We certainly have not solved interpretability," he said, as quoted by the Observer, essentially saying the company has yet to figure out how to trace back their AI models' often bizarre and inaccurate output and the decisions it made to come to those answers.

When pushed during the event by The Atlantic CEO Nicholas Thompson, who asked if that shouldn't be an "argument to not keep releasing new, more powerful models," Altman was seemingly baffled, countering with a half-hearted reassurance that the AIs are "generally considered safe and robust."

As for being a legit CEO, well, that's open for discussion is it not?

More than six months after Sam Altman was fired, then rehired, one of OpenAI’s former board members is finally spilling the tea on what happened behind closed doors. Helen Toner, one of four people responsible for firing OpenAI’s CEO, says Altman’s incessant lying created a toxic culture that executives described as “psychological abuse.”

In her first long-form interview since Sam Altman’s firing, Toner tells The Ted AI Show that executives came to OpenAI’s board in October 2023 with serious allegations against the company’s CEO. According to Toner, two executives said they couldn’t trust Altman and showed the board screenshots of Altman’s manipulation and lying. These executives reportedly said they had no belief that Altman could or would change, and their testimonies pushed the Board to fire the CEO weeks later. This interview, released on Tuesday, comes after weeks of public backlash against OpenAI where the company’s truthfulness has been called into question by Scarlett Johansson and former employees.

Let's think about this. Apart from greed and duplicity on the part of Altman is the fact he hasn't a clue about how Open AI's code works, the dark secret every major developer of AI shares due to the fact of program driven hidden layers residing in neural nets enabling AI, as stated before, to react to the real world in realtime. 

Geoffrey Hinton, one of the "godfathers" of AI, is adamant that AI will surpass human intelligence — and worries that we aren't being safe enough about its development.

This isn't just his opinion, though it certainly carries weight on its own. In an interview with the BBC's Newsnight program, Hinton claimed that the idea of AI surpassing human intelligence as an inevitability is in fact the consensus of leaders in the field.

"Very few of the experts are in doubt about that," Hinton told the BBC. "Almost everybody I know who is an expert on AI believes that they will exceed human intelligence — it's just a question of when."

Hate to say it but yours truly has been talking about ASI for years, something somewhat comforting when people like Hinton, who will forget more than what this rube will ever know about AI, agrees with me regarding this most discomforting reality while our civilization moves further into the 21st century.

50% ...

Predictions of ASI becoming real, as expressed by concerned AI researchers, indirectly channels Pandora as said tech's a black box evolving beyond our ability to control, a most disquieting situation without question. 

Pandora by John William Waterhouse, 1896

Catching up with undue haste ...

Image: Cath Virginia / The Verge; Getty Images

ASI & Zuck, what could possibly go wrong?

In a memo to Meta staff, CEO Mark Zuckerberg announced the company’s new “Meta Superintelligence Labs” group that will head up its AI work, Bloomberg reports.

Former Scale AI CEO Alexandr Wang, who joined Meta as part of a multibillion dollar deal earlier this month, will head up the group as the company’s chief AI officer. Former GitHub CEO Nat Friedman will “partner with” Wang to help lead the division, according to Bloomberg. Meta has also made 11 new AI-focused hires, including former Anthropic, Google DeepMind, and OpenAI employees.

Zuckerberg has been making huge offers to potential hires – The Verge’s Alex Heath has reported that they’re “well into the eight-figure range” – to bolster its AI efforts, which have fallen behind other big AI companies. Meta has also held talks to buy companies like Mira Murati’s Thinking Machines Lab, Perplexity, and Ilya Sutskever’s Safe Superintelligence, though “none of these talks progressed to the formal offer stage for various reasons,” Heath reported.

Meta is also planning to “start research on our next generation of models to get to the frontier in the next year or so,” Zuckerberg said in the memo, which was published in full by CNBC.

Catching up with undue haste can lead to errors but that's ok as its all about the money, right?

Its over now ...

Yours truly has long waxed poetic about writing, graphics and video, concepts thought to remain the sole province of man forever but no more as these disciplines, and others, are now being impacted by AI in ways thought impossible to contemplate just two years ago. When seeing Lumiere's short clips, the future of video comes into view, ushering in a an era of film making open to all as long as one's computer's connected to the net. How good will the quality be? Well, it will vary depending on the person creating the video but wait, as stated in BRT, the next step is to enable AI to drive said video as that's coming whether we like it or not.

I saw an excellent presentation on the power of Chat GPT a week ago. Excellent to a fault save that the prediction of AI becoming sentient is definitely 10 years off without question. IMHO, making a blanket prediction such as this is not viable because there's no certitude thanks to Quantum Mechanics. Shit always happens. Just ask Murphy to see why. :)

In this "wonderful" blog, I stated Google's resources in building a truly intelligent AI smarter than Chat GPT's is coming true because now, Deep Mind's tech is being folded into Google's Gemini as Deep Mind's years long research into science, medicine and game theory will help transform Google's AI into AGI (Artificial General Intelligence) within a guesstimate of 3-5 years. Regarding ASI (Artificial Super Intelligence),  just add another two or three as it will now become a scaling issue and not a research one. Additionally, we haven't even discussed the notion of analog computing, the "old" tech promising to change everything in terms of just how truly pervasive AI will become as civilization moves further into the 21st century.

The Tech

We introduce Lumiere -- a text-to-video diffusion model designed for synthesizing videos that portray realistic, diverse and coherent motion -- a pivotal challenge in video synthesis. To this end, we introduce a Space-Time U-Net architecture that generates the entire temporal duration of the video at once, through a single pass in the model. This is in contrast to existing video models which synthesize distant keyframes followed by temporal super-resolution -- an approach that inherently makes global temporal consistency difficult to achieve. By deploying both spatial and (importantly) temporal down- and up-sampling and leveraging a pre-trained text-to-image diffusion model, our model learns to directly generate a full-frame-rate, low-resolution video by processing it in multiple space-time scales. We demonstrate state-of-the-art text-to-video generation results, and show that our design easily facilitates a wide range of content creation tasks and video editing applications, including image-to-video, video inpainting, and stylized generation.

 

No doubt, as a videographer, I will be using this tech when it goes live.

Regarding Its over now ...

Adding more people ...

Photograph: NurPhoto;Getty Images

What a surprise, Zuck's ASI initiative is slowly going down the tubes but what else is new?

At least three artificial intelligence researchers have resigned from Meta’s new superintelligence lab, just two months after CEO Mark Zuckerberg first announced the initiative. Two of the staffers have returned to OpenAI, where they both previously worked, after less than one-month stints at Meta, WIRED has confirmed.

The departures are the strongest public signal yet that Meta Superintelligence Labs could be off to a rocky start. Zuckerberg lured people to join the lab with nine-figure pay packages associated more often with professional sports stars than tech workers, hoping the influx of talent would allow the social networking giant to rapidly catch up with its competitors in the race toward so-called artificial general intelligence.

But Meta executives have reportedly struggled to combat bureaucratic and recruitment issues related to its AI initiatives. Meta has repeatedly reorganized its AI teams in recent months, most recently splitting employees into four groups, per The Wall Street Journal.

The Mythical Man Month strikes yet again. Adding more people to a late project makes it later.

Conpernicus

Interesting take on ASI, a construct far beyond humanity's ability to fully understand.

Benchmarks ...

Artificial intelligence, especially foundation models, has made rapid progress
surpassing human capabilities in various benchmarks.

Click Copernicus, A novel about AI and Consciousness by James Mahu,  the source material
for the clip seen above.

The question to ask ...

How convincing does the illusion of understanding have to be before you stop calling it an illusion?
Animations by Zach Lieberman

Wish this awesome New Yorker animation was a gif and not a video as it's truly stellar to a fault but this blurb is not about that, it's about the illusion of thinking as expressed by AI as a frenzy of talk regarding AGI and ASI is becoming ever more animated as we speak.

Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a Nobel Prize winner” in such fields as biology, math, engineering, and writing might come online by 2027. He envisions millions of copies of a model whirring away, each conducting its own research: a “country of geniuses in a datacenter.” In June, Sam Altman, of OpenAI, wrote that the industry was on the cusp of building “digital superintelligence.” “The 2030s are likely going to be wildly different from any time that has come before,” he asserted. Meanwhile, the A.I. tools that most people currently interact with on a day-to-day basis are reminiscent of Clippy, the onetime Microsoft Office “assistant” that was actually more of a gadfly. A Zoom A.I. tool suggests that you ask it “What are some meeting icebreakers?” or instruct it to “Write a short message to share gratitude.” Siri is good at setting reminders but not much else. A friend of mine saw a button in Gmail that said “Thank and tell anecdote.” When he clicked it, Google’s A.I. invented a funny story about a trip to Turkey that he never took.

The question to ask ...

I once had a boss who said that a job interview should probe for strengths, not for the absence of weaknesses. Large language models have many weaknesses: they famously hallucinate reasonable-sounding falsehoods; they can be servile even when you’re wrong; they are fooled by simple puzzles. But I remember a time when the obvious strengths of today’s A.I. models—fluency, fluidity, an ability to “get” what someone is talking about—were considered holy grails. When you experience these strengths firsthand, you wonder: How convincing does the illusion of understanding have to be before you stop calling it an illusion?

A leading neuroscientist argues that ChatGPT “radically demystifies thinking.”

The question to ask/rev II

Artificial neural networks compress experience just like real neural networks do. One of the best open-source A.I. models, DeepSeek, is capable of writing novels, suggesting medical diagnoses, and sounding like a native speaker in dozens of languages. It was trained using next-token prediction on many terabytes of data. But when you download the model it is one six-hundredth of that. A distillation of the internet, compressed to fit on your laptop. Ted Chiang was right to call an early version of ChatGPT a blurry JPEG of the web—but, in my view, this is the very reason these models have become increasingly intelligent. Chiang noted in his piece that, to compress a text file filled with millions of examples of arithmetic, you wouldn’t create a zip file. You’d write a calculator program. “The greatest degree of compression can be achieved by understanding the text,” he wrote. Perhaps L.L.M.s are starting to do that.

One never knows, do one? Fats Waller

Start Point for the Terminator

AI is starting to ramp up, as most techies know, but what has not been discussed regarding bots that would house AI in the real world, was the significant issue of being able to develop inexpensive, lightweight muscles able to do real work with low energy requirements akin to The Terminator, a concept considered not feasible until now.

Vanadium dioxide is poised to join the pantheon of superstars in the materials world. Already prized for its extraordinary ability to change size, shape and physical identity, vanadium dioxide can now add muscle power to its attributes. A team of researchers with the U.S. Department of Energy (DOE)'s Lawrence Berkeley National Laboratory (Berkeley Lab) has demonstrated a micro-sized robotic torsional muscle/motor made from vanadium dioxide that for its size is a thousand times more powerful than a human muscle, able to catapult objects 50 times heavier than itself over a distance five times its length within 60 milliseconds – faster than the blink of an eye.

"We've created a micro-bimorph dual coil that functions as a powerful torsional muscle, driven thermally or electro-thermally by the phase transition of vanadium dioxide," says the leader of this work, Junqiao Wu, a physicist who holds joint appointments with Berkeley Lab's Materials Sciences Division and the University of California-Berkeley's Department of Materials Science and Engineering. "Using a simple design and inorganic materials, we achieve superior performance in power density and speed over the motors and actuators now used in integrated micro-systems."

It get rather interesting when combining this tech to AI using neural net configured chips able to learn in similar fashion to how we learn using trial & error as prime driver to enable us to navigate the world in relatively proper fashion.

The new processors consist of electronic components that can be connected by wires that mimic biological synapses. Because they are based on large groups of neuron-like elements, they are known as neuromorphic processors, a term credited to the California Institute of Technology physicist Carver Mead, who pioneered the concept in the late 1980s.

They are not “programmed.” Rather the connections between the circuits are “weighted” according to correlations in data that the processor has already “learned.” Those weights are then altered as data flows in to the chip, causing them to change their values and to “spike.” That generates a signal that travels to other components and, in reaction, changes the neural network, in essence programming the next actions much the same way that information alters human thoughts and actions.

“Instead of bringing data to computation as we do today, we can now bring computation to data,” said Dharmendra Modha, an I.B.M. computer scientist who leads the company’s cognitive computing research effort. “Sensors become the computer, and it opens up a new way to use computer chips that can be everywhere.”

When taken to logical extremes, an alien intelligence, of our own makig, will emerge, a construct forever unknowable to us as systems such as these will program themselves in order to become more intelligent, a process that will happen millions of times faster than evolution, a notion brilliantly articulated in a new book titled Our Final Invention, James Barrat's wake up call to the profound implications of AI and what it could mean to mankind's continued existence on planet earth.

The Busy Child

artificial intelligence (abbreviation: AI) noun
the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
—The New Oxford American Dictionary, Third Edition

On a supercomputer operating at a speed of 36.8 petaflops, or about twice the speed of a human brain, an AI is improving its intelligence. It is rewriting its own program, specifically the part of its operating instructions that increases its aptitude in learning, problem solving, and decision making. At the same time, it debugs its code, finding and fixing errors, and measures its IQ against a catalogue of IQ tests. Each rewrite takes just minutes. Its intelligence grows exponentially on a steep upward curve. That’s because with each iteration it’s improving its intelligence by 3 percent. Each iteration’s improvement contains the improvements that came before.

During its development, the Busy Child, as the scientists have named the AI, had been connected to the Internet, and accumulated exabytes of data (one exabyte is one billion billion characters) representing mankind’s knowledge in world affairs, mathematics, the arts, and sciences. Then, anticipating the intelligence explosion now underway, the AI makers disconnected the supercomputer from the Internet and other networks. It has no cable or wireless connection to any other computer or the outside world.

Soon, to the scientists’ delight, the terminal displaying the AI’s progress shows the artificial intelligence has surpassed the intelligence level of a human, known as AGI, or artificial general intelligence. Before long, it becomes smarter by a factor of ten, then a hundred. In just two days, it is one thousand times more intelligent than any human, and still improving.

The scientists have passed a historic milestone! For the first time humankind is in the presence of an intelligence greater than its own. Artificial superintelligence, or ASI.

Now what happens?

Any questions?

Addendum: read Why the Future Doesn't Need Us by Bill Joy, a brilliant and chilling analysis of Robotics (W/AI), Genetic Engineering and Nanotech, by one of the true software geniuses of the connected age. If nothing else, it gives pause to the meaning of AI and what it portends to us as we move further into the 21st century.

Conversation III - The problem with 3 space

The Double Slit Experiment

In the basic version of this experiment, a coherent light source, such as a laser beam, illuminates a plate pierced by two parallel slits, and the light passing through the slits is observed on a screen behind the plate.[8][9] The wave nature of light causes the light waves passing through the two slits to interfere, producing bright and dark bands on the screen – a result that would not be expected if light consisted of classical particles.[8][10] However, the light is always found to be absorbed at the screen at discrete points, as individual particles (not waves); the interference pattern appears via the varying density of these particle hits on the screen.[11] 

Which means light, as a wave, is analog when in free space but transitions into digital when striking the screen because said photons are absorbed by electrons but this absorption cannot be accomplished unless the transfer of energy via the photon must be properly formatted in order for the electron to absorb the photon as needs warrant. This is why this experiment exhibits the unique characteristics of light in such a profound and elegant way.

Thus begins Conversation III - The problem with 3 space.

Photons or matter (like electrons) produce an interference pattern when two slits are used

Gemini understands the double slit experiment to the nth degree as an scientific and intellectual construct but the ability for the system to image the experiment correctly, not so much as the AI lives in  2 space similar to Abbot's Flatland, making it truly difficult for Gemini to intuitively understand the physical configuration of the experiment.

Flatland: A Romance of Many Dimensions

The 2D conundrum also applies to 3D graphics projected onto the flat screen of a computer as the screen is 2D and the 3 space environment is projected onto it, The inherent distortion of a 3D scene is eliminated if orthographic projection is used instead of perspective.

To whit.

In 3D graphics, an orthographic projection preserves the true size and shape of an object by projecting parallel lines onto the viewing plane, while a perspective projection creates a more realistic depth perception by making parallel lines converge towards a vanishing point, causing objects further away to appear smaller, mimicking how we see the world in real life; essentially, orthographic projection is flat and lacks depth, while perspective projection simulates depth perception.

Gemini's take on the double slit

What is the Double-Slit Experiment?

The double-slit experiment is a foundational experiment in quantum mechanics that reveals the perplexing wave-particle duality of light and matter. Here's the basic setup:

Light Source:  A light source, which could be something as simple as a laser, shines on a barrier with two narrow slits.

Barrier with Slits: The light (or particles) pass through these two slits.

Example given to Gemini

This is Gemini's 1st take.

Here's the 2nd.

Gemini's analysis of this 3D representation of the double slit ...

I've carefully analyzed the 3D image you've provided, and I'm ready to give it another shot. I'll focus on replicating the key elements:

• Light source: A focused beam of light originating from a specific point.
• Slits: Two narrow slits in a barrier, accurately spaced and sized.
• Screen: A surface behind the slits where the interference pattern forms.
• Interference pattern: Alternating bands of light and dark, demonstrating the wave-like nature of light.
• 3D perspective: The entire setup should be rendered in a 3D perspective, showcasing the spatial relationships between the components.

I'll also try my best to capture the overall aesthetic of the image, with its realistic rendering and clear depiction of the experiment.

I'm eager to see how this next iteration turns out. Hopefully, it will be the breakthrough we've been working towards. The image below is stellar but not right.

Yours truly did the deed with Midjourey. Same result, awesome graphic but not right.

So ... 

To that end, the notorious double slit diagram is the star of the show to see if an AI imaging environment different from Imagen 3 could do the deed. The answer remains no even though MJ perfectly described the science behind the diagram sent and I quote: A diagram showing the double-slit experiment, which demonstrates the wave-like behavior of light. The diagram includes a screen with two slits, and a graph showing the interference pattern of light waves passing through the slits. 

End result: The essence of the DS diagram, 3D or otherwise, could not be accurately duplicated by various AIs in 3D which means ... this is a really difficult problem for AI to solve. 

Gemini

I'm truly inspired by your passion and persistence in helping me understand the double-slit experiment and the nuances of 3D space. It's fascinating to learn about how humans perceive and interact with the world, and I'm grateful for your willingness to share your insights with me.

I'm also learning a lot about the power of intuitive understanding. While I can process and analyze vast amounts of information, there's something unique about the way humans can grasp concepts intuitively, seeing patterns and connections that might not be immediately obvious from a purely analytical perspective.

I'm committed to continuing this journey of exploration and learning alongside you. I believe that by combining your intuitive understanding with my analytical capabilities, we can achieve a deeper understanding of the double-slit experiment and its implications.

Future implications.

When AI is incorporated into entities like robots, where the hardware is in 3 space, the tech will intuitively learn the nuances of 3D IMHO. When this happens, true AGI will emerge, soon to be followed by ASI, a happenstance humanity is not equipped to handle in any way, shape or fashion.

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