From Simple Patterns to Sentience’s Complexity

“In order for AI to be able to overtake a programmers job, implies that the client knows what he wants. We’re safe…”
This job related predicament rises, as I see it, only in a brief moment in a much broader natural course. It is the kind of meme that strives to survive, it probably deserves a definitive NFT minting as of 03.2022 before it will soon fall into oblivion.
I want to start tackling its survival efficiency by talking about the AI and its power as I see it from this stand point: in which in the past decade the AI’s potential reached only its first steps in its infancy with clear signals to world changing capabilities. This goes further down, through refinements (of its rightly chosen) ontology.
Preamble
We live in a world (or better said, this is the way the world works) in which almost everything employs from within some mechanics of refinement and adaptation. A machinery that moves things towards escaping chaos – and this with great energy consumption – but energy that partly comes from within (as the “will” opposed to the “death drive”). This goes from the inherent patterns in nature up to the end spectrum of the human activity(1). The underlying battle between order and entropy(2) on the underlying surface of our particular(3) universe with its laws. And above this, as the layer of simple emerging patterns to the ultimate, macro refinement substrate of sentient manifestations, and on top of it with the layer of symbolic, cultures and abstract thinking. A predictable pattern alright, further on rising within the brain energy patterns, a culmination tip, that leads to the creation of synthetic worlds, artificial sentience, transcendental states of being in the digital universe, as the next steps. A macro, ever growing vertical ontology at work.
Refinement
Within this broader context the refinement produces further deepening of the domains and within AI domain, the current advances allow neural training of some larger than ever data sets, like in the language, vision, with a touch of symbolic, towards incipient meaning. In the context of programming we see first results in training upon some good part of all the human written programming code. And that we are able to put that to work in the business requirements with the programming languages on the real use cases (necessary for a program to have a purpose) for now in the form of AI assisted programming(4).
And further refinement would lead to a more natural way of conceiving programs through language processing of the requirements, from the problems to the actual code generation. And with, again, a further refinement into the symbolic AI with the actual predictable outcome not by only answering the questions, but with solutions offered by AI prior asking the question(5). All that within a domain criteria based on programming/AI ethics, best practices solutions, security, cultural impact, etc.
Symbolic
On the side of symbolic AI at this time there is an upward trend of trying different models of processing, a process in itself that requires further research. At the same time I see that this process is hindered by the fact that the models are still mapping or try mimicking some partial models of the mind, of trying to explain how brain works, and by posing answers to the questions related to consciousness(6).
I am still on the path and researching on my own symbolic model within the essentials, unspoiled concepts advanced through the innovative approach by Ludwig Wittgenstein:

“The reason computers have no understanding of the sentences they process is not that they lack sufficient neuronal complexity, but that they are not, and cannot be, participants in the culture to which the sentences belong. A sentence does not acquire meaning through the correlation, one to one, of its words with objects in the world; it acquires meaning through the use that is made of it in the communal life of human beings.”

There is not only – many would call with yesterday’s standards as a “grim” future – but there is in fact to be reminded that one cannot oppose the refinements because it requires also effort and energy none is possessing enough. Through self cultivated death drive that will only help on the short run…so remember this meme and laugh at its NFT later.

(1) forms of life with language games adaptation, creation activities with continuous refinements of their ontological models, circulating concept cultures.
(2) with simple patterns from which something emerges and with the counter action of opposite forces from nature up to the psyche and symbolic, the death drive.
(3) multiverse theory, in which very briefly explained: the eternal timeless energy waves produces bubbles of universes each with its fundamentals.
(4) copilot software that has the basis all of the github source code.
(5) if we have the right domain question we have the answer, in that the answer is there, it is only that briefly something is obscuring it from view.
(6) on questions related to the knowledge of ourselves, which in fact, are not of scientific nature.

C. Stefan / 24.03.2022

Web3 & DeFi space

World Wide Web3
Brief history from simple showcase to owning the Internet:
https://www.youtube.com/watch?v=AFb5gosfKJY
https://www.youtube.com/watch?v=B0ZJMdSvAj8

Blockchain, Smart Contracts, NFT
https://www.youtube.com/watch?v=JPGNvKy6DTA
https://www.youtube.com/watch?v=22O6a87-GcQ
Impact:
https://youtu.be/0u6cho7YpQQ?t=560

DAO (Decentralized Autonomous Organization)
https://www.youtube.com/watch?v=pA6CGuXEKtQ

Owning your data
https://www.youtube.com/watch?v=P2n5HY-eidU
https://www.youtube.com/watch?v=kqnxZ_IByKE

Business Models
https://www.youtube.com/watch?v=AI1N6dY8vSQ
https://www.youtube.com/watch?v=-n5084IfnxU

Gaming
https://www.youtube.com/watch?v=BdtrE4TLaeE
Metaverse
https://www.youtube.com/watch?v=ExUovs0n4bA

Social Money
https://www.youtube.com/watch?v=Ka7QZM6zx40

DeFi
The space of future finances. The departure from the standard centralized (banks) finances model to the digital counterpart, decentralized. The new money model enabling the fuel that will drive the Web3.

Metaverse

  • The metaverse encompasses immersive environments, often (but not always) using virtual- or augmented-reality technology.
  • The metaverse is “always on” and exists in real time.
  • The metaverse spans the virtual and physical worlds, as well as multiple platforms.
  • The metaverse is powered by a fully functioning virtual economy, often (but not always) built on cryptocurrency and digital goods and assets, including nonfungible tokens (NFTs).
  • The metaverse enables people to have virtual identities, presence, and “agency,” including peer-to-peer interactions, transactions, user-generated content, and “world-building.”

Job Breakthroughs

Startup vs. Larger Company:
Working for a smaller company is that you get to make more of an impact: Working in a larger corporation might have more benefits or a higher salary but a startup is where you can really make a difference and see the influence your work is having on the business. You’re heavily involved in each stage of production and your opinion is more likely to carry weight than at a larger, more structured operation. Decentralization of big companies would be done through tokenization. The shares will be done through ICOs.
Jobs in IT:
In Artificial Intelligence, the Internet of Things, data security, virtual reality and augmented reality, virtual worlds (and virtual assets) and bank-less, free nodes back-boned, Internet of payment. Jobs to see as or related to: big data engineer, Software 2.0 Engineer (maintain Neural Networks that write code), full-stack developer, security engineer, IoT architect and VR/AR engineer and hybrid engineers, with agile mindsets through the teams, with solid technology stacks knowledge that working together are able to bind different ends of the domain spectrum (similarly like DevOps is to the “from Code to Infrastructure” mindset paradigm), runners of decentralized Internet (sustained by Blockchain and other similar technologies yet to come, in order to back-up the Virtual Assets in the Virtual Worlds in the Decentralized Network).
Thus the skills needed to succeed in the IT jobs of tomorrow revolve around security certifications, programming and applications development, proficiency with cloud, decentralized architectures and mobile technologies, and other specialized skill sets giving also way to the hybrid IT roles that bind the business to IT.
Roles grow vertically based on business domain vs. technology stacks. For example: a Solutions Architect has the business domain knowledge but has also a technical background. He will develop complex technology solutions in a specific business domain. Software Architect knows in a deeper way the technology stacks. He will design the architecture of the technical implementation. Technical Lead is one with deeper knowledge of the, or a part of the technology stack. He designs using established patterns, coaches teams into the adopted technologies and unlocks teams in order to succeed in project delivery.
Data Scientists: it is essential for data scientists to work with languages like R, Python, SAS, Hadoop, Netezza in which they apply their knowledge in statistics, mathematics (algebra), matrices (multivariable) calculus. And to have a knowledge in platforms like MapReduce, GridGain, HPCC, Storm, Hive, Pig, Amazon S3.
The user as valuable “in the network” resource, in parallel digital universes (eg. Metaverse). Their actions should be monetized and generate income. We are producing valuable data even now by only navigating on FB, Google and other social networks which the system themselves uses it to become better (the long therm plan is building the future AI systems together). The “Internaut” will be one of the nicest job of the future.