SwissCognitive Guest Blogger: Eleanor Wright, COO at TelWAI – “A New Era of Intelligent Robots”

Imagine a world where humanoid robots cook for you, care for your loved ones, and streamline your workday – all powered by AI smarter than ever before. The global AI in robotics market, projected to surpass $124 Billion by 2030, is set to make this vision a reality. As the capabilities of AI evolve, these machines will become our companions, caregivers, and coworkers, they’ll make mobility more affordable, transform access to services, and redefine the value of human effort.

From Amazon’s fleet of 750,000 warehouse robots to Tesla’s ambitions to build 10,000 humanoid Optimus robots this year, the age of robots is upon us. Dependent on sensors and actuation systems to navigate and interact with the physical environment, this new age of robotics hinges on the developments of AI, designed to mimic and learn from its biological makers. Equipping these robots with intelligence, engineers working across various domains of expertise, utilise AI to enable vision, natural language processing, sound processing, pressure sensing, and more.

Beyond sensing, AI also enables robots to reason, adapt, and learn, using approaches including—but not limited to—reinforcement learning, neural networks, and Bayesian networks. These models and methods enable robots to assess risks and determine actions, and by learning from experience, robots can adapt to new tasks and environments. Thus, AI enables robots to perceive, act, learn, and adapt, allowing them to perform tasks with greater autonomy and precision.

However, integrating AI into robotics isn’t seamless, it comes with hurdles. Robots struggle with real-time processing delays, adapting to messy unpredictable environments, squeezing efficiency from limited hardware, and understanding human quirks like vague commands or gestures. These challenges constrain capabilities and the pace at which robots enter and dominate markets.

So, how can these challenges be addressed?

Some developments in addressing these challenges include:

1. Parallel computing

Parallel computing involves dividing larger tasks into smaller, independent tasks that can be processed simultaneously rather than sequentially. This enables increased computational efficiency, reduced latency, and improved cost efficiency. In robotics, parallel computing allows robots to process inputs from LIDAR, radar, and cameras simultaneously, enabling them to navigate environments more effectively and efficiently.

2. Transfer learning

Transfer learning leverages pre-trained models to solve new, but similar, problems. In this approach, a model trained on one task or dataset is reused and fine-tuned for a related task. For example, in machine vision for defect detection in manufacturing, fine-tuning a pre-trained model on a smaller dataset of images allows it to quickly adapt to detect specific defects, such as cracks or dents, without needing to train a model from scratch.

3. Self-calibrating AI

Self-calibrating refers to AI systems that autonomously adjust their parameters, models, or processes to maintain optimal performance without manual intervention. In robotics, self-calibrating AI enables robots to adapt to changes in their environment, hardware, or tasks, ensuring they operate with optimized accuracy and efficiency over time.

4. Federated learning

Federated learning is a technique that enables AI systems to learn from distributed data sources whilst ensuring privacy and security. It allows AI to collaboratively train a shared model without transferring sensitive data, preserving privacy and reducing reliance on centralised storage. For example, delivery robots use federated learning to optimise pathfinding without sending raw data, such as sensor inputs or location, to a central server. Instead, they locally update their models and share improvements, preserving both privacy and security.

These developments indicate a key focus on efficiency, adaptability, and learning – all of which are essential for the continued evolution of robotics in complex, real-world environments. Additionally, these advancements contribute to a future where robots collaborate with humans, leveraging their ability to learn from experience and improve over time.

So, what’s next for AI in Robotics?

Just as AI agents are taking over the digital realm, they are about to flood robotics too. AI agents embedded in robotics will supercharge the autonomy and flexibility of robots, enabling them to communicate with humans and even interpret intentions by analysing gestures and potentially emotional cues. Crucial to human-robot interactions, AI agents may prove highly effective in assisted care, hospitality, and other service industries.

Additionally, as technologies like federated learning and edge computing evolve, robots will share knowledge without compromising privacy or relying on centralised data. This will improve scalability and efficiency by reducing the need for costly centralised storage and processing, and enable additional robots to integrate rapidly into existing networks.

So, where does this leave us?

Although there are abundant market opportunities for AI in robotics, the pace at which different markets adopt robotics will vary; with AI being a key factor driving this adoption. Crucial for overcoming challenges related to autonomy, adaptability, and decision-making, AI will empower robots to perform tasks once considered too complex or risky for automation. As AI continues to evolve, it will not only raise important concerns about safety, ethics, and integration but help address them; ensuring robots can work seamlessly alongside humans and contribute to a more productive future.

About the Author:

Holding a BA in Marketing and an MSc in Business Management, Eleanor Wright has over eleven years of experience working in the surveillance sector across multiple business roles.

Der Beitrag A New Era of Intelligent Robots – AI and Robotics erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Samir Anil Jumade – “The Relentless Tide of Technological Disruption: Are You Ready?”

The world is evolving at an unprecedented pace, driven by rapid technological advancements. Many industries that once seemed invincible have either vanished or are on the verge of collapse due to their failure to adapt. The rise of artificial intelligence (AI), automation, blockchain, and digital platforms is fundamentally reshaping how businesses operate.

In this article, we explore how past giants like Kodak and Nokia disappeared, how today’s industries are facing a similar existential crisis, and how individuals and businesses must prepare for this inevitable transformation.

The Rise and Fall of Industry Giants

Remember Kodak? In 1997, they employed 160,000 people and dominated the photography market, with their cameras capturing 85% of the world’s images. Fast forward a few years, and the rise of mobile phone cameras decimated Kodak, leading to bankruptcy and the loss of all those jobs. Kodak’s story isn’t unique. A host of once-dominant companies, like HMT, Bajaj, Dyanora, Murphy, Nokia, Rajdoot, and Ambassador, failed to adapt and were swept aside by the relentless tide of technological change. These weren’t inferior products; they simply couldn’t evolve with the times.

This isn’t just a nostalgic look back. It’s a stark warning. The world is changing faster than ever, and we’re on the cusp of another massive transformation – the Fourth Industrial Revolution. Think about how much has changed in the last decade. Now imagine the next ten years. Experts predict that 70-90% of today’s jobs will be obsolete within that time frame. Are we prepared?

Look at some of today’s giants. Uber, the world’s largest taxi company, owns no cars. Airbnb, the biggest hotel chain, owns no hotels. These companies, built on software and connectivity, are disrupting traditional industries and redefining how we live and work. This disruption is happening across all sectors.

Consider the legal profession. AI-powered legal software like IBM Watson can analyze cases and provide advice far more efficiently than human lawyers. Similarly, in healthcare, diagnostic tools can detect diseases like cancer with greater accuracy than human doctors. These advancements, while offering immense potential benefits, also threaten to displace a significant portion of the workforce.

The automotive industry is another prime example. Self-driving cars are no longer science fiction; they’re a rapidly approaching reality. Imagine a world where 90% of today’s cars are gone, replaced by autonomous electric or hybrid vehicles. Roads would be less congested, accidents drastically reduced, and the need for parking and traffic enforcement would dwindle. But what happens to the millions of people whose livelihoods depend on driving, car insurance, or related industries?

Even the way we handle money is transforming. Cash is becoming a relic of the past, replaced by “plastic money” and, increasingly, mobile wallets like Paytm. This shift towards digital transactions offers convenience and efficiency, but also raises questions about security, privacy, and the future of traditional banking.

From STD Booths to Smartphones: A Revolution in Communication

Think back to the time when STD booths lined our streets. These public call offices were once essential for long-distance communication. But the advent of mobile phones sparked a revolution that swept STD booths into obsolescence. Those who adapted transformed into mobile recharge shops, only to be disrupted again by the rise of online mobile recharging. Today, mobile phone sales are increasingly happening directly through e-commerce platforms like Amazon and Flipkart, further highlighting the rapid pace of change.

The Evolving Definition of Money

The concept of money itself is undergoing a radical transformation. We’ve moved from cash to credit cards, and now mobile wallets are gaining traction. This shift offers convenience and efficiency, but it also has broader implications. As we move towards a cashless society, we need to consider the potential impact on financial inclusion, security, and privacy.

The Message is Clear: Adapt or Be Left Behind

The message is clear: adaptation is no longer a choice; it’s a necessity. We must embrace lifelong learning and upskilling to navigate this rapidly changing landscape. We need to foster creativity, critical thinking, and problem-solving skills – qualities that are difficult for machines to replicate. The future belongs to those who can innovate, adapt, and thrive in a world increasingly shaped by technology. The question is: will you be ready?

Additional Points to Consider:

· The environmental impact of technological advancements, both positive and negative.

· The ethical considerations surrounding AI and automation.

· The role of government and education in preparing the workforce for the future.

· The potential for new industries and job roles to emerge. By staying informed and proactive, we can harness the power of technology to create a better future for all.

References:

1. D. Deming, P. Ong, and L. H. Summers, “Technological Disruption in the Labor Market,” National Bureau of Economic Research, Working Paper No. 33323, Jan. 2025.
2. K. Hötte, M. Somers, and A. Theodorakopoulos, “Technology and Jobs: A Systematic Literature Review,” arXiv preprint arXiv:2204.01296, Apr. 2022.
3. D. Acemoglu and P. Restrepo, “Assessing the Impact of Technological Change on Similar Occupations,” Proceedings of the National Academy of Sciences, vol. 119, no. 40, e2200539119, Oct. 2022.
4. D. Acemoglu and P. Restrepo, “Occupational Choice in the Face of Technological Disruption,” National Bureau of Economic Research, Working Paper No. 29407, Oct. 2021. 5.S. Y. Lu and R. Zhao, “Artificial Intelligence for Data Classification and Protection in Cross-Border Transfers,” IEEE Transactions on Big Data, vol. 7, no. 3, pp. 536-545, 2021.

About the Author:

Samir Jumade is a passionate and experienced Blockchain Engineer with over three years of expertise in Ethereum and Bitcoin ecosystems. As a Senior Blockchain Engineer at Woxsen University, he has led innovative projects, including the Woxsen Stock Exchange and Chain Reviews, leveraging smart contracts, full nodes, and decentralized applications. With a strong background in Solidity, Web3.js, and backend technologies, Samir specializes in optimizing transaction processing, multisig wallets, and blockchain architecture.

Der Beitrag The Relentless Tide of Technological Disruption: Are You Ready? erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Featured Guest Article: Patrick Hebron – “AI and the Revolution in Design, Engineering, and Problem-Solving Methodology”

A Note to the Reader

This illustrated essay invites you to imagine how we can create a more sustainable, creative, and livable world by applying the transformative power of AI to design, engineering, and everyday problem-solving. It examines how reimagining design and engineering processes can empower both novices and experts to bring ambitious ideas to life.

For the past 15 years, I’ve worked on creating tools that connect AI research to real-world applications with the goal of making design and engineering more accessible and impactful. This essay draws on those experiences to envision how AI can shape the future of our tools and the built systems around us. Starting with a broad vision and foundational premises, it then focuses on specific interaction mechanisms, optimization opportunities, industry implications, and areas where AI can have a significant impact through the orchestration of design and engineering pipelines.

Whether you’re a researcher, designer, engineer, or simply curious about the future of the built world, I invite you to join me in this exploration.

Introduction

If I had asked people what they wanted,
they would have said faster horses.
— Attributed to Henry Ford

Knowing what to want is a skill. It requires a systematic approach to defining goals, evaluating options, analyzing available data and assessing potential outcomes. Above all, it requires the audacity to imagine that things could be different, that an existing need could be met in a better way, or that something entirely new could emerge, transforming how we live, work, or understand the world.

It’s impossible to keep up with the latest developments across every field, so we rely on a kind of innovation republic, where domain experts and visionaries like Henry Ford and Steve Jobs represent our interests by recognizing the transformative potential of new technologies and shaping them into impactful products.

AI is enabling a shift towards something more like a direct democracy of innovation, where individuals can bypass traditional gatekeepers to create solutions for themselves.

Over the last few years, we have seen the beginnings of the revolution in AI-driven scientific discovery. DeepMind’s Nobel Prize-winning protein structure prediction system, AlphaFold, and tools like Sakana AI’s AI Scientist highlight how AI can enable foundational breakthroughs.

These discoveries may lay the groundwork, but they do not directly constitute the downstream solutions needed to address real-world problems. To bridge this gap, it is essential to augment the methodologies of both foundational sciences and applied fields like functional design and engineering, where AI-driven innovation can help to tackle humanity’s toughest challenges and improve everyday life.

Outcomes in design and engineering work can be enhanced by the advanced reasoning, holistic planning, and deep technical knowledge present in agentic AI systems. However, for AI to select real-world problems that matter to humans and solve them in ways that align with our sensibilities, it stands to reason that human participation of some kind is needed.

Human contributions to this work will inevitably evolve and take many forms, from direct collaboration with AI to indirect influence on its behavior, with participation ranging from hands-on tool use and intent expressions to passive guidance by individuals, groups, and even the broader public.

Tools of this kind will enable the development of more efficient, sustainable, and inspiring products and buildings. They can also supplement the work of organizations like the Peace Corps, the International Red Cross, and the U.S. Army Corps of Engineers, while directly empowering communities and individuals to tackle challenging problems.

The full realization of this future will require significant technical advancement, a re-envisioning of design and engineering software, and a reconsideration of fundamental assumptions, such as what constitutes a “user.”

Importantly, we do not need to wait for AGI to get started. By taking a scaffolding approach that pairs problem selection with the iterative extension of capabilities, we can tackle progressively harder problems and steadily increase the system’s real-world impact.[…]

Read more: www.patrickhebron.com

Der Beitrag AI and the Revolution in Design, Engineering, and Problem-Solving Methodology erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

AI in Corporate Budgets and National Strategies – SwissCognitive AI Investment Radar

The UK government is making a $17 billion commitment to AI, setting the stage for large-scale adoption with its AI Opportunities Action Plan. Meanwhile, Microsoft has confirmed a staggering £65.1 billion AI infrastructure investment, reinforcing the tech industry’s reliance on expanding AI data centers. In the U.S., Amazon is allocating $11 billion toward cloud and AI infrastructure in Georgia, further cementing its role as a key player in AI development.

The private sector is also making significant moves. Blackstone’s $300 million investment into AI data company DDN positions the firm at the forefront of AI-driven data storage and analytics. Meanwhile, Singapore secures a $7 billion Micron investment to strengthen its role in the AI supply chain. In the automotive industry, Hyundai is investing $16.6 billion to integrate AI into electric vehicle production, signaling a shift in manufacturing strategies.

Retail and consumer brands are also embracing AI, with spending projected to rise by 52% in 2025. A Honeywell survey reveals that over 80% of U.S. retailers plan to expand AI investments to improve customer experience and operational efficiency. However, while enterprises are willing to invest up to $250 million in generative AI, questions about return on investment persist.

AI is increasingly shaping global markets, not just as a technological tool but as a key driver of economic strategy. Whether through national policies, corporate spending, or AI-driven supply chains, investments in AI are becoming a defining force for the future of business and innovation.

Stay tuned for next week’s AI investment updates.

Previous SwissCognitive AI Radar: AI Investment Opportunities Worldwide.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

Der Beitrag AI in Corporate Budgets and National Strategies – SwissCognitive AI Investment Radar erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Building Tomorrow’s Tech: AI Investments in Full Swing – SwissCognitive AI Investment Radar

Welcome back to this week’s SwissCognitive AI Investment Radar, where we spotlight the latest in global AI investments shaping the tech landscape.

This week, we see a broad spectrum of strategic moves and financial commitments, from General Catalyst’s $8 billion leap into AI-driven enterprise transformation to Reflexivity’s $30 million for advancing AI-powered financial analysis. Across the Atlantic, the European Union pledges $1.5 billion for deep tech research, aiming to keep Europe competitive in an arena largely dominated by the U.S. and China.

Automotive innovation takes center stage as Toyota and NTT invest $3.3 billion to push forward predictive, accident-avoiding AI for self-driving cars by 2028. Meanwhile, Google’s $5.8 million initiative in Sub-Saharan Africa seeks to bridge the AI skills gap, enabling local talent to address challenges in health, climate, and more. AI’s influence is also reshaping sectors like architecture and construction, as industry players ramp up investments to integrate AI capabilities into their workflows.

From the defense sector, Helsing’s £350 million commitment underscores the importance of AI in national security, while Saudi Aramco’s VC arm dedicates $100 million to nurture AI startups. And as AI startups now command a third of U.S. venture funding, countries like Indonesia are positioning themselves as new hubs for AI with favorable policies and low energy costs.

Join us as we delve into these developments, capturing how AI’s financial momentum is redefining industries and shaping the future.

Previous SwissCognitive AI Radar: Tech Giants Lead AI Infrastructure, Startups Follow Suit.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

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Copyright: fortune.com – “Here’s The Real Reason 75% of Corporate AI Initiatives Fail”

Business leaders are rushing to harness the quasi-magical powers of artificial intelligence (AI), with a projected annual spend of $60 billion on AI models by 2026. Yet, revenue from AI is only expected to reach about $20 billion per year by that point, flagging a substantial gap between investment and returns. In fact, recent studies show that roughly 75% of Gen AI initiatives don’t succeed.

Since the launch of generative AI, we’ve been conducting extensive research involving CEO interviews and deep dives within leading companies. This work has provided inside knowledge about the success of AI initiatives and has culminated in the book The Humachine. Here are some of these insights.

One AI doesn’t fit all

AI is copyable—and one size doesn’t fit all. What’s not copyable is a unique business model, processes, and integration of humans with that technology.

Our research finds that the massive rush to apply AI technologies to existing business models and old processes will not lead to success.

Spencer Fung, the CEO of global supply chain giant Li & Fung, provides an analogy: “Companies acquiring AI without a new business model is like a company digitizing a horse and carriage—while the competition has created a digital automobile.”

Adding AI to a business model of the past doesn’t lead to competitiveness—it simply solidifies old processes. AI is essential but insufficient in providing a competitive advantage. Before attempting to integrate AI into their businesses, corporate leaders need to first reassess and update their business models.

The data doesn’t hold up amid volatility

AI is based on historical data that may not be reliable in unpredictable and ever-changing global business environments.[…]

Read more: www.fortune.com

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Copyright: forbes.com – “How To Tell Reality From Fiction Amid The AI-Driven Truth Crisis”

The artificial intelligence narrative swings between utopian dreams and dystopian nightmares, often overshadowing the nuanced reality of its current capabilities and limitations.

Among the myriad concerns surrounding AI, one particularly unsettling claim is that it might lead to a world in which it’s impossible to distinguish truth from fabrication. This fear isn’t unfounded; the rise of sophisticated technologies like deepfakes and generative AI has democratized the creation of deceptively realistic content, putting powerful tools of manipulation within reach of the average user.

But does this technological leap truly herald an era when reality becomes indistinguishable from fiction? And if so, what are the ramifications for a society whose democratic foundations rest upon the bedrock of informed decision making?

The Age Of Lies

When AI deepfake technology is used in Hollywood to de-age actors—for example, enabling Harrison Ford to once again play a young Indiana Jones—it’s harmless fun. But when the same technology is used to make it appear that political figures have spoken or acted in ways they never would, it’s far more worrying.

Recent examples include deepfakes of both Kamala Harris and Donald Trump. As we approach this year’s U.S. elections, the dangers of this are very obvious.

In another example, audio deepfakes have been used to “robocall” potential voters, urging them not to take part in elections, in a clear attempt to subvert democracy.

AI can also undermine the credibility of true information by making us wonder if it’s really a lie. The “liar’s dividend” refers to the advantage gained by sowing doubt and confusion, where the mere suggestion that something could be fake undermines trust, even in the absence of evidence.[…]

Read more: www.forbes.com

Der Beitrag How To Tell Reality From Fiction Amid The AI-Driven Truth Crisis erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

AI Investment Highlights and Strategic Developments – SwissCognitive AI Investment Radar

The latest edition of the SwissCognitive AI Investment Radar is here again, to bring you the updates from the AI funding world.

We begin with Elon Musk’s $5 billion xAI investment proposal, raising eyebrows over potential conflicts of interest with Tesla. Venture capital investment saw a 16% increase in Q1 2024, primarily driven by AI funding needs, with the U.S. leading this surge. Singapore’s Temasek Holdings plans a substantial $30 billion injection in the U.S. tech market, focusing on AI, semiconductors, and data centers over the next five years.

Meanwhile, Tiger Brokers’ AI chatbot, TigerGPT, is gaining traction despite some inaccuracies, proving its utility in financial data analysis. UK startup Fractile has exited stealth mode with $15 million in funding to develop AI chips that promise to revolutionize speed and cost efficiency.

Saudi Arabia’s ambitious $40 billion AI investment fund aims to partner with U.S. firms, supporting a diverse range of tech startups. In Canada, a significant portion of the population, particularly Gen Z, is turning to AI for financial management.

Google’s CEO defends its massive investments in AI data centers, while Silicon Valley’s tech giants are making a trillion-dollar leap of faith on AI infrastructure, betting on its transformative potential despite uncertain financial returns.

Join and explore these exciting developments and more, keeping you informed and ahead in the  evolving world of Artificial Intelligence investments.

Previous SwissCognitive AI Radar: AI Investment Booms and Market Shifts.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

Der Beitrag AI Investment Highlights and Strategic Developments – SwissCognitive AI Investment Radar erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

AI Investment Booms and Market Shifts – SwissCognitive AI Investment Radar

Previous SwissCognitive AI Investments Radar: Tech Giants and Startups Shaping the AI Landscape.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

Der Beitrag AI Investment Booms and Market Shifts – SwissCognitive AI Investment Radar erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

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