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
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

🫡

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
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
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.

🫡