New AI Investment Funds and Strategic Expansions – SwissCognitive AI Investment Radar

This week’s AI investment landscape sees bold financial commitments, expanding cloud infrastructure, and the growing influence of AI across industries. Oracle is set to invest £3.9 billion in the UK, alongside an additional $5 billion cloud expansion to strengthen AI adoption, signaling the company’s deep confidence in Britain’s AI future. Meanwhile, Saudi Arabia is launching a $40 billion AI fund, further establishing its role as a major player in the global AI race.

Microsoft’s AI investment strategy continues to gain momentum, earning an analyst upgrade as it builds out critical infrastructure. ARK Invest has joined a $403 million funding round for robotics firm Apptronik, highlighting investor enthusiasm for AI-powered automation. At the same time, Mirakl aims to push past $200 million in revenue with increased AI investments, showing how AI is reshaping business growth strategies.

In Asia, Thailand is attracting millions in AI data center investments, while Vietnam focuses on edge AI to compete in the global market. Azerbaijan is also setting its sights on AI by creating a strategy to attract foreign investment, positioning itself as an emerging tech hub.

AI’s role in finance and investment decision-making remains a focal point. National Grid Partners is committing $100 million to AI-driven energy solutions, while GapMinder Fund II is backing Romanian AI startup VoicePatrol, targeting real-time AI solutions for gaming. However, with AI’s growing influence, investors are warned about misinformation risks, reinforcing the need for well-vetted AI strategies.

With AI investments accelerating across industries, we continue to track how these financial commitments shape the broader technology and business landscape. Stay tuned for more insights in next week’s AI Investment Radar.

Previous SwissCognitive AI Radar: Major AI Funding 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.

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Big Moves in AI Funding and Infrastructure – SwissCognitive AI Investment Radar

In this week’s AI Investment Radar, we observe SoftBank’s bold $500 million investment in OpenAI’s latest funding round, positioning itself to capitalize on the anticipated $150 billion valuation. Meanwhile, Apple’s decision to step back from OpenAI’s funding conversations leaves Microsoft and Nvidia in the spotlight as primary investors.

Noteworthy movements extend beyond the tech giants, with Blackstone committing £10 billion to build one of the largest AI data centers in the UK, aiming to turn Northumberland into a major AI hub. Similarly, Google is making waves in Southeast Asia with a $1 billion investment into Thailand’s AI and cloud infrastructure, marking a significant push for regional AI growth.

Meanwhile, the healthcare sector is seeing substantial investments in AI-driven solutions, with Nvidia’s venture arm quietly funding advancements in robotic surgery and drug discovery. In addition, Cisco has launched a $1 billion fund to back AI startups, with a focus on secure and reliable AI technologies.

As AI demand fuels energy consumption, we also see a boom in power grid investments across Asia, led by firms like TEPCO, addressing the sector’s rapidly growing infrastructure needs. Join us as we break down this week’s most critical AI investment updates, exploring the key strategic decisions and financial movements defining the global AI landscape.

Previous SwissCognitive AI Radar: AI Funds, Energy Needs, and Tech Giants.

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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“Are robots really destined to take over restaurant kitchens?” This was the headline of an article published by Eater four years ago. One of the experts interviewed was Siddhartha Srinivasa, at the time professor of the Robotics Institute at Carnegie Mellon University and currently director of Robotics and AI for Amazon. He said, “I’d love to make robots unsexy. It’s weird to say this, but when something becomes unsexy, it means that it works so well that you don’t have to think about it. You don’t stare at your dishwasher as it washes your dishes in fascination, because you know it’s gonna work every time… I want to get robots to that stage of reliability.

The Covid Effect

The pandemic has had a massive economic impact all over the world, and one of the problems faced by many companies has been keeping their businesses running without putting employees at risk of infection. Many organizations are seeking to remain operational in the short term by automating tasks that would otherwise be carried out by humans. According to Digital Trends, since the start of the pandemic we have seen a significant increase in automation efforts in manufacturing, meat packing, grocery stores and more. In a June survey, 44 percent of corporate financial officers said they were considering more automation in response to coronavirus.

MIT economist David Autor described the economic crisis and the Covid-19 pandemic as “an event that forces automation.” But he added that Covid-19 created a kind of disruption that has forced automation in sectors and activities with a shortage of workers, while at the same time there has been no reduction in demand. This hasn’t taken place in hospitality, where demand has practically disappeared, but it is still present in agriculture and distribution. The latter is being altered by the rapid growth of e-commerce, with more efficient and automated warehouses that can provide better service.

China Leads the Way

China is currently in a unique position to lead the world’s automation economy. Although the country boasts a huge workforce, labor costs have multiplied by 10 over the past 20 years. As the world’s factory, China has a strong incentive to automate its manufacturing sector, which enjoys a solid leadership in high quality products. China is currently the largest and fastest-growing market in the world for industrial robotics, with a 21 percent increase up to $5.4 billion in 2019. This represents one third of global sales. As a result, Chinese companies are developing a significant advantage in terms of learning to work with metallic colleagues.

The reasons behind this Asian dominance are evident: the population has a greater capacity and need for tech adoption. A large percentage of the population will soon be of retirement age, without an equivalent younger demographic to replace it, leading to a pressing need to adopt automation in the short term.

China is well ahead of other countries in restaurant automation. As reported in Bloomberg, in early 2020 UBS Group AG conducted a survey of over 13,000 consumers in different countries and found that 64 percent of Chinese participants had ordered meals through their phones at least once a week, compared to a mere 17 percent in the US. As digital ordering gains ground, robot waiters and chefs are likely not far behind. The West harbors a mistrust towards non-humans that the East does not.

The Robot Evolution 

The pandemic was a perfect excuse for robots to replace us. But despite the hype around this idea, robots have mostly disappointed during the pandemic.

Just over 66 different kinds of “social” robots have been piloted in hospitals, health centers, airports, office buildings, and other public and private spaces in response to the pandemic, according to a study from researchers at Pompeu Fabra University (Barcelona, Spain). Their survey looked at 195 robot deployments across 35 countries including China, the US, Thailand, and Hong Kong.

Read more: www.singularityhub.com

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With the imposition of lockdowns, limitations of movement, the closure of borders and other measures to contain the virus, the operating environment of law enforcement agencies and those security services tasked with protecting the public from harm has suddenly become ever more complex. They find themselves thrust into the middle of an unparalleled situation, playing a critical role in halting the spread of the virus and preserving public safety and social order in the process. In response to this growing crisis, many of these agencies and entities are turning to AI and related technologies for support in unique and innovative ways. Enhancing surveillance, monitoring and detection capabilities is high on the priority list.

For instance, early in the outbreak, Reuters reported a case in China wherein the authorities relied on facial recognition cameras to track a man from Hangzhou who had traveled in an affected area. Upon his return home, the local police were there to instruct him to self-quarantine or face repercussions. Police in China and Spain have also started to use technology to enforce quarantine, with drones being used to patrol and broadcast audio messages to the public, encouraging them to stay at home. People flying to Hong Kong airport receive monitoring bracelets that alert the authorities if they breach the quarantine by leaving their home.

In the United States, a surveillance company announced that its AI-enhanced thermal cameras can detect fevers, while in Thailand, border officers at airports are already piloting a biometric screening system using fever-detecting cameras.

Isolated cases or the new norm?

With the number of cases, deaths and countries on lockdown increasing at an alarming rate, we can assume that these will not be isolated examples of technological innovation in response to this global crisis. In the coming days, weeks and months of this outbreak, we will most likely see more and more AI use cases come to the fore.

While the application of AI can play an important role in seizing the reins in this crisis, and even safeguard officers and officials from infection, we must not forget that its use can raise very real and serious human rights concerns that can be damaging and undermine the trust placed in government by communities. Human rights, civil liberties and the fundamental principles of law may be exposed or damaged if we do not tread this path with great caution. There may be no turning back if Pandora’s box is opened.

In a public statement on March 19, the monitors for freedom of expression and freedom of the media for the United Nations, the Inter-American Commission for Human Rights and the Representative on Freedom of the Media of the Organization for Security and Co-operation in Europe issued a joint statement on promoting and protecting access to and free flow of information during the pandemic, and specifically took note of the growing use of surveillance technology to track the spread of the coronavirus. They acknowledged that there is a need for active efforts to confront the pandemic, but stressed that “it is also crucial that such tools be limited in use, both in terms of purpose and time, and that individual rights to privacy, non-discrimination, the protection of journalistic sources and other freedoms be rigorously protected.”

This is not an easy task, but a necessary one. So what can we do?

Ways to responsibly use AI to fight the coronavirus pandemic

1. Data anonymization: While some countries are tracking individual suspected patients and their contacts, Austria, Belgium, Italy and the U.K. are collecting anonymized data to study the movement of people in a more general manner. This option still provides governments with the ability to track the movement of large groups, but minimizes the risk of infringing data privacy rights.
2. Purpose limitation: Personal data that is collected and processed to track the spread of the coronavirus should not be reused for another purpose. National authorities should seek to ensure that the large amounts of personal and medical data are exclusively used for public health reasons. The is a concept already in force in Europe, within the context of the European Union’s General Data Protection Regulation (GDPR), but it’s time for this to become a global principle for AI.
3. Knowledge-sharing and open access data: António Guterres, the United Nations Secretary-General, has insisted that “global action and solidarity are crucial,” and that we will not win this fight alone. This is applicable on many levels, even for the use of AI by law enforcement and security services in the fight against COVID-19. These agencies and entities must collaborate with one another and with other key stakeholders in the community, including the public and civil society organizations. AI use case and data should be shared and transparency promoted.
4. Time limitation:  Although the end of this pandemic seems rather far away at this point in time, it will come to an end. When it does, national authorities will need to scale back their newly acquired monitoring capabilities after this pandemic. As Yuval Noah Harari observed in his recent article, “temporary measures have a nasty habit of outlasting emergencies, especially as there is always a new emergency lurking on the horizon.” We must ensure that these exceptional capabilities are indeed scaled back and do not become the new norm.

Within the United Nations system, the United Nations Interregional Crime and Justice Research Institute (UNICRI) is working to advance approaches to AI such as these. It has established a specialized Centre for AI and Robotics in The Hague and is one of the few international actors dedicated to specifically looking at AI vis-à-vis crime prevention and control, criminal justice, rule of law and security. It assists national authorities, in particular law enforcement agencies, to understand the opportunities presented by these technologies and, at the same time, to navigate the potential pitfalls associated with these technologies.

Working closely with International Criminal Police Organization (INTERPOL), UNICRI has set up a global platform for law enforcement, fostering discussion on AI, identifying practical use cases and defining principles for responsible use. Much work has been done through this forum, but it is still early days, and the path ahead is long.

While the COVID-19 pandemic has illustrated several innovative use cases, as well as the urgency for the governments to do their utmost to stop the spread of the virus, it is important to not let consideration of fundamental principles, rights and respect for the rule of law be set aside. The positive power and potential of AI is real. It can help those embroiled in fighting this battle to slow the spread of this debilitating disease. It can help save lives. But we must stay vigilant and commit to the safe, ethical and responsible use of AI.

It is essential that, even in times of great crisis, we remain conscience of the duality of AI and strive to advance AI for good.

Read more – by techcrunch.com

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About this report Artificial intelligence (AI) will profoundly affect the ways in which businesses and governments engage with consumers and citizens alike. From advances in genetic diagnostics to industrial automation, these widespread changes will have significant economic, social and civic implications. As such, Intelligent Economies explores the transformative potential of AI on markets and societies across the developed and developing worlds.

This report, developed by The Economist Intelligence Unit and sponsored by Microsoft, draws on a survey of more than 400 senior executives working in various industries, including financial services, healthcare and life sciences, manufacturing, retail and the public sector. Survey respondents operate in eight markets: France, Germany, Mexico, Poland, South Africa, Thailand, the UK and the US.

Additionally, we conducted in-depth interviews with business leaders and experts in AI. We would like to thank the following for their insights and contributions to the research:

• Jeff Chen, lecturer, Gordon Institute of Business Science, University of Pretoria • Alex Konnaris, chief information officer, RMA Group • Juergen Maier, chief executive officer, Siemens UK • JP Rangaswami, chief data officer, Deutsche Bank • Daniel Ray, director of data science, NHS Digital • Sandra Wachter, research fellow, Oxford Internet Institute and Alan Turing Institute

Jessica Twentyman was the author of the report; Michael Hoffmann was the editor.

INTELLIGENT ECONOMIES: AIâ€s transformation of industries and society

Executive summary

Artificial intelligence (AI) is moving from the realm of science fiction to real- world adoption among private- and public-sector organisations globally. Today AI is used by financial services companies to serve customers better and detect fraud; by healthcare providers to more accurately diagnose illness and identify more effective treatments; by manufacturers to keep machines up and running on the plant floor and to streamline supply chains; and by city authorities to track and mitigate urban challenges such as traffic, pollution and crime.

As AI becomes increasingly embedded in society, it will not only change the businesses that adopt it but also have significant economic, social and civic effects on citizens and consumers. In short, national and regional economies will become more intelligent in the ways they produce and distribute goods and services. But such transformations will also introduce new challenges. Indeed, policymakers, economists and technology stakeholders are observing these changes closely, often with commitments to protecting the rights of workers whose jobs may be replaced by automation.[…]

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Sponsored by:
INTELLIGENT ECONOMIES: AIâ€s transformation of industries and society
A report from The Economist Intelligence Unit
2© The Economist Intelligence Unit Limited 2018

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The regional and global segmentation of the global Cognitive Computing market segments the market into major regions covering United States, North America, Canada, Asia-Pacific, China, India, Japan, South Korea, Australia, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Italy, Europe, Germany, France, UK, Russia, Rest of Europe, Central & South America, Brazil, Rest of South America, Middle East & Africa, Egypt, Turkey, South Africa, Rest of Middle East & Africa and rest of the world. According to the research report, these are the leading market and estimated to grow during the forecast period. Holding the immense share in the global market, it is growing with good speed. Our Research will focus on sector analysis, market trends and competitive landscape and drivers as well as conducts the detailed market research and develop this single-volume resource document.

Leading Players Of Cognitive Computing Market Are:

Google LLC, IBM corporation, Microsoft corporation, Oracle corporation, SAP Inc, Statistical Analysis System (SAS) Software Ltd, Saffron Technology Inc, Vicarious FPC Inc, Palantir Technologies Inc, Enterra Solutions LLC

Global Cognitive Computing Market Segmentation:

Global market segmentation, by technology:

Natural Language Processing
Machine Learning
Automated Reasoning Information
Retrieval Global market segmentation, by deployment:

On-premises
Cloud Global market segmentation, by application:

Robotics
Cyber Security
Social Media Monitoring
Self-driving cars
Gaming
Video Surveillance
eLearning
Global market segmentation, by end-use:

Banking, Financial Services and Insurance (BFSI)
Media & Communication Services
Manufacturing and Natural Resources
Aerospace and Defence
Transportation and Logistics
Government and Utilities
Others (Food & Beverages, Oil & Gas, Real Estate)

Report Coverage:

-Worldwide and Top 20 Countries Market Size of Cognitive Computing , and development forecast 2018-2027.

-Main manufacturers/suppliers of Cognitive Computing global and market share by regions, with company and product introduction, position in the Cognitive Computing market.

-Cost and profit status of Cognitive Computing, and marketing status.

-Market growth, challenges, and drivers.

-Market current status and development trend of Cognitive Computing by types and applications.

Some of the key pointers addressed in the report have been enlisted below:

-An elucidation of pivotal pointers such as the market share amassed by every region sales and the volume accumulated over the projected time frame.

-Further details about the manufacturer base, such as generic overview of the company, an overview of the firm in terms of the position it currently commands in the Cognitive Computing market, and its expanse in the industry.

-An exhaustive summary of the products developed by the manufacturers in question and a concise summary of the product portfolio with respect to parameters such as the product applications and sales volume every product type accounts for.

-Pivotal pointers such as Cognitive Computing market competition trends as well as the market concentration rate – basically inclusive of the specifics about some of the top players of the Cognitive Computing market.[…]

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While AI has been widely employed across industries, there remain many opportunities to be exploited by Thailand’s $14-billion media and entertainment industry. Broadcasters and media firms in Thailand face efficiency challenges in terms of delivering relevant and personalised content to consumers. An Ooyala poll in December 2017 revealed that 7 in 10 Thai media executives view their media operations as only minimally efficient or not efficient at all. In particular, 25 per cent of respondents highlighted the need to automate their entire operational value chain.

Drawing on the large amount of data generated from the consumption of videos, AI could improve the management and delivery of content as well as automate operations. Beyond that, AI could deliver better insights to help media executives make informed decisions and develop sound strategies for their business.

Here are three things AI could do for content production.

Make worthy content

Content producers are in a race to make original and creative content that appeals to consumers. More often than not, this process requires an extensive review of past content to gauge viewers’ interest and avoid duplication of content.

AI makes it easier for the publisher or broadcaster to understand the specific preference and behaviour of consumers by leveraging machine learning. For instance, if user X watches video A then clicks to watch video B, we can infer that the likelihood of user Y also wanting to watch video B is high if they had also watched video A. These patterns feed into a powerful neural network of decision-making that content producers could rely on to create personalised content for consumers.

Give content a re-birth

As a lot of money is being spent on producing a piece of content, the ability to make the most out of it is key. Localisation of the content to cater to each market’s needs and relevance is one way – and AI could help speed up the process. Tech giants including Microsoft and IBM have AI tools that makes it easier to transcribe or translate audio into other languages, so that you can sell your content to new markets.

Leveraging existing content is another way to profit. We can almost always hear the same pain point from broadcasters or publishers: “I don’t even know what I have in my archives at this point.” Locating, let alone monetising, relevant footage to supplement a news bulletin or a documentary often becomes a huge challenge for content companies as they sift through the vast amounts of video assets that sit in their archives. With AI, media organisations can index existing content with powerful metadata capture techniques, enabling them to easily identify and repurpose that archived content. […]

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In the ASEAN region, AI adoption rates are currently on the rise and growth has almost doubled in comparison to last year, according to a study carried out by IDC . Top AI uses in Southeast Asia include algorithmic market forecasting and automated asset and infrastructure management.

Indonesia and Thailand are the undisputed regional leaders at the time of adopting AI. The bronze medal goes to Singapore, which lately has been taking serious steps to position itself at the forefront of the AI market. By embracing the technology the country could start defeating its present economic challenges of slowing growth, falling capital investment, soft workforce growth and decelerated productivity.

AI could also potentially reinvigorate the state-island’s economy and boost its industrial profits. According to a recent report by Accenture, AI could add up to US$215 billion in gross value added across 11 industries by 2035. There’s no doubt that Singapore’s government is talking business when it comes to AI adoption.

Last year, a national initiative called AI Singapore was set “to catalyse, synergise and boost Singapore’s AI capabilities to power [Singapore’s] future, digital economy.”

The programme is driven by a government-wide partnership involving the National Research Foundation (NRF), the Smart Nation and Digital Government Office (SMART), the Economic Development Board (EDB), the Infocomm Media Development Authority (IMDA), SGInnovate, and Integrated Health Information Systems. It also brings together Singapore-based research institutions and AI startups and companies.

During its launch, the NRF announced that it will invest up to S$150 million (US$111 million) in the programme over a five-year period. And although there are still burning ethical issues surrounding the AI project and many more will keep emerging as it develops, Singapore is ready to embrace this priceless opportunity for its population and economy. […]

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