Interdisciplinary approaches

AI is transforming patient care and medical visits

AI is increasingly shaping the patient experience, from digital intake forms to AI-powered ambient scribes in exam rooms. Stanford experts explain that while these tools can streamline processes, patients should remain aware of how their data is collected, stored, and used.

De-identified information may still be shared for research, marketing, or AI training, raising privacy considerations.

AI is also transforming treatment planning. Platforms like Atropos Health allow doctors to query hundreds of millions of records, generating real-world evidence to inform faster and more effective care.

Patients may benefit from data-driven treatment decisions, but human oversight remains essential to ensure accuracy and safety.

Outside the clinic, AI is being integrated into health apps and devices. From mental health support to disease detection, these tools offer convenience and early insights. Experts warn that stronger evaluation and regulation are needed to confirm their reliability and effectiveness.

Patients are encouraged to ask providers about data storage, third-party access, and real-time recording during visits. While AI promises to improve healthcare, realistic expectations are vital, and individuals should actively monitor how their personal health information is used.

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Swiss scientists grow mini-brains to power future computers

In a Swiss laboratory, researchers are using clusters of human brain cells to power experimental computers. The start-up FinalSpark is leading this emerging field of biocomputing, also known as wetware, which uses living neurons instead of silicon chips.

Co-founder Fred Jordan said biological neurons are vastly more energy-efficient than artificial ones and could one day replace traditional processors. He believes brain-based computing may eventually help reduce the massive power demands created by AI systems.

Each ‘bioprocessor’ is made from human skin cells reprogrammed into neurons and grouped into small organoids. Electrodes connect to these clumps, allowing the Swiss scientists to send signals and measure their responses in a digital form similar to binary code.

Scientists emphasise that the technology is still in its infancy and not capable of consciousness. Each organoid contains about ten thousand neurons, compared to a human brain’s hundred billion. FinalSpark collaborates with ethicists to ensure the research remains responsible and transparent.

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Startup raises $9m to orchestrate Gulf digital infrastructure

Bilal Abu-Ghazaleh has launched 1001 AI, a London–Dubai startup building an AI-native operating system for critical MENA industries. The two-month-old firm raised $9m seed from CIV, General Catalyst and Lux Capital, with angels including Chris Ré, Amjad Masad and Amira Sajwani.

Target sectors include airports, ports, construction, and oil and gas, where 1001 AI sees billions in avoidable inefficiencies. Its engine ingests live operational data, models workflows and issues real-time directives, rerouting vehicles, reassigning crews and adjusting plans autonomously.

Abu-Ghazaleh brings scale-up experience from Hive AI and Scale AI, where he led GenAI operations and contributor networks. 1001 borrows a consulting-style rollout: embed with clients, co-develop the model, then standardise reusable patterns across similar operational flows.

Investors argue the Gulf is an ideal test bed given sovereign-backed AI ambitions and under-digitised, mission-critical infrastructure. Deena Shakir of Lux says the region is ripe for AI that optimises physical operations at scale, from flight turnarounds to cargo moves.

First deployments are slated for construction by year-end, with aviation and logistics to follow. The funding supports early pilots and hiring across engineering, operations and go-to-market, as 1001 aims to become the Gulf’s orchestration layer before expanding globally.

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AWS outage shows the cost of cloud concentration

A single fault can bring down the modern web. During the outage on Monday, 20 October 2025, millions woke to broken apps, games, banking, and tools after database errors at Amazon Web Services rippled outward. When a shared backbone stumbles, the blast radius engulfs everything from chat to commerce.

The outage underscored cloud concentration risk. Roblox, Fortnite, Pokémon Go, Snapchat, and workplace staples like Slack and Monday.com stumbled together because many depend on the same region and data layer. Failover, throttling, and retries help, but simultaneous strain can swamp safeguards.

On Friday, 19 July 2024, a faulty CrowdStrike update crashed Windows machines worldwide, triggering blue screens that grounded flights, delayed surgeries, and froze point-of-sale systems. The fix was simple; recovery wasn’t. Friday patches gained a new cautionary tale.

Earlier shocks foreshadowed today’s scale. In 1997, a Network Solutions glitch briefly hobbled .com and .net. In 2018, malware in Alaska’s Matanuska-Susitna knocked services offline, sending a community of 100,000 back to paper. Each incident showed how mundane errors cascade into civic life.

Resilience now means multi-region designs, cross-cloud failovers, tested runbooks, rate-limit backstops, and graceful read-only modes. Add regulatory stress tests, clear incident comms, and sector drills with hospitals, airlines, and banks. The internet will keep breaking; our job is to make it bend.

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SMEs underinsured as Canada’s cyber landscape shifts

Canada’s cyber insurance market is stabilising, with stronger underwriting, steadier loss trends, and more product choice, the Insurance Bureau of Canada says. But the threat landscape is accelerating as attackers weaponise AI, leaving many small and medium-sized enterprises exposed and underinsured.

Rapid market growth brought painful losses during the ransomware surge: from 2019 to 2023, combined loss ratios averaged about 155%, forcing tighter pricing and coverage. Insurers have recalibrated, yet rising AI-enabled phishing and deepfake impersonations are lifting complexity and potential severity.

Policy is catching up unevenly. Bill C-8 in Canada would revive critical-infrastructure cybersecurity standards, stronger oversight, and baseline rules for risk management and incident reporting. Public–private programmes signal progress but need sustained execution.

SMEs remain the pressure point. Low uptake means minor breaches can cost tens or hundreds of thousands, while severe incidents can be fatal. Underinsurance shifts shock to the wider economy, challenging insurers to balance affordability with long-term viability.

The Bureau urges practical resilience: clearer governance, employee training, incident playbooks, and fit-for-purpose cover. Education campaigns and free guidance aim to demystify coverage, boost readiness, and help SMEs recover faster when attacks hit, supporting a more durable digital economy.

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Tailored pricing is here and personal data is the price signal

AI is quietly changing how prices are set online. Beyond demand-based shifts, companies increasingly tailor offers to individuals, using browsing history, purchase habits, device, and location to predict willingness to pay. Two shoppers may see different prices for the same product at the same moment.

Dynamic pricing raises or lowers prices for everyone as conditions change, such as school-holiday airfares or hotel rates during major events. Personalised pricing goes further by shaping offers for specific users, rewarding cart-abandoners with discounts while charging rarer shoppers a premium.

Platforms mine clicks, time on page, past purchases, and abandoned baskets to build profiles. Experiments show targeted discounts can lift sales while capping promo spend, proving engineered prices scale. The result: you may not see a ‘standard’ price, but one designed for you.

The risks are mounting. Income proxies such as postcode or device can entrench inequality, while hidden algorithms erode trust when buyers later find cheaper prices. Accountability is murky if tailored prices mislead, discriminate, or breach consumer protections without clear disclosure.

Regulators are moving. A competition watchdog in Australia has flagged transparency gaps, unfair trading risks, and the need for algorithmic disclosure. Businesses now face a twin test: deploy AI pricing with consent, explainability, and opt-outs, and prove it delivers value without crossing ethical lines.

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AWS glitch triggers widespread outages across major apps

A major internet outage hit some of the world’s biggest apps and sites from about 9 a.m. CET Monday, with issues traced to Amazon Web Services. Tracking sites reported widespread failures across the US and beyond, disrupting consumer and enterprise services.

AWS cited ‘significant error rates’ in DynamoDB requests in the US-EAST-1 region, impacting additional services in Northern Virginia. Engineers are mitigating while investigating root cause, and some customers couldn’t create or update Support Cases.

Outages clustered around Virginia’s dense data-centre corridor but rippled globally. Impacted brands included Amazon, Google, Snapchat, Roblox, Fortnite, Canva, Coinbase, Slack, Signal, Vodafone and the UK tax authority HMRC.

Coinbase told users ‘all funds are safe’ as platforms struggled to authenticate, fetch data and serve content tied to affected back-ends. Third-party monitors noted elevated failure rates across APIs and app logins.

The incident underscores heavy reliance on hyperscale infrastructure and the blast radius when core data services falter. Full restoration and a formal post-mortem are pending from AWS.

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AI and fusion combine to accelerate clean energy breakthroughs

A new research partnership between Google and Commonwealth Fusion Systems (CFS) aims to accelerate the development of clean, abundant fusion energy. Fusion powers the sun and offers limitless, clean energy, but achieving it on Earth requires stabilising plasma at over 100 million degrees Celsius.

The collaboration builds on prior AI research in controlling plasma using deep reinforcement learning. Google and CFS are combining AI with the SPARC tokamak, using superconducting magnets to achieve net energy gain from fusion.

AI tools such as TORAX, a fast and differentiable plasma simulator, allow millions of virtual experiments to optimise plasma behaviour before SPARC begins operations.

AI is also being applied to find the most efficient operating paths for the tokamak, including optimising magnetic coils, fuel injection, and heat management.

Reinforcement learning agents can optimise energy output in real time while safeguarding the machine, potentially exceeding human-designed methods.

The partnership combines advanced AI with fusion hardware to develop intelligent, adaptive control systems for future clean and sustainable fusion power plants.

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Labels and Spotify align on artist-first AI safeguards

Spotify partners with major labels on artist-first AI tools, putting consent and copyright at the centre of product design. The plan aims to align new features with transparent labelling and fair compensation while addressing concerns about generative music flooding platforms.

The collaboration with Sony, Universal, Warner, and Merlin will give artists control over participation in AI experiences and how their catalogues are used. Spotify says it will prioritise consent, clearer attribution, and rights management as it builds new tools.

Early direction points to expanded labelling via DDEX, stricter controls against mass AI uploads, and protections against search and recommendation manipulation. Spotify’s AI DJ and prompt-based playlists hint at how engagement features could evolve without sidelining creators.

Future products are expected to let artists opt in, monitor usage, and manage when their music feeds AI-generated works. Rights holders and distributors would gain better tracking and payment flows as transparency improves across the ecosystem.

Industry observers say the tie-up could set a benchmark for responsible AI in music if enforcement matches ambition. By moving in step with labels, Spotify is pitching a path where innovation and artist advocacy reinforce rather than undermine each other.

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Between trips, Uber pilots paid AI data work

Uber is piloting ‘Digital Tasks’ in the US, letting select drivers and couriers earn by training AI models between trips.

Tasks include short selfie videos in any language, uploading multilingual documents, and uploading category-tagged images; each takes minutes, and pay varies by task.

Uber says demand came from US drivers seeking off-road income; participants can opt in via the Work Hub and need no extra experience.

Partners commissioning the data aren’t named. The pilot starts later this year, with potential expansion to non-drivers and wider markets.

The move diversifies beyond rides and delivery as robotaxis loom. Uber argues for more earning channels now, while autonomy scales over time.

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