Capacity development Archives | Page 184 of 332

AI tools bring new hope for cardiovascular medicine

AI, omics, and systems biology enable targeted drugs for heart disease pathways once considered untreatable. A new study in Frontiers in Science highlights how these innovations could revolutionise treatment and save millions of lives.

Heart disease remains the leading global killer, partly because generic treatments like statins do not account for individual biological differences.

Researchers say AI-powered precision medicine can identify new gene and protein targets, enabling personalised therapies for each patient’s unique heart disease.

RNA-based drugs are emerging as an up-and-coming solution. Unlike conventional medicines that reach only limited protein targets, RNA therapies can influence almost any gene and may be developed more quickly.

Early trials show they can lower cholesterol more effectively than traditional approaches, with potential to address long-standing ‘undruggable’ pathways in cardiovascular disease.

Experts say realising these treatments requires global leadership and collaboration across academia, industry, and healthcare. Bold investment and open science are crucial to make precision medicine global and reduce heart disease, expected to cause 26 million deaths annually by 2030.

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ABB sells Robotics division to SoftBank in $5.4 billion deal

The Swedish-Swiss electrical engineering corporation ABB has agreed to sell its Robotics division to Japan’s SoftBank Group for an enterprise value of $5.375 billion, abandoning plans for a spin-off.

However, the move marks one of the most significant robotics transactions in recent years, and reflects both firms’ ambition to drive the next era of AI-based automation.

A divestment that will allow ABB to focus on its core businesses in electrification and automation, while SoftBank expands its ‘Physical AI’ strategy.

ABB said the sale would create immediate shareholder value and that proceeds would be used according to its capital allocation principles.

The Robotics division, which employs around 7,000 people and generated $2.3 billion in 2024 revenues, will become part of SoftBank’s portfolio upon completion of the deal, expected by mid-to-late 2026. The transaction is projected to yield ABB a pre-tax book gain of about $2.4 billion.

SoftBank founder Masayoshi Son said the acquisition aligns with his vision to combine artificial superintelligence and robotics to ‘propel humanity forward’.

ABB’s CEO Morten Wierod said the partnership would unite ABB’s industrial expertise with SoftBank’s AI capabilities, strengthening its global leadership in advanced robotics.

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Opal’s global rollout spans 15 countries with major feature upgrades

Google is expanding access to Opal, its no-code AI mini-app builder. Introduced two months ago within Google Labs, the tool enables users to create AI-powered mini-apps through natural language prompts, eliminating the need for coding.

According to Megan Li, Senior Product Manager at Google Labs, the expansion follows strong early engagement from creators. Users can access Opal at opal.withgoogle.com and join its builder community through Discord.

New debugging features aim to make workflows more transparent and efficient. Users can now run workflows step by step in a visual editor or adjust specific steps in the console, with real-time error reporting.

Performance upgrades have been introduced to speed up app creation, while parallel run capabilities enable simultaneous workflow steps. The rollout covers India, Canada, Japan, South Korea, Vietnam, Indonesia, Brazil, Singapore, Colombia, El Salvador, Costa Rica, Panamá, Honduras, and Argentina.

Meanwhile, Google DeepMind has launched Gemini 2.5 Computer Use, a specialised model capable of interacting with user interfaces. Available in preview through the Gemini API, it can be accessed via Google AI Studio and Vertex AI Studio.

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Africa launches world’s largest tokenised economy with $5.5 billion

Global Settlement Network (GSN) and Diacente Group have partnered to establish Africa’s most advanced tokenised economy, valued at $5.5 billion in real-world infrastructure. The collaboration digitises assets across food production, minerals, renewable energy, and trade.

The initiative aims to create an inclusive, efficient economic system, leveraging blockchain to enhance emerging markets’ global participation.

Uganda leads with its first Central Bank Digital Currency (CBDC) pilot, deployed on GSN’s permissioned blockchain and backed by treasury bonds. Agro-processing hubs, mining operations, and solar plants underpin the tokenisation effort.

Fully compliant with KYC and AML regulations, the digital shilling enables over 40 million users to transact securely via smartphones and USSD, fostering financial inclusion across East Africa.

The project supports Uganda’s Vision 2040 and the African Union’s Agenda 2063, aligning with the goals of the African Continental Free Trade Area. Leaders project one million jobs and $10 billion in annual exports.

Ryan Kirkley, GSN co-founder, calls it a ‘programmable economy grounded in real assets,’ while Diacente’s Edgar Agaba emphasises attracting investment and empowering local industries through transparent, tech-driven systems.

The partnership sets a precedent for emerging markets, reducing reliance on intermediaries and unlocking global capital. Tokenisation integrated with national development drives sustainable growth, offering a scalable model for digital economies based on real infrastructure and regulatory collaboration.

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Power grid spending surges as US braces for data centre and AI boom

US electric utilities are set to spend nearly $208 billion on the power grid in 2025 and more than $1.1 trillion over the next five years, according to the Edison Electric Institute. The surge in investment reflects rising demand from data centres, artificial intelligence, and wider electrification across the economy.

EEI data shows that investor-owned utilities spent $765 billion on capital projects in the five years to 2024. The new spending represents a significant increase and is aimed at upgrading and expanding infrastructure to keep pace with the accelerating demand for electricity.

The growing investment comes as demand from energy-intensive technologies continues to rise. Data ce n tres and AI workloads are driving sustained growth in US power consumption, placing unprecedented pressure on existing infrastructure and prompting utilities to scale up their spending plans.

David Weeks, supply chain industry practice lead at Moody’s, warned that the escalating energy crisis could become a limiting factor across multiple industries. He said grid constraints and permitting delays must be factored into corporate supply chain strategies to avoid future disruptions.

As electrification spreads across the economy, grid reliability and capacity are becoming critical considerations for companies. The planned investment underscores the urgency of modernising the power grid to support economic growth while adapting to new technological demands.

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Machine learning helps prevent disruptions in fusion devices

Researchers at MIT have developed a predictive model that could make fusion power plants more reliable and safe. The approach uses machine learning and physics-based simulations to predict plasma instabilities and prevent damage during tokamak shutdowns.

Experimental tokamaks use strong magnets to contain plasma hotter than the sun’s core. They often face challenges in safely ramping down plasma currents that circulate at extreme speeds and temperatures.

The model was trained and tested on data from the Swiss TCV tokamak. Combining neural networks with physics simulations, the team achieved accurate predictions using few plasma pulses, saving costs and overcoming limited experimental data.

The system can now generate practical ‘trajectories’ for controllers to adjust magnets and temperatures, helping to safely manage plasma during shutdowns.

Researchers say the method could be particularly important as fusion devices scale up to grid-level energy production. High-energy plasmas in larger reactors pose greater risks, and uncontrolled terminations could damage the machine.

The new model allows operators to carefully balance rampdowns, avoiding disruptions and ensuring safer, more efficient operation.

Work on the predictive model is part of wider collaboration with Commonwealth Fusion Systems and supported by the EUROfusion Consortium and Swiss research institutions. Scientists see it as a crucial step toward making fusion a practical, reliable, and sustainable energy source.

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MIT AI reveals how antibiotic targets Crohn’s bacteria

MIT and McMaster researchers used AI to map how a narrow-spectrum antibiotic attacks harmful gut bacteria. Enterololin targets E. coli linked to Crohn’s flares while preserving most of the microbiome, providing a precise alternative to broad-spectrum antibiotics.

AI accelerated the process of identifying the drug’s mechanism of action, reducing a task that usually takes years to just months.

The team used DiffDock, a generative AI tool developed at MIT, to predict how enterololin binds to a protein complex called LolCDE in E. coli. Laboratory experiments, including mutant evolution, RNA sequencing, and CRISPR knockdowns, confirmed the AI predictions.

The method demonstrates how AI can provide mechanistic insights, guide experiments, and speed up early-stage antibiotic development.

Enterololin improved recovery and preserved the microbiome in mouse models compared with conventional treatments. Researchers aim to develop derivatives against resistant pathogens like Klebsiella pneumoniae, with early work underway at spinout company Stoked Bio.

The study highlights broader implications for precision antibiotics, which could treat infections without disrupting beneficial microbes. AI-driven mechanism mapping could speed up drug discovery, cut costs, and help tackle antimicrobial resistance.

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Google expands Gemini-powered AI Search across the globe

Google has expanded its AI Mode in Search, supporting over 35 new languages and 40 more countries and territories. The rollout expands access across Europe and other regions, reaching over 200 countries and territories worldwide.

The update aims to make AI-powered Search more accessible globally, allowing people to interact with Search in their native language. Expanding language support, Google will enable users to ask questions and access information in their preferred language.

AI Mode is powered by Google’s latest Gemini models, which deliver advanced reasoning and multimodal understanding. These capabilities help the system grasp the subtleties of local languages and provide relevant, context-aware answers, making AI Mode genuinely useful across diverse regions.

According to Google, people using AI Mode tend to explore topics in far greater depth, with queries nearly three times longer than traditional searches. The enhanced experience will continue to roll out globally over the coming week.

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Nobel Prize awarded for tunnelling in superconducting circuits

The 2025 Nobel Prize in Physics has been awarded to John Clarke, Michel Devoret and John Martinis for their experiments that brought quantum mechanical effects into macroscopic systems.

The Royal Swedish Academy of Sciences cited their ‘discovery of macroscopic quantum mechanical tunnelling and energy quantisation in an electric circuit’.

In classic quantum mechanics, particles can sometimes cross through energy barriers via a process known as tunnelling, behaviour that typically occurs at atomic or subatomic scales.

The laureates’ work showed that such quantum phenomena can appear in larger electrical circuits using superconductors and Josephson junctions, systems that were thought to be firmly in the domain of classical physics.

Their experiments (conducted in the mid-1980s) involved circuits made of superconducting materials separated by a thin insulating barrier. By finely tuning currents and electromagnetic stimuli, they were able to force a system to switch between zero-voltage and finite voltage states, essentially demonstrating that the circuit could ‘tunnel’ from one state to another.

In addition, they demonstrated energy quantisation in these systems, that the circuits absorb and emit energy in discrete packets, consistent with quantum theory.

This work is widely viewed as a foundational bridge between theoretical quantum mechanics and practical quantum technology. Superconducting circuits (such as qubits in quantum computers) rely on precisely these kinds of effects, and the laureates’ results helped validate the notion that quantum engineering is possible in engineered devices.

As the Nobel announcement puts it, their experiments ‘revealed quantum physics in action’ in a device small enough to hold in hand.

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Study shows how AI can uncover hidden biological mechanisms

Researchers in China have used AI to reveal how different species independently develop similar traits when adapting to shared environments. The study focuses on echolocation in bats and toothed whales, two distant groups that created this ability separately despite their evolutionary differences.

The Institute of Zoology, Chinese Academy of Sciences team found that high-order protein features are crucial to adaptive convergence. Convergent evolution is the independent emergence of similar traits across species, often under similar ecological pressures.

Led by Zou Zhengting, the researchers developed a framework called ACEP, which utilises a pre-trained protein language model to analyse amino acid sequences. This method reveals hidden structural and functional information in proteins, shedding light on how traits are formed at the molecular level.

The findings, published in the Proceedings of the National Academy of Sciences, reveal how AI can detect deep biological patterns behind convergent evolution. The study demonstrates how combining AI with protein analysis provides powerful tools for understanding complex evolutionary mechanisms.

Zou said the work deepens the understanding of life’s evolutionary laws and highlights the growing role of AI in biology. The team in China hopes this approach can be applied to other evolutionary questions, broadening the use of AI in decoding life’s hidden patterns.

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