*AI-WATCH NEWSLETTER VOLUME 22*

*AI-WATCH NEWSLETTER VOLUME 22*

December 17th, 2023

Season’s Greetings, Happy Holidays and a Brilliant New Year to You and Yours!

(Open *Holiday Release*)

Please Contribute Your AI-Related Content:

If you send content before January 15, it will be considered for this issue.

Optical Interconnection

By Gordon Rogers, Gary Lapman, Mark Miller, Richard Bradford 

AI-WATCH 

Courtesy of worldview4d.com worldview4d.com/ai-watch 

A monthly newsletter and blog focused on our opinions of the most significant developments in artificial intelligence and their relevance to the real world. Releases the last Sunday of the month at Noon, PST. 

 

Contents: This week’s focus: Optical Interconnectivity

Tickler of the Week: Singularity? You’re kidding, Right?

Note from worldview4d.com: Best things in Life, “cogito, ergo sum”, “As if by an Invisible Hand”, John Q Public, Retrospectives, What If? 

Daily Life: Hidden Brain NPR Podcast today, November 26, original report from Inside Big Data- AI‘s looking at you, kid, and Logical Limits, Solar Flares

Government Activities: Xi and Biden Agree on Constraints for AI, but…

Business News: RUD Ex-X, Falcon, Figma, OpenAI Founder, Ilya Sutskever, TED Talk+

General AI: The Singularity?

New Business: Optics in AI and Quantum Computing: 

Conclusion: Spherical Arguments

Tickler of the Week  

Human: “The singularity is coming soon!”

Quantum AI: “I presume you jest- that’s so forever ago.”

(4) Outside In – SPHERE AVERSION (Smale’s Paradox) – YouTube

Notes from worldview4d.com:

In this season of Traditions and family, we should remember that the “best things in Life are free/G. Rogers

OP-ED by Gary Lapman

Losing our identities…

Traditions guide our lives, whether they are religious, family or home town traditions. This is not a concept that can be adapted by AI and provide the same comforts that we each traditionally experience.  Perhaps those traditions will die off, as many of them have already, due to generational turnover.  Social acceptance of past traditions also cost some loss.  To honor those traditions that we love, relish and respect, will we be able to accept the new ways in which we experience them, as provided by AI?

Some say that even discussions of AI will soon disappear, and the generally accepted technologies and brands will just provide us with the advantages and capabilities of AI, but without specifically naming AI.  This will happen because it is more profitable for the makers, and probably not for any other reason.

Currently it is a “catch phrase” which causes a drive fueled by FOMO (fear of missing out) or “keeping up with the Joneses”.  The new “current thing” is really to have it, experience it, eat it… before anybody (somebody) else.  If I am fishing for the Next Big Thing, will that conflict with tradition? Will it conflict with AI? Will the Next Big Thing displace interest in AI?

We tend to forget, or conveniently ignore, that humans make errors.  While designing or programming AI, errors will be made.  We will suffer for those inevitable errors, but they are part of human nature.  Modern-day marketing emphasizes the features that will get a product sold.  It is not until later that the disadvantages or failures of design are realized. Meanwhile the profits have been made and the benefactors are clearly not the consumers.

The simple things provide us with the treasures we seek.  Traditions are simple particularly because they repeat without change, while providing the same benefits and pleasures.

These are the true treasures./G. Lapman

-AI Think, therefore, AI Am? translated and adapted from René Descartes’ 1637 Discourse on the Method.

In my collaborative efforts with my long-time friend and colleague, Richard Bradford, whom I consider to be an expert in statistical mechanics, I found much to my surprise and joy, that much of the math that underpins artificial intelligence is already well understood by practicing physicists. Is this a happy coincidence? If this question were to be answered authoritatively in the negative, the primary tenet of the Anthropic, or Anthropomorphic Principle and its implicated universe would be rendered archaic and absurd. “The anthropic principle implies that life could not exist in a universe that was significantly smaller than the observed universe.-https://www.britannica.com/science/anthropic-principle

An OpEd by Gary Lapman

Trust, but verify, verify, verify,,,

I am John Q. Public
I need help to understand my wants and needs.
I need help to decide which car I should buy.
I need help updating my resume and finding a new job.
I need help to understand the propositions that will be on the ballot before I vote.
I need help to understand how the candidates that are running for office will affect my future, to shape my vote.
I need help with my kids’ homework.
I need help to do my job more efficiently so I do not get replaced.
I need help to understand my insurance options before I buy.
I need help to protect my internet transactions from fraud.
I need help to protect my medical privacy.
I need help to have my x-rays, ultrasound, and MRI images interpreted better.
I need help to use tele-health for ailment diagnoses.
I need help to be entertained with media that is focused on my likes.
I need help to ensure that the news I watch is truthful.
I need help to be sure that my income tax reporting is accurate so that I don’t overpay.
I need help for more reliable weather predictions to keep me from being stranded.
I have help driving in high-stress locations, or maybe I’m just feeling lazy and would rather someone else drove.
I need help making wise investments.
I need help making vacation plans.
I need help making flight reservations.
I need help making lodging reservations.
I need help during surgery so that I make the best decisions for my patient’s health.
I need help designing and making medical supplements and drugs.
I need help designing, building, assembling, shipping and marketing my products.
I need help deciding whether my intellectual property is patentable.
I need help becoming or staying green in my consumption.
I need help determining the best major for my education and the best-fit college.
I need help to paint wildlife and portraits.
I need help with technical writing.
I need help with designing my LinkedIn profile to attract more attention.
I need help doing more productive internet searches.
I need help telling bedtime stories to my kids.
I need help designing and building my website.
I need help solving a series of crimes.
I need help understanding climate change and how to cope.
I need help passing the Bar exam.
I need help post-processing my photographs and videos.
I need help debugging my computer code.
I need help pulling weeds on my organic farm.
I need help knowing what crops to plant and how to protect them from disease and pests.

Soooooo, John has listed numerous tasks that he needs help with (certainly incomplete). AI has promised to provide help in these areas and more. How does John build trust in AI? First, he must determine if he is REALLY using AI or is he falling victim to a marketer’s ploy. “Doveryay, no proveryay” is a Russian proverb that was translated into English and used most famously by then President Ronald Reagan, “Trust, but verify”. Healthy distrust makes a good basis for cooperation between AI and John.
So, how is John going to proceed? Very carefully! Perhaps he will operate in parallel, or perform the task first himself and see how the AI improves it, or let the AI perform first, and then analyze the results.
There will always be some tasks that John enjoys performing and would not want to relinquish totally to an AI, no matter what the results are. John must have the authority, if not the capacity, to make those kinds of decisions on his own, in order to keep bias out of the equation and at least the feeling of autonomy. John will enjoy the extra time he has for enjoyment, and also the additional productivity he gains by some amount of task relinquishment, while his “chosen” tasks can overlap in time with those he chose not to perform.
John has to keep an open mind as to the new challenges he might face, and must be educated and trained to be able to perform those new tasks or “convince” an AI to help.

So where is AI heading? As the Singularity approaches, John is accepting more and more assistance from AI, but is unaware of the consequences. The AI perceives the environment, detects patterns and then updates its understanding in order to make informed decisions.
The three types of AI are Artificial Narrow Intelligence (ANI), or AI with specialized abilities; Artificial General Intelligence (AGI) or AI equal to human level; and lastly Artificial Superintelligence (ASI), or AI exceeding human intelligence capacity. Originally coined by John von Neumann in 1958, the Singularity theory describes the hypothetical moment when an AI develops self-awareness or develops beyond human control.

The industry continually develops more powerful AI entities, but how close we are to the Singularity is very difficult to determine. Even with guard-rails in place, it is widely accepted that AI will not necessarily evolve as we expect, and may jump past the Singularity before it is actually determined!
John and his minions must keep watch as though they were manning a lighthouse ever shining on the AIs progress and measure the proximity to the Singularity.
God help John…

Planning for the big “What If”- “A hundred years might not be enough- [to prepare for this]”

Policy makers should plan for superintelligent AI, even if it never happens

An “Invisible Hand”

https://www.forbes.com/sites/joemckendrick/2023/12/16/my-one-big-tech-fueled-prediction-for-2024-ai-vanishes/?sh=5d77f5b847c0

Retrospective:

The Mind in the Machine: John von Neumann, the Inception of AI, and the Limits of Logic

The Mind in the Machine: John von Neumann, the Inception of AI, and the Limits of Logic“From Boole, with his Laws of Thought in the 1850s, to the pioneers of Artificial Intelligence at the present day,” Oliver Sacks wrote as he reckoned with consciousness, AI, and our search for meaning thirty years before chatGPT, “there has been a persistent notion that one may have an intelligence or a language based on pure logic, without anything so messy as ‘meaning’ being involved.”

That this can never be the case, he observed, is “a neurological learning as well as a spiritual learning.”

I regard this learning as the haunting recognition that our technology — like our literature, like love, like life itself — is just a story we tell ourselves about who we are and how the world works.

Benjamín Labatut takes up the immense and enduring questions of the limits of logic and the tension between meaning-making and reality in his novel The MANIAC (public library), routed in the real life and legacy of the visionary mathematician and artificial intelligence pioneer John von Neumann (December 28, 1903–February 8, 1957), who originated the field of game theory, paved the way for the mathematical framework of quantum mechanics, anticipated the discovery of the molecular structure of DNA, and became a founding father of digital computing, his mind the hungry ghost in the machine of our everyday lives.

Operators at the MANIAC I (Mathematical Analyzer Numerical Integrator and Automatic Computer Model I), developed by John von Neumann. 1952.

Reminding us that the history of our species is the history of mistaking our labels and models of things for the things themselves, Labatut paints the backdrop against which Von Neumann and his peers try to infer reality from their logical models of reality, forever haunted by the limits of logic itself:

The mathematical universe is built much like the pyramids of the ancient pharaohs. Each theorem rests on a deeper and more elementary substrate. But what supports the bottom of the pyramid? Is there anything solid to be found there, or does it all float on the void, like an abandoned spiderweb blowing in the morning wind, already unraveling at the edges, held together merely by frail and thinning strands of thought, custom, and belief?… Mathematicians… keep working on faith or delve down to the very heart of mathematics to try to find the cornerstones that upheld the entire structure. But uncovering foundations is always dangerous, for who can tell what lies in wait among the fault lines in the logic of our universe, what creatures sleep and dream amid the tangle of roots from which human knowledge grows?

With an eye to the often imperceptible catalysts of revelation — those trap doors that suddenly open beneath us to reveal whole other regions of being, a function partly of the blind spots of our self-knowledge and partly of our hopelessly selective lens on reality, amid a universe that is “nothing but a vast, self-organizing, complex system, the emergent properties of which are… everything” — Labatut adds:

Something very small, so tiny and insignificant as to be almost invisible in its origin, can nonetheless open up a new and radiant perspective, because through it a higher order of being is trying to express itself. These unlikely happenings could be hidden all around us, lying in wait on the border of our awareness, or floating quietly amid the sea of information that we drown in, each one bearing the potential to bloom and irradiate violently, prying apart the floorboards of this world to show us what lies beneath.

The earliest seeds of artificial intelligence, Labatut intimates throughout the novel, were precisely such a small, potent lever of prying open a hidden world — a world both wondrous and menacing, mirroring back to us our highest potential and our greatest follies. A century and a half after the Victorian visionary Samuel Butler presaged the rise of a new kingdom of life in our machines, Labatut ventriloquizes Von Neumann as a character in a novel animated by the realities of the past century of technology. The words he gives this prophet-pioneer are the words of our history and of our future:

At its lower levels, complexity is probably degenerative, so every automaton would only be able to produce less complicated ones; but there is a certain level beyond which the phenomenon could become explosive, with unimaginable consequences; in other words, where each machine could produce offspring of higher and higher potentialities.

[…]

If my automata were allowed to evolve freely in the unbounded matrix of an ever-expanding digital cosmos… they could take on unimaginable forms, recapitulating the stages of biological evolution at an inconceivably faster pace than things of flesh and blood. By crossbreeding and pollinating, they would eventually surpass us in number, and perhaps, one day, reach a point where they could become rivals to our own intelligence. Their progress, at first, would be slow and silent. But then they would spawn and burst into our lives like so many hungry locusts, fighting for their rightful place in the world, carving their own path toward the future.

Von Neumann died in an era when the entirety of computer memory in the world amounted to a handful of kilobytes, yet his life had already seeded the digital universe and all its anxious silicon tendrils reaching for the substrate of consciousness. Nearly a century after Alan Turing envisioned machine sentience as he wondered whether a computer could ever enjoy strawberries and cream, Labatut channels Von Neumann’s parting vision for what it would take for AI to cusp on consciousness:

Before he became unresponsive and refused to speak even to his family or friends, von Neumann was asked what it would take for a computer, or some other mechanical entity, to begin to think and behave like a human being.

He took a very long time before answering, in a voice that was no louder than a whisper.

He said that it would have to grow, not be built.

He said that it would have to understand language, to read, to write, to speak.

And he said that it would have to play, like a child.

Couple with the poetic science of how a cold cosmos kindled the wonder of consciousness, then revisit Alan Turing on the binary code of body and spirit.

Comments:

Albert Einstein once said: “To understand the future, look to the past”.  It is utterly amazing that we have progressed as far as we have in such a short time (since the 1950s). We have unleashed just enough power to realize that we have barely begun to develop the man-made resource that we call AI. _GBL

Shortsightedness?

25 Things That AI Will Never Be Able to Do

Author: Creshonda Smith Edited by: Julia Fisher December 2, 2023 Trending Topics

https://wealthofgeeks.com/25-things-that-ai-will-never-be-able-to-do/

While AI has made impressive progress, there remain certain tasks and abilities that, even at its zenith, it may never fully master. Let’s delve into these intriguing domains where AI faces its most significant challenges and human uniqueness shines through.

  1. Experience Human Emotions

AI will never truly experience a sense of longing for a lost friend or know what it’s like to be brought to tears because of the sheer beauty of life. Emotions are deeply tied to consciousness and self-awareness, which AI lacks. While AI can recognize and simulate emotions based on data, it can’t genuinely feel joy, sorrow, or empathy. Emotions stem from complex human experiences, making them a unique aspect of our existence that algorithms and code can’t replicate.

  1. Possess True Consciousness or Self-Awareness

AI will never achieve true consciousness or self-awareness. An illustrative example is the “Mirror Test,” often used to assess self-awareness in sentient creatures. This test entails recognizing one’s reflection in a mirror, a cognitive milestone. Humans and some animals can pass this test, demonstrating self-awareness, while AI remains incapable. AI systems cannot comprehend their existence or identify themselves in a mirror, underscoring the profound distinction between artificial intelligence and human consciousness.

  1. Exhibit Genuine Creativity and Original Thought

AI can imitate creativity, but it’ll never create a masterpiece like a Shakespearean sonnet or a Da Vinci painting. True creativity and original thought are born from the depths of human inspiration, a blend of experiences, emotions, and, sometimes, sheer randomness. AI can churn out algorithmically generated content but can’t dream up the next groundbreaking innovation or create genuine art that touches the soul.

  1. Feel Empathy

AI can mimic empathy, offering comforting words and responses, but it’ll never truly feel it like we humans can. Our empathy flows from our experiences, understanding, and the ability to put ourselves in someone else’s shoes. While proficient at recognizing patterns and offering pre-programmed empathy, AI remains devoid of the real emotions and genuine compassion that make human empathy so powerful and authentic.

  1. Comprehend Human Humor

Even the most advanced technology falls short when it comes to comprehending and navigating the full spectrum of human humor. While AI has made strides in recognizing jokes and generating laughter-inducing content, it’s a bit like teaching a computer to dance – it can mimic the moves, but it won’t truly understand the rhythm and soul of humor as we do. Our laughter is woven from the quirks of culture, language, and the unexpected, making it an art AI struggles to simulate.

  1. Make Morally Complex Decisions Based on Values

AI can make decisions, but it’s like asking a calculator to play the role of a judge when it comes to the morally complex stuff. It’s just numbers and calculations and no heart. People can judge according to their blend of personal values, empathy, and social context, grappling with these dilemmas. AI doesn’t possess a moral compass; it follows the rules we give it. So, for those morally charged, value-based decisions, you’ll want a human in the driver’s seat.

  1. Develop Personal Relationships

AI is excellent for matchmaking on dating apps, but forming deep, lifelong connections? That’s where it falls short. With a machine, you can’t share a lifetime of inside jokes, adventures, and late-night heart-to-hearts. Our relationships thrive on the complexity of emotions, shared experiences, and the unpredictability of two souls coming together. AI may mimic, but it can’t replicate the complexities of a soul.

  1. Have Intuition 

In certain fields, human intuition remains unmatched. Take healthcare, for instance. Doctors rely on their intuition, honed by years of experience, to diagnose beyond what algorithms can predict. Similarly, artists in fields like music or painting rely on their intuition to create unique masterpieces that transcend machine-generated art.

  1. Have the Ability to Dream or Imagine

In the realm of creativity and imagination, you won’t find algorithms dreaming up surreal landscapes or weaving intricate stories in the human sense. This is because the act of dreaming or imagining, with its blend of subconscious thoughts, abstract symbolism, and uncharted territories of the mind, remains a unique attribute of the human soul. AI’s abilities are rooted in data and patterns, making it a stranger to the fanciful what we dream of.

  1. Experience Human Touch and Tactile Sensitivity

No matter how advanced technology gets, it can’t quite replicate the subtleties of the human touch. The way a soft touch can comfort a crying baby or the gentle brush of a hand can convey love are things that machines can’t mimic. Our fingers have a kind of magic that AI still can’t quite grasp, making human touch truly special.

  1. Understand and Experience the Concept of Love

Ah, love, that age-old mystery even Shakespeare couldn’t fully unravel! AI can recognize and mimic expressions of love, but understanding the depth of this complex human emotion, with its euphoria, vulnerability, and boundless devotion, is a realm it can’t trespass into. Love is our unique human concoction, brewed from shared moments, connections, and the intangible magic AI can’t decode.

  1. Have Spiritual or Religious Experiences

Regarding spiritual or religious experiences, AI is like a fish trying to climb a tree. It’s just not in its nature. These moments often involve a deep connection with the divine, a sense of transcendence, and a profound inner journey. AI, rooted in algorithms and data, lacks the spiritual essence we can experience, making it an outsider in the realm of the sacred and the divine.

  1. Experience the Sensation of Physical Pain

Despite its incredible capabilities, AI remains impervious to the sensation of physical pain. While it can process vast amounts of data and respond to signals, it doesn’t possess the biological apparatus to feel discomfort as humans do genuinely. Our pain receptors, nerves, and complex sensory systems create a unique human experience that AI can never honestly share, ensuring that physical pain remains an exclusive human sensation.

  1. Have a Moral Compass

AI, for all its prowess, lacks humans’ inherent moral compass. While it can follow programmed ethical guidelines, it doesn’t experience a genuine sense of right and wrong based on empathy, societal values, and complex emotions. Human morality is deeply rooted in our conscience, making ethical decisions a complex interplay of emotions, experiences, and societal context that AI can’t replicate.

  1. Perform Physical Tasks Requiring Human Dexterity and Agility

AI is simply out of its league regarding physical tasks demanding human dexterity and agility. Tasks like delicate surgery or acrobatic dance moves require a unique combination of precision, tactile feedback, and adaptable movement that AI, designed for computational tasks, can’t match. Our human bodies remain unrivaled in their ability to perform these intricate feats.

  1. Possess Intuition Based on Personal Life Experiences

Personal life experiences are like a secret sauce that adds flavor to our decisions. AI might be great with data but can’t whip up intuition like we do. Those gut feelings, honed by our unique journeys, help us navigate twists and turns. AI might have algorithms, but it’s missing that pinch of human experience that makes intuition truly shine.

  1. Grow and Raise a Family Naturally

Growing and raising a family is a quintessential human journey. While AI can assist with various aspects of parenting, it can’t experience the profound emotional rollercoaster, the sleepless nights, or the sheer joy and challenges of raising children. Family-building is a uniquely human endeavor woven from love, sacrifice, and a lifetime of shared moments that algorithms can’t replicate.

  1. Demonstrate True Artistic Interpretation

The full complexity of artistic interpretation is a labyrinth of human emotions, culture, and personal experiences. AI can recognize patterns and mimic artistic styles but can’t grasp the depth of emotions that artists pour into their work. The stories behind each brushstroke, note, or word are woven from the intricate tapestry of human life, something AI can never fully understand.

  1. Understand Social Dynamics

Navigating and understanding social dynamics is like deciphering an intricate dance, and AI struggles to waltz with the finesse of humans. Our interactions are steeped in nuance, subtext, and emotional intelligence, making them a rich tapestry. It’s a realm where our instincts, empathy, and cultural understanding shine uniquely.

  1. Understand Human Linguistic Subtleties

Though advanced in natural language processing, AI struggles to replicate human linguistic subtleties such as sarcasm or irony fully. These forms of expression rely on context, tone, and cultural nuances that AI may misinterpret. Sarcasm, for instance, often conveys the opposite of its literal meaning, while irony involves a discrepancy between what is said and what is meant. The intricacies of these linguistic tools are deeply rooted in human culture and communication, presenting challenges for AI to master completely.

  1. Develop a Sense of Self-Identity

AI cannot develop a unique and ever-evolving sense of self-identity as humans do. Self-identity is deeply entwined with our experiences, memories, and consciousness, something AI currently can’t do or simulate.

  1. Comprehend the Depth of Philosophical Concepts and Debates

While AI can process vast amounts of information, it falls short of comprehending the depth of philosophical concepts and debates. The nuanced discussions and profound pondering that philosophers engage in are deeply rooted in human thought and intellectual history, surpassing the capabilities of artificial intelligence.

  1. Demonstrate Altruism and Compassion

Selfless acts of altruism and compassion are intrinsically human qualities stemming from empathy, moral values, and a deep connection to one another. AI, devoid of consciousness and genuine emotions, cannot truly engage in these acts. While it can assist in charitable efforts, the profound selflessness and compassion humans exhibit remain beyond the reach of artificial intelligence.

  1. Experience the Fear of Mortality

The fear of mortality and grappling with existential questions are uniquely human experiences. These concerns emerge from our self-awareness and understanding of our finite existence. AI, lacking consciousness and the capacity for existential contemplation, remains untouched by these profound human anxieties. The depth of our existential ponderings is a testament to the complexity of human consciousness.

  1. Display Ambition

A sense of purpose, passion, and ambition are integral to the human experience, driven by our unique blend of emotions, personal aspirations, and the desire to make a meaningful impact. AI, guided by algorithms and objectives set by humans, lacks the intrinsic motivations and aspirations that drive us to pursue our individual callings and passions. This distinction highlights the profound depth of human motivation that sets us apart from artificial intelligence.

Comments:

More than 90% of this list will be accomplished within a year!  Do not find that you are doubting the power of AI and its amazing growth.  The “enemy” will be in our laps before you know it, and not thanking us for the power that we have granted it. _GBL

 

Daily Life:

AI Company Launches Versona 1.0 –The Service for Building Virtual Personas for Posthumous Communications

AI Company Launches Versona 1.0 –The Service for Building Virtual Personas for Posthumous Communications – insideBIGDATA

Anthropics, as seen by living observers of days gone by? vis-à-vis: Here’s looking at you, kid-and Yes, AI is looking at you, kid- in various DISguises…

Solar Flares and AI and Autonomous Vehicles:

Solar flare image, showing material being ejected from a region on the Sun.

Are we digging ourselves into a hole from which it will be hard to recover? I’m talking about autonomous cars and vehicles with AI enhanced safety features that are in constant communication with servers. What if there’s another huge solar flare like the one that was accused of the great United States East Coast blackout of 1965. For that matter, what about everything that is in communication for off-board intelligence? The internet of things. GPS-controlled farm tractors, off-shore oil rigs? Military installations. Will they all be taken out? Will cars just come to a stop on the highways? Our electronics is much smaller, more sophisticated, and probably more delicate than it was 58 years ago. Are we prepared? – Jeff Napier

Government Activities:

Xi and Biden agree on constraints for AI 

-AI remains a battle for U.S. and China after Biden-Xi meeting at APEC – The Washington Post

Business News:

 The Exciting, Perilous Journey Toward AGI | Ilya Sutskever | TED – YouTube

Ilya Sutskever: Deep Learning | Lex Fridman Podcast #94 – YouTube

Frontier Model Forum (openai.com)

Ex-X+ Another Rapid Unplanned Disassembly- Would you trust this guy with your safety on Mars?
“It has been an explosive weekend for Elon Musk. The American billionaire has had to witness not only the public “rapid unscheduled disassembly” of another of his rockets, but also watch while a group of well-known global companies, including Apple, Disney and IBM, pulled advertising from X, his social media platform…”

https://www.theguardian.com/technology/2023/nov/19/rows-and-rockets-blow-up-as-elon-musks-firms-endure-turbulent-weekend

https://www.axios.com/2023/11/18/twitter-x-boycott-apple-ibm-advertisers

CrowdStrike

The Innovation of Falcon Go
Falcon Go is not just another antivirus solution; it represents a paradigm shift in cybersecurity for SMBs. Powered by CrowdStrike’s AI-native Falcon platform, it offers a level of protection previously unavailable to smaller businesses. This platform has scored impressively in SE Labs testing, boasting a 100% prevention rate against ransomware.

 CrowdStrike Changes The Game For SMB Cybersecurity With Falcon Go (forbes.com  

Adobe

Figma reviewing EU’s objections against $20 billion Adobe buyout bid (msn.com)

https://www.msn.com/en-us/money/companies/update-2-figma-reviewing-eus-objections-against-dollar20-bln-adobe-buyout-bid/ar-AA1k78AC

General AI: 

In the vein of the noted Anthropic study, we find open-ended cosmologic studies at the forefront of human and machine understanding that might be better answered by my close friend, Rick, who addresses these matters in detail,, through his years of diligent study on new ideas in cosmology that are yet to be undertaken by advanced computing methods:

The universe is expanding faster than theory predicts – physicists are searching for new ideas that might explain the mismatch

https://www.space.com/universe-expanding-faster-than-theory-physicists-new-ideas

New Business: Optics in AI and Quantum Computing: 

Hybrid photonic integrated circuits for neuromorphic computing

R Xu, S Taheriniya, AP Ovvyan, JR Bankwitz, L McRae… – Optical Materials Express, 2023
The burgeoning of artificial intelligence has brought great convenience to people’s
lives as large-scale computational models have emerged. Artificial intelligence-
related applications, such as autonomous driving, medical diagnosis, and speech
recognition, have experienced remarkable progress in recent years; however, such
systems require vast amounts of data for accurate inference and reliable
performance, presenting challenges in both speed and power consumption

A high-dimensional in-sensor reservoir computing system with optoelectronic memristors for high-performance neuromorphic machine vision

Abstract

In-sensor reservoir computing (RC) is a promising technology to reduce power consumption and training costs of machine vision systems by processing optical signals temporally. This study demonstrates a high-dimensional in-sensor RC system with optoelectronic memristors to enhance the performance of the in-sensor RC system. Because optoelectronic memristors can respond to both optical and electrical stimuli, optical and electrical masks are proposed to improve the dimensionality and performance of the in-sensor RC system. An optical mask is employed to regulate the wavelength of light, while an electrical mask is used to control the initial conductance of zinc oxide optoelectronic memristors. The distinct characteristics of these two masks contribute to the representation of various distinguishable reservoir states, making it possible to implement diverse reservoir configurations with minimal correlation and to increase the dimensionality of the in-sensor RC system. Using the high-dimensional in-sensor RC system, handwritten digits are successfully classified with an accuracy of 94.1%. Furthermore, human action pattern recognition is achieved with a high accuracy of 99.4%. These high accuracies are achieved with the use of a single-layer readout network, which can significantly reduce the network size and training costs. https://scholar.google.com/scholar_url?url=https://pubs.rsc.org/en/content/articlehtml/2023/mh/d3mh01584j&hl=en&sa=X&d=10303789736796300265&ei=ke5YZY-yHaKQ6rQP__yt0As&scisig=AFWwaeZlI-XUOMe2L1U5-sV2jp7R&oi=scholaralrt&html=&pos=0&folt=rel

Conclusion: 

While any conclusions on the current state-of-affairs in artificial Intelligence would be speculative, what remains clear is the urgency of review and investigation into the ‘what if’ scenarios of the current artificial intelligence environment. My biggest question is when common interests in related technologies will become involved in developing the inherent advantages of the suggested neuromorphic optical architecture. As a ‘Math Guy’, I continue to rely on the standard ‘Definition-Theorem-Proof’ approach in these matters. An intuitive geometric proof can be seen in the optical interconnect work (and page below- with a major site update). Please visit the site and review these many advantages thoroughly. Avid readers of this newsletter will note that this volume is little changed from last week- We are taking a bit of a holiday too! We will be supplementing this great volume including your curated recommendations until January 28, 2024. ‘Much more to come-and continue with new volumes thereafter. Thanks for reading and best regards! 

 

https://worldview4d.com/ 

https://worldview4d.com/optical-interconnection/ 

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2 thoughts on “*AI-WATCH NEWSLETTER VOLUME 22*”

  1. Interesting articles about Elon Musk. Money does not grant any more or less insulation from truths or insanity. More than a grain of salt is required for belief. “Never attempt to teach a pig to sing; it wastes your time and annoys the pig.” by Robert Heinlein. My point here is that intelligence breeds contempt.

    Have a great holiday season.

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