The world’s third largest economy and host nation for GITEX EUROPE x Ai Everything, Germany’s role as the European economic and technology leader is confirmed as its ICT sector is projected to reach €232.8bn in 2025 (Statista).

GITEX EUROPE x Ai Everything is Europe’s largest tech, startup and digital investment event, and is organised by KAOUN International. It’s hosted in partnership with the Berlin Senate Department for Economics, Energy and Public Enterprises, Germany’s Federal Ministry for Economic Affairs and Climate Action, Berlin Partner for Business and Technology, and the European Innovation Council (EIC).

Global tech engages for cross-border and industry partnerships

The first GITEX EUROPE brings together over 1,400 tech enterprises, startups and SMEs, and platinum sponsors AWS and IBM. Also in sponsorship roles are Cisco, Cloudflare, Dell, Fortinet, Lenovo, NTT, Nutanix, Nvidia, Opswat, and SAP.

GITEX EUROPE x Ai Everything will comprise of tech companies from over 100 countries and 34 European states, including tech pavilions from India, Italy, Morocco, Netherlands, Poland, Serbia, South Korea, UK, and the UAE.

Trixie LohMirmand, CEO of KAOUN International, organiser of GITEX worldwide, said: “There is a sense of urgency and unity in Europe to assert its digital sovereignty and leadership as a global innovation force. The region is paving its way as a centre-stage where AI, quantum and deep tech will be debated, developed, and scaled.”

Global leaders address EU’s tech crossroads

Organisers state there will be over 500 speakers, debating a range of issues including AI and quantum, cloud, and data sovereignty.

Already confirmed are Geoffrey Hinton, Physics Nobel Laureate (2024); Kai Wegner, Mayor of Berlin; H.E. Jelena Begović, Serbian Minister of Science, Technological Development and Innovation; António Henriques, CEO, Bison Bank; Jager McConnell, CEO, Crunchbase; Mark Surman, President, Mozilla; and Sandro Gianella, Head of Europe & Middle East Policy & Partnerships, OpenAI.

Europe’s moves in AI, deep tech & quantum

Europe is focusing on cross-sector AI uses, new investments and international partnerships. Ai Everything Europe, the event’s AI showcase and conference, brings together AI architects, startups and investors to explore AI ecosystems.

Topics presented on stage range from EuroStack ambitions to implications of agentic AI, with speakers including Martin Kon, President and COO, Cohere; Daniel Verten, Strategy Partner, Synthesia; and Professor Dr. Antonio Krueger, CEO of German Research Centre for Artificial Intelligence.

On the show-floor, attendees will be able to experience Brazil’s Ubivis’s smart factory technology, powered by IoT and digital twins, and Hexis’s AI-driven nutrition plans that are trusted by 500+ Olympic and elite athletes.

With nearly €7 billion in quantum investment, Europe is pushing for quantum leadership by 2030. GITEX Quantum Expo (GQX) (in partnership with IBM and QuIC) covers quantum research and cross-industry impact with showcases and conferences.

Speakers include Mira Wolf-Bauwens, Responsible Quantum Computing Lead, IBM Research, Switzerland; Joachim Mnich, Director of Research & Computing, CERN, Switzerland; Neil Abroug, Head of the French National Quantum Strategy, INRIA; and Jan Goetz, CEO & Co-Founder, IQM Quantum Computers, Finland.

Cyber Valley: Building a resilient cyber frontline

With cloud breaches doubling in number and AI-driven attacks, threat response and cyber resilience are core focuses at the event. Fortinet, CrowdStrike, Kaspersky, Knowbe4, and Proofpoint will join other cybersecurity companies exhibiting at GITEX Cyber Valley.

They’ll be alongside law enforcement leaders, global CISOs, and policymakers on stage, including Brig. Gen. Dr. Volker Pötzsch, Chief of Division Cyber/IT & AI, Federal Ministry of Defence, Germany; H.E. Dr. Mohamed Al-Kuwaiti, Head of Cybersecurity, UAE Government; Miguel De Bruycker, Managing Director General, Centre for Cybersecurity Belgium; and Ugo Vignolo Lutati, Group CISO, Prada Group.

GITEX Green Impact: For a sustainable future

GITEX Green Impact connects innovators and investors with over 100 startups and investors exploring how green hydrogen, bio-energy, and next-gen energy storage are moving from R&D to deployment.

Key speakers so far confirmed are Gavin Towler, Chief Scientist for Sustainability Technologies & CTO, Honeywell; Julie Kitcher, Chief Sustainability Officer, Airbus; Lisa Reehten, Managing Director, Bosch Climate Solutions; Massimo Falcioni, Chief Competitiveness Officer, Abu Dhabi Investment Office; and Mounir Benaija, CTO – EV & Charging Infrastructure, TotalEnergies.

Convening the largest startup ecosystem among 60+ nations

GITEX EUROPE x Ai Everything hosts North Star Europe, the local version of the world’s largest startup event, Expand North Star.

North Star Europe gathers over 750 startups and 20 global unicorns, among them reMarkable, TransferMate, Solarisbank AG, Bolt, Flix, and Glovo.

The event features a curated collection of earlys and growth-stage startups from Belgium, France, Hungary, Italy, Morocco, Portugal, Netherlands, Switzerland, Serbia, UK, and UAE.

Among the startups, Neurocast.ai (Netherlands) is advancing AI-powered neurotech for Alzheimer’s research; CloudBees (Switzerland) is the delivery unicorn backed by Goldman Sachs, HSBC, and Lightspeed; and Semiqon (Finland), the world’s first CMOS transistor with the ability to perform in cryogenic conditions.

More than 600 investors with $1tn assets under management will be scouting for new opportunities, including Germany’s Earlybird VC, Austria’s SpeedInvest, Switzerland’s B2Venture, Estonia’s Startup Wise Guys, and the US’s SOSV.

GITEX ScaleX launches as a first-of-its-kind growth platform for scale-ups and late-stage companies, in partnership with AWS.

With SMEs making up 99% of European businesses, GITEX SMEDEX connects SMEs with international trade networks and investors, for funding, legal advice, and market access to scale globally.

Backed by EISMEA and ICC Digital Standards Initiative, the event features SME ecosystem leaders advising from the stage, including Milena Stoycheva, Chairperson of Board of Innovation, Ministry of Innovation and Growth, Bulgaria; and Oliver Grün, President, European Digital SME Alliance and BITMi.

GITEX EUROPE is part of the GITEX global network tech and startup events, taking place in Germany, Morocco, Nigeria, Singapore, Thailand, and the UAE.

For more information, please visit: www.gitex-europe.com.

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We spoke to Kay to discuss the promise and pitfalls of generative AI, the future of the Metaverse, and how organisations can prepare for a decade of unprecedented digital transformation.

Generative AI has captured global attention, but there’s still a great deal of misunderstanding around what it actually is. Could you walk us through what defines generative AI, how it works, and why it’s considered such a transformative evolution of artificial intelligence?

It’s very exciting because it represents the next iteration of artificial intelligence. What generative AI allows you to do is ask questions of the world’s data simply by typing a prompt. If we think back to science fiction, that’s essentially what we’ve always dreamed of — just being able to ask a computer a question and have it draw on all its knowledge to provide an answer.

How does it do that? Well, it predicts which word is likely to come next in a sequence. It does this by accessing enormous volumes of data. We refer to these as large language models. Essentially, the machine ‘reads’ — or at least accesses — all the data available on the open web. In some cases, and this is an area of legal contention, it also accesses IP-protected and copyrighted material. We can expect a great deal of legal debate in this space.

Once the model has ingested all this data, it begins to predict what word naturally follows another, enabling it to construct highly complex and nuanced responses. Anyone who has experimented with it knows that it can return some surprisingly eloquent and insightful content simply through this predictive capability.

Of course, sometimes it gets things wrong. In the AI community, we call this ‘hallucination’ — essentially, the system fabricates information. That’s a serious issue because in order to rely on AI-generated outputs, we need to reach a point where we can trust the responses. The problem is, once a hallucination enters the data pool, it can be repeated and reinforced by the model.

While much has been said about generative AI’s technical potential, what do you see as the most meaningful societal and business benefits it offers? And what challenges must we address to ensure these advantages are equitably realised?

AI is now accessible to everyone, and that’s incredibly powerful. It’s a hugely democratising tool. It means that small and medium-sized enterprises, which previously couldn’t afford to leverage AI, now can.

However, we also need to be aware that most of the world’s data is created in the United States first, followed by Europe and China. There are clear challenges regarding the datasets these large language models are trained on. They’re not truly using ‘global’ data. They’re working with a limited subset. That has led to discussions around digital colonisation, where content generated from American and European data is projected onto the rest of the world, with an implicit expectation that others will adopt and use it.

Different cultures, of course, require different responses. So, while there are countless benefits to generative AI, there are also significant challenges that we must address if we want to ensure fair and inclusive outcomes.

The Metaverse has seen both hype and hesitation in recent years. From your perspective, what is the current trajectory of the Metaverse, and how do you see its role evolving within business environments over the next five years?

It’s interesting. We went through a phase of huge excitement around the Metaverse, where everyone wanted to be involved. But now we’ve entered more of a Metaverse winter, or perhaps autumn, as it’s become clear just how difficult it is to create compelling content for these immersive spaces.

We’re seeing strong use cases in industrial applications, but we’re still far from achieving that Ready Player One vision — where we live, shop, buy property, and fully interact in 3D virtual environments. That’s largely because the level of compute power and creative resources needed to build truly immersive experiences is enormous.

In five years’ time, I think we’ll start to see the Metaverse delivering on more of its promises for business. Customers may enjoy exceptional shopping experiences—entering virtual stores rather than simply browsing online, where they can ‘feel’ fabrics virtually and make informed decisions in real time.

We may also see remote working evolve, where employees collaborate inside the Metaverse as if they were in the same room. One study found that younger workers often lack adequate supervision when working remotely. In a Metaverse setting, you could offer genuine, interactive supervision and mentorship. It may also help with fostering colleague relationships that are often missed in remote work settings.

Ultimately, the Metaverse removes physical constraints and offers new ways of working and interacting—but we’ll need balance. Many people may not want to spend all their time in fully immersive environments.

Looking ahead, which emerging technologies and AI-driven trends do you anticipate will have the most profound global impact over the next decade. And how should we be preparing for their implications, both economically and ethically?

That’s a great question. It’s a bit like pulling out a crystal ball. But without doubt, generative AI is one of the most significant shifts we’re seeing today. As the technology becomes more refined, it will increasingly power new AI applications through natural language interactions.

Natural Language Processing (NLP) is the AI term for the machine’s ability to understand and interpret human language. In the near future, only elite developers will need to code manually. The rest of us will interact with machines by typing or speaking requests. These systems will not only provide answers, but also write code on our behalf. It’s incredibly powerful, transformative technology.

But there are downsides. One major concern is that AI sometimes fabricates information. And as generative AI becomes more prolific, it’s generating massive volumes of data 24/7. Over time, machine-generated data may outnumber human data, which could distort the digital landscape. We must ensure the AI doesn’t perpetuate falsehoods it has previously generated.

Looking further ahead, this shift raises deep questions about the future of human work. If AI systems can outperform humans in many tasks without fatigue, what becomes of our role? There may be cost savings, but also the very real risk of widespread unemployment.

AI also powers the Metaverse, so progress there is tied to improvements in AI capabilities. I’m also very excited about synthetic biology, which could see huge advancements driven by AI. There’s also likely to be significant interplay between quantum computing and AI, which could bring both benefits and serious challenges.

We’ll see more Internet of Things (IoT) devices as well—but that introduces new issues around security and data protection.

It’s a time of extraordinary opportunity, but also serious risks. Some worry about artificial general intelligence becoming sentient, but I don’t see that as likely just yet. Current models lack causal reasoning. They’re still predictive tools. We would need to add something fundamentally different to reach human-level intelligence. But make no mistake—we are entering an incredibly exciting era.

Adopting new technologies can be both an opportunity and a risk for businesses. In your view, how can organisations strike the right balance between embracing digital transformation and making strategic, informed decisions about AI adoption?

I think it’s vital to adopt the latest technologies, just as it would have been important for Kodak to see the shift coming in the photography industry. Businesses that fail to even explore digital transformation risk being left behind.

However, a word of caution: it’s easy to jump in too quickly and end up with the wrong AI solution — or the wrong systems entirely — for your business. So, I would advise approaching digital transformation with careful thought. Keep your eyes open, and treat each step as a deliberate, strategic business decision.

When you decide that you’re ready to adopt AI, it’s crucial to hold your suppliers to account. Ask the hard questions. Ask detailed questions. Make sure you have someone in-house, or bring in a consultant, who knows enough to help you interrogate the technology properly.

As we all know, one of the greatest wastes of money in digital transformation happens when the right questions aren’t asked up front. Getting it wrong can be incredibly costly, so take the time to get it right.

Photo by petr sidorov on Unsplash

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Unlike anything seen to date, the Manus AI agent doesn’t just chat with users – it is allegedly capable of independently tackling complex multi-step tasks with minimal human guidance.

Developed by Chinese startup Butterfly Effect with financial backing from tech giant Tencent Holdings, Manus AI agent has captured global attention for its ability to bridge the gap between theoretical AI capabilities and practical, real-world applications. It uses an innovative multi-model architecture that combines the strengths of multiple leading language models.

Breakthrough autonomous task execution

In a post on X, Peak Ji Yichao, co-founder and chief scientist at Butterfly Effect, said that the agentic AI was built using existing large language models, including Anthropic’s Claude and fine-tuned versions of Alibaba’s open-source Qwen.

Its multi-model nature allows Manus to use different AI strengths according to what’s demanded of it, resulting in more sophisticated reasoning and execution capabilities.

“The Manus AI agent represents a fundamentally different approach to artificial intelligence,” CNN Business stated. According to coverage, Manus “can carry out complex, multi-step tasks like screening resumés and creating a website,” and “doesn’t only generate ideas but delivers tangible results, like producing a report recommending properties to buy based on specific criteria.”

Real-world performance assessment

In an extensive hands-on evaluation, MIT Technology Review tested the Manus AI agent in three distinct task categories: compiling comprehensive journalist lists, conducting real estate searches with complex parameters, and identifying candidates for its prestigious Innovators Under 35 program.

“Using Manus feels like collaborating with a highly intelligent and efficient intern,” wrote Caiwei Chen in the assessment. “While it occasionally lacks understanding of what it’s being asked to do, makes incorrect assumptions, or cuts corners to expedite tasks, it explains its reasoning clearly, is remarkably adaptable, and can improve substantially when provided with detailed instructions or feedback.”

The evaluation revealed one of the Manus AI agent’s most distinctive features – its “Manus’s Computer” interface, which provides unprecedented transparency into the AI’s decision-making process.

The application window lets users observe the agent’s actions in real time and intervene when necessary, creating a collaborative human-AI workflow that maintains user control while automating complex processes.

Technical implementation challenges

Despite impressive capabilities, the Manus AI agent faces significant technical hurdles in its current implementation.MIT Technology Reviewdocumented frequent system crashes and timeout errors during extended use.

The platform displayed error messages, citing “high service load,” suggesting that computational infrastructure remains a limitation.

The technical constraints have contributed to highly restricted access, with less than 1% of wait-listed users receiving invite codes – the official Manus Discord channel has already accumulated over 186,000 members.

According to reporting from Chinese technology publication36Kr, the Manus AI agent’s operational costs remain relatively competitive at approximately $2 per task.

Strategic partnership with Alibaba Cloud

The creators of the Manus AI agent have announced a partnership with Alibaba’s cloud computing division. According to a South China Morning Post report dated March 11, “Manus will engage in strategic cooperation with Alibaba’s Qwen team to meet the needs of Chinese users.”

The partnership aims to make Manus available on “domestic models and computing platforms,” although implementation timelines remain unspecified.

Parallel advancements in foundation models

The Manus-Alibaba partnership coincides with Alibaba’s advances in AI foundation model technology. On March 6, the company published its QwQ-32B reasoning model, claiming performance characteristics that surpass OpenAI’s o1-mini and rivalling DeepSeek’s R1 model, despite a lower parameter count.

CNN Businessreported, “Alibaba touted its new model, QwQ-32B, in an online statement as delivering exceptional performance, almost entirely surpassing OpenAI-o1-mini and rivalling the strongest open-source reasoning model, DeepSeek-R1.”

The claimed efficiency gains are particularly noteworthy – Alibaba says QwQ-32B achieves competitive performance with just 32 billion parameters, compared to the 671 billion parameters in DeepSeek’s R1 model. The reduced model size suggests substantially lower computational requirements for training and inference with advanced reasoning capabilities.

China’s strategic AI investments

The Manus AI agent and Alibaba’s model advancements reflect China’s broader strategic emphasis on artificial intelligence development. The Chinese government has pledged explicit support for “emerging industries and industries of the future,” with artificial intelligence receiving particular focus alongside quantum computing and robotics.

Alibaba will invest 380 billion yuan (approximately $52.4 billion) in AI and cloud computing infrastructure in the next three years, a figure the company notes exceeds its total investments in these sectors during the previous decade.

As MIT Technology Review’s Caiwei Chen said, “Chinese AI companies are not just following in the footsteps of their Western counterparts. Rather than just innovating on base models, they are actively shaping the adoption of autonomous AI agents in their way.”

The Manus AI agent also exemplifies how China’s artificial intelligence ecosystem has evolved beyond merely replicating Western advances. Government policies promoting technological self-reliance, substantial funding initiatives, and a growing pipeline of specialised AI talent from Chinese universities have created conditions for original innovation.

Rather than a single approach to artificial intelligence, we are witnessing diverse implementation philosophies likely resulting in complementary systems optimised for different uses and cultural contexts.

The post Manus AI agent: breakthrough in China’s agentic AI appeared first on AI News.

Released in November 2024, the Commission’s annual report outlined 32 recommendations that could fundamentally alter how the two countries interact, with artificial intelligence taking centre stage in a new chapter of strategic rivalry.

US-China: the AGI moonshot and critical tech controls

At the heart of the report lies an ambitious proposal: establishing a government-backed programme to develop AGI – AI systems that could match and potentially exceed human cognitive abilities. 

However, the recommendation is just one piece of a larger technological puzzle, including export controls, investment screening, and new trade policies to preserve US technological advantages. 

The proposed AGI initiative would provide multi-year contracts to leading AI companies, cloud providers, and data centre operators. It would be backed by the Defense Department’s highest priority, “DX Rating” – a designation typically reserved for critical national security projects. 

This level of government involvement in AI development mirrors the urgency seen in previous technological races. It raises crucial questions about the role of state intervention in an industry primarily driven by private sector innovation.

The Commission’s tech-focused recommendations extend beyond AI. Notable proposals include restricting imports of Chinese-made autonomous humanoid robots with advanced dexterity, locomotion, and intelligence capabilities. 

The report also targets energy infrastructure products with remote monitoring capabilities, reflecting growing concerns about connected technologies in critical infrastructure. The report builds on existing export controls in the semiconductor space by recommending stronger oversight of technology transfers and investment flows. 

This comes as China continues to build domestic chip-making capabilities despite international restrictions. The Commission suggests creating an Outbound Investment Office that prevents US capital and expertise from advancing China’s technological capabilities in sensitive sectors.

Reshaping trade relations and investment flows

Perhaps most significantly, the report recommends eliminating China’s Permanent Normal Trade Relations (PNTR) status—a move that could reshape the technology supply chain and trade flows that have defined the global tech industry for decades. This recommendation acknowledges how deeply intertwined the US and Chinese tech ecosystems have become, while suggesting that this interdependence may now pose more risks than benefits.

Data transparency is another key theme, with recommendations for expanded reporting requirements on investments and technology transfers. The Commission calls for better tracking of investments flowing through offshore entities, addressing a significant blind-spot in current oversight mechanisms.

The report’s release comes at a critical juncture in technological development. China’s push for self-sufficiency in vital technologies and its “new quality productive forces” initiative demonstrates Beijing’s determination to lead in next-generation technologies. Meanwhile, AI capabilities and quantum computing breakthroughs have raised the stakes in technology competition.

However, the Commission’s recommendations face practical challenges. Achieving AGI remains a complex scientific challenge that may not yield quick results, regardless of funding levels. Additionally, restrictions on technology transfers and investment could have unintended consequences for global innovation networks that have historically benefited both nations.

If these recommendations are implemented, the tech industry may need to navigate an increasingly complex regulatory landscape. Companies would face new compliance requirements for international investments, technology transfers, and collaborative research projects.

Challenges and future implications

The effectiveness of the proposed measures will likely depend on coordination with allies and partners who share similar technological capabilities and concerns. The report acknowledges this by recommending multilateral approaches to export controls and investment screening.

US-China technological competition has entered a new phase where government policy may play a more direct role in shaping development. Whether this approach accelerates or hinders innovation remains to be seen, but the tech industry should prepare for increased scrutiny and regulation of international technological collaboration.

(Photo by Nathan Bingle)

See also: Chinese firms use cloud loophole to access US AI tech

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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The following is a short excerpt summarising a segment of an episode from the AI Geeks Podcast between the veteran, serial technology entrepreneur (Silicon Valley, Europe and Asia) Henry Nash, and the London-based serial tech entrepreneur Tim El-Sheikh (AI Geeks founder and host):

Understanding the real cost of AI

The debate often revolves around the integration of AI into our environment and the tools required for it. While these aspects are indeed important, the long-term cost of running and maintaining AI in production is a crucial factor that will determine the success of your AI strategy. 

The real winners in this AI race will be those who can strike the best balance between accuracy, trustworthiness, and cost-effectiveness while maintaining an optimal aperture for the flow of information.

From science experiments to real-world applications

The fascination with large language models (LLMs) and their capabilities often leads to overlooking the real-world applications of AI. Teams should focus on how they can use AI to perform valuable work and accelerate businesses by augmenting their people and processes. The hype cycles around AI often present it as a magic solution that will replace all existing systems and processes, which is far from reality. 

The real challenge lies in making AI practical and achieving a reasonable return on investment (ROI). In simple terms, you should treat AI as a journey, not as a product. It’s nothing like building a website or an app, it’s much more complex in most scenarios and, thus, costs significantly more to deploy and manage.

The future of AI is ethical implementation and skill augmentation of people, not replacement

The typical, “tech-bro” AI hype often revolves around the idea of replacing workers. However, as mentioned above, the real value of AI lies in augmenting human capabilities, not replacing them.

For instance, in the HR sector, AI can handle the mundane questions that HR personnel get asked every day, freeing them up to focus on more strategic HR management and worker welfare. This approach not only enhances productivity but also respects the value of human roles and expertise, as demonstrated by Tim’s company Nebuli.com and their Nano for Teams enterprise generative AI ecosystem for HR and other departments.

To achieve a reasonable ROI, your deployment must involve identifying and pinpointing the right areas where AI can help and putting your efforts into those. The true value of AI is achieved by building an ecosystem that helps people (i.e. employees, decision-makers, and end users) become better, happier, more productive, and more data-driven, empowered by a culture of collective innovation, creativity, and agility. It is about human-machine intelligence, not just machine intelligence!

Listen to the full, two-hour discussion covering the above point in more detail, with a segment about quantum computing as the potential upcoming star of the tech world. You can listen for free via AIGeeks.com.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.
Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Shifting from AI hype to practical, ethical, and sustainable implementation appeared first on AI News.

What’s even more remarkable to witness is the rate at which both individuals and companies are embracing the AI ecosystem. A recent survey by McKinsey revealed that the number of companies that have adopted generative AI in at least one business function doubled within a year to 65%, up from 33% at the beginning of 2023. 

However, like most technological advancements, this nascent area of innovation is not short of challenges. Training and running AI programs is resource intensive endeavour, and as things stand, big tech seems to have an upper hand which creates the risk of AI centralisation. 

The computational limitation in AI development 

According to an article by the World Economic Forum, there is an accelerating demand for AI compute; the computational power required to sustain AI development is currently growing at an annual rate of between 26% and 36%.   

Another recent study by Epoch AI confirms this trajectory, with projections showing that it will soon cost billions of dollars to train or run AI programs. 

“The cost of the largest AI training runs is growing by a factor of two to three per year since 2016, and that puts billion-dollar price tags on the horizon by 2027, maybe sooner,” noted Epoch AI staff researcher, Ben Cottier. 

In my opinion, we’re already at this point. Microsoft invested $10 billion in OpenAI last year and, more recently, news emerged that the two entities are planning to build a data center that will host a supercomputer powered by millions of specialised chips. The cost? A whopping $100 billion, which is ten times more than the initial investment. 

Well, Microsoft is not the only big tech that’s on a spending spree to boost its AI computing resources. Other companies in the AI arms race, including Google, Alphabet, and Nvidia are all directing a significant amount of funding to AI research and development. 

While we can agree that the outcome could match the amount of money being invested, it is hard to ignore the fact that AI development is currently a ‘big tech’ sport. Only these deep-pocketed companies have the ability to fund AI projects to the tune of tens or hundreds of billions. 

It begs the question; what can be done to avoid the same pitfalls that Web2 innovations are facing as a result of a handful of companies controlling innovation? 

Stanford’s HAI Vice Director and Faculty Director of Research, James Landay, is one of the experts who has previously weighed in on this scenario. According to Landay, the rush for GPU resources and the prioritisation by big tech companies to use their AI computational power in-house will trigger the demand for computing power, ultimately pushing stakeholders to develop cheaper hardware solutions.

In China, the government is already stepping up to support AI startups following the chip wars with the US that have limited Chinese companies from seamlessly accessing crucial chips. Local governments within China introduced subsidies earlier this year, pledging to offer computing vouchers for AI startups ranging between $140,000 and $280,000. This effort is aimed at reducing the costs associated with computing power.

Decentralising AI computing costs

Looking at the current state of AI computing, one theme is constant — the industry is currently centralised. Big tech companies control the majority of the computing power as well as AI programs. The more things change, the more they remain the same. 

On the brighter side, this time, things might actually change for good, thanks to decentralised computing infrastructures such as the Qubic Layer 1 blockchain. This L1 blockchain uses an advanced mining mechanism dubbed the useful Proof-of-Work (PoW); unlike Bitcoin’s typical PoW which uses energy for the sole purpose of securing the network, Qubic’s uPoW utilizes its computational power for productive AI tasks such as training neural networks. 

In simpler terms, Qubic is decentralising the sourcing of AI computational power by moving away from the current paradigm where innovators are limited to the hardware they own or have rented from big tech. Instead, this L1 is tapping into its network of miners which could run into the tens of thousands to provide computational power. 

Although a bit more technical than leaving big tech to handle the backend side of things, a decentralised approach to sourcing for AI computing power is more economical. But more importantly, it would only be fair if AI innovations would be driven by more stakeholders as opposed to the current state where the industry seems to rely on a few players. 

What happens if all of them go down? Make matters worse, these tech companies have proven untrustworthy with life-changing tech advancements. 

Today, most people are up in arms against data privacy violations, not to mention other affiliated issues such as societal manipulation. With decentralised AI innovations, it will be easier to check on the developments while reducing the cost of entry.  

Conclusion 

AI innovations are just getting started, but the challenge of accessing computational power is still a headwind. To add to it, Big tech currently controls most of the resources which is a big challenge to the rate of innovation, not to mention the fact that these same companies could end up having more power over our data – the digital gold.  

However, with the advent of decentralised infrastructures, the entire AI ecosystem stands a better chance of reducing computational costs and eliminating big tech control over one of the most valuable technologies of the 21st century.

The post AI capabilities are growing faster than hardware: Can decentralisation close the gap? appeared first on AI News.

In its 2024 Environmental Report, Google discloses a concerning trend: a staggering 50% surge in emissions over the past five years. This surge can be attributed mainly to the heightened energy requirements of its AI-powered data centres. This alarming surge threatens to derail Google’s ambitious climate goals and underscores a growing conflict between technological progress and environmental sustainability.

The report, reflecting Google’s progress toward meeting its environmental goals last year, shows that the company’s total greenhouse gas emissions increased from 9.7 million metric tons of CO2 equivalent in 2019 to 14.3 million metric tons in 2023. The figure is 48% higher than in 2019, the company said, and 13% higher than in 2022. Google attributed the rise mainly to the energy consumption of its data centres, which power AI applications such as Google Search, Google Assistant, and various cloud services, as well as emissions from its supply chain

“AI is at an inflection point, and many factors will influence its ultimate impact—including the extent of AI adoption, our ability to mitigate its footprint, and the pace of continued innovation and efficiency,” the report stated. For context, as with most Big Tech, Google’s commitment to sustainability has been a cornerstone of its corporate ethos. The tech giant has pledged to operate on 24/7 carbon-free energy by 2030, aiming to set a precedent for the industry. 

However, the latest figures cast a shadow over these aspirations. AI technologies, especially those that involve deep learning and large language models, are notoriously energy-intensive. Training these models requires vast computational power, translating into substantial energy use.

“As we further integrate AI into our products, reducing emissions may be challenging due to increasing energy demands from the greater intensity of AI compute, and the emissions associated with the expected increases in our technical infrastructure investment,” Google admitted in the report.

This trend poses a significant challenge to Google’s sustainability objectives. The paradox here is striking: the technologies that promise to revolutionise industries, enhance efficiencies, and drive innovation also contribute to an escalating environmental crisis. Google’s case is not unique. Other tech giants like Microsoft and Amazon also grapple with the dual pressures of advancing AI and reducing their environmental impact. 

However, Google’s recent spike in emissions is a stark reminder of the urgent need for a balanced approach. “System-level changes are needed to address challenges such as grid decarbonisation, evolving regulations, hard-to-decarbonise industries, and the availability of carbon-free energy,” the report stated. To reconcile its AI ambitions with its climate goals, Google admits that it must intensify its efforts in several areas. 

First, there needs to be a greater emphasis on developing more energy-efficient AI models. Advances in AI chip design, such as Google’s Tensor Processing Units (TPUs), are a step in the right direction. Still, more must be done to optimise AI algorithms’ energy efficiency. Research into low-power AI and quantum computing could provide breakthroughs in this regard.

Second, Google should continue to invest heavily in renewable energy sources. While the company has made significant strides in purchasing renewable energy, achieving a 24/7 carbon-free energy supply remains a formidable challenge. The 2024 Environmental Report emphasises, “Our path to 24/7 carbon-free energy is fraught with challenges, but it is a critical component of our sustainability strategy. We are committed to overcoming these obstacles through innovation and collaboration.”

The International Energy Agency estimates that data centres’ total electricity consumption could double from 2022 levels to 1,000TWh (terawatt hours) in 2026, approximately Japan’s level of electricity demand. Calculations by research firm SemiAnalysis reckon that AI will result in data centres using 4.5% of global energy generation by 2030. Frankly, Google is not the first major technology company to point to the rapid expansion of AI as a barrier to reaching environmental goals. 

In May, Microsoft Corp. announced that its carbon emissions have increased by 30% since 2020 as the business increased its investment in AI. The rise made the company’s ambition of achieving net-zero emissions by 2030 considerably more complicated than when it announced its carbon-negative goal.

In conclusion, most tech giants’ ambitious AI-driven future is at odds with their environmental goals. This presents a formidable challenge that requires innovative solutions and unwavering commitment. Google and Microsoft’s recent environmental report provides a sobering reminder of the stakes.  

As tech giants like Google strive to lead the AI revolution, it must also lead in forging a sustainable path forward. The industry can only achieve its vision of a carbon-free future by addressing these dual priorities while continuing to innovate.

(Photo by Solen Feyissa)

See also: Google ushers in the “Gemini era” with AI advancements

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The proposed rules, focusing on curbing investments in AI, quantum computing, and semiconductors, represent the latest salvo in what many observers call a “tech cold war.” These restrictions aim to prevent China from gaining ground in technologies critical to national security, particularly those with potential military applications.

China’s Ministry of Commerce responded with “severe concern and resolute opposition,” accusing the US of politicizing and weaponizing trade and commerce issues. The ministry’s statement urges the US to “respect the rules of a market economy and the principle of fair competition,” calling for cancelling the proposed rules and improving economic relations.

The Chinese government’s strong reaction underscores the significance of these restrictions. Beijing views them as an attempt to hinder China’s technological progress and economic development, a claim it has frequently levelled against Washington in recent years. The ministry went further, asserting that the US move would “pressure the normal development of China’s industry” and disrupt the “security and stability” of global supply chains.

This latest development is part of a broader pattern of increasing technological rivalry between the US and China. The trade dispute began in 2018 under the Trump administration and has already resulted in substantial tariffs on both sides. Additionally, the US has taken steps to restrict the activities of numerous Chinese tech firms within its borders and has encouraged global enterprises to limit their business in China.

US draws new battle lines in tech race with China

As Bloomberg puts it, the recently released Notice of Proposed Rulemaking (NPRM) is essentially one of several bureaucratic steps set in motion by an executive order issued last August. The proposed US rules are comprehensive in scope, covering various types of investments, including equity acquisitions, certain debt financing, joint ventures, and even some limited partner investments in non-US pooled investment funds. 

However, the proposal includes exemptions, such as investments in publicly traded companies and full ownership buyouts, possibly to balance national security concerns with maintaining some level of economic engagement. The focus on AI in these restrictions is particularly noteworthy. 

The US administration has expressed concerns about China developing AI applications for weapons targeting and mass surveillance, highlighting the dual-use nature of this technology and the ethical considerations surrounding its development. This emphasis on AI reflects its growing importance in future technological and economic competitiveness.

The price of this tech tug-of-war

The potential impact of these rules extends far beyond the immediate US-China relationship. They could lead to a further decoupling of the US and Chinese tech ecosystems, potentially accelerating China’s efforts to achieve technological self-sufficiency. Moreover, these restrictions could have ripple effects on international collaborations in scientific research and technological development, potentially slowing progress across the board.

From a geopolitical perspective, this move will likely further complicate US-China relations, which are already strained by trade disputes and human rights concerns. It may also prompt other countries to reassess their policies regarding tech investments and knowledge sharing with China.

The challenge for the Biden administration will be to effectively protect US national security interests without stifling innovation or causing undue economic harm. China’s assertion of its right to take countermeasures adds another layer of uncertainty to an already complex situation. How Beijing responds could have significant implications for global trade and technology development.

(Photo by Chenyu Guan)

See also: US introduces new AI chip export restrictions

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The ambitious plans were announced this week by President Biden and Japanese Prime Minister Kishida Fumio following Kishida’s Official Visit to the White House.

While the leaders affirmed their commitment across a broad range of areas including defence, climate, development, and humanitarian efforts, the new technology collaborations took centre stage and underscore how the US-Japan alliance is evolving into a comprehensive global partnership underpinned by innovation.

AI takes centre stage

One of the headline initiatives is a $110 million partnership between the University of Washington, University of Tsukuba, Carnegie Mellon University, and Keio University. Backed by tech giants like NVIDIA, Arm, Amazon, and Microsoft—as well as Japanese companies—the program aims to solidify US-Japan leadership in cutting-edge AI research and development.

The US and Japan also committed to supporting each other in establishing national AI Safety Institutes and pledged future collaboration on interoperable AI safety standards, evaluations, and risk management frameworks.

In a bid to mitigate AI risks, the countries vowed to provide transparency around AI-generated and manipulated content from official government channels. Technical research and standards efforts were promised to identify and authenticate synthetic media.

Quantum leaps

Quantum technology featured prominently, with the US National Institute of Standards and Technology (NIST) partnering with Japan’s National Institute of Advanced Industrial Science and Technology (AIST) to build robust quantum supply chains.

Trilateral cooperation between the University of Chicago, University of Tokyo, and Seoul National University was also announced to train a quantum workforce and bolster competitiveness.  

The US and Japan additionally welcomed new commercial deals including Quantinuum providing Japan’s RIKEN institute with $50 million in quantum computing services over five years.

Several semiconductor initiatives were unveiled such as potential cooperation between Japan’s Leading-edge Semiconductor Technology Center (LSTC) with the US National Semiconductor Technology Center and National Advanced Packaging Manufacturing Program. The countries pledged to explore joint semiconductor workforce development initiatives through technical workshops.

Other announced commercial deals spanned cloud computing, telecommunications, batteries, robotics, biotechnology, finance, transportation and beyond—highlighting how the alliance is fusing public and private efforts.

Developing humans

Initiatives around STEM education exchanges, technology curriculums, entrepreneur programs, and talent circulation efforts emphasised the focus on developing human capital to power the coming wave of digital innovation.

While the technological breakthroughs grab attention, the proliferation of initiatives aimed at training, exchanging, and nurturing the innovators, researchers, and professionals across these domains could prove just as vital. The US and Japan appear determined to strategically develop and leverage human resources in lockstep with their efforts to establish cutting-edge AI, quantum, chip, and other advanced tech capabilities.

Both nations clearly recognise that building complementary ecosystems across vital technologies is essential to bolstering competitiveness, economic prosperity, and national security in an era of intensifying strategic competition.

(Photo by Tong Su)

See also: Microsoft AI opens London hub to access ‘enormous pool’ of talent

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Ten times more powerful than its predecessor, but using less electricity thanks to Lenovo’s direct water cooling, the new supercomputer will power AI research for UK industry

The new supercomputer is part of the Hartree Centre’s £210 million Hartree National Centre for Digital Innovation (HNCDI) programme, which provides UK industry access to state-of-the-art digital technologies and expertise and is complementary to investments in the wider AI Research Resource (AIRR). 

It will support the HNCDI’s rapidly expanding supercomputing and AI activities, and will be installed later this year at its new £30 million supercomputing centre, currently under construction.   

A leap in supercomputing processing power

A 44.7 petaflop system, the Lenovo ThinkSystem Neptune will perform more than 44 quadrillion floating point operations (calculations) per second.

To put this into context, if you were to carry out one calculation per second, it would take nearly 1400 million years to reach this number.

The new GPU-based system (graphics processing unit) is perfect for AI workloads, and marks a significant leap for the Hartree Centre’s capabilities, with ten times the processing power of its current system, Scafell Pike. Furthermore, it will be more power-efficient, taking up less space and using less electricity per unit of performance.

The new supercomputer uses innovative warm water cooling which can reduce energy demands by up to 40% while boosting performance by up to 10%.

Powering UK Industry with AI

Located at STFC’s Daresbury Laboratory, at Sci-Tech Daresbury in the Liverpool City Region, the Hartree Centre is the UK’s only supercomputing centre dedicated to industry engagement. This capability will drive forward innovation in industry use cases and applications.

Its HNCDI programme plays a vital role in equipping businesses with skills and technical knowledge to adopt emerging digital technologies, including supercomputing, quantum computing, and AI.

It is enabling productivity, innovation and growth in UK organisations through access to these advanced supercomputing technologies, which are typically available only to academia and large-scale industry,

Solving global challenges

At the HNCDI, the new supercomputer will be strategically positioned to contribute to discovery-led industrial research, focusing on solutions to global challenges in areas such as:

• weather and climate modelling
• cleaner energy initiatives
• drug discovery
• health technologies
• new materials
• automotive advancements
• legal applications

This includes the Hartree Centre’s continued collaboration with the UK Atomic Energy Authority, which is using the Centre to research new reactors for clean nuclear fusion energy.

Ultimately, the new supercomputer will reduce the time and cost associated with making research breakthroughs, including for organisations such as the Met Office, Unilever and Rolls Royce, that the Hartree Centre has continued to work with over the last decade.

Kate Royse, director, STFC Hartree Centre, said: “We are very excited to be working with Lenovo on our next generation of supercomputer at the Hartree Centre. Our mission is to equip UK industry with the knowledge, skills and compute needed to fully unlock the potential of advanced digital technologies. With our new supercomputer we will be able to support UK industry in the use of big data and AI technologies to enable UK businesses to take a leading role internationally on the responsible adoption and exploitation of AI technology.”

Noam Rosen, EMEA director HPC/AI, Lenovo, said: “Lenovo is equally enthusiastic about our collaboration with the Hartree Centre on its ambitious journey to revolutionize HPC and AI capabilities in the UK. Our collaboration is not just about delivering a state-of-the-art supercomputer; it’s about building a versatile, robust, and powerful system tailored to meet the Centre’s diverse and evolving needs. From advanced modeling and simulation in various scientific disciplines to pioneering work in AI and machine learning, this new power-efficient supercomputer will be a cornerstone for innovation, pushing the boundaries of big data and AI technologies to bolster the UK industry’s global leadership in responsible and ethical technology adoption.”

Mark Thomson, Executive Chair, STFC, said: “STFC’s agreement with Lenovo is an exciting milestone in our mission to provide UK businesses with access to the vital infrastructure and expertise that will help them to grow and succeed on a global scale, which in turn will drive productivity and job creation. By enabling UK industry to adopt advanced digital technologies, we are supporting the government ambitions to build a competitive and innovative digital economy that will both turbo drive economic growth and reap societal benefits for the UK, as well as for the UK to be a global AI superpower.”

The HNCDI new Lenovo supercomputer in numbers:

• The ThinkSystem Neptune can perform the same number of calculations as 20,790 top of the range smartphones
• An hour of calculation on a market leading smartphone would take 0.17 seconds
• It can hold 4500 hours of 4k video in its working memory
• It can hold 60,000 hours of 4k video in its hard disks

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The new Memorandum of Understanding on compute was signed in Ottawa by UK Technology Secretary Michelle Donelan and Canadian Minister for Innovation, Science and Industry François-Phillippe Champagne. It cements the two countries’ partnership on AI by committing them to explore ways to give researchers and companies affordable access to the high-powered computing capacity required for cutting-edge AI systems.

Compute power and data are essential ingredients for developing modern AI models and applications. As AI rapidly advances, access to state-of-the-art computing infrastructure is increasingly vital for conducting groundbreaking research and staying globally competitive. The UK-Canada agreement recognises this and aims to foster joint innovation by improving compute access.

Specifically, under the new agreement, the UK and Canada will look at opportunities for collaborating on providing compute power for shared research priorities like biomedicine. They also intend to work together – and with like-minded countries – on sustainable models for sharing compute capabilities. 

The compute agreement builds on a wider UK-Canada science and technology partnership also renewed during Secretary Donelan’s visit. This partnership identifies quantum computing, AI, semiconductors and clean energy as key areas for increased collaboration between British and Canadian researchers. It also focuses on coordinating scientific diplomacy efforts relating to new technologies.

Academics and researchers from both countries have been actively involved in collaborative programs, with £350 million awarded by UK Research and Innovation between 2020 and 2023. This includes pioneering initiatives like the first industry-led partnership on quantum technologies and a project on arctic ecosystems in collaboration with Inuit Tapiriit Kanatami.

The latest accords reinforce the two countries’ “unique partnership” across science and innovation, said Secretary Donelan. She emphasised their commitment to harnessing emerging technologies as an “active force for good.”

Minister Champagne echoed this, saying the agreements will have “positive impacts across all fields of research and innovation.” He highlighted opportunities to link leading AI researchers in both countries.

The renewal of UK-Canada science ties comes as Secretary Donelan meets with AI experts and companies during a three-day visit. She held discussions on the future of AI with Yoshua Bengio, a pioneer in the field and recipient of the Turing Award, computing’s highest honour.

With a combined $5 trillion economy, the UK and Canada have committed to collaborating closely on technological innovation for the benefit of both countries and the wider world. The compute accord marks an important step toward realising that vision in the critical field of AI.

(Photo by Scott Graham on Unsplash)

See also: Financial services introducing AI but hindered by data issues

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GlobalData highlights a 14 percent compound annual growth rate (CAGR) increase in related patent filings from 2020 to 2022, underscoring the vast influence and potential of quantum AI across industries.

Adarsh Jain, Director of Financial Markets at GlobalData, emphasises the transformative nature of Quantum AI:

“Quantum AI represents a transformative advancement in technology. As we integrate quantum principles into AI algorithms, the potential for speed and efficiency in processing complex data sets grows exponentially. This not only enhances current AI applications but also opens new possibilities across various industries. 

The surge in patent filings is a testament to its growing importance and the pivotal role it will play in the future of AI-driven solutions.”

Kiran Raj, Practice Head of Disruptive Tech at GlobalData, highlights that while AI thrives on data and computational power, the inner workings of the technology often remain unclear. Quantum computing not only promises increased power but also potentially provides greater insights into these workings, paving the way for AI to transcend its current capabilities.

GlobalData’s Disruptor Intelligence Center analysis reveals significant synergy between quantum computing and AI innovations, leading to revolutionary impacts in various industries. Notable collaborations include HSBC and IBM in finance, Menten AI’s healthcare advancements, Volkswagen’s partnership with Xanadu for battery simulation, Intel’s Quantum SDK, and Zapata’s collaboration with BMW.

Raj concludes with a note of caution: “Quantum AI offers the potential for smarter, faster AI systems, but its adoption is complex and demands caution. The technology is still in its early stages, requiring significant investment and expertise.

“Key challenges include the need for advanced cybersecurity measures and ensuring ethical AI practices as we navigate this promising yet intricate landscape.”

(Photo by Anton Maksimov 5642.su on Unsplash)

See also: Google expands partnership with Anthropic to enhance AI safety

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

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