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Artificial Intelligence Automation Business Business Strategy Engineering Innovation Robots Strategy Technology Technology Strategy

Update on Tesla’s Optimus #Robot – it is progressing fast

Tesla’s Optimus Robot learning from humans

The most impressive part is the technique employed by the Tesla team for accelerating the robot’s dexterity: the robot physically learns from human actions. 

Now, let’s step back and analyse Tesla’s master plan here:

(Putting on my business tech strategy goggles) 

1. Tesla builds electric cars augmented with software programmability.

2. Tesla provides an electric grid as a service.

3. Tesla builds gigafactories that maximize the automation of car manufacturing. Almost every single part of the pipeline is robotized and optimized for speed of production.

4. Tesla builds Powerwalls (by providing energy storage, it also creates a decentralized power station network).

5. Tesla brings autonomous driving (FSD) to Tesla cars. Essentially, cars are now transportation robots governed by the most advanced AI fleet management system.

6. Tesla builds its own chips (FSD Chip and Dojo Chip)

7. Tesla builds its own supercomputers.

8. Tesla launches Optimus, which aims to replace the human workforce in factories and warehouses.

9. X.ai, which has recently raised $6 billion, X’s supposedly “child” AI company, brings the Grok AI model trained on X/Twitter data. While you may say X data is not the best, X has a algorithm balanced with human judgment (community notes), AND the company regroups the largest set of news publishing companies. Basically, it automates curation and accuracy.

10. A version of the Grok AI model will likely power Optimus’s human-to-robot conversational interface.

11. Tesla cars will be turned into robotaxis, disrupting not only taxi companies but also Uber (the Uber/Tesla partnership may not be a coincidence), and eating into the shares of Lyft and BlaBlaCar.

12. Tesla will enter the general services business, and retail industries to offer multi-purpose usage robots – cleaning services for business offices, grocery stores, filling the workforce shortage in the catering (hotel-restaurant-bar…) industry, etc.

Tesla is not the only one moving in the “Robot Fleet Management” business. Chinese companies like BYD (EV) offer strong competition, and there are several robot startups (like Boston Dynamics and Agility Robotics) racing for the pole position.

#AI #artificialintelligence #Robotics #Optimus #EV #software #EnergyStorage #Automation #powerwall #AutonomousVehicles #FSD #chips #HighPerformanceComputing #Robots #GrokAI #NLP #robotaxis #innovation #WorkforceAutomation

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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.

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Bitcoin Blockchain Business Business Strategy Cardano Cryptocurrencies Ethereum How to Polkadot Strategy Technology Technology Strategy Web 3.0

How to grasp the blockchain world and safely walk your first steps into Web 3.0

The following is a quick guide explaining how to become acquainted with the world of blockchain, crypto, and web 3.0:

  1. First, I invite you to start with these videos:
    1. What is a Blockchain: https://youtu.be/rYQgy8QDEBI
    2. The difference between Bitcoin and Ethereum blockchains: https://youtu.be/0UBk1e5qnr4
    3. What is a Smart Contract: https://youtu.be/ZE2HxTmxfrI
    4. What is a Stablecoin: https://youtu.be/pGzfexGmuVw
    5. What is an NFT: https://youtu.be/FkUn86bH34M
  2. Understand the key concepts of web 3.0 by googling them: Blockchain, Wallet, Cryptocurrency, (crypto) token, Mining, PKI, tokens, Smart Contracts, Dapps, Decentralized Exchanges (DEX), Staking, ICO, ITO, Layer 1/2/3 protocols, transaction fees, consensus, etc.
  3. Know what are the major Web 3.0 technologies, their differences, and their value propositions like Bitcoin, Ethereum, Polkadot, Cardano, Cosmos, Polygon, Hyperledger, IPFS, Storj, Solana, Tether, etc. Not only the network but also the development tooling and the distribution means.
  4. Understand what new business models, organization models, like DAO, and features the Web 3.0 is bringing with respect to Web 2.0. Then research how Web 2.0 and 3.0 complement each other.
  5. Select one Blockchain technology and stick to it, in the beginning, to understand how Dapps are being built, distributed, and promoted in the ecosystem. Some of the most popular depending on your areas of interest: Uniswap (DeFi), OpenSea (Digital Art, NFT), Axie Infinity (Gaming), …
  6. Understand token economics and how it is possible to have such a huge valuation and market capitalization.
  7. Learn by doing!
    • Learn to use blockchain tools like Etherscan and Bitcoin Explorer, to see all Ethereum Blockchain transactions. And now is the time to look up your own wallet!
    • Then, you could fund your wallet using the most popular and safest Crypto Trade Exchanges like Kraken, Coindesk, or Crypto.com.
      Notice that you can buy cryptocurrencies with Paypal, but you currently cannot transfer them to your own wallet. Paypal is holding bitcoin for you.
  8. Follow the various companies and foundations expanding the web 3.0 (tech websites, Twitter) to grasp how the ecosystem is expanding. Then, ask yourself how these companies are regulated.
  9. Interact on LinkedIn, Twitter, and Reddit with knowledgeable people and enthusiasts.
  10. If you are an IT engineer, start programming with Solidity. I find the Truffle Suite genuinely good to build Smart Contracts and NFTs in an easy way.
Categories
Business Business Strategy Data Data Architecture Information Technology Legal Technology Strategy

The European Data Act: actually, can your data become a reliable source of income?

The European Data Act has recently been published.

It aims at clarifying and strengthening the governing framework of the #dataeconomy.

In the nutshell (extract):

“The Data Act will give both individuals and businesses more control over their data through a reinforced data portability right, copying or transferring data easily from across different services, where the data are generated through smart objects, machines, and devices.”

For example, a car or machinery owner could choose to share data generated by their use with its insurance company.

Such data, aggregated from multiple users, could also help to develop or improve other digital services, e.g. regarding traffic, or areas at high risk of accidents.”

Some thoughts on this

1️⃣ I wonder to what extent the boundaries of your data ownership can be explicitly defined, then transparently coded in IT systems, so that a “data asset” is legally bound to you as your property.

2️⃣ After this, you could ask Facebook, Instagram, and TikTok to share a piece of the cake: % of the revenue generated from your data.
Let’s face it, it looks like a game-changer, if it can really be implemented.

3️⃣ Ultimately, you can capitalize on GPDR architecture. It pushes the concepts of data ownership, consent management, data counters, data KPI, data censorship management, IAM, data expiry management, etc.

4️⃣ Beyond multicloud oversight solutions, this is an excellent use case for permissioned blockchain, like Hyperledger Fabric. (e.g. Infrachain )

5️⃣ Innovative business models to arise like “Mutual Data Funds”, or Open Data Lakes”, where a set of businesses or individuals would provide a set of qualified and certified data sources to act as “Value Added Data Sources”, something similar to Bloomberg or Reuters for financial News.

Also, these Mutual Data Pools are fitted to be plugged as Oracles in blockchains (#ethereum#chainlink#binance, etc.)

I can already envision the pitch of startups like “We are the Bloomberg of space mining Data” (which would be awesome by the way👍)

6️⃣ This could boost the API economy. But also push further the adoption of GraphQL and AsyncAPI standards.

7️⃣ I reckon open industry data models are a much better way to start. It would help regulators (e.g. Commission de Surveillance du Secteur Financier (CSSF) , CNPD – Commission nationale pour la protection des données , CNIL – Commission Nationale de l’Informatique et des Libertés), auditors and regtech (e.g. Scorechain ) to have a common ground to build their control frameworks and oversight infrastructure.
Now, it is time to stitch them together.

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