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IBM advances quantum computing understanding with new project

IBM has introduced two new quantum processors, named ‘Nighthawk’ and ‘Loon’, aimed at major leaps in quantum computing. The Nighthawk chip features 120 qubits and 218 tunable couplers, enabling circuits with approximately 30% greater complexity than previous models.

The Loon processor is designed as a testbed for fault-tolerant quantum computing, implementing key hardware components, including six-way qubit connectivity and long-range couplers. These advances mark a strategic shift by IBM to scale quantum systems beyond experimental prototypes.

IBM has also upgraded its fabrication process by shifting to 300 mm wafers at its Albany NanoTech facility, which has doubled development speed and boosted physical chip complexity tenfold.

Looking ahead, IBM projects the initial delivery of Nighthawk by the end of 2025 and aims to achieve verified quantum advantage by the end of 2026, with fully fault-tolerant quantum systems targeted by 2029.

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AI Scientist Kosmos links every conclusion to code and citations

OpenAI chief Sam Altman has praised Future House’s new AI Scientist, Kosmos, calling it an exciting step toward automated discovery. The platform upgrades the earlier Robin system and is now operated by Edison Scientific, which plans a commercial tier alongside free access for academics.

Kosmos addresses a key limitation in traditional models: the inability to track long reasoning chains while processing scientific literature at scale. It uses structured world models to stay focused on a single research goal across tens of millions of tokens and hundreds of agent runs.

A single Kosmos run can analyse around 1,500 papers and more than 40,000 lines of code, with early users estimating that this replaces roughly six months of human work. Internal tests found that almost 80 per cent of its conclusions were correct.

Future House reported seven discoveries made during testing, including three that matched known results and four new hypotheses spanning genetics, ageing, and disease. Edison says several are now being validated in wet lab studies, reinforcing the system’s scientific utility.

Kosmos emphasises traceability, linking every conclusion to specific code or source passages to avoid black-box outputs. It is priced at $200 per run, with early pricing guarantees and free credits for academics, though multiple runs may still be required for complex questions.

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NVIDIA brings RDMA acceleration to S3 object storage for AI workloads

AI workloads are driving unprecedented data growth, with enterprises projected to generate almost 400 zettabytes annually by 2028. NVIDIA says traditional storage models cannot match the speed and scale needed for modern training and inference systems.

The company is promoting RDMA for S3-compatible storage, which accelerates object data transfers by bypassing host CPUs and removing bottlenecks associated with TCP networking. The approach promises higher throughput per terabyte and reduced latency across AI factories and cloud deployments.

Key benefits include lower storage costs, workload portability across environments and faster access for training, inference and vector database workloads. NVIDIA says freeing CPU resources also improves overall GPU utilisation and project efficiency.

RDMA client libraries run directly on GPU compute nodes, enabling faster object retrieval during training. While initially optimised for NVIDIA hardware, the architecture is open and can be extended by other vendors and users seeking higher storage performance.

Cloudian, Dell and HPE are integrating the technology into products such as HyperStore, ObjectScale and Alletra Storage MP X10000. NVIDIA is working with partners to standardise the approach, arguing that accelerated object storage is now essential for large-scale AI systems.

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New funding round by Meta strengthens local STEAM education

Meta is inviting applications for its 2026 Data Centre Community Action Grants, which support schools, nonprofits and local groups in regions that host the company’s data centres.

The programme has been a core part of Meta’s community investment strategy since 2011, and the latest round expands support to seven additional areas linked to new facilities. The company views the grants as a means of strengthening long-term community vitality, rather than focusing solely on infrastructure growth.

Funding is aimed at projects that use technology for public benefit and improve opportunities in science, technology, engineering, arts and mathematics. More than $ 74 million has been awarded to communities worldwide, with $ 24 million distributed through the grant programme alone.

Recipients can reapply each year, which enables organisations to sustain programmes and increase their impact over time.

Several regions have already demonstrated how the funding can reshape local learning opportunities. Northern Illinois University used grants to expand engineering camps for younger students and to open a STEAM studio that supports after-school programmes and workforce development.

In New Mexico, a middle school used funding to build a STEM centre with advanced tools such as drones, coding kits and 3D printing equipment. In Texas, an enrichment organisation created a digital media and STEM camp for at-risk youth, offering skills that can encourage empowerment instead of disengagement.

Meta presents the programme as part of a broader pledge to deepen education and community involvement around emerging technologies.

The company argues that long-term support for digital learning will strengthen local resilience and create opportunities for young people who want to pursue future careers in technology.

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Microsoft links datacentres into an AI superfactory

Microsoft has opened Fairwater, a new class of AI datacentres networked across the US. Atlanta began operating in October and links with the Wisconsin build to act as a single superfactory. The design targets faster training for models used by Microsoft, OpenAI and Copilot.

Fairwater sites pack hundreds of thousands of advanced GPUs with liquid cooling. Company materials highlight near-zero operational water use at Atlanta’s system and efficiency improvements in Wisconsin. Coverage confirms multi-site networking intended to accelerate model development.

Residents and experts voice concern over noise, power demand and water risks near proposed AI hubs. Georgia communities have pursued restrictions, citing environmental strain and rising utility bills, while Wisconsin groups demand transparency.

Microsoft expanded its Wisconsin investment and cancelled a separate Caledonia plan after severe local pushback. The Mount Pleasant project continues, with commitments on infrastructure costs and efficient cooling noted in filings and reports.

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EU and Switzerland deepen research ties through Horizon Europe agreement

Switzerland has formally joined Horizon Europe, the EU’s flagship research and innovation programme, together with Digital Europe and the Euratom Research and Training Programme.

An agreement, signed in Bern by Commissioner Ekaterina Zaharieva and Federal Councillor Guy Parmelin, that grants Swiss researchers the same status as their EU counterparts.

They can now lead projects, receive EU funding, and access every thematic pillar, reinforcing cross-border collaboration in fields such as climate technology, digital transformation, and energy security.

The accord, effective from 1 January 2025, also enables Switzerland to become a member of Fusion for Energy in 2026, thereby integrating its researchers into ITER, the world’s largest fusion energy initiative.

Plans include Swiss participation in Erasmus+ from 2027 and in the EU4Health programme once a separate health agreement takes effect.

A development that forms part of a broader package designed to deepen EU–Swiss relations and modernise cooperation frameworks across science, technology, and education.

The European Commission reaffirmed its commitment to finalising ratification of all related agreements, ensuring long-term collaboration and strengthening Europe’s position as a global leader in innovation and research.

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AI-powered Google Photos features land on iOS, search expands to 100+ countries

Google Photos is introducing prompt-based edits, an ‘Ask’ button, and style templates across iOS and Android. In the US, iPhone users can describe edits by voice or text, with a redesigned editor for faster controls. The rollout builds on the August Pixel 10’s debut of prompt editing.

Personalised edits now recognise people from face groups, so you can issue multi-person requests, such as removing sunglasses or opening eyes. Find it under ‘Help me edit’, where changes apply to each named person. It’s designed for faster, more granular everyday fixes.

A new Ask button serves as a hub for AI requests, from questions about a photo to suggested edits and related moments. The interface surfaces chips that hint at actions users can take. The Ask experience is rolling out in the US on both iOS and Android.

Google is also adding AI templates that turn a single photo into set formats, such as retro portraits or comic-style panels. The company states that its Nano Banana model powers these creative styles and that templates will be available next week under the Create tab on Android in the US and India.

AI search in Google Photos, first launched in the US, is expanding to over 100 countries with support for 17 languages. Markets include Argentina, Australia, Brazil, India, Japan, Mexico, Singapore, and South Africa. Google says this brings natural-language photo search to a far greater number of users.

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Google flags adaptive malware that rewrites itself with AI

Hackers are experimenting with malware that taps large language models to morph in real time, according to Google’s Threat Intelligence Group. An experimental family dubbed PROMPTFLUX can rewrite and obfuscate its own code as it executes, aiming to sidestep static, signature-based detection.

PROMPTFLUX interacts with Gemini’s API to request on-demand functions and ‘just-in-time’ evasion techniques, rather than hard-coding behaviours. GTIG describes the approach as a step toward more adaptive, partially autonomous malware that dynamically generates scripts and changes its footprint.

Investigators say the current samples appear to be in development or testing, with incomplete features and limited Gemini API access. Google says it has disabled associated assets and has not observed a successful compromise, yet warns that financially motivated actors are exploring such tooling.

Researchers point to a maturing underground market for illicit AI utilities that lowers barriers for less-skilled offenders. State-linked operators in North Korea, Iran, and China are reportedly experimenting with AI to enhance reconnaissance, influence, and intrusion workflows.

Defenders are turning to AI, using security frameworks and agents like ‘Big Sleep’ to find flaws. Teams should expect AI-assisted obfuscation, emphasise behaviour-based detection, watch model-API abuse, and lock down developer and automation credentials.

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Data infrastructure growth in India raises environmental concerns

India’s data centre market is expanding rapidly, driven by rapid AI adoption, mobile internet growth, and massive foreign investment from firms such as Google, Amazon and Meta. The sector is projected to expand 77% by 2027, with billions more expected to be spent on capacity by 2030.

Rapid expansion of energy-hungry and water-intensive facilities is creating serious sustainability challenges, particularly in water-scarce urban clusters like Mumbai, Hyderabad and Bengaluru. Experts warn that by 2030, India’s data centre water consumption could reach 358 billion litres, risking shortages for local communities and critical services in India.

Authorities and industry players are exploring solutions including treated wastewater, low-stress basin selection, and zero-water cooling technologies to mitigate environmental impact. Officials also highlight the need to mandate renewable energy use to balance India’s digital ambitions with decarbonisation goals.

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Researchers urge governance after LLMs display source-driven bias

Large language models (LLMs) are increasingly used to grade, hire, and moderate text. UZH research shows that evaluations shift when participants are told who wrote identical text, revealing source bias. Agreement stayed high only when authorship was hidden.

When told a human or another AI wrote it, agreement fell, and biases surfaced. The strongest was anti-Chinese across all models, including a model from China, with sharp drops even for well-reasoned arguments.

AI models also preferred ‘human-written’ over ‘AI-written’, showing scepticism toward machine-authored text. Such identity-triggered bias risks unfair outcomes in moderation, reviewing, hiring, and newsroom workflows.

Researchers recommend identity-blind prompts, A/B checks with and without source cues, structured rubrics focused on evidence and logic, and human oversight for consequential decisions.

They call for governance standards: disclose evaluation settings, test for bias across demographics and nationalities, and set guardrails before sensitive deployments. Transparency on prompts, model versions, and calibration is essential.

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