Big Tech AI: the truth or wishful thinking?
Man should not create machines in his own image and likeness.
"Wishful thinking is the formation of beliefs based on what might be pleasing to imagine, rather than on evidence, rationality, or reality; the illusion that what you wish for is actually true. type of: fancy, fantasy, illusion, phantasy".
"When we embark on a course of action which is unconsciously driven by wishful thinking, all may seem to go well for a time, in what may be called the 'dream stage'. But because this make-believe can never be reconciled with reality, it leads to a 'frustration stage' as things start to go wrong, prompting a more determined effort to keep the fantasy in being. As reality presses in, it leads to a 'nightmare stage' as everything goes wrong, culminating in an 'explosion into reality', when the fantasy finally falls apart."
We’ve all heard a lot of hype, hope and fear about artificial intelligence and machine learning, neural networks and deep learning, large language models and chatbots, intelligent automation and humanoid robotics.
According to ARK’s research, BIG IDEAS 2024: Disrupting the Norm, Defining the Future, a technological convergence among disruptive technologies will define this decade.
Five major technology platforms—Artificial Intelligence, Public Blockchains, Multiomic Sequencing, Energy Storage, and Robotics—are coalescing and should transform global economic activity.
As a result, the annualized equity return associated with disruptive innovation could exceed 40% during the next seven years, increasing its market capitalization from ~$19 trillion today to roughly $220 trillion by 2030.
All is well and good except one thing. It is all wishful thinking mixed with a mass delusion.
THERE IS NO REAL AND TRUE OR INTERACTIVE AI (AIAI), YET. BUT THERE IS A MORE ADVANCED DATA-TRANSFORMING HARDWARE, SOFTWARE, AND CLOUD TECHNOLOGY MISBRANDED AS AI, ML, DL, or NN PLATFORMS, being really Fake and False AI, ML, DL, NN platforms.
Examples of Fake AI Technology
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,
Mistral AI's?open source?models,
text-to-image?AI image generation?systems such as?Stable Diffusion,?Midjourney?and?DALL-E,
text-to-video?AI generators such as?Sora.
OpenAI,?Anthropic,?Microsoft,?Google, and?Baidu?with numerous smaller startups have been involved in the R & D & P of generative AI models.
GenAI has uses in cybercrime, fake news?or?deepfakes?to deceive or manipulate people, and the mass replacement of human jobs.
All the big tech AI is a giant bubble to be busted before soon.
Truth/Reality AI vs. Fake/False AI
To distinguish a real and true AI from a fake and false AI is rather simple:
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To summarize the major points:
Today's AI is Not-AI, Artificial Intelligence is NOT the simulation of human intelligence processes, or replicating and mimicking the human body/brain/brains/behavior/business. The anthropomorphization of AI, as narrow/weak AI, human-like, human level, general AI, or artificial superintelligence, is "creating machines in the image of humans", with all the consequences.
Today's ML is Not-ML, Machine Learning can NOT "learn from data"; computer algorithms can not be "trained" to find relationships and patterns in data, to solve problems, make predictions, classify information, cluster data points, or generate content. ML is NOT imitating the way that humans learn.
Today's NNs are Not-NNs, Neural Networks are mathematical structures which are NOT patterned after the human brain; neural networks are digital, static and symbolic, while the biological brain is dynamic, plastic and analog
Today's DL is Not-DL, Deep learning or Deep NNs are NOT modelled after the human brain, and DL models CAN NOT "recognize" complex patterns in pictures, text, sounds, and other data to produce accurate insights and predictions.
Today's GenAI is Not-AI, Generative AI CAN NOT "create" new content and ideas, including conversations, stories, images, videos, and music.
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SUPPLEMENT
Five major technology platforms—Artificial Intelligence, Public Blockchains, Multiomic Sequencing, Energy Storage, and Robotics—are coalescing and should transform global economic activity.
Technological convergence could create tectonic macroeconomic shifts more impactful than the first and second industrial revolutions. Globally, real economic growth could accelerate... to more than 7% during the next 7 years as robots reinvigorate manufacturing, robotaxis transform transportation, and artificial intelligence amplifies knowledge worker productivity.
Catalyzed by breakthroughs in artificial intelligence, the global equity market value associated with disruptive innovation could increase from 16% of the total* to more than 60% by 2030.
As a result, the annualized equity return associated with disruptive innovation could exceed 40% during the next seven years, increasing its market capitalization from ~$19 trillion today to roughly $220 trillion by 2030.
"Artificial Intelligence is Computational systems and software that evolve with data can solve intractable problems, automate knowledge work, and accelerate technology’s integration into every economic sector.
The adoption of Neural Networks should prove more momentous than the introduction of the internet and potentially create 10s of trillion dollars of value. At scale these systems will require unprecedented computational resources, and AI-specific compute hardware should dominate the Next Gen Cloud datacenters that train and operate AI models.
The potential for end-users is clear: a constellation of AI-driven Intelligent Devices that pervade people's lives, changing the way that they spend, work, and play. The adoption of artificial intelligence should transform every sector, impact every business, and catalyze every innovation platform".
What's PostFlow? Find out at postflow.goautomates.ai // Applied AI & Data Enthusiast, AI Content Creator at PostFlow: writing about the future of content creation here.
6 个月Your insights bring a necessary dose of skepticism to the conversation around artificial intelligence and machine learning.