Busting the Big Tech AI bubbles
We all live in the exceptional, unusual or extraordinary times of full uncertainty, when the future of humanity could be decided by its emerging and digital technologies.
We’ve all heard a lot of hype, hope and fear about artificial intelligence, smart hyper-automation and humanoid robotics.
But what has never been heard of in all this overhyping by Big Media is that
THERE IS NO REAL AND TRUE OR AUTONOMOUSLY INTERACTIVE AI (AIAI), YET. BUT THERE IS A MORE ADVANCED DATA-TRANSFORMING HARDWARE, SOFTWARE, AND CLOUD TECHNOLOGY MISBRANDED BY BIG TECH AS AI, ML, or DL PLATFORMS, aka FAKE/FALSE/MISBRANDED AI.
And this refers to all the companies misbranding or mislabeling their products and services as integrating AI technologies .
And that means if AI is the most overhyped technology of all time, the world should beware the big tech Ponzi/pyramid schemes and economic bubbles , with the aggregate market cap exceeding $10T.
In other words, Fake vs. True AI is becoming the Turing-like IQ test for human intelligence, individual or collective.
The big tech or the tech giants, not simply the largest technology companies in the world, but the biggest company in the world by market cap: Company/Sector/Market Cap (in USD)
#1 MicrosoftTechnology $3.1 trillion
#2 AppleTechnology $2.68 trillion
#3 NvidiaTechnology $2.21 trillion
#5 Alphabet (Google)Technology $1.84? trillion
#6 AmazonE-commerce $1.81 trillion
#7 Meta PlatformsSocial Media $1.26 trillion
#10 TSMCSemiconductors $708.75 billion
The Big Tech companies are dominant players in digital technologies, cloud computing,?consumer electronics,?e-commerce,?home automation,?online advertising,?self-driving cars,?social networking,?software, streaming media, and nor humanoid robots, all led by AI and ML.
They are the?most valuable public companies due to misbranding themselves as leading AI companies.
From Alphabet/Google and Amazon to Apple and Microsoft , every major tech company is dedicating resources to AI sold as enabling "machines to model and simulate the capabilities of the human mind".
Can big tech AI oligopolies take over the world?
All the world has heard of artificial intelligence (AI), artificial general intelligence (AGI), machine learning (ML), deep neural networks (DNN), large language model (LLM) chatbots, generative AI , or humanoid robots.
Today's AI is experiencing an explosion of Big Tech R & D, Big Media coverage, and public focus. It is getting massive popularity online and offline, in social media and networks, schools and universities, organizations and enterprises, with every corner of every business implementing AI/LLMs, and the next trendy AI products.
In all this global hype, three simple truths have been missing:
To disrupt the big tech deepfake AI oligopolies, we are to file the Global AI Class Actions vs. the Big Tech Seven [Alphabet, Amazon, Apple, Meta, Microsoft & OpenAI, Nvidia, Tesla], which rationales were documented in the LinkedIn postings, and supported from different parts of the world, from Africa to America.
The global AI class action lawsuits are to seek damages, compensatory and punitive, up to 40% of market cap of the Big Seven; for the commercial fakery of AI technology, deliberate misleading advertising and unethical business practices and massive commercial fraud, such a Deepfake Anti-Human Technology, massive IPRs infringements and personal data and cheap and prison labor exploitation powering the big tech fake AI.
The settlement amount, up to 40% of the Big Seven market cap, >> $10T, will go to
The Guardrails for the Big Tech Fake AI
Big technology companies are recklessly pursuing profits from artificial intelligence (AI) and urgent action is needed to mitigate the risks from the rapidly growing sector, the UN secretary general, António Guterres, has warned, addressing the World Economic Forum meeting in Davos 2024 .
In a fierce attack on the technology multinationals, António Guterres told that every breakthrough in [generative] AI increased the threat of unintended consequences.
UN Secretary-General warned about the "existential threats posed by runaway climate chaos, and the runaway development of AI without guard rails," and that the international community had no strategy to deal with either.
The UN General Assembly has recently adopted a landmark resolution on the promotion of “safe, secure and trustworthy” AI systems that will also benefit sustainable development for all. As it is, "its water use, energy use, e-waste, and need for critical minerals, AI could trash our chances of a sustainable future".
Again, the Federal Trade Commission issued a strong warning to vendors: stop lying about your AI.... The agency plans to scrutinize Microsoft, Amazon and Google for their investments in the A.I. start-ups OpenAI and Anthropic [Federal Trade Commission Launches Inquiry Into A.I. Deals by Tech Giants ].
Gary Gensler, Chair of the Securities and Exchange Commission (SEC), has warned recently that some companies were engaging in AI washing, which can break U.S. securities law, mislead consumers and harm investors.
[Vendors can avoid AI washing by being truthful when labeling a product, avoiding exaggeration and preparing a strong compliance strategy with the in-house legal team to shield against future lawsuits].
Big Tech AI as a High-Tech Fraud: Fake It until Never Make It
They never never could think or reason or feel or perceive or learn or plan or understand or create as humans.
Humans are humans, machines are machines, they only could complement each other acting in their specific ways.
Computers are getting better, but computer algorithms are still designed to have the very narrow capabilities needed to perform well-defined jobs, like NL tasks, translation, spell checking, searching the internet or data transformation.
This is a far cry from the human general intelligence needed to deal with the world, humans, machines, environments, physical or virtual, unfamiliar situations by assessing what is happening, why it is happening, and what the consequences are of taking action.
Computers cannot formulate ideas or rules or theories, do inductive reasoning or make plans. Computers do not have the emotions, feelings, inspiration or imagination to write poems, novels, articles, or movie script. Computers do not know, in any meaningful sense, what things/concepts/data/words mean. Computers do not have the knowledge/experience/wisdom humans accumulate by studying and living life.
All human-mimicking AI computing systems are INTELLIGENT as electronic, scientific, graphing calculators, be it specialized AI hardware and software, weak AI models, ML, DL, Generative AI, LLMs, as GPT-3, GPT-4, Bing Chat, Bard, Stable Diffusion, Anthropic, Claude, etc.
What Are LLMs? Numbers, Statistics, and Probabilities
The "secret sauce" tricks of LLMs are rather old, "Lies, damned lies, and statistics".
A LLM is a probabilistic model of a natural language, dealing with numbers/embeddings, statistical algorithms and correlations and probabilities, combining large datasets (scraped web data from the public internet) and neural networks, as transformers-based DNNs with multi-heard attention mechanisms.
It is neither cognitive models, nor world knowledge models, but just statistical and probabilistic modeling of big data sets.
LLMs are used as the so-called Generative AI systems prompt-generating similar data (text, images or other data) using generative statistical models of the joint probability distribution P{X, Y} of the given observable and target variables <X, Y>.
The transformer-based?DNNs?have enabled a;; the boom?of generative AI systems in the early 2020s.
Some examples of the LLMs are?OpenAI's?GPT?series of models (e.g.,?GPT-3.5?and?GPT-4, used in?ChatGPT?and?Microsoft Copilot),?Google's?PaLM?and?Gemini,?xAI's?Grok,?Meta's?LLaMA?family of open-source models,?Anthropic's?Claude?models, and?Mistral AI's?open source?models,?text-to-image?AI image generation?systems such as?Stable Diffusion,?Midjourney?and?DALL-E, and?text-to-video?AI generators such as?Sora.
Companies such as?OpenAI,?Anthropic,?Microsoft,?Google, and?Baidu?with numerous smaller startups have been involved in the R & D & P generative AI models.
Generative AI has uses in software development, healthcare, finance, entertainment, customer service,?sales and marketing,?art, writing,?fashion,?and product design, as well as in?cybercrime, fake news?or?deepfakes?to deceive or manipulate people, and the mass replacement of human jobs.
Now, what is it all really?
First, GenAI/LL models?DO NOT learn?but compute the patterns and structure of their input?training data, generating the data with similar statistic characteristics.
Second, its transformer-based DNNs mix word contexts in a way that makes it really good at guessing the next word.
Third, LLMs are "trained" to "rote learn" on massive amounts of information, public or licensed materials, unlawfully scraped from the internet.
This could cover books, blogs, news sites, Wikipedia articles, reddit discussions, social media conversations, Quora's answers, Google's search results, billions of poems and music lyrics, billions of homework assignments and their solutions, billions of standardized test questions and their answers, billions of examples of code doing all sorts of things, billions of online questions and answers, including my 3.8K answers and 3.4K posts on Quora or 433 articles on the LinkedIn platform . and innumerable posts on the FB/AI/ML/DL .
In reality, we have something different, predictive analytics, statistical computing, or computational statistics, mathematical programming, and probability theory, all sold as AI, ML, DL, which is really a fake and false AI/GenAI.
NO statistical algorithms?can "learn from?data?and?generalize?to unseen data, performing?tasks?without explicit?instructions", without having the world modeling and reality simulation engines (ALL REALITY SIMULATOR).
This all is led by the big tech LLM chatbots, marked with the following real features:
Large Language Models are trained on the internet, having also trained on all the biases and prejudices, illusions and delusions of humanity, thus regurgitating stereotypical assumptions, conspiracy theories, political misinformation, etc.
LLMs models do not have the knowledge of the world as “core beliefs”, the world modeling and reality simulation engine. They are simply tokens guessers trying to predict what the next tokens would be if the same sentence were to appear on the internet.
LLMs do not have any sense of truth or right or wrong, any idea of factuality and reality.
LLMs "hallucinates" making nonsensical mistakes due to the training data having a lot of inconsistent material.
LLMS are auto-regressive, when errors accumulate due to the "self-attention" mechanisms. Even if only one error is made, everything that comes after might be tied to that error, becoming a cascade of infinite errors.
You should always verify the outputs of a LLM, which the result of mixing and matching some information bits and pieces to assemble a reasonable sounding response.
The quality of response is directly proportional to the quality of the input prompt, not from the statistically "smart" model.
The LLM remembers and know nothing, it doesn’t “remember” what has happened in the exchange. It is all a programming trick to make the guessing model look like it is "having a conversation" because the log of the conversations becomes a fresh new input.
LLMs don’t do problem-solving or planning, having no goals, and the backward-looking Transformers' self-attention can only be applied to the input words that have already appeared.
So, ChatGPT as a Transformer based LLM, with or without instruction tuning and reinforcement learning with human feedback (RLHF), has nothing to do with intelligence, being dumb and dull as stochastic calculators.
As a resu;t, training a massive fake AI model , the size of GPT-4, would currently take about 8,000 H100 chips, and 15 megawatts of power, enough to power about 30,000 typical British homes.
Now, NVIDIA has recently announced Project GR00T, Generalist Robot 00 Technology, a general-purpose foundation model for humanoid robots, acts as the mind of robots, making them capable of learning skills to solve a variety of tasks, designed to further its work driving breakthroughs in robotics and embodied AI.
The Big Tech Seven AI as a Fake and False AI (ff/AI)
There are Real and True Intelligence and False and Fake Intelligence, with some intermediaries, as true negatives or false positives.
The Examples of Real and True Intelligence
Real Human Intelligence, which is about knowing and categorizing, interpreting and understanding, qualifying and interacting with the world, at all levels and scopes, in the most effective and sustainable ways. Its general intelligence consists in the mental world models (World Model Engine).
Real Machine Intelligence [AI, ML, DL and NLP/NLU, LLMs, Chatbots, Robotics and Automation], which is about knowing and classifying, quantifying and interacting with the world, at all levels and scopes, in the most effective and sustainable ways. Its general intelligence consists in the world modeling and reality simulating engine (World Model Engine) programmed as a hypergraph causal networks (HGCN), a mathematical representation of reality and its data, consisting of hypernodes (representing causal variables, entities and changes) and hyperedges (representing all the causal relationships or interactions among and between the variables). It reifies all the valuable scientific models and theories, laws and facts, including statistical classifiers, AI models and ML algorithms, as DL neural networks, graph NNs, knowledge graphs, etc.
The Examples of False and Fake Intelligence
Fake and False Intelligence [AI, ML, DL and NLP/NLU, LLMs, Chatbots, Robotics and Automation] is about
领英推荐
fake knowing and classifying,
fake learning and understanding,
fake inference and predictions,
all with false outcomes.
Its fake and false intelligence consists statistical models and correlations and patterns matching in big data, in False input-False output (FIFO, like GIGO or RIRO).
It is the least reflected in the OECD teleological definition of an AI system :
"AI system is a machine-based system that, for explicit or implicit?objectives,?infers, from the input it receives, how to generate outputs such as predictions,?content,?recommendations, or decisions?that?can?influence?physical or virtual environments.?Different?AI systems vary in their?levels of autonomy?and adaptiveness after deployment".
We can make a clear distinction between AI and non-AI systems.
It is plain that AI machines involve a material cause, efficient cause, and formal cause, but hardly a final cause, to effectively interact with its environments, physical or digital, social or virtual.
AI technologies are cyber-physical, man-machine systems autonomously, interacting with the world of reality, as physical or social, digital or virtual environments, in the most efficient and sustainable and intelligent ways.
It is capable to constantly learn to know the world, its content, interactions and behaviors, in all its complexity and generality, of all possible scopes and scales, levels and detail.
All is in the general context of reality, its categories and classes, systems and networks, individuals and instances, relationships and interactions, rules and regularities, or as fundamental data variables, structures, relationships, and values.
In all, all the Big Tech AI is a mislabeled and misbranded AI, a fake and false AI (FF/AI), AI washing , the like greenwashing, being a threat to progress due to the illusion of knowledge and induced mass delusion:
Alphabet FF/AI
Amazon FF/AI
Apple FF/AI
Meta FF/AI
Microsoft & OpenAI FF/AI
Nvidia FF/AI,
Tesla FF/AI
Nvidia FF/AI
In short, the whole model of ff/AI tech stack — "from apps, to models, to cloud, to chips, only work because of gigantic training datasets at enormous cost (in ChatGPT’s case, by OpenAI) and extraordinary amounts of computing power, which are provided by cloud infrastructure services. In the cloud layer, three oligopolies are dominant — Amazon Web Services, Google Cloud Platform and Microsoft Azure (which has a major investment in OpenAI).
Cloud infrastructure itself depends on highly advanced computer chips called semiconductors. In the chip layer, one company, NVIDIA, dominates the design of the most advanced semiconductors; one company, TSMC, manufactures them; and only one company, ASML, produces the machines needed for manufacturing".
[How States Can Keep Big Tech from Dominating AI : A handful of tech giants are poised to control AI. States like California and New York can do something about it]
Disrupting the big tech AI by Real and True AI
The rationale of the big tech seven class action vs. [Alphabet, Amazon, Apple, Meta, Microsoft & OpenAI, Nvidia, Tesla] is documented in the LinkedIn postings which are supported from many parts of the world, from Africa to America.
The lawsuits are to seek damages, compensatory and punitive, up to 40% of market cap of the Big Seven; for the commercial fakery of AI technology, deliberate misleading advertising and unethical business practices and massive commercial fraud, such a Deepfake Anti-Human Technology, massive IPRs infringements and personal data exploitation.
The settlement amount, up to 40% of the Big Seven market cap, >> $10T, will go to
European regulators trying to crack down on Big Tech with no big effects, the?EU's multi-billion antitrust activities fines and penalties?would hardly be ever recovered, considering all the loopholes.
The European Parliament has adopted the Artificial Intelligence Act, establishing the first AI regulatory framework to date. This act bans AI applications considered high-risk, including biometric and facial recognition for sensitive characteristics, social scoring systems, and AI that could manipulate or exploit vulnerabilities. AI systems in critical sectors like infrastructure, education, and employment will need to adhere to stringent requirements, including risk assessments, transparency, and human oversight.
Meanwhile, the Big Tech oligopolies are booming and blooming, which is mostly due to deliberate misleading advertising and unethical business practices such as massive IPRs infringements and personal data exploitation.
The?Big Seven's market capitalization exceeds $10 trillion?of all companies: 8,184?and?total market cap: $101.738 T.
Conclusion
Computers are getting powerful, faster, and cheaper, but computer algorithms are still designed to have the very narrow capabilities needed to perform well-defined tasks, like NL tasks, as translation, spell checking, searching the internet or data transformation. This is a far cry from the real intelligence needed to deal with the world, physical or digital, with unfamiliar situations by assessing the what and who, where and when, why and how, as what is happening, why it is happening, and what the consequences are of taking action.
That's why we formulated the General Real Intelligence Rule (RIR):
If natural intelligence or artificial intelligence, be it human intelligence, AI models, ML, DL, LLMs, Chatbots, humanoid robots and automation, is unable to interact with the world or compute cause-and-effect, ruling all realities, physical or virtual, then they are deeply unintelligent, having fake learning, fake understanding, fake intelligence, fake inferences, fake language, with the false outcomes, predictions, decisions, recommendations, communication, or actions.
Resources
SUPPLEMENT 1
The Big Tech AI: "NVIDIA Fake AI Platform": Beware of the AI Mass Delusion…
Among the many organizations expected to adopt the Blackwell series of the GB200 “superchip” misbranded as AI chips are Amazon Web Services, Dell Technologies, Google, Meta, Microsoft, OpenAI, Oracle, Tesla and xAI.
Sundar Pichai, CEO of Alphabet and Google: “Scaling services like Search and Gmail to billions of users has taught us a lot about managing compute infrastructure. As we enter the AI platform shift, we continue to invest deeply in infrastructure for our own products and services, and for our Cloud customers. We are fortunate to have a longstanding partnership with NVIDIA, and look forward to bringing the breakthrough capabilities of the Blackwell GPU to our Cloud customers and teams across Google, including Google DeepMind, to accelerate future discoveries.”
Andy Jassy, president and CEO of Amazon: “Our deep collaboration with NVIDIA goes back more than 13 years, when we launched the world’s first GPU cloud instance on AWS. Today we offer the widest range of GPU solutions available anywhere in the cloud, supporting the world’s most technologically advanced accelerated workloads. It's why the new NVIDIA Blackwell GPU will run so well on AWS and the reason that NVIDIA chose AWS to co-develop Project Ceiba, combining NVIDIA’s next-generation Grace Blackwell Superchips with the AWS Nitro System's advanced virtualization and ultra-fast Elastic Fabric Adapter networking, for NVIDIA's own AI research and development. Through this joint effort between AWS and NVIDIA engineers, we're continuing to innovate together to make AWS the best place for anyone to run NVIDIA GPUs in the cloud.”
Michael Dell, founder and CEO of Dell Technologies: “Generative AI is critical to creating smarter, more reliable and efficient systems. Dell Technologies and NVIDIA are working together to shape the future of technology. With the launch of Blackwell, we will continue to deliver the next-generation of accelerated products and services to our customers, providing them with the tools they need to drive innovation across industries.”
Demis Hassabis, cofounder and CEO of Google DeepMind: “The transformative potential of AI is incredible, and it will help us solve some of the world’s most important scientific problems. Blackwell’s breakthrough technological capabilities will provide the critical compute needed to help the world’s brightest minds chart new scientific discoveries.”
Mark Zuckerberg, founder and CEO of Meta: “AI already powers everything from our large language models to our content recommendations, ads, and safety systems, and it's only going to get more important in the future. We're looking forward to using NVIDIA's Blackwell to help train our open-source Llama models and build the next generation of Meta AI and consumer products.”
Satya Nadella, executive chairman and CEO of Microsoft: “We are committed to offering our customers the most advanced infrastructure to power their AI workloads. By bringing the GB200 Grace Blackwell processor to our datacenters globally, we are building on our long-standing history of optimizing NVIDIA GPUs for our cloud, as we make the promise of AI real for organizations everywhere.”
Sam Altman, CEO of OpenAI: “Blackwell offers massive performance leaps, and will accelerate our ability to deliver leading-edge models. We’re excited to continue working with NVIDIA to enhance AI compute.”
Larry Ellison, chairman and CTO of Oracle: "Oracle’s close collaboration with NVIDIA will enable qualitative and quantitative breakthroughs in AI, machine learning and data analytics. In order for customers to uncover more actionable insights, an even more powerful engine like Blackwell is needed, which is purpose-built for accelerated computing and generative AI.”Blackwell are Amazon Web Services, Dell Technologies, Google, Meta, Microsoft, OpenAI, Oracle, Tesla and xAI.
Elon Musk, CEO of Tesla and xAI:?“There is currently nothing better than NVIDIA hardware for AI.”
Named in honor of David Harold Blackwell — a mathematician who specialized in game theory and statistics, and the first Black scholar inducted into the National Academy of Sciences — the new architecture succeeds the NVIDIA Hopper? architecture, launched two years ago.
SUPPLEMENT 2. Ponzi Schemes
A?Ponzi scheme is a form of?fraud?that lures?investors?and pays?profits?to earlier investors with?funds?from more recent investors
They use vague verbal guises such as "hedge?futures trading", "high-yield investment programs", or "offshore investment" to describe their income strategy. It is common for the operator to take advantage of a lack of investor knowledge or competence, or sometimes claim to use a proprietary, secret investment strategy to avoid giving information about the scheme.
A?pyramid scheme?is a form of fraud similar in some ways to a Ponzi scheme, relying as it does on a mistaken belief in a nonexistent financial reality, including the hope of an extremely high rate of return.
A pyramid scheme typically collapses much faster because it requires exponential increases in participants to sustain it.
An?economic bubble?(also called a?speculative bubble?or a?financial bubble) is a period when current?asset prices?greatly exceed their?intrinsic valuation, being the valuation that the underlying long-term fundamentals justify. Bubbles can be caused by overly optimistic projections about the scale and sustainability of growth (e.g.?dot-com bubble), and/or by the belief that intrinsic valuation is no longer relevant when making an investment (e.g.?Tulip mania). They have appeared in most asset classes, including?equities?(e.g.?Roaring Twenties),?commodities?(e.g.?Uranium bubble),?real estate?(e.g.?2000s US housing bubble), and even esoteric assets (e.g.?Cryptocurrency bubble). Bubbles usually form as a result of either excess liquidity in markets, and/or changed investor psychology. Large multi-asset bubbles (e.g.?1980s Japanese asset bubble?and the?2020–21 Everything bubble), are attributed to central banking liquidity (e.g. overuse of the?Fed put).
Organize a Big Tech fake AI Abolition Movement
As it is expressed by Liza Featherstone in " The Scariest Part About Artificial Intelligence": Between its water use, energy use, e-waste, and need for critical minerals that could better be used on renewable energy, A.I. could trash our chances of a sustainable future.
"If there was an A.I. abolition movement, I’d join it today, ideally advocating exuberantly cruel penalties for the tech moguls who have ensnared us in this destructive and frivolous gambit".
[FAKE] A.I. provides nothing that we truly need.
A.I. isn’t worth its significant costs. You don’t have to be a Luddite—or an insecure creative like me—to fear this technology and the sinister disregard for the human future it reflects. Communities, governments, and even those working in the tech industry should shut these dangerous and parasitical robots down before it’s too late.