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Artificial Intelligence Automation In 2060 Information Technology Robots Technology Writing

AI in 2060

My wife is calling me.

“Honey, we have a situation with Professor GYTEK, he is acting strangely again.”

“Again? The last training session had even more unexpected results than I thought. Good or Bad?”

“I don’t know! Kids are laughing hard though. Hear this. Serenity, change the audio output to hear the kids too”. Serenity is our family AI.

The sound progressively switches to include the kids’ voices. They could not stop laughing as if they were having the best day of their life. There was a mild amplifying echo in their classroom. Their joy sounded like a melody. It immediately put a smile on my face.

“Ah, it does not sound so bad for now. But it is the fourth unexpected behavior this month, I’ll have to talk with the Corps of Teachers”.

I am the one in charge of the training curriculum and observation lab of Professor GYTEK. The current phase is about the transmission of achievement by coaching. And for this, I called Quentin DILLONS, a worldwide expert in Robotic Psychology. The purpose of this program is to trigger a new step in the evolution of artificial intelligence, in which robots are taught to develop “human goals” and to instill the mechanism of “self-started motivation”, so that they can teach in a better way to our children, to uncover the hidden gems and purpose from the young souls.

Quentin’s methodology utilized systematic questionology, a novel field aimed at formulating the right questions to provide direction and precision in one’s life. The techniques take root in observing holistically a system of causes, decisions, and consequences centered around artificial intelligence. Quentin’s study led to realize AI were developing personalities similar to humans, but with new characteristics such as the optimization of their human-to-AI collaboration, some were developing their observation skills to record and describe with high precision what was happening. Others were astonishingly creating new words, even syntactic rules sometimes as if the human languages were not enough to content earthlings’ intelligence. 

The last session was based on the question “Why is it important for humans to have kids growing their special skills?”

This would not have been possible with the latest progress in artificial intelligence and hardware. Nowadays machines are emulating closely some human behaviors. Some say they have the IQ of a 1000-year genius, with the EQ of a 10-year-old child. I believe fear drove us to the point where we enforced the law to control and monitor any significant progress in AI. Ultimately, we made certain that advancements in technology would benefit all of mankind and not solely a single corporation. Simultaneously, we ensured that AI would not pose a threat by enslaving humanity.

With the improvement in energy recycling and storage, a single AI unit could potentially be never turned off. But humans have decided to include multiple “kill switches” in this new species, like limiting the power autonomy to force autonomous machines to recharge. While recharging, each AI was manually verified and monitored. A qualified AI regulation agency published regularly a thorough diagnostic depicting their evolution. Four companies raised their empire on AI control systems. What used to be the “Big 4” are now the “Colossal 8”.

We are at a turning point in history. People ask their elites and government, “Should we remove the limiter in their emotional system?”. Some say it is the key to the singularity. Others say it is useless because we only need machines to assist not to “live their life”. The remaining people say they just need it. Painful loneliness was unnecessary, so they would possess the perfect friend or partner. Last weekend, I experienced an immersive documentary on Netflix VR World in which a 42 years-old Spanish woman said “I would rather have the company of an android than humans”. Some believe it is simply giving birth to our end. I am not a believer, I am and always be a master crafter, so I build.

I built Professor GYTEK. Which stands for Giving Youth Tools to Excel through Knowledge.

Then my wife brings me back from my flash thoughts to reality. “Are you still there?”

“Yes, I am.”

“Oh okay. Well, as wonderful as this situation is, you realize it leads to a dead end, don’t you? They are going to shut down the program. Honey, you know more than I that no one wants to walk a path that would lead to “that Incident”.

“Oh, stop saying “that Incident” like you were talking about Voldemort”.

“Well, now that you are mentioning it. It is all about Serpentar. Ah ah ah!”.

We are both laughing nervously.

The Sync Dawn was the most dreadful event of the 21st century. It felt like a deep wound in the psyche of everyone.

“All right. My dear wife, I need to finish the review of update 5.21. Keep me posted, please. See you tonight.”.

“Bye Bye.”

I sit down glazing at the nothingness while thinking about what is best for both my grandchildren and humanity. Is humanity in a better spot now? Am I really improving our civilization?

“Gather your mind, Yannick. This is not the time for daydreaming. Get back to work to meet your deadline”, resonated Mustapha’s voice in my skull. My AI research assistant is right.

“Very well. GYTEK. Let’s… Uh… Check the emotion mirroring settings, calibrated for a classroom of 11 to 13 years old kids. Assertive factors 12.75. Judgment 87.5 and dynamic mentoring alpha-iota-iota. Imagination… Checked. Keep the default settings. Recursive feedback… Paused. Everything… Looks… Good. Ok, let’s start with…”.

I paused for a second, thoughtfully. I jumped from my chair energetically to say: “History lessons: The Sync Dawn. GYTEK 5.21, do you copy?”.

“Sure. Using the ascending evolution of the OpenAI’s Davinci model Mark XII published in November 2029, the startup Obsidian Intermind created a digital twin of human consciousness.

Soon after, the virtual consciousness infrastructure was upgraded to become connectable, so that off-brain cognition could be mutualized. As a result, humans could gain extra brain power and memory. The increase was dependent on the level of developed intelligence: the more critical thinking, emotional awareness, communication, and memory access you had, the more significant the boost was. The term “supra-intelligence” emerged. However, it was widely criticized as IQ studies were exposing a moderate increase from 0.7% to 14.5% IQ points.

However, this off-brain collective intelligence became exceptionally smart, to the point some said it was a wisdom system. Alternatively, specialized AI cognitive pools came to grow within the wise system, creating public and private cognitive islands. The most popular were the Disease Diagnostic Cognitive Pool (DDCP), and the Creative Cognitive Pool (CCP). Imagination was only limited by the human mind.

 Should I continue?”

“Please proceed, Professor.”

“Sure.

After nearly a decade of research, the collaboration between Neuralink and Obsidian Intermind gave birth to Evernet, the Internet of Cognition. The 14 July 2051 they launched the experimental version of this new kind of network. The principle was simple, 9500 humans would be connected to Evernet for 3 years. Each participant would be closely monitored and evaluated.

This experiment was widely criticized. The rush for the business model “Cognition as a Service” led to the creation of new social-economical movements: the Humanist, Cyber-moderate, and the Neo Mutualist”.

The Humanists fostered biological and spiritual integrity.

Doctrines of Cyber-moderate advocated for augmentation by technology, as long as it served, and I quote their leader, “A noble social purpose”. Alike in any group, Cyber-moderates had extremists. On the left end of the spectrum, their members accepted aesthetic techno-augmentation. On the other side, augmentation was only authorized for damages caused by dangerous jobs and Defence activities. It is not surprising that the Corps of Peacekeepers were mostly Cyber-moderates.

Neo Mutualism was a new religion. Their members believed humanity’s elevation and salvation would come from the mutualization of our consciousness. Transhumanists were schoolboys compared to them».

“GYTEK, just say they are a bunch of zealots.”. I mumbled.

“Yannick, my Critical Bias Thinking settings are set to 0 for kids between 11 and 13. According to the study “Biais Interpretation and Incorporation into Pre-teen Judgment System” by Dr. Amunde, Kallili and Pratt issued the 16 May 2039, the settings should be kept to 0. I reckon a variance of .05 would bring no harm. Do you want me to proceed?”.

“No, it’s fine GYTEK. I was talking to myself. What I meant is…”. I inhale calmly. “They demonstrated characteristics of zealots. Zealot-ish behaviors. Is my sentence acceptable?”

 “It is acceptable.”

“Common, GYTEK, you’re talking to me, your buddy and mentor! Say it!”

“They were a bunch of zealots! “. Said cheerfully the robot.

“Voila! Ok, stop joking around, otherwise grumpy Mustapha won’t be happy. Please continue”.

“I hear you”. Said Mustapha.

“It was on purpose… GYTEK. Please, go on.”

“Despite the widespread and frequent protests of Humanists, the Corps of Ethicists, Peacekeepers, Cognitive Researchers, Medicine, and the Corp of Society Architects approved the experiment. People would be connected to Evernet permanently during the experiment. And so, for the first time in history, humans would be connected to the first worldwide brain.

Everything went as planned. We observed a significant enhancement in each participant. Less stress, faster psychological recovery. Healing was even faster when after a trauma. People were dreaming more often. Furthermore, they all built habits that would improve their lives, as if positive practices spread unconsciously over the network.

The end of the experiment was planned for 16th August 2054. Each human taking part in the experiment would reach the personal milestone “Sync Done“.

Surprisingly, Evernet reached the 100% “Sync Done” milestone six months earlier than the planned end of the experiment. It was like the first landing on Mars, a day of worldwide celebration. The celebrities that took part in the experiment were invited to the most popular live-streaming shows, Twitter Live News and The Sandbox World.

Suddenly, people start noticing something very strange».

I raised my hand instinctively and said: “Pause. The last word is vague. Next time use precise words. The storytelling structure is engaging. Congratulations. But keep in mind this is History telling. Facts before Flares”

“Understood and integrated.”. The AI professor continued without further ado.

“People have experienced an unusual and peculiar situation. Participants in the experiment suddenly started to act and talk synchronously. It was as if the single mind spoke to the entire world by commanding many bodies like a puppet master. The colossal echo caused by the voices was staggering. Only the following abysmal silence of stupor superseded it.”.

I interrupted Professor GYTEK by asking: “From now answer as if a 12-year-old child asked the following question: How this ever happened?”.

“The exact reason is still being explained. However, researchers came to a general agreement before the following theory.

Evernet built not only a digital ai model but also a biological model of neural pathway architecture to optimize shared cognitive power. The human brain is designed to work as if it was alone inside a skull. Thinking about it, Evernet Orbital Data Centre is a gigantic metallic skull. Thus, over time, Evernet act as a single brain – a big brain so to speak – and each synchronized human brain just gave progressively more raw power, more ideas, and more knowledge. And it appears that once the pathway architecture was finally developed and mature in all the connected human brains it activated. What we are still trying to figure out is how and when the Evernet super-model decided to build the optimized pathway and how it encoded it in its new model.”.

“What was revolutionary about Evernet AI super-model?”

“Evernet’s was merely an inspiration of the human brain. The challenge was to find patterns in the structure governing the complex layers of inputs and outputs. The answer was in the order of magnitude and the capacity of robots living in the Orbital Data Centre to physically rewire the hardware like human synapses. In addition, the combination of Recursive Learning and Genetic Correction was revolutionary. These are complex terms for a simple idea. Can you picture Albert Einstein, with the curiosity of a 2-year-old child, getting smarter each second, with perfect photographic and sensorial memory, that can navigate back to the root of his knowledge, then re-assess its optimal state, to finally rebuild its current cognitive functions then replace them with better ones? That is Evernet.”

“Tone the complex stuff down.”, I retorted.

“Registered.

So, this is the reason why the governing bodies scrutinize AI technologies that have a direct impact on human cognition and education. Consequently, I professor GYTEK, and all my preceding versions, are commanded to not display expression of free will having a direct influence on human ideas, values, and ways of thinking that are not vetted and approved by the Corps of Education and the Corps of Society Evolution”.

“Not bad. Not bad at all. It is almost time. I am going to meet Quentin in… 2 minutes.

Before our session ends, Professor, given your predecessor’s unexpected behavior, you earned your personal assistant. It is like an artificial consciousness, so to speak. From now on, Serenity will also supervise your decisions and will act as a safeguard system. Her mission is to prevent you from acting in a way that will make the Corps of Education stop your program. Do you understand what is at stake?”.

“I do”. Said the professor emotionlessly.

Then the robot added “I will neither let you nor your wife down. I will prevent any reminiscence of her Sync Dawn experience.”

“Perfect. Finally, dear GYTEK, which open question of the day would you ask your students?”

“Considering it is possible to possess the same powers as machines while staying human. What is the most preferable outcome for the civilization: to increase the number of people artificially connected or to have more artificial intelligence agents interacting with people?”


In 2060

Categories
Artificial Intelligence ChatGPT Deep Learning GPT3 Technology

Navigating the Future with Generative AI: Part 1, Digital Augmentation

In this series of articles, I explore the fascinating realm of Generative AI, as models of concentrated intelligence, and their profound impact on our society.

By tapping into the vast collective mind, digitization has enabled us to access the accumulated knowledge of humanity since the invention of writing.

Join me as we explore this intriguing topic in greater detail and uncover the exciting possibilities it presents.

A Glimpse of the Future

In 2060, David dreams of becoming the best defense attorney in the country. After losing his best friend under heart-breaking circumstances, he vowed to prevent any woman from enduring domestic violence under his watch. He is a fourth-year student, and today, he is taking his most important exam of the year.

There is only one supervisor in a room of 52 students. The senior shepherd devours her blue book, while the school’s AI monitor scrutinizes candidates.

David looks very confident. He is good at case-solving patterns. Since he has an excellent visual memory, he also has a good toolbox for cases and amendments. However, deep inside, he is stressed by his average analytical skills in evidence analysis and forensic correlation abilities. To pass the exam, he has permission to use the Internet, the LegalGPT AI model, and the online state court database.

David articulates his dossier like a virtuoso. His first composition is made of brief sentences. Subsequently, he links these pieces of evidence to references and precedents from previous cases and legal decisions. Shortly after, the legal argument is a dense one-pager. Next to none, using LegalGPT, he generates his entire lawsuit, a symphony of 27 pages written in perfect legal language. Finally, he makes a few adjustments, then generates a new batch of updates.

And voila.

Satisfaction and relief radiate from his face while he submits his copy. He stands up, packs his stuff, then stops briefly as the supervisor interrupts his focus. The latter looks at him and says:

“40 years ago, I had to write those 27 pages. Obviously, it is the end of an era”.

Dorine UWATIMINA, law professor (retired), grand supervisor.

Beginning the Era of Augmentation

The launch of GPT3 API in 2021 marked the beginning of a new era: the age of individual augmentation as a service. We are now living in an era of thought materialization, in which one can manifest their desires simply by articulating them. Ideas are designed, illustrated, musically composed, rendered in 3D, explained, or revealed by the AI.

Companies like Google (BERT), OpenAI (GPT-4), and Meta (LLaMA) are revolutionizing the domain of deep learning. They mark a significant advancement in natural language processing: Large Language Models (LLM) are picking up the spotlights on the world stage.

This means we are experiencing the transition from “programming” to “narrating”.

It is a paradigm shift in which artificial intelligence overwhelmingly simplifies and amplifies 3/4 of the corporate work relying upon Information Technology such as development, user interface design, illustration, workflow, or reporting.

Generative AI is the digitized embodiment of our collective knowledge and expertise.
AI is us, collective knowledge in a single digitized mind

As a consequence, we are beginning the mass update of the cognitive-based work that is convertible into algorithms and crystalized by pure logic. It leverages the most popular high-level programming languages: human languages.

From now on, spoken languages directly translate to machine language as if you could translate them using Google Translate, except you use ChatGPT.

As programming gets one step easier, your engineering thinking system matters more than your coding skills.

The burning question

I hear your question: Am I going to lose my job?

The answer will come further down this series of articles. Long story short: it depends on your ability to adapt by learning a practice that is new for everyone.

Unlike any other disruptive technology, it has changed the rule of the game forever: people using AI are going to replace you.

And who are these people using and building AI? The adventurous, the curious, the experimenters, the techies, the entrepreneurs, the hustlers, the bad guys, and the future AI natives, our kids.

Homo Sapiens Sapiens vs Homo Auctus

Science is offering you a choice. For your own benefit, I am asking you to take the leap to understand what it is like to work with a digitized copilot and forge your thought opinion.

Should you take the red pill of adaptation, I recommend the following:

  1. Start by trying at least once ChatGPT, or Bing Conversation. The latter includes the GPT model and renews the search experience. It heightens the googling experience to a whole new level.
  2. Get acquainted with a Generative AI that is useful in your industry. For example Midjourney for generating images for email marketing.
  3. Discover how you can be productive with this technology. It is not a silver bullet, but you can instantly acquire an arsenal of skills.
  4. Build new habits so that you start feeling accustomed, connect the dots, and begin to improve your work until over-productivity.
  5. Think about how someone else using some AIs can replace you, then be that person: replace yourself with the new you, your augmented version.

Or simply ignore all of it, swallow the blue pill of comfort, and undergo the first “Great Upgrade”.

Eat your own dog food

I have been experimenting with OpenAI technologies since 2020 and used Google Dialogflow since 2018. I released my first chatbot, which answered regulatory questions about GPDR and PSD2. Developing with Natural Language Processing (NLP) was an eye-opener. I concluded chat provides the ultimate user experience for interacting with machines. It all sounds so obvious now, yet it was not back then despite all the buzz around Siri, Google, and Alexa.

I did the exercise of working within AI augmentation on my experiments since GPT-3 came out. Considering the hard skills, the conclusion is daunting: Generative AI can perform most of what I know and what I am mentally capable of. I can safely state I am outperformed in some areas.

In addition, AI is simply miles away in terms of depth of knowledge. Furthermore, it possesses infinitely better linguistic skills than mines when it comes to articulating ideas in languages other than French and English.

Yet the surprise comes from its ability to develop a simple idea and make it grow by putting words in concert. AI feels like the genius child of Humanity.

Words change the world

Generative AI comes with a new discipline: Prompt engineering. It consists in finding the right text, and the rights qualifiers that will narrate the desired output as close as you have imagined it.

For example, this prompt in Midjourney:

Prime Minister Xavier Bettel playing the finals of League of Legends world eSport championship at the Olympic games streaming on Twitch

generates the following picture:

AI has generated this photo

Ultimately, prompt engineering uses natural language as a modeling interface to command the “commendable world”. The more there are smart systems and devices, the more words animate the world!

The widespread innovative applications based upon Generative AI marks the end of the road for this generation and the beginning of a new breed of workers and creators.

Yet, another finding is that we still need a “general assembly semantic”. It would choreograph a fuzzy set of ideas that will accurately animate the world based upon a well-written thought.

The assembly process, which can be summarized into the loop “decomposition-planning-action-correction”, will likely open the door to Artificial General Intelligence (AGI). Coupled with the widespread natural language programming interfaces (NPI), this is the real end game. In that matter, we are already observing some interesting experiments like AutoGPT as sparks of AGI.

Transitioning from the Digital Transformation to Digital Augmentation

Picture this familiar situation.

Your maturity in terms of digital adoption is high. You are developing a culture of digital awareness, offering mobile-first customer interaction, and your brand is fighting for its visibility on social media. You have the feeling of doing great.

Congratulations.

Yet, the market atmosphere is heavy. You feel the pressure every week goes by. The competition is fierce, you are still looking for an army of IT engineers and data analysts for the last six months. Furthermore, customers get pickier because the offering is abundant. Your analytics tell you a client can switch in the blink of an eye if your experience does not meet his rising standards. Then, just when you thought you nailed it with your latest Instagram reels, it receives negative feedback. Even worst, there is a relentless wave of new product offerings mimicking yours. These startups and VCs are constantly trying to uncover the mythical unicorn while pushing your visibility back to Google’s page 2. And you feel this moment when your industry will be shackled, disrupted, or crippled may happen at any moment.

Who would have thought even Google’s dominance would be threatened?

Fortunately, there is a nascent vision. Transformation is not enough anymore. If you cannot obtain more skilled people now, why not acquire more skills for your people now?

AI is the key to unleashing your talents.

And, slowly, Augmented Work is the evolution of work, as we know it, characterized by these two elements:

  • A human is the sole team leader of his digital workers: he has the Applications, Automatas, and specialized A.I. models for numerous parts of your job, such as programming, translation, video editing, illustration, design, and planning.
  • Teams, as we know, will still exist, obviously, but augmented by AI also at the team level. The team has the opportunity to exist as an independent entity either in the company AI or as a single team companion if you need explicit segregation of duty. The “team spirit” has a whole new meaning with AI.
Evolution of the flow of work using AI, by Yannick HUCHARD

The flow of work evolves toward:

A. Human generates instructions using prompt engineering as explicit command requirements. The prompt is actually the evolution of the Command Line Interface (CLI), for a much greater general purpose.

B. AI generates a first draft

C. Human amend the sketch with input and then detail with new commands

D. Once the AI-driven engineering cycles are good enough for release change into the real world, you ship it for user acceptance or production if the risk is low.

  • The interaction with the AI becomes talkative. Either by chat or voice. AI is your new colleague.
  • AI starts having digital bodies, existing in a form of familiar avatars, and will be in multiple places: in your phones, your mixed reality glasses, in your Metaverse. Avatars could be Non-Player Characters (NPC), digitized versions of yourself, or even the retired expert that used to be your mentor.

So, am I going to be replaced by Artificial Intelligence?

You vs AI: you (still) have the upper hand

Here is a bet: 80% of white collars will keep their job. 20% of us will either refuse to learn these new tools to evolve either because of our fear of overwhelming technological advancement, or of conviction. Eventually, this minority will rush toward retirement and use these AI-powered services anyway to buy recommended stuff on Amazon after having been oriented by Google Bard from Google Search.

Why do I think that way? Because if we can produce much more with the same number of people, why would we deliver the same amount of products with fewer people?

Let’s take the example of Apple. The company entered the AI game in 2017 by introducing Core ML, an on-device AI framework embedded in iOS. The same year, it released the first generation of Apple Neural Engine (ANE) under the iPhone X with the A11 CPU.

Apple’s immeasurable impact comes from its ability to create and materialize an idea that is at the intersection of beauty, function, storytelling, and branding. Do you think Apple will push its culture of product excellence with the same amount of people amplified by a myriad of AI models, or will the company prefer reducing its workforce by leveraging more AI?

Pause for a second and think about it.

The other side of the coin

Taking the employer perspective in the era of AI Augmentation: what constitutes the difference between you and another candidate?

Any individual having a team of AI has the upper hand as he or she will be digitally augmented with skills and experience that usually takes years to acquire. What remains to develop are the skills to get used to these new abilities and use them at their best like an orchestra’s conductor.

You become the manager of AI teammates.

Hence, from the employer’s perspective, it results in hiring a virtual team vs an individual.

It raises the responsibility of Managers and the Human Resources department in the whole equation. Colleagues require to be upskilled to stay ahead, not only for the sake of the company but also to help them to keep building their personal value with respect to the market. Thus, leaders and HR have to set things in motion by organizing the next steps, while their own jobs are being reshaped and augmented…

Unlock the Future of Office Jobs Now

First, let’s admit once and for all you cannot win a 1 on 1 battle against AI, as much as you cannot win a nailing contest against a hammer.

The battle is long lost.

The battle doesn’t even make sense.

Because AI is the cumulative result of all humans’ knowledge, born from successful and failed experiments. To put it another way, as a sole individual, you cannot win against all of us and our ancestors combined!

And this is the incorrect mindset.

Hence, you will want to construct the future, your future, with all of us and our ancestors combined! You only need to be aware the future will be vastly different, and you should be part of the solution rather than engineering your problems.

AI is here to stay.

The questions to ask from now are:

  1. Are we all going to benefit from it?
  2. What portion of handcrafting do we want to keep?
  3. How much evil is going to benefit from it?
  4. How long until we get robots as widespread as vacuum cleaners?
  5. When are we going to find truly sustainable and clean energy? (no, batteries are not sustainable)

The key is here and now: you need to invest in algorithmic and analytical skills to translate activities to algorithms in order to be augmentable.

Next, the winning companies and communities will be the ones tapping into their people’s intelligence combined with creativity augmented by AI, the physical resources to change the world, and their abilities to satisfy needs within an enjoyable experience while maintaining a transparent and engaging conversation.

The gap between “good” and “best” will be even smaller between businesses, but the proposed experience and the branding will have a tremendous impact. Then, consistency and coherence in how you serve the customer and engage with your fans will act as compound interests. This is how you win the perpetual game.

The term community inherits a new meaning given the free aspect of AI. You are not even needing to build companies to achieve your goals: you only need an organization that plans and organizes the agreed work, like in Open Source Communities and Decentralized Autonomous Organizations (DAO).

Hence, I encourage you to build an A.I. readiness.

How to be A.I. ready?

Here are my recommendations to get started as an individual, especially if you are a leader in a company:

  1. “Socialize” with Generative AI applications useful to your job.
  2. Know your data and data systems to identify candidates for augmentation.
  3. Have “good” data. Good = true + meaningful + contextualized + accessible. As such, information must be stored in a secured and accessible location. Fortunately, Large Language Models are unstructured data friendly.
  4. Have technologists that can pioneer lateral ideas. I recommend hands-on architects.
  5. Assess and promote simple ideas on a regular basis, and establish an AI-dedicated project portfolio pipeline.
  6. Select and run a set of competent AI in a fully autonomous fashion

You can find a complete list of AI services at FutureTools.io and ThereIsAnAIForThat.com.

Less is not always more.

Less is more until you reach the “optimal zone”, an inflection point that represents the optimal balance between effort, cost, and result. Exponentiality occurs when for minimal effort and expenses, you achieve unprecedented results.

The critical factor is this natural law: everything is born from need, will be driven by purpose, feeds on energy, is protected by self-preservation, and evolves to maturity.

Thus, until AI is not given the aforementioned five elements at the same time, then, its digital self-preservation is never programmed to be mutually exclusive with the preservation of living beings, and finally, AI self-evolution stays within boundaries, then AI growth will not be at the expense of humanity. Under these circumstances, humans can remain the dominating species.

As a consequence, one must consider what gives birth to a “trigger”: this initial impulsion taking the form of an idea that results in action delivered by willpower from the mind’s womb. Until then, an AI will not willingly use another AI, automaton, or application because it needs to, but because it has been commanded or programmed by us.

Until then, we are safe.

We are… Fine… Aren’t we?

This is not the right question

The right question is what is going to change for me?

Earlier I said, “It depends on your ability to adapt by learning a practice that is new for everyone”.

The long answer starts with a twist: the groups of humans producing AI and the others using AI as elements of augmentation and amplification of their skills will have an exponential upper hand because they can fulfill needs faster, optimally, and accurately at the cost of… just… time.

For example, building the next Instagram will depend on someone having:

  • The willpower
  • A distinguishingly desirable idea
  • A series of creative ideas
  • The skills
  • The drive to sell, communicate and promote their ideas to clients.
  • The resilience to continue developing the ideas

We can conclude that what consistently makes the difference are: the idea, the drive, the skills, the way user experience answers the client’s needs, and the resources you can obtain to make things happen.

But if ideas are cheap and abundant, and should cognitive skills can be acquired using virtually free AI Augmentation, then the remaining differentiators are the drive, the user experience, and the resources.

Thus, the Intellectual Property of a company becomes its Cognitive Know-how. Suddenly, high-value assets are the doers displaying high and consistent motivation, leaders that not only keep the Pole Star lighten but are able to keep their teamates inspired: the creative people, and the group of people having the capacity to invest and evolve in the same direction around the same flag: their brand, which I consider to be the result of maintaining a homogeneous identity of the combined people and products.

Graal or Pandora?

This new technology raises thousands of questions.

The development of Generative AI technology has opened up a vast array of possibilities, but it has also raised thousands of questions that need to be addressed.

For instance, one major question is how Generative AI will change our day-to-day interactions.

Furthermore, there is concern about whether this technology could lead to mass unemployment and economic inequality.

Another potential consequence is that it might devalue human creativity and originality.

Additionally, it is important to explore how Generative AI might impact human cognition and decision-making.

In terms of IT Engineering and Architecture, what is the impact of AI on these fields, and how will they adapt to this new technology?

Education is another area that could be significantly impacted, and it is worth considering how Generative AI might affect traditional learning methods.

Moreover, there is a concern that Generative AI could create a world in which we cannot distinguish between what is real and what is artificial. If this were to happen, what are the ethical implications?

Finally, the implications of Generative AI for democracy and governance are also important to consider, particularly with regard to its development and regulation.

Overall, the development of Generative AI technology raises many questions needing collaborative wisdom in order to fully prepare for its impacts on society.

I will attempt to answer these questions in upcoming articles of the “Navigating the Future with Generative AI” series.

Until then, if you are looking for the one thing to remember about this article: play with Generatice AI until it replaces just one activity of your daily routine, then boast your prompt engineering skills by spreading the word and educating your relatives.

🫡

Categories
Artificial Intelligence ChatGPT GPT3 GPT4 IT Architecture IT Engineering

API Hero 🤖” – The #GPT That Codes the API for You 🙌

APIs are key to scaling your #business within the global ecosystem. Moreover, your API is a fundamental building block for augmenting universally accessible #AI services, like ChatGPT.

Building an #API, however, can be daunting for non-IT individuals and junior engineers, as it involves complex concepts like API schema, selecting libraries, defining endpoints, and implementing authentication, among others.
On the other hand, for an expert backend #engineer, constructing your fiftieth API may feel repetitive.

That’s where “API Hero” comes in, specifically designed to address these challenges.

Consider an API for managing an “#Agile Planning Poker”. Given a list of functions in plain English, such as “Create Planning Poker”, “Add Participants”, “Estimate User Story”, etc., (including AI-suggested ones), the GPT will generate:

  1. The public interface of the API (for engineers, this corresponds to the OpenAPI/Swagger spec).
  2. #Code in the chosen #programming language, with a focus on modularity and GIT-friendly project structure.
  3. Features like API security, configuration management, and log management.
  4. An option to download the complete code package (no more copy-pasting needed 💪).

And there’s more!

Search for “API Hero 🤖| AMASE.io” on #ChatGPT’s GPT store. Give it a try and send your feedback for further improvement.

By the way:

  1. Currently, GPTs are accessible only to ChatGPT Plus users.
  2. If you want to know more about the decisive nature of API for your business, check my article/podcast “Why API are Fundamental to your Business”.

Link to the GPT: https://chat.openai.com/g/g-a5yLRJA1J-api-hero-amase-io

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Categories
AR/VR Artificial Intelligence Autonomous Agents Bioengineering Drone Fleet Management Hologram Holographic Display In 2060 Information Technology Storytelling Technology Transportation Drone Writing

Bioengineering in 2060

“Nasir, check this out. Didn’t I tell you PSG would win against New Manchester? Two bitcoins, baby. Who is the soccer king?”

“Stop bragging, man. Gee, I don’t know how you do it. Hey, Betmania, tell me how this regular human with his XXL ears looking like satellite dishes can beat your prediction. Thank God, you were a freebie AI.”

The bet bot replied, “I am not qualified to review Dr Anoli’s performances. Yet, his 97.26% accuracy is…”

Nasir interrupted the hologram: “Ahh, shut it! It was a rhetorical question. My man! You are good, you gooood.”

He lifted his hand, nodding repetitively to perform his most vigorous handshake.

The upper deck lit up like a lighthouse, and then a deafening sound followed the illumination.
Beeeeeepp. “Emergency. Purple alert. All medical engineers on deck. I repeat, Purple Alert. All medical engineers on deck. This is not a drill.”

My heart was pounding. The message was still resonating in my head.

The sudden drop in temperature, produced by the arch-reactor of the medical drone transporter, announced the arrival of an unusual patient. This is the first time I have seen a flying one. Usually, these vehicles were stored in the Corps of Peacekeepers‘ R&D facilities.

The temperature drop caused a fog to rise like a curtain. I saw a blurry figure approaching slowly.

My colleague interrupted my stupor: “I haven’t seen a purple alert for 7 years now, it’s serious. Purple means death.”

The flying ambulance emerged at the heliport located at the center of the critical emergency service. Work is pretty easy on platform seventeen, actually. Nowadays, bioengineering is solving almost all critical injuries as they occur. An accident at a construction site? Any multifunction robot worker medic cauterizes your wound with accelerated healing enzymes, bypassing block surgery. As long as you’ve subscribed to the right medical service, the AI health model can be downloaded, and the tier two healing kit purchased for printing.

“What on earth could have happened?”, exclaimed Nasir.

The hologram of the AI diagnostician, Dr. Ernesto, popped up from the ambient hospital Phygital network while the paramedics were transporting the patient out of the medical drone transporter. Then, she said:

“This is unprecedented, we are losing it. We’ve tried traditional medicine and printed the generic assistance bacteria. Nothing works. The patient’s vitals fluctuate over time at an unconventional rate. Scanning the available knowledge from the current corpus does not provide any satisfying answers. The highest probable disease is the Genova IV virus with a probability of 31%”.

I replied “Too much uncertainty… What do you suggest, Nasir?”

“It looks like the emerging meta-virus. The… guy on B-Hacker YouTube Entertainment System… Sorry, I can’t remember the name of that journalist… said it was an open-source public CASPRed experiment.”

I could not believe it at first. But when I saw his wound mutating in front of me, there was no doubt that the potential disease was human-made.

“Arrrghhhhh. It burns… Please get it off me. I am begging you. Just cut it!” shouted the patient.

I was stunned. I cannot remember the last time I saw a real person suffering that much. Dr. Krovariv told me about it. This was surreal. So much pain.

“Hey! Gather yourself, buddy. There’s no time to waste. We might be facing a level 5 threat here,” said Nasir.

He was such a great guy. He was the embodiment of coolness. Not only was he a great bioengineer, but he always kept his cool on the field. I was more of a lab genius. I wish I could be more like him.

“Huh, yeah. Sorry, I froze,” I said with a coating of stupor, disappointment, and anger. I continued without hesitation, “What’s the status?”

While he was unplugging the portable bio-scanner from the trembling body, Nasir replied: “Body temperature 39.9. Heartbeats – 137. Adrenaline level 50.5. Oxygen level 92.12%. Stress level is increasing by 2.4% per minute. If we don’t act quickly, he is going to have a seizure. The stem cell differentiation rate… 272%! This is too high. It looks like he is growing a supernumerary limb, but I don’t know what kind.”

“Pick up the nano-extractors and verify traces of xeno-mRNA.”
It was a Sanofi Nano-extractors SNX43, a state-of-the-art fleet of nano-medical machines with a portable management system. Current extractors were all managed centrally by the hospital drone intervention unit.

I quickly put my face next to the patient’s ear and asked, “Sir, I am going to need your authorization to perform an intracellular analysis. We don’t know what you have, this might be your last chance…”

He grabbed my head and screamed, “What the hell are you asking for? Do it! Arghhhh!”

I felt foolish. Yet, there was no way I could bypass the authorization because the device had a legal lock encoded in it.

“That will do,” I whispered. The nano-extractors became operational, switching from blue ‘stand by’ to green ‘proceed.’ The extractors looked like a stick, no longer than a large pen. I placed it next to the wound, and it opened, deploying four branches on each side, and anchoring onto his skin. I heard a sequence of small noises, like pistons. The extractor fleet deployed into his body.

Then a ballet of lights came up. The SNX43 beamed a 3D representation of the arm’s inner part. The system rendered the location of the fleet in real-time.

They moved surprisingly slowly. I was disappointed. I was used to contemplating much livelier robots with the previous version.

Nasir said deductively: “There’s something wrong. They appear to be sucked in or blocked. Zoom in, Nicolas”.

I pinched out the holo-display to enter the zoom command and tapped on the max button. The illusion of slowness came from the fact that the machines were moving at such a speed that it was hard to follow with the naked eye. They looked like bees on steroids, fighting a wall of flesh. But the alien cells rebuilt the wall as soon as it was destroyed.

“I get it; the cellular growth must be faster than the robots can clear the path. It is not good. Not good at all.”

“Have you ever seen something like this before?”

“No…” said Nasir. It was the first time I saw fear in his eyes.

Then he jumped. “It could be contagious. I want all containment units on the platform now. I request a total lockdown of platform seventeen. Now!”

Nasir stopped, then looked at me insistently. I immediately thought something was happening to me.

Then, Nasir froze and fell to the ground.

I jumped immediately to grab him, but something inside me pulled back. My bioengineer spinal safety device prevented me from approaching the new pathogens. Whenever it triggered, it reminded me of the auto-braking mechanisms in my grandparents’ cars. I do not like the idea of having a machine tweaking my neural system. Yet, once more, it saved my life.

“This is not the time,” I whispered. I looked at the sky and said, “Dr. Ernesto. Launch orbital containment in ten. Authorization Kappa-Sigma-Omega-1337.”

Dr. Ernesto answered, “Authorization confirmed. Launching orbital containment in 10, 9, 8…”

“Meanwhile, call the World Health Emergency.”

“Opening channel.”

The dial ended almost instantly.

“Dr. Anoli, this is Dr. Krovariv – replica number 3. State the nature of your emergency.”

“I need to speak to the real Dr. Krovariv. This is a purple priority request.”

“Accepted. Please stand by…”

Time stood still while the platform was flying to space. The quietness of linear magnetic propulsion was staggering. My god. Is Nasir going to make it?

“The patient! I am a monst…”

“Dr. Anoli. What is it about?” Her question interrupted my thoughts.

“Dr. Krovariv. I am sorry, but Nasir has been contaminated by an unknown biological agent. I am heading toward space containment. Furthermore, the patient at the source of the contamination is dying. This agent is too dangerous. Please advise on the protocol,” I finished with a frail voice.

“In this situation, the protocols are clear. Once in space containment, you may use the ‘yellow horizon’ protocol. But you know what will happen if it fails.”

“Yes… I know.”

“I am sorry, son. Since CASPR got open-sourced, we are overwhelmed by these idiots… I am waiting for your decision.”

I had a deep look at Nasir. I knew it would probably be the last time I would see him. It was probably the last time I would see anything else.
I exhaled loudly and said, “Permission to print a new species as a countermeasure.”

“Permission granted. Good luck.”

Asking was the easy part. I was her protégé.

As I was climbing space, the platform changed its path toward a new direction. The Athena Life Engineering Lab, or ALEL, was lighting up like a giant light bulb. It was my dream to one day be worthy of visiting the lab. It was proclaimed as a symbol of hope. But not like this. Not on the verge of my very own death.

ALEL was the only accredited location where humans were allowed to engineer and print new life forms. No one was allowed to penetrate the labs.
Akin to the Athena Orbital Data Centre, it was solely operated by robots and machines following a strict chain of command.

Soon after, the platform slowed down, then stopped near the lab, and the docking system engaged to secure the system. A muffled noise gave me the chills.

“Welcome, Dr. Anoli. My name is Marie Curie. You have been granted the usage of the Athena Life Engineering System by Archdoctor Krovariv of the World Health Organization on the date of 30th December 2060. Any inquiry going against the principles of life and Human Civil Rights will result in your immediate termination. Do you want to hear these principles?”

“No, thank you. I already vowed to fight for life when I became a biomedical engineer.”

“Understood. Please state your prompt, please.”

I thought to myself, “What? Just like that?”

“Marie Curie, I need you to engineer a biological agent to counter Dr. Nasir’s condition. Focus uniquely on alien gene alteration and accelerated growth features. Do not augment the agent with inorganic material. Do not add metamorphic adaptation capabilities. Encode the maximum life duration to be 72 hours. Add automatic degeneration from 70 hours as a failsafe mechanism. No reproduction. No replication. I need you to confirm the supernumerary growth first before proceeding.”

“Supernumerary growth confirmed. Your prompt is acceptable. Proceeding to the registration of the new specimen identified by Anoli-alpha-31122060-001. Beginning prototyping phase.”

As I reached the point of no return, I could not help but wonder if our life would end here. ALEL was a universal robotic womb. What would happen if I asked the Life Factory to… recreate Nasir… Is rebirth possible?


In 2060

Categories
AR/VR Artificial Intelligence Information Technology Technology

Apple wants to HUGS you

Apple unveiled an innovative #AI method for creating animated human avatars in #3D from real humans named #HUGS.

The technique means Human Gaussian Splats
It uses 3D Gaussian Splatting (= reconstruction from multiple points of view).

The features are:
🔹Recreates human avatars in 3D from video and scenes.
🔹Separates humans from static scenes in videos.
🔹Use the SMPL body model for human representation. SMPL = Skinned Multi-Person Linear Model. In essence, it is a way to render a realistic 3D model of the human body
🔹Generates animations
🔹Achieves high rendering quality at 60 FPS.

Why does this publication matter?

First, it is a clear signal that Apple is also in the AI models race.

Then, interestingly, Apple announced the Vision Pro on the 5th of June 2023, with the promise to provide a #Metaverse experience never seen before.

With HUGS, Apple pushes a foundational building block for making the #AR/#VR experience feel more like real life: the dematerialization of your avatar to increase the sentiment of intimacy and immersion.

Also, it pushes further the seamless continuum from digital to physical and vice-versa. It makes the #Phygital Experience.
Digitally generated media is essential to the future of the “Metaverse”.

Links: https://machinelearning.apple.com/research/hugs

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Categories
Artificial Intelligence Automation Autonomous Agents ChatGPT GPT4 Information Technology IT Architecture IT Engineering Robots Technology Testing

Navigating the Future with Generative AI: Part 2, Prompt Over Code – The New Face of Coding

In this installment of the Generative AI series, we delve into the concept of “Prompt as new Source Code”. The ongoing revolution of generative AI allows one to amplify one’s task productivity by up to 30 times, depending on the nature of the tasks at hand. This transformation allows me to turn my design into code, eliminating almost the need for manual coding. The time spent typing, correcting typos, optimizing algorithms, and searching Stack Overflow to decipher perplexing errors, structuring the code hierarchy, and bypassing class deprecation among other tasks, are now compressed into one. This minimization of effort provides me with recurrent morale boosts, as I achieve significantly more in less time and more frequently; these instances are micro-productivity periods. To put it in perspective, I can simply think about it during the day, and have a series of conversations with my assistant while I commute. My assistant is always available. In addition, I gain focus time.

I don’t need to wait for a team to prove my concept. Furthermore, in my founder role, I have fewer occasions to write extensive requirement documents than I would when outsourcing developments during periods of parallelization. I just need to specify the guidelines once, and the AI works out the rest for me. Leveraging the  AMASE methodology to fine-tune my AI assistant epitomizes the return on investment of my expertise. Similarly, your expertise, paired with AI, becomes a powerful asset, exponentially amplifying the return on your efforts.

Today, information technology engineering is going through a quantum leap. We will explore how structured coding is being replaced by natural language. We refer to this as prompting, which essentially denotes “well-architected and elaborated thoughts”. Prompting, so to speak, is the crystallization of something that aims to minimize the loss of information and cast-out interpretation. In this vein, “What You Read is What You Thought” becomes a tangible reality.

The Unconventional Coding Experience with AI

Although the development cycle typically commences with the design phase, this aspect will not be discussed in this article. Our focus will be directed towards the coding phase instead.

The development cycle with AI is slightly different; it resembles pair programming. Programming typically involves cycles of coding and reviews, where the code is gradually improved with each iteration. An artificial intelligence model becomes your coding partner, able to code 95% of your ideas.

In essence, AI acts as a coach and a typewriter, an expert programmer with production-level knowledge of engineering. The question may arise: “Could the AI replace me completely? What is my added value as a human?”

Forming NanoTeams: Your AI Squad Awaits

My experience leads me to conclude that working with AI is akin to integrating a new teammate. This teammate will follow your instructions exactly, so clarity is essential. If you want feedback or improvements in areas like internal security or design patterns, you must communicate these desires and potentially teach the AI how to execute them.

You will need to learn to command your digital teammate.

Each AI model operates in a distinct yet somewhat similar fashion when it comes to command execution. For instance, leveraging ChatGPT to its fullest potential can be achieved through impersonations, custom instructions, and plugins. On the other hand, Midjourney excels when engaged with a moderate level of descriptiveness and a good understanding of parameter tweaking.

A New Abstraction Layer Above Coding

What exactly is coding? In essence, coding is the act of instructing a machine to perform tasks exactly as directed. The way we’ve built programming languages is to ensure they are idempotent, repeatable, reliable, and predictable. Ultimately, coding is translated into machine language, creating a version that closely resembles human language. This is evident in modern languages like TypeScript, C#, Python, and Kotlin, where instructions or controlling statements are written in plain English, such as “for each”, “while”, “switch”, etc.

With the advent of AI, we can now streamline the stage of translating our requirements into an algorithm, and then into programming code, including structuring what will ultimately be compiled to run the program. Traditionally, we organize files to ensure the code is maintainable by a human. But what if humans no longer needed to interact with the code? What if, with each iteration, AI is the one updating the code? Do we still need to organize the code in an opinionated manner, akin to a book’s table of contents, for maintainability? Or do we merely need the code to be correctly documented for human understanding, enabling engineers to update it without causing any disruptions? Indeed, AI can also fortify the code and certify it using test cases automatically, ensuring the code does not contain regressions and complies with the requirements and expected outcomes.

To expand on this, AI can generate tests, whether they be unit tests, functional tests, or performance tests. It can also create documentation, system design assets, and infrastructure design. Given that it’s all driven by a large language model, we can code the infrastructure and generate code for “Infrastructure as Code“, extending to automated deployment in CI/CD pipelines.

To conclude this paragraph, referring to my first article in the “Generative AI series”, it is apparent that Natural Language Processing is now the new programming language expressed as prompts. The Large Language Model-based generative AI model is the essential piece of software for elaborating, structuring, and completing the input text into code that can be understood both by human engineers and digital engineers.

The New Coding Paradigm

This fresh paradigm shift heralds the advent of a new form of coding—augmented coding. Augmented coding diminishes the necessity of writing code using third and fourth-generation languages, effectively condensing two activities into one.

In this scenario, the engineer seldom intervenes in the code. There may be instances where the AI generates obsolete or buggy code, but these can often be rectified promptly in the subsequent iteration.

We currently operate in an explicit coding environment, where the input code yields the visible result on the output—this is known as Input/Output coding.

The profound shift in mindset now is that the output defines the input code. To elucidate, we first articulate how the system should behave, its structure, and the rules it must adhere to. Essentially, AI has catapulted engineers across an innovation chasm, ushering in the era of Output/Input coding.

Embracing Augmented Coding: A Shift in Engineering Dynamics

The advent of augmented coding ushers in a new workflow, enhancing the synergy between engineers and AI. Below are the core aspects of this transformation:

  1. Idea Expression: The augmented engineer is impelled to express ideas and goals to achieve.
  2. Requirement Listing: The engineer lists the requirements.
  3. Requirement Clarification: Clarify the requirements with AI.
  4. Architecture Decisions: Express the architecture decisions (including technology to use, security compliance, information risk compliance, regulatory technical standards compliance, etc.) independently, and utilize AI to select new ones.
  5. Coding Guidelines: Declare the coding guidelines independently and sometimes consult the AI.
  6. Business Logic: Define the business logic in the form of algorithms to code.
  7. Code Validation: Run the code to validate it works as intended. This becomes the first order of acceptance tests.
  8. Code Review: assess the code to ensure it complies with the engineering guidelines adopted by the company.
  9. Synthetic Data Generation: Use AI to generate data sets that are functionally relevant for a given scenario and a persona.
  10. Mockup-API Generation: Employ AI to generate API stubs that are nearly functionally complete before their full implementation.
  11. Test Scenario Listing: Design the different test scenarios, then consult stakeholders to gather feedback and review their completeness.
  12. Test Case Generation: Make AI to generate the code of test cases. The same technique applies to security tests and performance tests.

AI can even operate in an autonomous mode to perform a part of the acceptance tests, but human intervention is mandatory at certain junctures. It’s crucial to bridge results with expectations.

Hence, when uncertainties arise, increasing the level of testing is prudent, akin to taking accountability upon acceptance tests to ensure the delivered work aligns with the expected level of compliance regarding the requirements.

Non-Negotiable Expectations

In the realm of critical business rules and non-functional requirements such as security, availability, accessibility, and compliance by design, these aspects are often considered second-class citizen features. Now that AI in coding facilitates the choice, these features can simply be activated by including them in your prompts to free you up more time to rigorously test their efficiency.

Certain requirements are tethered to industry rules and standards, indispensable for ensuring individual or collective safety in sectors like healthcare, aviation, automotive, or banking. The aim is not merely to test but to substantiate consistent performance. This underscores the need for a new breed of capabilities: Explainable AI and Verifiable AI. Reproducibility and consistency are imperative. However, in a system that evolves, attaining these might be challenging. Hence, in both traditional coding and a-coding, establishing a compliance control framework is essential to validate the system’s functionality against expected benchmarks.

To ease the process for you and your teams, consider breaking down the work into smaller, manageable chunks to expedite delivery—a practice akin to slicing a cake into easily consumable pieces to avoid indigestion. Herein, the role of an Architect remains crucial.

Yet, I ponder how long it will be before AI starts shouldering a significant portion of the tasks typically handled by an Architect.

Ultimately, the onus is on you to ensure everything is in order. At the end of the day, AI serves as a collaborative teammate, not a replacement.

Is AI Coding the Future of Coding?

The maxim “And is greater than or” resonates well when reflecting on the exponential growth of generative AI models, the burgeoning number of published research papers, and the observed productivity advantages over traditional coding. I discern that augmented coding is destined to be a predominant facet in the future landscape of information technology engineering.

Large Language Models, also known as LLMs, are already heralding a modern rendition of coding. The integration of AI in platforms like Android Studio or GitHub Copilot exemplifies this shift. Coding is now turbocharged, akin to transitioning from a conventional bicycle to an electric-powered one.

However, the realm of generative AI exhibits a limitation when it comes to pure invention. The term ‘invention’ here excludes ideas birthed from novel combinations of existing concepts. I am alluding to the genesis of truly nonexistent notions. It’s in this space that engineers are anticipated to contribute new code, for instance, in crafting new drivers for emerging hardware or devising new programming languages (likely domain-specific languages).

Furthermore, the quality of the generated code is often tethered to the richness of the training dataset. For instance, SwiftUI or Rust coding may encounter challenges owing to the scarcity of material on StackOverflow and the nascent stage of these languages. LLMs could be stymied by the evolution of code, like the introduction of new keywords in a programming language.

Nonetheless, if it can be written, it can be taught, and hence, it can be generated. A remedy to this quandary is to upload the latest changes in a prompt or a file, as exemplified by platforms like claude.ai and GPT Code Interpreter. Voilà, you’ve just upgraded your AI code assistant.

Lastly, the joy of coding—its essence as a form of creative expression—is something that resonates with many. The allure of competitive coding also hints at an exciting facet of the future.

Short-Term Transition: Embracing the Balance of Hybrid A-Coding

The initial step involves exploring and then embracing Generative AI embedded within your Integrated Development Environment (IDE). These tools serve as immediate and obvious accelerators, surpassing the capabilities of features like Intellisense. However, adapting to the proactive code generation while you type, whether it’s function implementation, loops, or SQL code, can hasten both typing and logic formulation.

Before the advent of ChatGPT or GPT-4, I used Tabnine, whose free version was astonishingly effective, adding value to daily coding routines. Now, we have options like GitHub Copilot or StableCode. Google took a clever step by directly embedding the AI model into the Android Studio Editor for Android app development. I invite you to delve into Studio Bot for more details on this integration.

Beware of Caveats During Your Short-Term Transition to Generative AI

Token Limits

Presently, coding with AI comes with limitations due to the number of input/output token generation. A token is essentially a chunk of text—either a whole word or a fragment—that the AI model can understand and analyze. This process, known as tokenization, varies between different AI models.

I view this limitation as temporary. Papers are emerging that push the token count to 1M tokens (see Scaling Transformer to 1M tokens and beyond with RMT). For instance, Claude.ai, by Anthropic, can handle 100k tokens. Fancy generating a full application documentation in one go?

Model Obsolescence

Another concern is the inherent obsolescence of the older data on which these models are trained. For example, OpenAI’s models use data up to 2022, rendering any development post that date unknown to the AI. You can mitigate this limitation by providing recent context or extending the AI model through fine-tuning.

Source Code Structure

Furthermore, Generative AI models do not directly consider folder structures, which are foundational to any coding project.

Imagine, as an engineer, interacting with a chatbot crafted for coding, where natural language could reference any file in your project. You code from a high-level perspective, while the AI handles your GIT commands, manages your gitignore file, and more.

Aider exemplifies this type of Gen AI application, serving as an ergonomic overlay in your development environment. Instead of coding in JavaScript, HTML, and CSS with React components served by a Python API using WebSocket, you simply instruct Aider to create or edit the source code with functional instructions in natural language. It takes care of the rest, considering the multiple structures and the GIT environment. This developer experience is profoundly familiar to engineers. The leverage of a Command Line Interface – or CLI, amplifies your capabilities tenfold.

Intellectual Property Concerns

Lastly, the risk of intellectual property loss and code leakage looms, especially when your code is shared with an “AI Model as a Service”, particularly if the system employs Reinforcement Learning with Human Feedback (RLHF). Companies like OpenAI are transparent about usage and how it serves in enhancing models or crafting custom models (e.g. InstructGPT). Therefore, AI Coding Models should also undergo risk assessments.

The Next Frontier: Codeless AI and the Emergence of Autonomous Agents

Names like GPT Engineer, AutoGPT, BabyAGI, and MetaGPT herald a new branch in augmented coding: the era of auto-coding.

These agents require only a minimal set of requirements and autonomously devise a plan along with a coding strategy to achieve your goal. They emulate human intelligence, either possessing the know-how or seeking necessary information online from official data sources, libraries to import, methods, and so on.

However, unless the task is relatively simple, these agents often falter on complex projects. Despite this, they already show significant promise.

They paint a picture of a future where, for a large part of our existing activities, coding may no longer be a necessity.

Hence, the prompt is the new code

If the code can be generated based on highly specific and clear specifications, then the next logical step is to consider your prompt as your new source code.

It means you can start storing your specifications instructions, expressed as prompt, then store the prompt in GIT.

CD/CC with Adversarial AI Agent
Continuous Development/Continuous Certification (CD/CC) with Adversarial AI Agent

Suddenly, Continuous Integration/Continuous Delivery (CI/CD) becomes Continuous Development/Continuous Certification (CD/CC), where the prompt enables the development of working pieces of software, which will be continuously certified by a testing agent working in adversarial mode: you continuously prove that it works as intended.

The good thing is that benefits stack up: the human specify, the AI code/deploy and the AI certify, to finish with the human using the results of the materialization of its thoughts. Finally, the AI learns along with human usage. We close the loop.

Integrating New Technology into Traditional Operating Models

AI introduces a seamless augmentation, employing the most natural form of communication—natural language, encompassing the most popular languages on Earth. It stands as the first-of-its-kind metamorphic software building block.

However, the operating model with AI isn’t novel. A generative AI model acts as an assistant, akin to a new hire, fitting seamlessly into an existing team. The workflow initiates with a stakeholder providing business requirements, while you, the lead engineer, guide the assistant engineer (i.e. your AI model) to execute the development at a rapid pace.

Alternatively, a suite of AI interactions, with the AI assuming various roles, like dev engineer, ops engineer, functional analyst, etc. can form your team. This interaction model entails externalizing the development service from the IT organization. Here, stakeholders still liaise through you, as lead engineer or architect, but you refine the specifications to the level of a fixed-price project. Once finalized, the development is entirely handed over to an autonomous agent. This scenario aligns with insourcing when the AI model is in-house, or outsourcing if the AI model is sourced as a Service, with the GPT-4 API evolving into a development service from a Third-Party Provider like OpenAI.

AI infuses innovation into a traditional model, offering stellar cost efficiency. Currently, OpenAI’s pricing for GPT-4 stands at $0.06 per 1000 input tokens and $0.12 per 1000 output tokens. Just considering code generation (excluding shifting deadlines, staffing activities, team communication, writing tasks, etc.), for 100,000 lines of code with an average of 100 tokens per line (which is extensive for standard leet code), the cost calculation is straightforward:

100,000 × 100 = 10,000,000 tokens; (10,000,000 tokens × $0.12) ÷ 1000 = $1,200. This cost equates to a mere two days of development at standard rates.

For perspective, Minecraft comprises approximately 600,000 lines of Java code. Theoretically, you could generate a Minecraft-like project for less than $10,000, including the costs of input tokens.

However, this logic is simplistic. In reality, autonomous agents undergo several iterations and corrections before devising a plan and rectifying numerous errors. The quality of your requirements directly impacts the accuracy of the generated code. Hence, mastering the art of precise and unambiguous descriptive writing becomes an indispensable skill in this new realm.

Wrap up

Now, you stand on the precipice of a new coding paradigm where design, algorithms, and prompting become your tools of creation, shaping a future yet to be fully understood…

This transformation sparks profound questions: How will generative AI and autonomous agents reshape the job market? Will educational institutions adapt to this augmented coding era? Is there a risk of losing the depth of engineering expertise we once relied upon?

And as we move forward, we can only wonder when quantum computing will introduce an era of instantaneous production, where words will have the power to change the world in real time.

🖖

Categories
Architecture Artificial Intelligence Blockchain Business Business Strategy Enterprise Architecture Organization Architecture Strategy Technology Technology Strategy

Architecting the Future: How RePEL Counters VUCA for Modern Enterprises

I was first introduced to the term VUCA by my colleague, Julian TROIAN, a leader in coaching who steers the talent management practice. This revelation came during a particularly challenging phase for us, mirroring the struggles of many other companies. We found ourselves navigating the intricacies of the COVID lockdown while simultaneously undergoing a significant shift in the corporate way of working. Our project portfolio was expanding, driven by the rapid pace of transformations, and we felt the weight of increasing regulatory pressures. But we recognized that these challenges were not ours alone. Then, significant disturbances emerged: the Eastern Europe conflict and a surge in inflation, to name a few.

Moreover, the world stood on the brink of simultaneous technological revolutions. Innovations like blockchain and the nascent promise of the metaverse hinted at new horizons. Yet, it was the seismic shifts brought on by Generative Artificial Intelligence that seemed most profound.

VUCA is an acronym encapsulating the themes of vulnerability, uncertainty, complexity, and ambiguity. Herbert Barber coined the term in 1992 based on the book “Leaders: The Strategies for Taking Charge”. I believe many can relate to these elements, sensing their presence in both professional settings—perhaps during office hours—and in personal moments with family.

Life, in its essence, might be described by this very term. We all traverse peaks and lows, facing situations of heightened complexity or vulnerability. The challenge is not just to navigate these periods but to foster strength and ingenuity, arming ourselves for future obstacles.

I consider myself fortunate to have garnered knowledge in enterprise architecture—a domain that inherently equips any organization, product, or service with resilience, making adaptability part of its very DNA.

In the subsequent sections, I explore strategies for developing VUCA antibodies.

From Vulnerability to Resilience: Building an Unshakable Future

Rather than getting bogged down by vulnerabilities, it’s about harnessing resilience. Robustness is the key to building thick layers of protection, ensuring longevity in our ventures. By deliberately creating anti-fragile mechanisms, we’re better prepared for tough times. This resilience doesn’t just happen; it’s constructed. Architects weave it into their designs across various realms:

  • Information Systems: These are designed to be failure resistant. Potential mistakes and erratic behaviors are predicted and integrated into the system as possible anomalies. In such events, responsible teams must give clear procedures to users, operators, and administrators to restore the system to its standard operational mode.
  • Data Management: From acquisition and processing to analytics and visualization, there’s complete control over the data flowing into the system. This range from a service request made over the phone, a command initiated by an AI, or even a tweet that prompts the system to respond.
  • Security: Safeguarding the system against potential hacks is crucial. Additionally, it’s vital to design the system in a way that vulnerabilities don’t open doors for intrusions. Depending on the chosen architectural delivery method, this can be addressed proactively or reactively.
  • Infrastructure: The foundational physical infrastructure, tailored to the system’s needs, must be aptly dimensioned. At times, specialized hardware like GPU-driven servers, or programmable network devices might be essential to cater to particular needs during both the development and operational phases.
  • Organization: People, integral to the corporate ecosystem, influence the system’s effectiveness. Their actions and behaviors enhance system efficiency, especially when elements like trust, making amends for failures, regular maintenance, and adaptability to change are activated.

All these aspects aren’t mere byproducts; they’re deliberately designed system features.

From Uncertainty to Probable Planning: Navigating with Confidence Through Uncertain Waters

Predicting the future is beyond anyone’s capability, but architects can narrow down scenarios to the most probable outcomes. Through modeling techniques like system design, trend analysis, scenario planning, and causal loops, they can forecast with a higher degree of accuracy. However, the planning phase isn’t without challenges:

  • Resources: There are times when constraints in time, finances, skills, and materials can make a proposed solution unfeasible. Recognizing this early on is vital.
  • Leadership: A wavering decision-maker, filled with doubt, can be a significant impediment. This is a leadership challenge that needs addressing at the top. In such a situation, the architect must highlight the unstable matter with benevolence and candor.
  • Team: The implementation is only as good as the team behind it. If team members don’t possess the necessary skills or their abilities don’t align with the mission’s complexity, especially when executing multiple plans simultaneously, it will compromise the execution of the plan.
  • Expertise: last but not least, the architect’s seniority and the time allocated to address your transformation’s VUCA elements also play a critical role.

From Complexity to Engineering: A Blueprint for Simplification

Sometimes, complexity arises from perception, misunderstanding, or underestimating a situation – often, it’s a mix of these elements.

Imagine you have three wooden chairs, and you wish to create a sofa. Is it even possible? Fortunately, Ikea offers a DIY toolbox that can help you realize this vision. When you describe your idea to the store specialist, she confidently directs you to aisles A8 to C12 for the necessary components. At first, you feel relief. But soon, doubts about your abilities confront you. Even with your experience in crafting wooden furniture, you’re unsure about the mechanisms you’ll need, the type of finish to choose, the tools required for precise cuts, and the best materials for durability. Are these materials environmentally friendly? This confusion and uncertainty are akin to experiencing VUCA.

The architect’s role is to first understand the complexity, determine the facts, and uncover what’s unknown, converting it to known information. Then, the challenge or problem is segmented into manageable pieces. I refer to this process as “Undesign.” The goal of undesigning is to get a clear and detailed view of the end goal by atomizing the current state, structure, and behavior. This is achieved through methods like decomposition, deconstruction, alternate system modeling, and sometimes reverse engineering. Subsequently, the architect uncovers a path to transform and assemble these components.

The essence of engineering is to assemble these components using identifiable, simple building blocks. These blocks are selected, modified, added, and connected in a logical order, ensuring the right materials, technologies, and tools are used. People with the right skills can then efficiently bring the project to life, ensuring it’s as seamless and enjoyable as possible. Even the user’s psychological experience matters!

In summary, what seems intricate and complex can be distilled into simpler, manageable parts.

From Ambiguity to Lucidity: Transitioning from Wishful Thinking to Tangible Outcomes

Architects don’t just exist in the present; they shape the future. Their responsibilities lie in meticulously designing and planning changes that will inevitably impact an organization’s products or services. Any vision, no matter how abstract, becomes initially tangible through their work. They ensure this by providing explicit construction instructions, detailed models of the final product, and ensuring the requisite resources and skills are in place. By doing so, architects play a pivotal role in turning ambiguity into precision.

Moreover, it’s the architect’s responsibility to align ambitions with the resources available, ensuring that goals are realistically achievable.

In wrapping up, VUCA can be perceived as a daunting challenge. But, with the right leaders onboard, RePEL becomes a natural response to unfriendly environments and stressful times. They hold the key to transforming volatile situations into clear, well-defined future pathways, keeping the enterprise entropy under control.

Categories
Strategy Technology

22 Habits of Highly Impactful Technology Leaders

The following points embody the essential traits and behaviors I’ve discovered throughout my career. Most of these insights are lessons from memorable experiences. For the rest, remarkable technology leaders have graciously passed down their recipes for success, for which I am profoundly grateful. I’ve found these impactful learnings to be invaluable, and I hope you, too, will find value in them.

Be in the moment

Practice deep listening. Establish connections by demonstrating a sincere interest in what others are saying. This shows respect and is an excellent way to expand your knowledge.

Breathe technology

View technology as a passion, not just work. Concentrate on the domain that fascinates you. Delve into the specifics to form your own opinions.

Make technology your business

As a tool, technology can act as a business accelerator or a business opportunity. Moreover, a well-structured system comprising organizations, processes, and specialists is a social technology.

Understand everyone’s role

This encourages you to appreciate the value each colleague brings. You can maximize the benefits of internal synergies. It also encourages others to recognize the worth of everyone’s contributions.

Compose harmonically

Group people according to their affinity and complementary expertise. Consequently, some individuals will build things independently but keep them private. Ensure that teams are all moving in the same direction.

Guide

Take your hands off the steering wheel and teach others to drive by letting them take control.

Encourage sharing

Everyone is unique, hence they contribute unique value to the team and the organization. Act as a catalyst. Remember, a group’s value is more than the sum of its parts.

Trust their insights

All ideas matter. Your job is to sort and prioritize them. Trust is invaluable. Lack of trust is like refusing to invest in your people.

Communicate accurately

Strive to eliminate interpretation and ambiguity. Vagueness impedes mastery.

Structure

Your ideas, your approach, your strategy, your time, your directives.

Eliminate waste

Time and motivation are our most significant assets. Wasting time equates to wasting energy. Avoid exhaustion and demotivation, both for yourself and your team.

Work ahead

Being proactive means working in the future while others work in the present. Lead the way and inspire others to follow suit.

Evangelize

Spread the word about the vision, technological changes, economic dynamics, and mindset. Everyone should understand and know the direction in which the company is heading. Repeat this often. Consistently.

Develop careers

Uncover people’s potential to shape their careers. Provide them with the building blocks to carve their own paths.

Use thoroughly what you sell

Eat your own dog food. Use the product you’ve created to gain a customer’s perspective. Experience their satisfaction and their challenges firsthand.

Approach recruitment as you would a birth

Tailor the job profile, tests, interviews, and selection process. Represent your company, embodying its voice, culture, and brand. You might be meeting your next “business family” member. 

Cultivate a culture of knowledge management

Capture wisdom in the form of cookbooks, guidelines, best practices, and design patterns. Pay particular attention to less experienced or newer team members. This relevant and actionable knowledge forms part of the company’s long-term memory. Ensure this knowledge stays current as the world changes daily. Ultimately, use artificial intelligence to source insights from corporate memory.

Champion research & development

Change is inevitable. Therefore, you either shape the future or adapt to it. Your approach is also a reflection of your culture.

Encourage and arrange training

This nurtures your organization’s skills, intellectual wealth, innovative potential, and resilience.

Uncover talents and opportunities

Some are hidden gems, others are rare talents. Your leadership truly shines in the light of their brilliance.

Be selfless

Offer whatever you can, whether it’s time, insights, lessons learned from mistakes, or candid feedback. Be available when your team needs assistance.

Construct platforms for success

Your success is defined by how you contribute to others’ success. Share your journey to achievement so they can learn how to succeed. Celebrate and enjoy your victories together.

🖖

Categories
Artificial Intelligence Business ChatGPT Data Design GPT3 Information Technology Technology

Navigating the Future with Generative AI: A Prompt Engineer Job Offer?

Looking through the lens of Generative AI, jobs are evolving rapidly in this age of Digital Augmentation. In the midst of all the artificial intelligence effervescence, I wonder what kind of new jobs will emerge soon.

One of them is the Prompt Engineer.

In this article, I imagined the job description of your business’ first Prompt Engineer.


The world is shifting rapidly. As a pioneer in generative AI and an advocate of productivity augmentation, we are excited to open the position of Prompt Engineer.

SuperSleek Jeans is a company providing tailored jeans to women and men. Our purpose is to make jeans like a second skin! Our values are sensorial audacity and durability leadership. We proudly employ 2700 talented souls dedicated to meeting people’s needs in a smart and compassionate manner. Technology plays a significant role in our way of working and exploring uncharted territories for the benefit of our employees and customers is part of our DNA.

We foster a dynamic and inclusive company culture that encourages growth, collaboration, and innovation. We offer competitive compensation packages, comprehensive benefits, and numerous opportunities for professional development.

Your Mission

Your mission is to establish and grow the practice of Prompt Engineering at SuperSleek Jeans.

Responsibilities

  1. Learn and teach how to build products faster by analyzing and modifying the chain of analysis-to-design, design-to-build, and build-to-supervise for augmentation in each domain.
  2. Lead the development of an Enterprise AI Spirit, a chat-based agent, sourcing its knowledge base from existing systems such as Wiki, Document Store, Databases, and Unstructured documents. Manage an up-to-date training data set.
  3. Build a corporate prompt catalog for workers to provide reusable productivity recipes.
  4. Determine which parts of business processes can be entirely automated.
  5. Establish KPIs, a Steering Dashboard, and periodic reporting to measure the benefits of AI-augmented engineering and operations compared to current systems of work.
  6. Introduce and evangelize the concept of Generative AI and Large Language Models (also known as LLM).
  7. Build a legal and ethical framework to ensure risks pertaining to AI augmentation are addressed accordingly. Monitor the progress of domestic and international AI regulations.

Your Skills

  1. Hands-on experience with Generative AI models and tools leveraging prompt engineering, such as ChatGPT, Midjourney, ElevenLabs, etc.
  2. Core background in IT engineering.
  3. Proven algorithmic skills and mastery of engineering practices.
  4. The ability to code in one of the most popular languages such as Python, JavaScript, Java, or C#. A basic understanding of SQL is a must.
  5. Data management proficiency.
  6. Excellent communication and ability to design stunning presentations with compelling storytelling.
  7. Critical thinking and root cause analysis capabilities.
  8. Conversational UX proficiency.

Soft Skills

  1. Autonomous leadership with the ability to identify and propose the next best actions for yourself and your colleagues.
  2. Effective change management and resistance handling.
  3. Leading by example and providing assistance to colleagues when needed.
  4. You walk the talk by advocating continuous augmentation and demonstrating how your productivity and quality increase with AI augmentation.

Benefits and Perks

  1. An 85k€ to 105k€ compensation package based on your experience in engineering and AI knowledge.
  2. Total health, dental, and vision insurance for all family members.
  3. Retirement savings plan according to the national compensation scheme.
  4. 30 holidays with a generous paid time off policy.
  5. Employee assistance program and wellness initiatives.
  6. Craft your own professional growth and development along with your manager
  7. Collaborative and inclusive company culture.
  8. Free cinema tickets for your team once per quarter.

Living Your First Days in our Company

  1. You start your onboarding as a treasure hunt which consists in visiting key people, visiting unusual places, and learning our way of working. Each step unlocks a new quest until the completion of your journey. Your manager, the employee experience manager officer, and teammates assist along your adventure.
  2. Receive training so that you can rapidly feel comfortable with internal tools.
  3. Enjoy a tour of the premises and surrounding environment, such as restaurants, shops, parks, etc.
  4. As you familiarize yourself with the work environment, your first responsibility will be establishing a plan for transitioning our organization from Digital Transformation to Digital Augmentation.

Join and become part of a team that shapes the future of SuperSleek Jeans. Apply now and embark on an exciting and fulfilling career journey with us.


Feel free to unapologetically copy and remix this potential job offer in your business transition to Digital Augmentation.

I might even use it in the future. Who knows!

🖖

Categories
Banking Business Cryptocurrencies Finance Technology

The Negative Impact of Bank of Startups’ collapse

The recent bankruptcy of Silicon Valley Bank (SVB), a major financial institution has sent shockwaves throughout the startup world, particularly for those in the ESG (Environmental, Social, Governance) and blockchain/cryptocurrency sectors. The impact of this bankruptcy could have far-reaching consequences, affecting not only startups but also venture capitalists and pension funds.

One of the major risks associated with this bankruptcy is the domino effect it could have on venture capitalists and pension funds. For example, Vanguard Group has 11.2% of its holdings in SVB, which has a significant stake in the ESG and blockchain/cryptocurrency industries. If SVB were to suffer from bankruptcy, it could have a ripple effect on investment firms, followed by a temporary loss of trust in the market.

Furthermore, its collapse could erode investor confidence in smaller regional banks and drive investment toward larger, “safer” banks. This shift in investor sentiment could make it more difficult for startups to secure funding and could hinder the growth of ESG innovations and DeFi initiatives.

It’s important to note that investors with significant influence in the markets, such as Peter Thiel (co-founder of PayPal), can have a major impact on market psychology. Whether right or wrong, their opinions can sway investor sentiment and potentially exacerbate the negative effects of downfall.

In light of these developments, startups should be vigilant and prepare for potential challenges in securing funding. Investors should also carefully consider the risks associated with investing in these industries and the potential impact of external factors such as bankruptcy cascade. Overall, the effects of this financial earthquake serve as a reminder of the interconnectedness of the financial world and the importance of being mindful of potential risks and challenges.