New AI tools aim to speed discovery of effective HIV vaccines

Over 40 million people worldwide are living with HIV, a chronic infection that remains a leading cause of death. Developing an effective vaccine has proven difficult due to the virus’s rapid mutations and the vast volume of clinical data produced during trials.

Scripps Research has received $1.1 million from CHAVD to purchase high-performance computing and AI technology. The investment lets researchers analyse millions of vaccine candidates faster, speeding antibody identification and refining experimental vaccines.

StepwiseDesign enables the AI system to evaluate vaccine-induced antibodies and identify the most promising candidates for development. The system has found rare antibodies that neutralise HIV in uninfected individuals, showing its ability to detect extremely rare precursors.

Researchers hope the computational framework will not only fast-track HIV vaccine development but also be applied to other complex pathogens, including influenza and malaria. The project highlights collaboration and innovation, with potential to improve global health outcomes for millions at risk.

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Sundar Pichai warns users not to trust AI tools easily

Google CEO Sundar Pichai advises people not to unquestioningly trust AI tools, warning that current models remain prone to errors. He told the BBC that users should rely on a broader information ecosystem rather than treat AI as a single source of truth.

Pichai said generative systems can produce inaccuracies and stressed that people must learn what the tools are good at. The remarks follow criticism of Google’s own AI Overviews feature, which attracted attention for erratic and misleading responses during its rollout.

Experts say the risk grows when users depend on chatbots for health, science, or news. BBC research found major AI assistants misrepresented news stories in nearly half of the tests this year, underscoring concerns about factual reliability and the limits of current models.

Google is launching Gemini 3.0, which it claims offers stronger multimodal understanding and reasoning. The company says its new AI Mode in search marks a shift in how users interact with online information, as it seeks to defend market share against ChatGPT and other rivals.

Pichai says Google is increasing its investment in AI security and releasing tools to detect AI-generated images. He maintains that no single company should control such powerful technology and argues that the industry remains far from a scenario in which one firm dominates AI development.

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Europe’s digital sovereignty advances through SAP’s new AI collaborations

SAP has announced new partnerships with Bleu, Capgemini, and Mistral AI to advance Europe’s digital sovereignty. The collaboration combines SAP’s expertise in enterprise software with France’s AI ecosystem to develop secure, scalable, and sovereign cloud solutions for governments and regulated sectors.

Bleu and Delos Cloud have established a Franco-German alliance focused on crisis resilience, creating joint capabilities for early detection, analysis, and remediation of cyber incidents. Their cooperation supports rapid response in extreme scenarios and reinforces control over critical infrastructure.

SAP and Capgemini are expanding their partnership to advance sovereign agentic AI and strengthen cybersecurity across Europe. Their new Sovereign Technology Partnership will deliver data management, cloud services, and automation tools for public and regulated sectors.

SAP and Mistral AI are also deepening their collaboration to create Europe’s first full sovereign AI stack. SAP will offer Mistral’s frontier models through its sovereign AI foundation on SAP BTP, while both companies co-develop industry-specific AI applications designed for engineering and R&D workloads.

These partnerships form part of SAP’s broader sovereign cloud strategy, backed by more than €20bn in investment. SAP states that its aim is to provide a secure, compliant, and locally controlled infrastructure that enables innovation while safeguarding European data, assets, and long-term technological independence.

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UNESCO and SAP selected the AI system EDiSON for the Solomon Islands

SAP and UNESCO have agreed to deploy the AI-supported disaster management system EDiSON in the Solomon Islands.

The platform, created by SAP Japan and the start-up INSPIRATION PLUS, utilises the SAP Business Technology Platform with machine learning to merge real-time meteorological information with historical records, rather than relying on isolated datasets.

A system that delivers predictive insights that help authorities act before severe weather strikes. It anticipates terrain damage, guides emergency services towards threatened areas and supports decisions on evacuation orders.

The initiative aims to serve as a model for other small island states facing similar climate-related pressures.

UNESCO officials say the project strengthens early warning capacity and encourages long-term resilience. EDiSON will become operational in 2026 and aims to offer a scalable approach for nations with limited technical resources.

Its performance in Japan has already demonstrated how integrated data management can overcome fragmented information flows and restricted analytical tools.

The design of EDiSON enables governments to adopt advanced disaster preparedness systems instead of relying on costly, bespoke infrastructure. A partnership that seeks to improve national readiness in the Solomon Islands, where earthquakes, tsunamis, cyclones and floods regularly threaten communities.

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Web services recover after Cloudflare restores its network systems

Cloudflare has resolved a technical issue that briefly disrupted access to major platforms, including X, ChatGPT, and Letterboxd. Users had earlier reported internal server error messages linked to Cloudflare’s network, indicating that pages could not be displayed.

The disruption began around midday UK time, with some sites loading intermittently as the problem spread across the company’s infrastructure. Cloudflare confirmed it was investigating an incident affecting multiple customers and issued rolling updates as engineers worked to identify the fault.

Outage tracker Down Detector also experienced difficulties during the incident, later showing a sharp rise in reports once it came back online. The pattern pointed to a broad network-level failure rather than isolated platform issues.

Users saw repeated internal server error warnings asking them to try again, though services began recovering as Cloudflare isolated the cause. The company has not yet released full technical details, but said the fault has been fixed and that systems are stabilising.

Cloudflare provides routing, security, and reliability tools for a wide range of online services, making a single malfunction capable of cascading globally. The company said it would share further information on the incident and steps taken to prevent similar failures.

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Misconfigured database triggered global Cloudflare failure, CEO says

Cloudflare says its global outage on 18 November was caused by an internal configuration error, not a cyberattack. CEO Matthew Prince apologised to users after a permissions update to a ClickHouse cluster generated a malformed feature file that caused systems worldwide to crash.

The oversized file exceeded a hard limit in Cloudflare’s routing software, triggering failures across its global edge. Intermittent recoveries during the first hours of the incident led engineers to suspect a possible attack, as the network randomly stabilised when a non-faulty file propagated.

Confusion intensified when Cloudflare’s externally hosted status page briefly became inaccessible, raising fears of coordinated targeting. The root cause was later traced to metadata duplication from an unexpected database source, which doubled the number of machine-learning features in the file.

The outage affected Cloudflare’s CDN, security layers, and ancillary services, including Turnstile, Workers KV, and Access. Some legacy proxies kept limited traffic moving, but bot scores and authentication systems malfunctioned, causing elevated latencies and blocked requests.

Engineers halted the propagation of the faulty file by mid-afternoon and restored a clean version before restarting affected systems. Prince called it Cloudflare’s most serious failure since 2019 and said lessons learned will guide major improvements to the company’s infrastructure resilience.

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Poll manipulation by AI threatens democratic accuracy, according to a new study

Public opinion surveys face a growing threat as AI becomes capable of producing highly convincing fake responses. New research from Dartmouth shows that AI-generated answers can pass every quality check, imitate real human behaviour and alter poll predictions without leaving evidence.

In several major polls conducted before the 2024 US election, inserting only a few dozen synthetic responses would have reversed expected outcomes.

The study reveals how easily malicious actors could influence democratic processes. AI models can operate in multiple languages yet deliver flawless English answers, allowing foreign groups to bypass detection.

An autonomous synthetic respondent that was created for the study passed nearly all attention tests, avoided errors in logic puzzles and adjusted its tone to match assigned demographic profiles instead of exposing its artificial nature.

The potential consequences extend far beyond electoral polling. Many scientific disciplines rely heavily on survey data to track public health risks, measure consumer behaviour or study mental wellbeing.

If AI-generated answers infiltrate such datasets, the reliability of thousands of studies could be compromised, weakening evidence used to shape policy and guide academic research.

Financial incentives further raise the risk. Human participants earn modest fees, while AI can produce survey responses at almost no cost. Existing detection methods failed to identify the synthetic respondent at any stage.

The researcher urges survey companies to adopt new verification systems that confirm the human identity of participants, arguing that stronger safeguards are essential to protect democratic accountability and the wider research ecosystem.

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The future of the EU data protection under the Omnibus Package

Introduction and background information

The Commission claims that the Omnibus Package aims to simplify certain European Union legislation to strengthen the Union’s long-term competitiveness. A total of six omnibus packages have been announced in total.

The latest (no. 4) targets small mid-caps and digitalisation. Package no. 4 covers data legislation, cookies and tracking technologies (i.e. the General Data Protection Regulation (GDPR) and ePrivacy Directive (ePD)), as well as cybersecurity incident reporting and adjustments to the Artificial Intelligence Act (AIA).

That ‘simplification’ is part of a broader agenda to appease business, industry and governments who argue that the EU has too much red tape. In her September 2025 speech to German economic and business associations, Ursula von der Leyen sided with industry and stated that simplification is ‘the only way to remain competitive’.

As for why these particular laws were selected, the rationale is unclear. One stated motivation for including the GDPR is its mention in Mario Draghi’s 2024 report on ‘The Future of European Competitiveness’.

Draghi, the former President of the European Central Bank, focused on innovation in advanced technologies, decarbonisation and competitiveness, as well as security. Yet, the report does not outline any concrete way in which the GDPR allegedly reduces competitiveness or requires revision.

The GDPR appears only twice in the report. First, as a brief reference to regulatory fragmentation affecting the reuse of sensitive health data across Member States (MS).

Second, in the concluding remarks, it is claimed that ‘the GDPR in particular has been implemented with a large degree of fragmentation which undermines the EU’s digital goals’. There is, however, no explanation of this ‘large fragmentation’, no supporting evidence, and no dedicated section on the GDPR as its first mention being buried in the R&I (research and innovation) context.

It is therefore unclear what legal or analytical basis the Commission relies on to justify including the GDPR in this simplification exercise.

The current debate

There are two main sides to this Omnibus, which are the privacy forward and the competitive/SME side. The two need not be mutually exclusive, but civil society warns that ‘simplification’ risks eroding privacy protection. Privacy advocates across civil society expressed strong concern and opposition to simplification in their responses to the European Commission’s recent call for evidence.

Industry positions vary in tone and ambition. For example, CrowdStrike calls for greater legal certainty under the Cybersecurity Act, such as making recital 55 binding rather than merely guiding and introducing a one-stop-shop mechanism for incident reporting.

Meta, by contrast, urges the Commission to go beyond ‘easing administrative burdens’, calling for a pause in AI Act enforcement and a sweeping reform of the EU data protection law. On the civil society side, Access Now argues that fundamental rights protections are at stake.

It warns that any reduction in consent prompts could allow tracking technologies to operate without users ever being given a real opportunity to refuse. A more balanced, yet cautious line can be found in the EDPB and EDPS joint opinion regarding easing records of processing activities for SMEs.

Similar to the industry, they support reducing administrative burdens, but with the caveat that amendments should not compromise the protection of fundamental rights, echoing key concerns of civil society.

Regarding Member State support, Estonia, France, Austria and Slovenia are firmly against any reopening of the GDPR. By contrast, the Czech Republic, Finland and Poland propose targeted amendments while Germany proposes a more systematic reopening of the GDPR.

Individual Members of the European Parliament have also come out in favour of reopening, notably Aura Salla, a Finnish centre-right MEP who previously headed Meta’s Brussels lobbying office.

Therefore, given the varied opinions, it cannot be said what the final version of the Omnibus would look like. Yet, a leaked draft document of the GDPR’s potential modifications suggests otherwise. Upon examination, it cannot be disputed that the views from less privacy-friendly entities have served as a strong guiding path.

Leaked draft document main changes

The leaked draft introduces several core changes.

Those changes include a new definition of personal and sensitive data, the use of legitimate interest (LI) for AI processing, an intertwining of the ePrivacy Directive (ePD) and GDPR, data breach reforms, a centralised data protection impact assessment (DPIA) whitelist/blacklist, and access rights being conditional on motive for use.

A new definition of personal data

The draft redefines personal data so that ‘information is not personal data for everyone merely because another entity can identify that natural person’. That directly contradicts established EU case law, which holds that if an entity can, with reasonable means, identify a natural person, then the information is personal data, regardless of who else can identify that person.

A new definition of sensitive data

Under current rules, inferred information can be sensitive personal data. If a political opinion is inferred from browsing history, that inference is protected.

The draft would narrow this by limiting sensitive data to information that ‘directly reveals’ special categories (political views, health, religion, sexual orientation, race/ethnicity, trade union membership). That would remove protection from data derived through profiling and inference.

Detected patterns, such as visits to a health clinic or political website, would no longer be treated as sensitive, and only explicit statements similar to ‘I support the EPP’ or ‘I am Muslim’ would remain covered.

Intertwining article 5(3) ePD and the GDPR

Article 5(3) ePD is effectively copied into the GDPR as a new Article 88a. Article 88a would allow the processing of personal data ‘on or from’ terminal equipment where necessary for transmission, service provision, creating aggregated information (e.g. statistics), or for security purposes, alongside the existing legal bases in Articles 6(1) and 9(2) of the GDPR.

That generates confusion about how these legal bases interact, especially when combined with AI processing under LI. Would this mean that personal data ‘on or from’ a terminal equipment may be allowed if it is done by AI?

The scope is widened. The original ePD covered ‘storing of information, or gaining access to information already stored, in the terminal equipment’. The draft instead regulates any processing of personal data ‘on or from’ terminal equipment. That significantly expands the ePD’s reach and would force controllers to reassess and potentially adapt a broad range of existing operations.

LI for AI personal data processing

A new Article 88c GDPR, ‘Processing in the context of the development and operation of AI’, would allow controllers to rely on LI to process personal data for AI processing. That move would largely sideline data subject control. Businesses could train AI systems on individuals’ images, voices or creations without obtaining consent.

A centralised data breach portal, deadline extension and change in threshold reporting

The draft introduces three main changes to data breach reporting.

  • Extending the notification deadline from 72 to 96 hours, giving privacy teams more time to investigate and report.
  • A single EU-level reporting portal, simplifying reporting for organisations active in multiple MS.
  • Raising the notification threshold when the rights and freedoms of data subjects are at ‘risk’ to ‘high risk’.

The first two changes are industry-friendly measures designed to streamline operations. The third is more contentious. While industry welcomes fewer reporting obligations, civil society warns that a ‘high-risk’ threshold could leave many incidents unreported. Taken together, these reforms simplify obligations, albeit at the potential cost of reducing transparency.

Centralised processing activity (PA) list requiring a DPIA

This is another welcome change as it would clarify which PAs would automatically require a DPIA and which would not. The list would be updated every 3 years.

What should be noted here is that some controllers may not see their PA on this list and assume or argue that a DPIA is not required. Therefore, the language on this should make it clear that it is not a closed list.

Access requests denials

Currently, a data subject may request a copy of their data regardless of the motive. Under the draft, if a data subject exploits the right of access by using that material against the controller, the controller may charge or refuse the request.

That is problematic for the protection of rights as it impacts informational self-determination and weakens an important enforcement tool for individuals.

For more information, an in depth analysis by noyb has been carried out which can be accessed here.

The Commission’s updated version

On 19 November, the European Commission is expected to present its official simplification package. This section will be updated once the final text is published.

Final remarks

Simplification in itself is a good idea, and businesses need to have enough freedom to operate without being suffocated with red tape. However, changing a cornerstone of data protection law to such an extent that it threatens fundamental rights protections is just cause for concern.

Alarms have already been raised after the previous Omnibus package on green due diligence obligations was scrapped. We may now be witnessing a similar rollback, this time targeting digital rights.

As a result, all eyes are on 19 November, a date that could reshape not only the EU privacy standards but also global data protection norms.

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AI energy demand strains electrical grids

Microsoft CEO Satya Nadella recently delivered a key insight, stating that the biggest hurdle to deploying new AI solutions is now electrical power, not chip supply. The massive energy requirements for running large language models (LLMs) have created a critical bottleneck for major cloud providers.

Nadella specified that Microsoft currently has a ‘bunch of chips sitting in inventory’ that cannot be plugged in and utilised. The problem is a lack of ‘warm shells’, meaning data centre buildings that are fully equipped with the necessary power and cooling capacity.

The escalating power requirements of AI infrastructure are placing extreme pressure on utility grids and capacity. Projections from the Lawrence Berkeley National Laboratory indicate that US data centres could consume up to 12 percent of the nation’s total electricity by 2028.

The disclosure should serve as a warning to investors, urging them to evaluate the infrastructure challenges alongside AI’s technological promise. This energy limitation could create a temporary drag on the sector, potentially slowing the massive projected returns on the $5 trillion investment.

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AI threatens global knowledge diversity

AI systems are increasingly becoming the primary source of global information, yet they rely heavily on datasets dominated by Western languages and institutions.

Such reliance creates significant blind spots that threaten to erase centuries of indigenous wisdom and local traditions not currently found in digital archives.

Dominant language models often overlook oral histories and regional practices, including specific ecological knowledge essential for sustainable living in tropical climates.

Experts warn of a looming ‘knowledge collapse’ where alternative viewpoints fade away simply because they are statistically less prevalent in training data.

Future generations may find themselves disconnected from vital human insights as algorithms reinforce a homogenised worldview through recursive feedback loops.

Preserving diverse epistemologies remains crucial for addressing global challenges, such as the climate crisis, rather than relying solely on Silicon Valley’s version of intelligence.

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