Bogdan Bocse, CEO @ Knosis, vorbește cu doamna Mihaela Ghiță despre AI, Deep Fake, Deep Learning și diferențele dintre arta creată de roboți și cea creată de oameni, în cadrul emisiunii „Știința 360”, rubrica „Dimensiunea Științifică a Artei”, de la Radio Romania Cultural.
Dimensiunea Științifică a Artei
Care e diferența dintre Deep Fake și Deep Learning, doi termeni care creează adesea confuzie?
„Noi am ajuns să ne temem de tehnologia nouă, care ar putea să ne ajute, din cauza faptului că nu putem s-avem încredere în aproapele nostru.” – Bogdan Bocșe
Când AI-ul creează ARTĂ
Există experimente în care computerul, sau inteligența artificială, creează artă: că e vorba de desene după model, sau reproduceri sau chiar lucrări abstracte să le zicem ”originale” create de aceste mașini.
Cert este că programatorii creează algoritmi inteligenți utilizați pentru a picta, a scrie poezii sau a compune muzică.
Întrebarea care se pune, este una de ordin filosofic:
Cine este de fapt creatorul, Inteligența Artificială?
Sau Inteligența Artificială este doar un alt instrument de care se folosesc artiștii?
Dimensiunea Științifică a Artei
Care e diferența dintre arta făcută de om și cea făcută de computer?
Mașinile pot face artă demonstrabil mai bine, sau demonstrabil mai rău, decât oamenii?
„Ne așteptăm de la profesorii umani să aibă o programă. (…) Însă, oamenii, în societatea lor, sunt cei programați. Ce e robotul în cazul acesta?”
The only relevant metric is how many of the 8 billion minds on this planet think efficiently using concepts that outreach to Artificial Intelligence, mathematics to topology, and to computer science.
At Knosis, we use the power of 4AI and created a marketplace where human attention and knowledge meet the Machine Learning algorithms to create ?????? ????????????, able to:
We’ll get back to you as soon as possible with suggestions suited for jump-starting your journey into machine learning, computer vision, predictive analytics and emergent technology.
Does AI do more HARM than GOOD to the world? Bogdan Bocse, CEO @ KNOSIS, explains his perspective in a dialogue about Sustainable Development Goals and Artificial Intelligence.
Does AI do more GOOD or HARM to the world?
The answer to your question depends on the collective choice we, as a civilization, have not yet made. And that choice has to do with picking one of two roads.
The path of evidence-based science
If we pick the road of understanding WHY these concepts work: WHY Artificial Intelligence work, how to make it more efficient, or how to make it make itself more efficient.
If we go down that road of, let’s say, science, of investigation, of measurement, of having measurable statements in our communication, in our products and in our interfaces, then decidedly, all emerging technology, which is colloquially called „Artificial Intelligence” is our only chance for the future.
The current path
However, if we keep down the current path of maximising, profit, consumerism and usability, for the laziness of the mind of the uneducated masses who consume, if our primary objective is to increase the consumption of the masses, which I will emphasise that at the moment, unfortunately, and regrettably, 80% – 90% of Artificial Intelligence deployments are used for processes which maximise consumption, if we keep doing this, the only thing AI will help us to do is to burn the planet faster.
Now, so it’s the decision we face with Artificial Intelligence and with all the connected & associated technology, like distributed ledger, the Internet of Things, all of these are instruments from the same Symphony.
If we conduct the symphony for the purpose of maximising the objectives of the 19th century, then, I think, it will shorten the lifespan of our civilization.
And from a karmic point of view, I can’t help but agree that if we use super technology in order to just think about ourselves, we should disappear and make room for something else.
80% – 90% of the industry is explicitly part of the problem
However, if we take this call to action that nature has put upon us – to invest in technology that is sustainable, which makes itself more sustainable by operation – and there are a lot of initiatives, some of which are in our current portfolio, that can be part of the solution – but regrettably, at the moment, 80% – 90% of the industry is explicitly part of the problem by the fact that they are recklessly, recklessly increasing the energy footprint and the carbon footprint of grossly inefficient computational deployments, which are usually referred to as the cloud.
So basically, the part of it that is destroying the Earth is the Cloud. Not the technology itself, but the centralization of it.
Artificial Intelligence has been a DREAM of humankind, a PERFECT TOOL designed to solve the issues we have been long thinking of, in a FASTER, SMARTER way, WITH fewer RESOURCES. But what is Artificial Intelligence?
BUT are all these expectations around AI REALISTIC or are they simply SCIENCE-FICTION SCENARIOS?
Well… to find out, we have to clarify:
what Artificial Intelligence stands for
and most importantly what it does NOT stand for.
We have been talking about Artificial Intelligence for many YEARS, and every time we think of MORE and MORE diverse areas in which this technology can be used (boom! ideas, flashes, connections, neurons signals in a fast-forward glimpse), when in fact, WE DON’T NOTICE IT ANYMORE, yet we use it in our everyday life.
What is Artificial Intelligence?
At a very low level, a pocket computer, a smartphone and a microwave oven contain and show:
INTELLIGENCE – [as the ability to solve autonomously a defined set of problems]
of ARTIFICIAL origin – [built and put in place through the human activity]
Aware
Aware – the system is integrated with FAST and CLEAR DATA SOURCES that CAPTURE relevant and correct information on the observed/controlled phenomena.
For example: a mobile phone that can record position, acceleration, image and sound is partially “aware” of its environment.
Augmented
Augmented – the system has the ability to APPLY existing FUNCTIONS OVER the DATA provided and to DETERMINE NEW FUNCTIONS, in pursuit of (multiple) objectives.
For example: a financial analyst (human or artificial) who observes and identifies new patterns in the behaviour of credit consumers, with the dual goal of limiting his/its exposure and maximizing his/its profitability.
Automatic
Automatic – the SYSTEM CAN PERFORM ALL INTERNAL TASKS of calculation and ANALYSIS without strictly requiring human supervision.
For example: when our SYSTEMS are at a HIGH LEVEL OF USE ? ? ? and AUTOMATICALLY decide to temporarilyadd, for a fee, ADDITIONAL COMPUTING RESOURCES in one of the computing assemblies, in order to reach a DEADLINE of completion of processing.
Autonomous
Autonomous – the SYSTEM can CARRY OUT ITS ACTIVITY without requiring human supervision.
For example: an industrial process, an autonomous machine such as autonomous vacuum cleaner (we’ve been long dreaming of – ❤️❤️❤️) or the industrial robots or the dancing Robots.
Now let’s come back to what AI can do and what it can’t do!
It is probably one of the questions that are on the lips of all those who want to better understand this technology.
While Artificial Intelligence is most of the time seen as A CRUTCH TO COMPENSATE for the HUMAN COMPETENCE or LACK OF EFFICIENCY, we need to (re)connect this concept to technical, economic and practical reality.
But how do we do that?
Well, we will try our best to explain that in the following minutes.
So, what is Artificial Intelligence and what it can do?
AI can help us DISCOVER a WRONG SOLUTION FASTER so that WE CAN MOVE FASTER TO THE RIGHT ONE.
At the same time, AI CAN HELP US GET THE INFORMATION and INTERPRETATIONS we need to make RELIABLE DECISIONS IN SHORTER TIME.
In order words, FAIL FAST!
So, what AI can’t do?
ACCOUNTABILITY
As we established what AI could do for us, there is, however, one thing that ARTIFICIAL INTELLIGENCE CANNOT DO: TO TAKE ON OUR RESPONSIBILITY.
We, as directors, coordinators, administrators of a company, remain ACCOUNTABLE for the mistakes made by our employees, or … in this case by a system.
And one thing is for sure!
There are domains that can be partially/entirelyled by Artificial Intelligence, such as Project Management: where algorithms can pursue much more advanced solutions than those used by humans, HUMANS and MACHINES can TEAM UP TO ENHANCE THEIR CAPABILITIES.
And one example we can name here is the P.E.R.T. model which, although it has been known since 1960, only now becomes feasible with the help of AI and modern computing power, precisely because of the large volume of calculations required to apply the method.
Now just imagine the change to see in the world and AI will help!
Artificial Intelligence at Knosis
At Knosis, we use the power of 4AI and created a marketplace where human attention and knowledge meet the Machine Learning algorithms to create ?????? ????????????, able to:
encode & decode
classify
process
visual
textual patterns
and – SOON –
multi-lingual &
natural language models
… through computer vision technology.
Join us in building a universal dictionary of concepts from which people and machines can learn, in perfect symbiosis, by:
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