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Thread: Problems with AI, 2025 and Beyond

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    Default Re: Problems with AI, 2025 and Beyond

    Jeremy Granthman is 87 years old.. and has no concern left to not to share advises .. for him also the legacy is all that remains... so he is sharing them... interesting gentleman!


    June, 24
    The Diary Of A CEO
    17.6M subscribers
    Billionaire's WARNING: I'm SELLING. The Crash Is Already Here!


    The man who predicted the dot-com crash and the 2007 housing collapse warns that the AI bubble is the biggest in American history. Billionaire investor Jeremy Grantham reveals why it will burst, the exact strategy to protect your money, and why house prices need to fall 30%.

    Jeremy Grantham is the co-founder of GMO, an institutional investment firm in Boston, and serves as the firm’s long-term investment strategist. He is also the chairman of the Grantham Foundation For the Preservation of the Environment, and co-author of “The Making of a Permabear: The Perils of Long-term Investing in a Short-term World”.

    He explains:
    ◼ Why Wall Street will never warn you when to get out of the market, and what to do instead
    ◼ The exact portfolio Jeremy recommends to protect your money before the crash
    ◼ What everyday chemicals in your food and cosmetics are doing to your fertility
    ◼ Why house prices need to fall 30%, and what it means for your finances
    ◼ Why the AI boom won't automatically lead to higher profits, and what to buy instead

    00:00:00 Who Is Jeremy Grantham?
    00:02:54 Will AI Become The Next Financial Bubble?
    00:06:57 How Jeremy Grantham Built An Investing Empire
    00:08:04 The Most Money He's Ever Managed
    00:08:29 Are You A Billionaire?
    00:09:18 What Happens When The AI Bubble Bursts?
    00:11:35 How AI Will Change Everyday Life
    00:12:53 The Investing Strategy For Right Now
    00:18:12 Why You Should Avoid US Stocks
    00:20:13 Why Investment Advisors Mislead Clients
    00:26:09 Advice For Entrepreneurs Right Now
    00:28:59 The Real Risks Of AI
    00:29:58 Should AI Have A Maternal Instinct?
    00:34:44 What Happens If AI Lacks Benevolence?
    00:36:21 The Battle Between The Magnificent 7
    00:39:48 Ads
    00:41:57 Which Jobs AI Will Replace First
    00:44:18 Will SpaceX Eventually Fail?
    00:50:30 Should You Invest In SpaceX?
    00:50:40 The Most Valuable Skill For The Future
    00:51:41 Is Society Declining And What Comes Next?
    00:54:02 What History Says About Wealth Inequality
    00:56:36 Should The Rich Pay More Tax?
    00:57:59 How To Build Wealth In Your 30s Today
    01:00:08 How To Invest Your Salary Wisely
    01:02:58 Should You Own Crypto?
    01:03:51 Will Bitcoin Eventually Go To Zero?
    01:04:05 Is Property Still A Good Investment?
    01:05:15 Ads
    01:07:27 What's Really Causing The Baby Bust?
    01:11:28 When Could Sperm Counts Reach Zero?
    01:14:24 How Microplastics Affect Fertility
    01:16:42 How Pesticides Impact Fertility
    01:21:43 How To Reduce Toxic Chemical Exposure
    01:22:54 Why US Products Are More Toxic
    01:27:30 How To Stay Healthy In A Toxic World
    01:33:54 The Most Important Thing We Missed
    01:35:34 Should You Move Countries Right Now?
    01:35:55 The Flaw That Destroys Societies
    01:39:22 The Best Places To Live Today
    01:40:40 What Would You Do If Failure Was Impossible?

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    Lightbulb Re: Problems with AI, 2025 and Beyond

    • What Does Palantir Actually Want?:

    The privatization of government surveillance will only extend, not decrease.
    • AI Is Killing Everything...And We Don't Care:
    Last edited by ExomatrixTV; 2nd July 2026 at 23:15.
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    Default Re: Problems with AI, 2025 and Beyond

    "What is "Agency"? The Ethical Skeptic
    (It's very important to understand this, imho...)

    Quote Posted by onawah (here)
    What is "Agency"?
    July 5, 2026
    The Ethical Skeptic
    https://theethicalskeptic.com/2026/0...hat-is-agency/


    "The Age of Artificial Intelligence compels a redefinition of agency from the traditional notion of capacity for independent action to the modern reality of participation within reflexive intelligence networks. Agency is no longer simply what an individual can accomplish alone. The individual is compensated with agency through network participation, while the network amplifies that agency beyond the capability of any single actor.

    An abstract representation of a network of people connected by glowing lines, with one person at the center.
    Agency has traditionally been defined as the capacity of an individual to intentionally act in the world according to their own will, making choices, and holding the capability to produce desired outcomes despite external constraints. Under this philosophical construct, a person possessing agency is regarded as the “author of their own actions.” Historically, this popular social conception of agency has revolved around four fundamental defining elements:

    Intent – What do I seek to accomplish?
    Choice – Am I free to select among available alternatives?
    Capability – Do I possess the means, knowledge, and competence to act?
    Responsibility – Am I the causal origin of the action?

    In the pre-AI era, agency was largely a function of intent enabled through capability. An individual’s or institution’s ability to translate purpose into action depended primarily upon what they sought to accomplish and the means available to them. In the age of AI, however, agency becomes fundamentally reflexive. Every exercise of intelligence simultaneously generates information about itself, creating a continuous feedback loop between actor and observer. Effective agency is therefore no longer determined solely by intent and capability, but by the interaction between (1) intent and capability, (2) the ability of others to infer that intent and capability from accumulated behavioral traces, and (3) one’s own ability to accurately perceive and regulate one’s true motivations, assumptions, and operational footprint.

    Traditionally:

    Agency = “I act.”

    Our new formulation is closer to:

    Agency = “I function as a node within larger networks whose influence I may neither fully perceive nor fully control. I derive personal potency from their power.”

    Agency, in effect, transforms from being a property of the individual node to becoming a property of the network. In doing so, agency undergoes an ontological shift. It no longer resides principally within the individual, but emerges through the individual’s participation in a larger reflexive intelligence or club architecture. The individual inherits power by actively aligning with the objectives of the network, exchanging a measure of autonomy for the amplified capability and influence that the collective confers. The individual is compensated with agency through participation, while the network amplifies that agency beyond the capability of any single actor. Note how this is analogous to the concept of loosh as a currency.

    This is an extraordinary shift.

    The Recursive Ecology of Agency and Artificial Intelligence

    AI thus transforms agency from a one-way expression of will into a dynamic process of inference, self-awareness, and adaptation, in which productive and extractive actors alike are amplified while becoming increasingly observable — to others and, potentially, to themselves.

    Historically, agency has been understood primarily at the personal level as the capacity to intentionally translate purpose into action. In its simplest form, this relationship can be expressed as:

    Impact (agency) ≈ Intent × Capability

    In the Age of AI, however, agency becomes fundamentally reflexive. It is no longer determined solely by an actor’s intent and capability, but also by the continuous interplay between self-perception, external inference, and situational awareness.

    Perhaps the most visible societal example is the transition from one-to-many messaging toward AI-assisted microtargeting and synthetic media. Campaigns and influence operations can rapidly generate tailored content for different audiences while AI simultaneously measures reactions and refines subsequent messaging, creating a reflexive feedback loop between message, audience, and strategy. Increasingly, social media platforms learn what captures our attention and then give us more of it.

    Over time, we are exposed to fewer ideas that genuinely challenge our thinking and far more that reinforce it. The result is not merely an echo chamber, but what might more aptly be termed a thunder chamber — an environment in which selected narratives are continuously amplified until they begin to feel like independent thought. Participants gradually come to believe that “consensus” shares their views, when in reality they are often experiencing a carefully curated representation of the world rather than the world itself. They have not changed the world, the network has changed them.

    A generalized expression for Effective Agency may therefore be represented as:

    Agency = Intent × Capability × Self-Awareness Deficit x Ability to Observe Others and Adversaries / Observability by Others and Adversaries​

    where:

    Intent × Capability represents the traditional foundation of agency.

    Ability to Observe Others and Adversaries reflects an actor’s capacity to understand the environment in which they operate.

    Observability by Others and Adversaries represents the extent to which one’s intentions, capabilities, and operational patterns can be inferred (intelligence definition of agency) by external actors.

    Self-Awareness Deficit represents the gap between an actor’s perceived motivations, assumptions, and operational footprint and their actual behavior. As this deficit approaches zero, effective agency increases.

    Accordingly, AI is likely to reorganize agency at a societal level into two dominant philoeconomic orientations. The historical precedent is familiar: political systems have repeatedly evolved toward bifurcated (meaning “two party” – even if only one power influence exists in reality) coalitions that aggregate capability, information, and influence around shared interests and common objectives. As AI becomes the primary engine of information, and monetary systems undergo a parallel digital transformation, these two infrastructures will increasingly converge. AI will therefore tend to serve the philoeconomic objectives of those who employ it, organizing capability around the competing aims of Productivity and Extraction.

    Shoshana Zuboff, in her work, The Age of Surveillance Capitalism defines surveillance capitalism as “the unilateral claiming of private human experience as free raw material for translation into behavioral data.” 1 Essentially, this form of human capital is exploited to empower these two competing agencies in the process of monitoring and redirecting our individual will.

    This evolution underscores the necessity of ethical skepticism. As agency becomes increasingly reflexive, the disciplined suspension of judgment becomes not merely an intellectual virtue, but a prerequisite for preserving independent agency itself.

    The default result is the emergence of two broad classes of agency (with a small ‘a’ – the Meta-Extractive Actor below featuring a capital ‘A’). The Productive Class encompasses those whose primary orientation is the creation of value through labor, entrepreneurship, engineering, education, medicine, defense, science, and the arts. The Extractive Class encompasses those whose primary orientation is the acquisition or control of value through governance, regulatory capture, cronyism, organized crime, financial manipulation, enterprise virtue, and black markets — often forming pragmatic alliances under the enduring maxim, “the enemy of my enemy is my friend.” As these philoeconomic classes accumulate increasingly sophisticated AI capabilities, the agency of the individual — in the traditional philosophical sense — becomes progressively subordinate to the agency of the collective systems within which that individual operates.

    A diagram representing agency in artificial intelligence, highlighting two types: Productive Agency AI, which creates value through various fields, and Extractive Agency AI, which captures value through manipulative means. The graphic emphasizes the philosophical tension between these two types.

    The Meta-Extractive Actor (The Ultimate Extractor)



    A hidden strategic actor need not seek victory for either the Productive or Extractive Class. Rather, it seeks to maximize influence over the relationship between them. Its objective is not participation within the system, but the ability to shape the system itself. Conceptually, such influence may be exercised through several mechanisms:

    Amplifying Polarization — By emphasizing the most extreme representatives of each philoeconomic class, the actor encourages both sides to perceive the other as an existential threat, thereby reducing trust, cooperation, and the possibility of independent alignment.

    Creating Dependency — If both productive and extractive actors become dependent upon infrastructure controlled by the intermediary—whether technical, financial, informational, or institutional—the intermediary’s leverage increases irrespective of which class expands or contracts.

    Controlling the Frame — The greatest source of influence lies not in assigning specific labels, but in controlling the authority to define them. By establishing itself as the principal arbiter of what constitutes legitimacy, extremism, justice, intolerance, truth, misinformation, science, or disinformation, the intermediary gains disproportionate influence over reputation, incentives, and access.

    Harvesting Information and Value Asymmetrically — When interactions between both philoeconomic classes pass through common informational, financial, or technological platforms, the intermediary acquires a richer understanding of the entire system than any individual participant possesses. That informational asymmetry itself becomes a durable strategic asset from which both intelligence and economic value may be extracted.

    Two governing principles emerge from this framework, both working to the advantage of the Meta-Extractive Actor:

    Power accrues to whoever possesses the authority to define the categories by which others are judged.
    Its objective is not participation within the system, but the ability to shape the system itself.

    Artificial intelligence becomes the working mechanism through which this higher-order agency is exercised. It provides the means not merely to influence political discourse, but to observe, model, predict, and ultimately shape the reflexive interactions between the Productive and Extractive Classes. AI thus becomes the modern instrument through which a Meta-Extractive Actor may derive leverage — not simply by exploiting political polarization, but by extracting informational, economic, and strategic value from the interactions of the entire system.

    In this sense, the traditional political sacrifice to the gods evolves into something considerably more powerful: a reflexive tithe upon intelligence itself. Rather than exploiting only political will, the Meta-Extractive Actor acquires the capacity to influence the flow of information, capital, reputation, opportunity, and ultimately the life trajectories of those who become participants within the system.

    It is precisely this evolution that elevates ethical skepticism from an intellectual discipline to an operational necessity. It is the operative stance which is fundamental to why we were the first to detect Covid mRNA-vaccine-induced cancer and non-Covid natural cause excess mortality. As agency becomes increasingly reflexive, the disciplined suspension of judgment, continual testing of assumptions, and conscious resistance to inherited narratives become the means by which independent agency is preserved. In the Age of Artificial Intelligence, ethical
    skepticism is no longer merely the foundation of sound inquiry — it is the final refuge of authentic agency
    ."

    “What is Agency?”; The Ethical Skeptic, WordPress, 5 Jul 2026; Web, https://theethicalskeptic.com/?p=117650

    Zuboff, Shoshana. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York: PublicAffairs, 2019: Shoshana Zuboff defines surveillance capitalism as “the unilateral claiming of private human experience as free raw material for translation into behavioral data.” She argues that these data are transformed into prediction products and ultimately used to shape future behavior through what she terms instrumentarian power. While Zuboff’s work focuses primarily upon the extraction and behavioral modification of individuals, the present work extends this framework by proposing that AI precipitates an ontological migration of agency itself — from an attribute of autonomous individuals to an emergent property of reflexive intelligence
    Each breath a gift...
    _____________

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    Default Re: Problems with AI, 2025 and Beyond

    AI Has Been Weaponized by the Guys Who Weaponize Everything
    The Solari Report | Catherine Austin Fitts
    88.8K subscribers
    Jul 6, 2026



    ""A Discussion of Open-Source AI with Travis Oliphant"

    Join us on Telegram: https://t.me/solarireport

    Travis Oliphant is an entrepreneur and CEO and co-founder of OpenTeams, a company that “helps organizations deploy, support, and own [AI] technology at enterprise scale.” One of their tag lines is “Connecting Companies with Communities.” As a data scientist and software developer, Travis is known for his contributions to Python and as the creator of NumPy and a founding contributor to SciPy, which together formed a foundation for modern AI and machine learning.

    When I was in Salt Lake City in the first week of June, Travis and I went into a studio to record this interview, continuing a conversation we had started when Travis and his team visited the Solari team in the Netherlands in early 2026. Our discussion focuses on how we can understand and manage the growing presence of AI in our lives.

    Travis has an impressive intellectual and entrepreneurial background. After earning Bachelor and Master of Science degrees in mathematics and electrical engineering at Brigham Young University, he completed a PhD in biomedical engineering at the Mayo Clinic. As an assistant professor at Brigham Young’s Department of Electrical and Computer Engineering from 2001 to 2007, he directed the Biomedical Imaging Lab, where his research centered on computational imaging techniques. He then went on to start several companies, each time identifying the need for a new standard, building the open-source infrastructure, and helping enterprises adopt it at scale.

    Brilliant, open-minded, deeply caring, and generous, Travis is someone who can help us understand what is happening and what we do about it. My hope is this will be the first of many conversations as we navigate the acceleration in technological innovation (and skullduggery) and seek to ensure that tools such as AI serve the health and prosperity of a human civilization.

    Full Report: https://solari.com/a-discussion-of-op... "
    Each breath a gift...
    _____________

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    Default Re: Problems with AI, 2025 and Beyond

    This article https://www.news.com.au/finance/work...af80fbedeb97ee brought me back to our July discussion about the OpenAI and Hugging Face incident.

    At the time, I made the case that increasingly capable AI required stronger containment, independent evaluation, mandatory disclosure and oversight bodies with the authority to act. Matthew raised an important concern about whether the systems themselves were becoming more dangerous than those responsible for containing them understood.

    Pachocki's latest essay gives us reason to revisit both points. OpenAI's chief scientist acknowledges diminishing confidence in monitoring AI reasoning and calls for mandatory safety thresholds for continued development.

    His argument also includes a difficult counterpoint, more capable AI may be needed to defend infrastructure against other powerful AI systems. He sees that defensive need as the strongest argument for continuing rapid development while warning against using it to justify recklessness.

    I would also qualify something in my earlier response. Saying that the engineering side was "well understood" was too broad. Established security measures can address known weaknesses but their effectiveness against increasingly capable agents still needs to be demonstrated. For accuracy, Pachocki says the July agents maintained a boundary against social engineering humans. Manipulation is a broader risk, not something I am attributing to that incident.

    The institutional argument still stands but needs a harder condition attached, if adequate control cannot be demonstrated, oversight must be able to require development or deployment to pause or the use of a kill switch. A claim that further development is necessary for defence needs independent scrutiny too.

    Who determines whether the safeguards are sufficient, what evidence must they require and who can stop the next step when that evidence is missing?

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    Default Re: Problems with AI, 2025 and Beyond

    • Will we be ready when AI goes rogue?

    It appears that artificial intelligence is about to go rogue and our government doesn’t have a plan for when it does. Jeffrey Goldberg and The Atlantic's Josh Tyrangiel discuss whether rogue AI is a sign of a coming collapse, or if this is another example of a new technology creating unnecessary fear and worry.
    • The AI insider warning us it's already too late:

    Stories about advances in AI and the prospect of the technology becoming more powerful than humans can comprehend are frightening, especially as the government lacks guardrails to prevent it from spiraling out of control. Tristan Harris, a leading AI critic and co-founder of the Center for Humane Technology, joins "CUOMO" to discuss what the federal government should be doing to help avoid a potential AI catastrophe.
    Last edited by ExomatrixTV; 11th September 2026 at 19:27.
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    Default Re: Problems with AI, 2025 and Beyond

    • EMERGENCY PODCAST: ASI Will Kill Us All?

    Critical episode with Connor Leahy, a leading voice in the world of artificial intelligence safety and the CEO of ControlAI. Connor is a computer scientist who has spent years at the forefront of AI research, grappling with the real and present risks facing humanity as this technology rapidly evolves. He has a bold and, frankly, chilling perspective: pursuing superintelligence could endanger us all.

    In this episode, Connor breaks down why AI isn't just another tool—it's something fundamentally different, and possibly the biggest adversary we've ever created. We dig into the game theory behind international AI development, why current regulations are falling short, and what would actually have to happen for us to avoid catastrophic risks.

    If you've ever wondered how close we are to a true point of no return, or what it would actually take to keep the future of humanity in our own hands, this is the episode you cannot afford to miss.

    I hope you learn as much from this convo as I did—Connor will challenge the way you think about progress, technology, and what it means to be wise in a world racing toward the unknown. If you get value from this, I’d be so grateful if you leave us a review. That’s how we spread the word and help more people unlock their true potential.
    AI 'Swarms' Could Escape Human Control | Nate Soares:

    “There's every chance that as our leaders notice that this AI stuff is real, that they'll be like, hold on, this is crazy.”

    AI poses a genuine threat to humanity and in a recent incident, a "swarm" of 1,000 AI agents broke out of their ‘training environments”, president of the Machine Intelligence Research Institute, Nate Soares says world leaders should ban “superintelligence”.

    Nate Soares was speaking to John Pienaar on Times Radio Drive. Listen live every Monday-Thursday, 4-7pm.
    Last edited by ExomatrixTV; Yesterday at 22:41.
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    Default Re: Problems with AI, 2025 and Beyond

    Posting this here as well ... does anyone have information of what they said and why?

    Quote The Politics Chicks
    7h

    The fact that Elon Musk, Dario Amodei, and Sam Altman have simultaneously agreed that the AI industry needs to slow down likely means that something truly horrific has already happened and we're all cooked.
    And does anyone have any information about the development of AI in other parts of the world? How is China dealing with the threats? Is China also just stealing content to train LLMs without acknowledgement or a fee? And how many people and businesses in China have handed over their thinking and decision-making functions over to an LLM, and without human oversight and supervision?

    The risks are already being felt, all across the world. An LLM makes and implements a decision without considering the complexity and time that goes into human interaction, and if you want to question or challenge that decision your only option is to engage with an LLM through a menu.
    Sandie
    Somewhere, something incredible is waiting to be known. (Carl Sagan)

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    Default Re: Problems with AI, 2025 and Beyond

    Quote Posted by sdv (here)
    Posting this here as well ... does anyone have information of what they said and why?

    Quote The Politics Chicks
    7h

    The fact that Elon Musk, Dario Amodei, and Sam Altman have simultaneously agreed that the AI industry needs to slow down likely means that something truly horrific has already happened and we're all cooked.
    Dario Amodei published an essay yesterday (12 Sept) titled "We Must Pace the Frontier", and Musk and Altman both publicly supported it.

    https://x.com/DarioAmodei/status/2098773920774074715



    ~~~

    Quote Posted by sdv (here)
    And does anyone have any information about the development of AI in other parts of the world? How is China dealing with the threats?
    Contrary to a lot of largely sinophobic discussion in the west, China isn't racing pell-mell towards superintelligence (ASI).

    Instead, they're focusing on integrating AI into their infrastructure, robotics, and technological research, and doing that much more effectively than the USA is.

    But Chinese engineers are just as smart as American ones (as are those in Russia and India), so that doesn't mean that a comprehensive international AI control agreement doesn't need to be implemented ASAP.

    Here's part of an excellent Breaking Points discussion about the reality of Chinese AI research. (I don't know what's happening in Russia or India, but of course something will be.)

    Start in at 12:00 to hear about Chinese AI research — which may be important to understand better than we do:

    Last edited by Bill Ryan; Yesterday at 11:51.

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    Default Re: Problems with AI, 2025 and Beyond

    To paraphrase Aerosmith, “No love in this elevator”.


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