Tag: Generative AI

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Navigating the Future with Generative AI: Part 4, Unstoppable AGI and Superintelligence?

AI - AGI and Superintelligence
AI - AGI and Superintelligence
AGI and Superintelligence 1

1. Connecting the Dots Between Two Life-Changing Milestones for Humanity

In a Times Magazine interview, Yann Lecun remarked, “I don’t like to call [it] AGI because human intelligence is not general at all.” This viewpoint challenges our common understanding of Artificial General Intelligence (AGI) versus the supposed limitations of human intelligence. The term “artificial general intelligence” itself seems overused and often misunderstood. While it initially appears intuitive, upon closer examination, nearly everyone with an informed perspective offers a different definition of AGI.

The fog only thickens with Ilya Sutskever, Chief Scientist behind the wildly popular GPT generative AI model. In an MIT Technology Review interview, he states, “They’ll see things more deeply. They’ll see things we don’t see,” followed by, “We’ve seen an example of a very narrow superintelligence in AlphaGo. […] It figured out how to play Go in ways that are different from what humanity collectively had developed over thousands of years. […] It came up with new ideas.”

Before DeepMind’s AlphaGo versus Lee Sedol showdown in 2016, we had IBM’s Deep Blue chess victory against Garry Kasparov in 1997. The unique aspect of these AIs is their mastery within a single, specific domain. They aren’t general, but superintelligent—surpassing human capability—within their respective areas.

In this article within the “Navigating the Future with Generative AI” series, we’ll explore two inevitable stages in humanity’s future: AGI and Superintelligence.

2. Defining AGI: What Do We Really Mean?

Numerous definitions exist for what we call AGI and superintelligence. These terms often intertwine in contemporary discussions around artificial intelligence. However, these are two very distinct concepts.

Firstly, AGI stands for Artificial General Intelligence. This signifies a state of artificial intelligence built upon several building blocks: machine learning, deep learning, reinforcement learning, the latest advancements in Generative AI and Imitation Learning algorithms, and basic code. These all contribute to a level of versatility in task execution and reasoning. This developmental stage of synthetic intelligence mirrors what an average human can achieve autonomously in various areas, demonstrating a generalized capability to perform diverse tasks.

These tasks stem from a foundation of knowledge—akin to schooling—combined with basic learning for completing new, periodically defined objectives to achieve specific goals. These goals exist within a work setting: finalizing an audit ensuring corporate compliance with AI regulations, ultimately advising teams on mitigation strategies. Conversely, they exist in daily life: grocery shopping, meal preparation for the next day, or organizing upcoming tasks. This AGI, working on behalf of a real human, benefits from globally accessible expertise. These attributes enable assistance, augmentation, and ultimately, complementation of everyday actions and professional endeavors. In essence, it acts as a controllable assistant: available on demand and capable of executing both ad-hoc and everyday tasks. The operative word here is general, implying a certain universality in skillsets and the capacity to execute the spectrum of daily tasks.

I share Yann Lecun’s view: a key missing element in current AI models is an understanding of the physical world. Let’s be more precise:

  • An AI requires a representation of physics’ laws but also an operational model determining when these laws apply. A child, after initial stumbles, inherently understands future falls will occur similarly, even without knowledge of the gravitational force field. They can learn, sense, and anticipate the effects of Earth’s gravity. Similarly, our bodies grasp the concept of weight calculation without comprehending its mathematical expression before formal learning.
  • Beyond this world model, an AI needs to superimpose a system of constraints, continuously reaffirming the very notion of reality. For example, we understand that wearing shoes negates the feeling of the hard ground beneath. Our preferred sneakers, due to their soles, elevate us a couple of centimeters, offering a slight cushioning effect while running. We trust the shoes won’t detach, having secured the laces. We vividly recall fastening those blue shoes before beginning our run as usual. Most importantly, we possess the unshakeable belief we won’t sink into the asphalt, knowing it doesn’t share mud’s consistency. Thus, we can confidently traverse our favorite path, striving for personal satisfaction, aiming to break that regional record.
  • An AI needs not only the ability to plan but also the capacity to simulate, adapt, and optimize plans and their execution. Recall your last meticulously planned trip. Coordinates meticulously plotted on your GPS, you set off with time to spare. But alas, the urban data was outdated, missing the detour at the A13 freeway entrance. Then, misfortune struck: an accident reported on the south freeway, traffic condensing from three lanes into one. Stuck in a bottleneck, only two options remain—pushing forward in hope or finding an alternate route. Checking your watch: 23 minutes left to reach your destination. This is how dynamic and complex planning a task can be. And yet, humans are capable of handling this all the time.
  • An AI requires grounding in reliable and idempotent functionalities, echoing the foundation of classical computing: programming, logic, and arithmetic calculation. The ability to call upon an internal library, utilize external APIs, and perform computations is paramount. This forms the basis of real-world grounding, maintaining “truth” as the very infrastructure of AGI. It’s about providing an action space yielding predictable, stable results over time, much like the verified mathematical theorems and laws of physics backed by countless empirical papers. Take, for instance, the capacity to predict a forest drone fleet’s movements using telemetric data, factoring in wind speed and direction, geospatial positioning, the relative locations of each drone and its neighbors, interpreting visual fields, and detecting obstacles (trees, foliage, birds, and so on).
  • An AI have to capitalize on real-time sensory input to infer, deduce, and trigger a decision-action-observation-correction loop akin to humans. For instance, smelling smoke immediately raises an alarm, compelling us to locate the fire source and prevent potential danger. Smartphones, equipped with cameras and microphones, display similar capabilities. Taking this further, devices like Raspberry Pis, when combined with diverse electronic sensory components, can even surpass human sensory capacities. Consider a robot with ultraviolet, infrared, or ultrasonic sensors, allowing it to “sense” things beyond our perception. This lends literal meaning to Ilya Sutskever’s statement.

This implies that AGI won’t necessarily be beneficial or provide significant added value in highly specialized fields, especially in areas where humans have been traditionally adept. This applies to domains like fundamental research, inventiveness, and engineering design – areas I believe will remain constrained by the currently available knowledge pool on the internet. This limitation arises because AGI’s continued advancement is largely driven by companies tailoring it to their specific expertise, often regarded as intellectual property.

Thus, we progressively journey towards AEI: Artificial Expert Intelligence. This translates to a model or agent, a pinnacle expert in its field. Imagine an AEI on par with the top 5% of experts (> 2σ) on this planet, reaching Olympian levels, like AlphaGeometry and AlphaProof, who secured the Silver Medal at the International Mathematical Olympiad.

The architectures with the most potential rely on active collaboration between expert models (Mixture of Experts) and between agents (Mixture of Agents). Even when individual model performance within this collaborative framework isn’t the absolute best, the collaborative outcome exhibits a quality level on par with, if not exceeding, that of the best individual models like GPT4-o. It’s a striking testament that collaboration, be it human or artificial, remains the most effective avenue to reach any objective.

3. Humanity’s Inevitable Ascent Towards Superintelligence

Revisiting the human versus machine narrative, 2018 marked a pivotal encounter: AlphaStar versus TLO (Dario Wunsch), then MaNa (Grzegorz Komincz), two professional gamers from the renowned StarCraft Team Liquid. Created by Google DeepMind, AlphaStar is a digital prodigy trained on the collective experience of 600 agents, equivalent to 200 years of playing StarCraft.

Consider the inherent imbalance when directly contrasting human capabilities against those of AI:

  1. Replication Capacity: AIs can be copied indefinitely.
  2. Relentless Training: AIs train ceaselessly, needing no sleep, nourishment, or breaks.
  3. Absolute Focus: AIs exhibit unwavering concentration on their designated tasks.
  4. Self-improvement through concurrent learning: AIs hone their abilities by training against their evolving intelligence, devising novel strategies to secure victory.
  5. Linear scalability: the more computing and memory resources you add, the greater the performance

The outcome: an AI consistently outmaneuvering the crème de la crème of a strategic open-world video game’s premier league. And as if that weren’t enough, it maintains its position within the Grandmaster league.

Here lies the very essence of an intelligence surpassing human decision-making abilities within a similarly vast and dynamic environment: this is what we classify as Superintelligence, or ASI.

Superintelligence, from my perspective, transcends mere human intelligence and even surpasses collective human intelligence. It indicates that even a group of individuals, regardless of their combined expertise and knowledge, would be outpaced, left trailing by an artificial intelligence capable of going beyond their cumulative potential.

Imagine instead a new form of synergy: a “super” human system collaboratively engaged in highly cognitive functions with this Superintelligence. This involves humans directing or, perhaps more accurately, guiding this Superintelligence based on our needs. While this Superintelligence operates with its own raison d’être, it wouldn’t clash with the fundamental purpose of humanity. This Superintelligence possesses access to those superior functions—understanding the universal model within which humanity exists. It possesses the model of reality itself.

Moreover, it resides within a self-improvement and discovery paradigm, continuously unveiling novel operations, new paradigms, and potentially even new forms of energy. Think entirely new physics laws that govern our universe; laws that humans, as of yet, have not uncovered. This encompasses diverse domains: medicine, engineering, revolutionary material science, new composite development, and engineering breakthroughs for unprecedented construction methods. Envision a symbiotic relationship between humans and machines fulfilling humanity’s ambitions. The limitations posed by individual human existence or the current state of collective human intelligence dissolve; no longer a barrier, it morphs into an expansive vision of human evolution, a potential accelerator for progress.

It even prompts new questions: How far can humans evolve? Or more precisely, how quickly?

However, we shouldn’t discount the possibility that artificial Superintelligence won’t be seen—or won’t see itself—as a novel species.

Therefore, being as rational as possible, we cannot accurately predict if this species would afford humanity the same compassion and civil collaboration that we strive for with our fellow human beings. It’s even plausible that they won’t hold any particular regard, instead pursuing their objectives, much like we think little of stepping on ants while daydreaming in a beautiful landscape, lost in contemplation, our thoughts oscillating between everyday worries and future aspirations.

4. What Would Constitute Human Superintelligence?

Human superintelligence embodies the culmination of all accumulated knowledge, discoveries, experiences, and yes, even the mistakes made by our ancestors to this point. Ultimately, this human superintelligence represents the collective “us” of today. It’s what fuels our intricate logistics and supply chains, our relentless pursuit of natural resources. It underpins our scientific endeavors: from breakthroughs in biology, mathematics, and agriculture, to understanding our global economic system – allowing us to manage our resources effectively, allocate them efficiently, and strategize our reinvestments. Money, in this light, transforms into a socio-economic technology.

Essentially, when comparing human superintelligence—today’s collective human intellect—with artificial superintelligence, a stark contrast emerges in their evolutionary cycles. Artificial intelligence advances at a significantly faster pace, powered by recent breakthroughs in training using our data. This data, importantly, reflects our findings, the mirror to thousands of years of human advancement accessible through the internet. This hints that artificial superintelligence would evolve at a much faster rate than humanity itself.

This rapid advancement stokes anxieties about potential disruption within the job market. Tech titans like Sam Altman advocate for Universal Basic Income (UBI) as a safety net for those displaced by artificial intelligence or robotics, allowing individuals to meet their basic needs even after losing their jobs. At that juncture, work itself detaches from its traditional role: that direct link between labor, contribution to the value chain, recognized worth, and societal standing. Instead, we confront the image of an economic umbilical cord, individuals sustained by the state-funded by fellow citizens.

While I remain undecided on my stance regarding UBI’s necessity, it compels contemplation. When UBI becomes a reality for a significant portion of the population, what function does money truly serve within our society? How do we sustain work motivation beyond “earning a living” when basic needs are met without active contribution? What ripples will be felt throughout a sovereign currency? Will the collective of people continue to control the economy, or is the future in the hands of AI-driven megacorporations?

There are so many answers yet to be uncovered.

After all, maybe “computing” should be considered a universal right. Therefore, we would shift the focus from UBI to UBC, Universal Basic Computing.

5. AGI and Superintelligence: Steering Toward a Future of Abundance or Ruin?

The next cycle hinges on resource accessibility and access to “programming” the world. Initially, artificial intelligence, at the very least, will permeate our daily lives. We are transitioning to personalized AI assistants, specializing in our chosen pursuits, whether robotics for errands, learning assistance for mastering a new language, or perfecting one’s singing voice. Next to none, specialized AI coaches will emerge to achieve elite athletic status, along with AI tutors guiding our artistic development beyond the readily available generated art of today.

Simultaneously, this superintelligence would be managing our complex systems: national infrastructures, electricity grids, vast transportation and logistical networks. Thus, it can drive early warning systems for natural disasters or power next-generation weather prediction platforms that incorporate oceanic currents. It will even account for stellar events such as shifts in the sun’s activity, factoring in our solar system’s dynamic positioning.

In conclusion, these are just glimpses into the potential futures shaped by AGI and superintelligence. However, the core message remains: we stand at a critical juncture. Depending on our collective appetite for progress, we could be headed toward a future of abundance or stumble along the path toward our own undoing.

Science offers an incredible opportunity: the chance to break free from a civilization driven by profit-motivated conflicts and ideological clashes. Instead, it enables collaboration guided by a neutral, third-party entity—one that embodies the best of what we, as a species, have strived for, built, and imagined. This collaboration offers a path for our societal framework to truly evolve.

The future is bright if we make it right.

🫡

Categories
web architecture Artificial Intelligence Automation Autonomous Agents Information Technology Services Technology User Experience UX

Navigating the Future with Generative AI: Part 3, Building the AInternet – AI, Web, and Customer Experience

AI for Customer Services in car leasing company

A Revealing Experience

Allow me to share a personal experience that perfectly illustrates the challenges I will discuss. I was involved in a car accident where a vehicle coming from the opposite direction severely damaged the right side of my car. Following the procedure, I filed an accident report with the other party, although I found myself unable to provide my insurance number simply because I didn’t have it readily available at that moment.

In the meantime, I went to my regular dealership so that an appraisal could be carried out and the next steps for repair could be determined. I then contacted my leasing company, and one of their agents agreed with me and the dealer that I would drop off the vehicle within two weeks. A replacement vehicle would be provided, and the full repair would take one to two weeks.

However, due to my lack of foresight, I did not deem it necessary to contact them again initially. A few days later, I received a letter from them informing me of the accident – which was correct – but also stating that I had not submitted the accident report and that without it, their insurance reserved the right not to cover the damages. In fact, I had sent this document a week earlier, but to the wrong email address. Out of habit, I had used their general contact details, avoiding contacting the agent in charge of my leasing file – who had recently retired. As a precaution, I had even added the generic address, but clearly without success since the insurance department had not received it.

I then called them back urgently to obtain clarification. They confirmed that the accident report was missing, and the agent, with great understanding which I acknowledge, told me that I had to send it to another specific address because the insurance department had not been notified by their colleagues in charge of customer relations. Moreover, the latter was not authorized to provide me with a replacement vehicle until the repair shop had received their approval – even though it was the approved dealership where I had been carrying out all maintenance operations for years.

This kind employee then offered, as an exception, to handle my entire case without further difficulty since the drop-off of my vehicle was imminent, just a few days away. She knew also that my leasing contract was expiring and that I would have to return the vehicle in two weeks to obtain a new one.

While this situation caused me a little stress, it was only temporary. An hour later, the agent contacted me again to confirm that everything was settled: I could bring my vehicle the following Monday and a replacement vehicle would be provided for the duration of the repairs.

Lessons from This Experience

You may be wondering why I am sharing this story with you.

First of all, I was unaware of the procedures governing the reporting of an incident in the context of a leasing contract. Should I first contact my company, directly the historical leasing company, or the new one? When I called them, why didn’t I reach the dedicated claims and insurance department directly? Why didn’t I find any information about this on their website? Why, when everything seemed clear to me – that I would drop off my vehicle within two weeks, that a replacement vehicle would be waiting for me, and that the repairs would be handled smoothly – did things unfold differently due to a lack of following the proper procedure?

Beyond that, how can a single service company exhibit such a lack of communication between two complementary departments?

The Revolution of the “AInternet”


We are entering a new era where artificial intelligence will be at the heart of exchanges between human beings. Where everyone previously had to search for information themselves on the Internet, navigating from site to site and compiling data to find a company’s contact details, the instructions for a recipe, the contacts of a repairman, or browse the Yellow Pages, the new paradigm will rely on exchanges between humans, intermediated or not by an artificial intelligence capable of performing synchronous or asynchronous tasks, i.e. in the background, to provide immediate knowledge to the user rather than forcing them to seek it out.

And to return to my use case, the AInternet brings a revolutionized customer experience that unfolds as follows:

When I am involved in an incident, I ask my personal AI assistant to help me fill out the accident report digitally. I do not have to provide all the information since my assistant has a global context encompassing data related to my vehicle, its insurance, my contract, my identity card, my passport, my postal and telephone contact details, my insurer, the maintenance status of my car, its technical inspection certification, etc. All this information allows for automatic and complete filling of this type of interaction.

Next, I only need to ask my assistant to contact the assistants of my leasing company and my insurance company, to ensure that the report I have validated and electronically signed is transmitted and processed by these two parties.

The assistant of the leasing company then informs the agent that a replacement vehicle is required and that an approved garage must be contacted to book an appointment for the repairs. It also determines whether my car should be taken directly to the dealership in charge of its regular maintenance. The relevant agent then handles my vehicle accordingly.

The agent only has to ask their assistant for the contact details of my garage to reach out directly.

From there, a genuinely empathic human relationship is established as we build a frictionless mutual understanding of the situation. Following the garage’s preliminary appraisal report, the leasing agent and the garage are prepared to agree on an appointment date, which is then recorded in the various systems.

The garage proceeds in an automated manner with the reservations and orders for the spare parts necessary for the repairs.

Simultaneously, the leasing company manages with the insurance company all the steps required to allow for the vehicle reparation and the provision of a replacement vehicle during the downtime.

Finally, the agent contacts me personally, by phone or message on a platform such as WhatsApp, to confirm everything is in order:

The incident has been properly recorded and the insurance company will cover all costs. An appointment has been set with my garage. A replacement vehicle will be provided during this period. An estimated date for returning the repaired vehicle has been communicated. They wish me an excellent day with a smile, since their assistant and mine have handled the entire procedure seamlessly. This augmented interaction allows us to reach new heights of fluidity and ubiquity in exchanges.

I am optimistic, indeed. Why wouldn’t I be? The transformation is already in motion.

The Internet will no longer be confined to a vast catalog of information to consult, such as books, encyclopedias, or applications, where interactions must be initiated and orchestrated by us, humans. But the orchestration between an individual and an organization, between two individuals, or between an organization and a computer system, will be performed like a symphony by intelligent agents, artificial intelligences.

This demonstrates an evolution of the World Wide Web architecture, which will constitute a veritable system of systems composed of human beings, applications, automata, and artificial agents.

The challenge from now on to enable this progression towards the era of digital augmentation will be to build artificial intelligence at the heart of human interactions. It is a matter of UX innovation.

It will no longer be a question of programming these interactions in advance by limiting the possibilities, but rather of training these artificial intelligences to handle a wide range of possible scenarios while framing and securing the use cases that could result from malicious computer hacking.

Ensuring a secure web environment requires a multi-layered approach that goes beyond safeguarding the AI models themselves. Equal vigilance must be applied at the integration points, where we erect robust firewalls and implement stringent access controls. These protective measures aim to prevent artificial intelligence from inadvertently or maliciously gaining entry to sensitive resources or confidential information that could compromise the safety and well-being of individuals, imperil organizations, or even threaten the integrity of the entire system.

Thus, emerging risks, such as jailbreaking, aimed at deceiving an artificial intelligence devoid of physical senses such as sight, hearing, and spatial awareness, allowing the authentication of a person, a company, or a system, will have to be compensated by other supervision and protection mechanisms.

It is on this note that this article concludes. We are living in an era of transition rich in exciting developments, and it will be up to you to build the Internet of tomorrow: the Augmented Internet.

🖖

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

🫡

Categories
Technology AR/VR Artificial Intelligence Information 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

🫡

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

Architecting the Future: How RePEL Counters VUCA for Modern Enterprises

RePEL vs VUCA
RePEL vs VUCA

I was first introduced to the term VUCA by my ex-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
Technology Artificial Intelligence Business ChatGPT Data Design GPT3 Information Technology

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

A model pausing for SuperSleek Jeans Fashion
A model pausing for SuperSleek Jeans Fashion

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.

YH SuperSleek Jeans fashion brand logo 01 1

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
Technology Artificial Intelligence ChatGPT Deep Learning GPT3

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

Age of AI

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.

https://open.spotify.com/episode/3H976fAfFmNDif1zmTjNuT?si=bsUrGirpQ5iKWwy1Hkw0hg

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

Red pill or Blue pill?

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:

YH Prime minister Xavier Bettel playing the finals of League of Legends
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.

🫡