Machina Sapiens vs. Human Sapiens, or why Musk is after humanoid robots while being deeply scared of AI
We have recently seen the Tesla AI Day with a lot of hype and no any AI, if not to count an actor who played a humanoid robot.
As a part of hype, the Tesla CEO surprised the world with his promise to produce the Tesla humanoid robot next year, as the next generation of automation, including a general purpose, bi-pedal, humanoid robot capable of performing tasks that are unsafe, repetitive or boring.
Many started questioning themselves, why Musk is after humanoid robots while being deeply scared of AI.
A moralizer could suggest that it is all about money, power and fame, a troika of wild horses driving our nature. And we usually say one thing, while doing something different. This is generally in human nature.
CNBC might propose that the Tesla Bot is an example of Musk’s showmanship, in which he announces that Tesla is working on exciting products scheduled for years into the future to energize backers including employees, customers, and investors.
Often, those announcements don’t happen on the timeline predicted.
For instance, at an ‘Autonomy Day” event in Apr. 2019, Musk said the company would have 1 million autonomous “robotaxis” on the road in 2020. Those robotaxis are nowhere to be seen.
In October 2016, Musk held an event at Universal Studios’ back lot in Los Angeles to show off a product he called the Solar Roof. The solar roof tiles on display turned out to be merely conceptual.
A forward-looking techno-businessman might think that it is a smart move; for the emerging market of humanoid robots could be domineering in the fast emerging Narrow AI/ML/DL/Robotics Industry.
Let me remind, “robotics develops machines that can substitute for humans and replicate human actions”, integrating computer science and engineering. And a robot is a programmable machine capable of carrying out a complex series of actions automatically, cost-effectively replacing human labor of any complexity.
In a sense, we are talking about artificial human beings or digital humans or non-organic human-like creatures, as Machina Sapiens:
Technical advancements in efficient, human-replacing and cost-effective robot models. ML/DL/ANN algorithms and high demand from military and defence, healthcare industry, and growing trend for automation of big industries are opening major investment opportunities for the fast growth of the global humanoid robot market.
Global Humanoid Robot Market
Tesla wants to be within key humanoid robot global market players, as
SoftBank (Japan), ROBOTIS (South Korea), Hyundai, KAWADA ROBOTICS (Japan), Honda Motor (Japan), UBTECH ROBOTICS (China), Hajime Research Institute (Japan), Hanson Robotics (Hong Kong), DST Robot Co. (South Korea), PAL Robotics (Spain), Toyota Motor (Japan), ROBO GARAGE Co., PAL Robotics, Sarcos Robotics, Istituto Italiano di Tecnologia (Italy), Engineered Arts (UK), Robotics Lab (Spain), and National Aeronautics and Space Administration (NASA, US).
Boston Dynamics was bought by Hyundai for $1,1bn. Before it had been purchased by Google in 2013, then Japanese investment firm SoftBank in 2017, which bought it from Google for $100 million before injecting $37 million more in 2019. Now, Hyundai holds an 80 percent stake in the company and SoftBank retains the remaining 20 percent
I should mention here a robotic sex tech industry. It is promised that the ‘sex tech’ industry combining the huge advances in Narrow Artificial Intelligence (NAI) and Robotics technologies is “to produce new and novel ways to experience sexual pleasure”. Growth estimates see that the sex robotic market valuation almost doubling by 2026, to $ 60bn.
In all, the robotic market is divided by components, motion time and application:
Homo Sapiens vs. Machina Sapiens
?There is a conceptual research article presenting three notions on the similarities and differences between human- and artificial intelligence:
1) the fundamental constraints of human (and artificial) intelligence, 2) human intelligence as one of many possible forms of general intelligence, and 3) the high potential impact of multiple (integrated) forms of narrow-hybrid AI applications.
It stresses that trustworthiness, explainability, and ethics are characterized by implicit anthropocentric and anthropomorphistic conceptions and, for instance, the pursuit of human-like intelligence as "the golden standard for Artificial Intelligence".
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It briefly summarizes a few fundamental differences between human and artificial intelligence (Bostrom, 2014):
‐Basic structure: Biological (carbon) intelligence is based on neural “wetware” which is fundamentally different from artificial (silicon-based) intelligence. As opposed to biological wetware, in silicon, or digital, systems “hardware” and “software” are independent of each other (Kosslyn and Koenig, 1992). When a biological system has learned a new skill, this will be bounded to the system itself. In contrast, if an AI system has learned a certain skill then the constituting algorithms can be directly copied to all other similar digital systems.
‐Speed: Signals from AI systems propagate with almost the speed of light. In humans, the conduction velocity of nerves proceeds with a speed of at most 120?m/s, which is extremely slow in the time scale of computers (Siegel and Sapru, 2005).
‐Connectivity and communication: People cannot directly communicate with each other. They communicate via language and gestures with limited bandwidth. This is slower and more difficult than the communication of AI systems that can be connected directly to each other. Thanks to this direct connection, they can also collaborate on the basis of integrated algorithms.
‐Updatability and scalability: AI systems have almost no constraints with regard to keep them up to date or to upscale and/or re-configure them, so that they have the right algorithms and the data processing and storage capacities necessary for the tasks they have to carry out. This capacity for rapid, structural expansion and immediate improvement hardly applies to people.
‐In contrast, biology does a lot with a little: organic brains are millions of times more efficient in energy consumption than computers. The human brain consumes less energy than a lightbulb, whereas a supercomputer with comparable computational performance uses enough electricity to power quite a village (Fischetti, 2011).
These kinds of differences in basic structure, speed, connectivity, updatability, scalability, and energy consumption will necessarily also lead to different qualities and limitations between human and artificial intelligence. Human- versus Artificial Intelligence
How to create artificial human beings, digital humans, or AI humanoids
All what humanoid robots need to become real digital humans is a robust common sense model:
AHB = Humanoid Robot + AI/ML/DL algorithms + Common Sense Mechanism
Aristotle had first discussed "common sense" as the ability with which animals (including humans) process sense-perceptions, memories and imagination in order to reach basic judgments.
But humans have real reasoned thinking as intellect, which takes them beyond their common sense.
The mind, animal or human, links and categorizes different sensory modalities, tastes, colours, feelings, smells and sounds, in order to make sense of the world, perceiving real things in terms of the "common sensibles" (or "common perceptibles").
In today’s AI/ML/DL. this subject is studied by Multimodal Bayes Network Machine Model.
Since the information in real world usually comes as different modalities, multimodal learning models are aimed to represent the joint representations of different modalities.
A lot of models/algorithms have been implemented to retrieve and classify a certain type of data, but only separately, e.g., image or text or audio.
A common sense model or algorithm is able to jointly represent the information to capture the causal correlation structure between different modalities, as real-world multimodal data sets of different types of information as text, speech, audio, vision, and smell.
Machine’s experience of the world is multimodal — it computes the environment, virtual and physical, in biologically unrestricted ways, much exceeding human perceptual functions, as to see objects, hear sounds, feel the texture, smell odors, and taste flavors.
And having a common sense mechanism is a causal path to the digital humans or artificial human beings or humanoid robots with the commonsense machine intelligence.
Conclusion
We are embarking into the "new brave world" of autonomous entities, the Internet of autonomous things, from self-navigating drones and autonomous cars and military robots (ground, sea, air, water, space), with information-collection or target-attack capabilities, to humanoid robots as artificial human beings.
And who is to win in the forthcoming great technological competition, Machina Sapiens or Human Sapiens is an open question.
Resources
Global AI Academy: AI4EE
Bin Akademiker Und Arithmetiker. Bin auch Grammatiker, Sowie ?sthetiker.
3 年In RUR, ?apek,?introduced us to the notion of artificial intelligence at war with humanity. But the history of life shows that, at least at the cellular and lower levels, many of the mutations in species with resulting changes in aptitudes have occurred when different forms merge or collaborate to become new types. Science fiction has explored equivalent changes occurring when technology is blended with humans, from spectacles and artificial limbs to the Borg, and RUR (on the dark side), with Asimovs Laws of robotics, Cyborgs and Androids as more neutral representatives of future meetings between technology and humanity. So while your point may be a valid warning of the effect of AI on humankind (like RUR) that is likely a much narrower view of the future interactions (including merging) of AI and wetware.