AI Funding Highlights – SwissCognitive AI Investment Radar

This week’s AI investment landscape has been defined by diverging strategies, capital flows, and a widening discussion around equity, access, and economic consequence. On one side, the U.S. and EU are outlining ambitious visions for leadership. While the Stargate initiative pushes scale and speed, the EU’s dual strategy of financial commitment and regulatory positioning is placing ethical trust at the heart of its long game.

At the institutional level, signals of maturity are surfacing. Stanford’s AI Index highlighted pressure points shaping enterprise tech strategy, while BCG’s IT Spending Pulse underlined a shift: budgets are recalibrating as generative AI moves from novelty to core capability. Large investors are responding in kind—Bay Area-based SignalFire closed a $1 billion fund focused solely on applied AI companies, and Microsoft’s AI alliance with MSCI emphasizes the financial sector’s shift to AI-informed strategies.

From a regional angle, the Gates Foundation is betting $7.5 million on Rwanda as a launch point for AI scaling hubs in health, agriculture, and education. Canada attracted a CAD$150 million investment from Siemens for a global AI R&D center focused on battery production, while Italy’s Axyon AI secured €4.3 million for financial forecasting, and Ukraine’s QurieGen raised €2.2 million for AI-driven cancer drug R&D.

Meanwhile, a different class of firms is recalibrating customer interaction models. Arta Finance unveiled a suite of AI agents for portfolio insight, and startups skipping traditional funding stages—especially in Europe—signal a shift toward faster, more efficient capital strategies. But UNCTAD’s report reminds us that AI’s projected $4.8 trillion global impact comes with significant risks: unless addressed, the gap between early adopters and the rest could deepen.

This week’s updates confirm that the race is no longer about who adopts AI—it’s about how, and at what cost.

Previous SwissCognitive AI Radar: From Mega Rounds to Market Ripples .

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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This week in AI: speed, scale, and the next generation of intelligence:

Tencent’s new model aims to outpace DeepSeek-R1
AI transforms railway bridge safety and design
Amazon unveils AI-powered Alexa Plus
UK rethinks AI policies to protect creative industries
OpenAI teases GPT-4.5 with improved accuracy
…and more!

The AI world never slows down—see you next time with fresh updates!

Warm regards,

The Team of SwissCognitive

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Dalith Steiger-Gablinger, Co-Founder SwissCognitive – “AI Takes Center Stage at Davos 2025: A SwissCognitive Perspective”

As the snow-capped peaks of Davos played host to the World Economic Forum 2025, the air was thick with excitement and a palpable sense of urgency. This year’s theme, “Collaboration for the Intelligent Age,” set the stage for intense discussions on artificial intelligence (AI) and its potential to reshape our world. As co-founders of SwissCognitive, Andy Fitze and I, Dalith Steiger, had the privilege of being flies on the wall at various public side events, soaking in the insights and debates that unfolded.

The buzz around AI was impossible to ignore, with sessions ranging from “Harnessing AI for Social Innovation” to “The Pulse of AI Innovation”. Clearly, the technology has moved beyond mere hype and into the realm of transformative force. As James Ong, one of the panellists, aptly put it, “We need to rethink the philosophy and the relationship between AI and human beings.” AI is not just a tool; it’s a paradigm shift that will redefine how we work, live, and interact with the world around us.”

“We need to rethink the philosophy and the relationship between AI and human beings.” James Ong, Founder and Director of Artificial Intelligence International Institute [AIII]

One of the most striking aspects of the discussions was the emphasis on collaboration. Gone are the days of siloed AI development. The consensus at Davos was clear: to harness the full potential of AI and ensure its benefits are widely distributed, we need unprecedented levels of cooperation between governments, businesses, and civil society.

Another discussion that deeply resonates with our vision at SwissCognitive is the AI discussion in avoiding the pitfalls of the digital divide, emphasising the need for AI to “lift all boats” rather than exacerbate existing inequalities. We strongly advocated for inclusive AI development.

The ethical implications of AI were another hot topic. The sentiment that we are not just building algorithms; we are shaping the future of humanity was echoed across multiple panels, with discussions ranging from AI’s impact on privacy to its potential to either mitigate or exacerbate climate change.

As we navigated the bustling streets of Davos, Andy and I found ourselves in impromptu discussions with fellow attendees. One of the enlightening discussions was while waiting for the Meta hot chocolate or queuing for the entrance of the Dome. One thing that was present through all our exchanges. People engaged openly, with respect and humour.

The energy was infectious, with everyone from startup founders to policymakers eager to share their perspectives on AI’s future. One conversation that stuck with us was with a young entrepreneur who’s using AI to tackle food waste in developing countries. It was a powerful reminder of AI’s potential to address some of our most pressing global challenges and SDGs.

The governance of AI emerged as a critical theme throughout the forum. With the rapid pace of AI development, there’s a growing recognition that our regulatory frameworks need to evolve just as quickly. The call for adaptive, agile governance structures was loud and clear. We shouldn’t govern 21st-century technology with 20th-century laws!

“We shouldn’t govern 21st-century technology with 20th-century laws!” during a Chatham rules debate

Perhaps the most stimulating discussions, however, centred around the potential of AI to complement human capabilities rather than replace them. AI should be seen as a co-pilot, not an autopilot. As advocates of collaboration between humans and AI, Andy and I were heartened to hear leaders from different sectors emphasise the importance of involving humans in development.

“AI should be seen as a co-pilot, not an autopilot.” during a Chatham rules debate

The Open Source Revolution: A Game-Changer in the Global AI Race

Another topic that consistently emerged in our conversations was the growing importance of open source in AI development. This trend is not just reshaping the technological landscape; it’s also challenging the traditional narrative of national AI supremacy.

The United States’ commitment to investing a staggering $500 billion in AI over the next three years is undoubtedly headline-grabbing. However, as Yann LeCun, VP & Chief AI Scientist at Meta, astutely pointed out during several discussions in Davos, the real story might be the rise of open-source models rather than any single nation’s dominance.

LeCun’s perspective is particularly illuminating: “To people who see the performance of DeepSeek and think: ‘China is surpassing the US in AI.’ You are reading this wrong. The correct reading is: ‘Open source models are surpassing proprietary ones.'”

“Open source LLM models are surpassing proprietary ones.” Yann LeCun, VP & Chief AI Scientist at Meta

This shift towards open source is democratising AI development on a global scale. LeCun explained that “DeepSeek has profited from open research and open source (e.g. PyTorch and Llama from Meta). They came up with new ideas and built them on top of other people’s work. Because their work is published and open source, everyone can profit from it. That is the power of open research and open source.”

Indeed, the open-source movement in AI is gaining momentum rapidly. Models like Llama 2, Mistral, and DeepSeek are not just matching but, in some cases, surpassing the capabilities of proprietary giants like GPT-4 and Google Gemini. This trend is reshaping the AI ecosystem, offering adaptability, cost-efficiency, and privacy compliance that many enterprises find increasingly attractive.

The implications of this shift are profound. While national investments like the U.S.’s $500 billion commitment are crucial, the collaborative nature of open-source development means that innovations can come from anywhere. This global pool of talent and ideas could potentially accelerate AI development far beyond what any single nation or company could achieve alone.

Moreover, the open source movement aligns with the growing calls for AI transparency and accountability. One tech executive at Davos noted, “We’re not just building algorithms; we’re shaping the future of humanity.” Open source development allows for greater scrutiny and collective problem-solving, potentially leading to safer and more ethical AI systems.

“We’re not just building algorithms; we’re shaping the future of humanity.” CEO during a Panel in Davos

As we reflect on the discussions at Davos, it’s clear that the future of AI is not just about who can invest the most money. It’s about fostering a global ecosystem of innovation, collaboration, and shared progress. The rise of open source in AI is not just a technological trend; it’s a paradigm shift that could redefine how we approach some of the world’s most pressing challenges.

In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets but those who can best harness the collective intelligence of the global AI community. As we move forward, it will be fascinating to see how this open-source revolution continues to shape the future of AI and, by extension, our world.

“In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets, but those who can best harness the collective intelligence of the global AI community.” Andy Fitze, Co-Founder SwissCognitive

As the forum drew to a close, we left Davos with a sense of cautious optimism. The challenges ahead are significant, but so too is the collective will to address them. The conversations made it clear that we are at a pivotal moment in the development of AI, and the decisions we make now will shape its trajectory for years to come. This future belongs to the young generations. We, the older generation, must be aware that every decision we make won’t affect us, as it will affect the younger generations! This responsibility is imperative!

As we return to our work at SwissCognitive, we’re more energised than ever to continue fostering dialogue and collaboration in AI. The insights gained at Davos will undoubtedly inform our efforts to build a future where AI truly lifts all boats, creating a rising tide of innovation and prosperity for all.

“We are the change we wanna see”, Yip Thy Diep Ta, Founder & CEO @ J3D.AI, House of Collaboration

In reflecting on our experience, Andy remarked, “The technical possibilities of AI are astounding, but it’s the human ingenuity in applying these technologies that will truly change the world.” I couldn’t agree more, adding, “AI has the power to amplify our human potential, but only if we approach its development with empathy, wisdom, and a commitment to inclusivity.“

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SwissCognitive Guest Blogger: Shivi Gupta – “Who Owns the Sound? AI in Music and the Legal Landscape”

Attending a live gig, enjoying the music from your favourite artist or band? What if it can come to your couch, with the feeling that they are performing right there in front of you? But hey, who is producing the music? Is it AL or Al

The creation is revered, but more than the creation, the creators are worshipped. Recently, Sony, Universal, and Warner have sued Suno and Udio (GenAI music startups), claiming copyright infringement in training models, to protect the artists affiliated with these giants.

Major record labels are protecting their clients, the artists, the great ones who produce music that can rarely be replicated. But in the day and age of generative AI or (GPT Generative Pretrained transformer), music is also replicated by machine learning algorithms to make songs sound like the original creators.

As one of the popular web3 music websites Unchainedmusic.io wrote in their article “Deepfake vocal synthesizers, an innovation in AI technology, can make a singer’s voice sound like a famous artist. Under English and EU law, it is unlikely that a style of singing, whether generated through deep learning, AI or vocal imitation, is protectable by copyright. However, other forms of intellectual property, such as passing off, may be relevant in some jurisdictions.”

There is no common universal law against intellectual property, and most countries have their own rules, copyrights, patents. Any commercial use begets a request or a permission from the creator who owns the intellectual property of their voice.

Problem:

All music can be created eclectically with different styles, lyrics and genres. GenAI music might saturate the market with more and more music generated by machine learning algorithms.

Possibility:

Music lovers will rely on humans creating songs as it has the emotional factor, the timber, tone, pitch, stretch, diction, accent are some of the unique human characteristics which helps us being empathetic and understanding of the singer’s mindset.

Probability:

These AI created songs will be used by ad companies and video editors to feature a product or sell a service with an attractive UX.

Musicians will continue creating great records and go on tours, and fill stadiums.

Editors, marketers, sales representatives will use GenAI music in elevators, advertisements, branding, showcase of their products and services. The GenAI music will complement the product *-as-a-service.

Proposed Solution:

Follow rules created by the countries in which these AI tools are used. For classical music the law states that as mentioned by edwardslaw.ca “it covers original literary, dramatic, musical, and artistic works of authorship. This is during the lifetime of the author, the remainder of the calendar year in which the author dies, plus 70 additional years (the Canadian copyright lifespan recently increased from 50 to 70 years in June of 2022). Once this term expires, the work becomes public domain. “ So works from Beethoven, Mozart et al. can be performed in public without permission or paying a fee – royalty free. So any music which has been recorded prior to 1974 can be used since it has entered the public domain, but if you have the London symphony orchestra uploaded their recording of Beethoven’s symphony number 5, one can’t use that without the permission from the orchestra.

For example this particular youtube video can’t be reused without BBC’s permission:

More on copyright of voices: “According to Herndon, much of vocal mimicry comes down to personality rights. “You cannot copyright a voice, but an artist retains exclusive commercial rights to their name and you cannot pass off a song as coming from them without their consent,” she wrote in a recent Twitter thread, citing previous legal cases related to vocal impersonation.”

More about ethics in AI.

About the Author:

Shivi Gupta is a  passionate data scientist and full-stack developer, working in the industry for over a decade. An AI expert navigating through the world of real vs generated content. With a focus on ethics , he creates websites, mobile applications, chatbots all powered by AI.

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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.

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Copyright: hbr.org – “6 Ways AI Changed Business in 2024, According to Executives”

For decades, companies have struggled to capture and integrate data into their decision-making. In spite of protracted efforts, the results have been decidedly mixed. Last year, just 37% of companies reported that efforts to improve data quality had been successful. But recently, something significant has changed: Generative AI has spurred greater interest and investment in data quality and broader data capabilities. After all, great AI relies on great data. Gone are the days when executives dismissed investments in initiatives like these as “just another data project.” Now, to succeed with AI, companies are doubling down on finally getting data right.

This is the principal finding of the 2025 AI & Data Leadership Executive Survey, an industry benchmark survey of Fortune 1000 and global business leaders that I first launched in 2012.
This year’s survey was conducted by the educational Data & AI Leadership Exchange, in partnership with DataIQ, a global community of data and AI leaders. The invitation-only survey respondents comprised senior business leaders from 125 leading companies. This year, 97.6% of survey respondents identified themselves as C-suite executives or equivalents within their organization.

Their responses highlight the extent to which AI has come to drive corporate agendas across the board in just the past year. While most organizations (76.2%) report that they have been using earlier forms of AI, such as machine learning, for more than three years, it has been the arrival of generative AI that has fueled the rapid growth of AI utilization and adoption. This year’s survey findings suggest that we are experiencing a once-in-a-generation transformational moment, akin to the founding of the internet in the 1990s.[…]

Read more: www.hbr.org

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Copyright: fastcompany.com – “25 Experts Predict How AI will Change Business and Life in 2025”

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Copyright: cio.com – “12 AI predictions for 2025”

This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.

Generative AI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption.

Vendors are adding gen AI across the board to enterprise software products, and AI developers haven’t been idle this year either. We’ve also seen the emergence of agentic AI, multi-modal AI, reasoning AI, and open-source AI projects that rival those of the biggest commercial vendors.

According to a Bank of America survey of global research analysts and strategists released in September, 2024 was the year of ROI determination, and 2025 will be the year of enterprise AI adoption.

“Over the next five to 10 years, BofA Global Research expects gen AI to catalyze an evolution in corporate efficiency and productivity that may transform the global economy, as well as our lives,” says Vanessa Cook, content strategist for Bank of America Institute.

Small language models and edge computing

Most of the attention this year and last has been on the big language models —  specifically on ChatGPT in its various permutations, as well as competitors like Anthropic’s Claude and Meta’s Llama models. But for many business use cases, LLMs are overkill and are too expensive, and too slow, for practical use.

“Looking ahead to 2025, I expect small language models, specifically custom models, to become a more common solution for many businesses,” says Andrew Rabinovich, head of AI and ML at Upwork. LLMs aren’t just expensive, they’re also very broad, and not always relevant to specific industries, he says.

“Smaller models, on the other hand, are more tailored, allowing businesses to create AI systems that are precise, efficient, robust, and built around their unique needs,” he adds.[…]

Read more: www.cio.com

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Copyright: forbes.com – “4 Questions To Design Your Personal Relationship With AI In 2025”

Artificial intelligence is bound to weave through the year that we have just entered. Over the past months it has become a constant companion for millions, on the desktop, the phone or both. The pace is accelerating.

Whether we want to recognize it or not, AI is steadily reshaping how we work, play, socialize, and think. From algorithmically driven movie suggestions on Netflix and deals on Amazon to ChatGTP for the creation, and editing of text and audio visuals; passing via ai powered dating to 24/7 companion technology. And that’s only the consumer-facing side of AI’s expanding fingerprint. Much more is going on behind the scenes. AI-powered decision making has been changing human lifes at mass scale for years, from human resource management to the attribution of social services, insurance schemes and legal systems. The tech free space is shrinking.

AI 2024

In the U.S., the generative AI market is projected to grow from $36.06 billion in 2024 to $356 billion by 2030, driven by applications in industries like healthcare, finance, and retail. And that’s just one piece of the worldwide giga business that generative AI represents. Globally 65% of organizations now use generative AI regularly, according to McKinsey. That’s double the percentage from just a year ago. In China up to 83% of business leaders actively use these tools.

Unfortunately there is no « free lunch ». Generative AI models consume massive amounts of energy. A single query to an advanced model like ChatGPT can use ten times the electricity of a standard Google search. Globally, data centers powering AI could double their energy demands by 2026. That makes their environmental footprint extensive.[…]

Read more: www.forbes.com

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Copyright: theconversation.com – “What is an AI Agent? A Computer Scientist Explains the Next Wave of Artificial Intelligence Tools”

Interacting with AI chatbots like ChatGPT can be fun and sometimes useful, but the next level of everyday AI goes beyond answering questions: AI agents carry out tasks for you.

Major technology companies, including OpenAI, Microsoft, Google and Salesforce, have recently released or announced plans to develop and release AI agents. They claim these innovations will bring newfound efficiency to technical and administrative processes underlying systems used in health care, robotics, gaming and other businesses.

Simple AI agents can be taught to reply to standard questions sent over email. More advanced ones can book airline and hotel tickets for transcontinental business trips. Google recently demonstrated Project Mariner to reporters, a browser extension for Chrome that can reason about the text and images on your screen.

In the demonstration, the agent helped plan a meal by adding items to a shopping cart on a grocery chain’s website, even finding substitutes when certain ingredients were not available. A person still needs to be involved to finalize the purchase, but the agent can be instructed to take all of the necessary steps up to that point.

In a sense, you are an agent. You take actions in your world every day in response to things that you see, hear and feel. But what exactly is an AI agent? As a computer scientist, I offer this definition: AI agents are technological tools that can learn a lot about a given environment, and then – with a few simple prompts from a human – work to solve problems or perform specific tasks in that environment.

Rules and goals

A smart thermostat is an example of a very simple agent. Its ability to perceive its environment is limited to a thermometer that tells it the temperature.[…]

Read more: www.theconversation.com

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