A hacker has exploited decentralised exchange KiloEX, draining approximately US$7.5 million by manipulating its price oracle mechanism. The breach led to an immediate suspension of the platform and sparked a cross-industry investigation involving cybersecurity firms and blockchain networks.
The vulnerability centred on KiloEX’s price feed system, which allowed the attacker to manipulate the ETH/USD feed by inputting an artificial entry price of 100 and closing it at 10,000.
According to cybersecurity firm PeckShield, this simple flaw enabled the attacker to steal millions across multiple chains, including $3.3 million from Base, $3.1 million from opBNB, and $1 million from BNB Smart Chain.
KiloEX is working with various security experts and blockchain networks such as BNB Chain and Manta Network to recover the stolen assets.
Funds are reportedly being routed through cross-chain protocols like zkBridge and Meson. Co-founder of Fuzzland, Chaofan Shou, described the breach as stemming from a ‘very simple vulnerability’ in oracle verification, where only intermediaries were validated rather than the original transaction sender.
The attack caused KiloEX’s token price to plummet by over 29% and came just one day after the platform announced a strategic partnership with DWF Labs, aimed at fuelling growth. KiloEX has promised a full incident report and a bounty programme to encourage asset recovery.
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The individuals, identified by Harbin police as Katheryn A. Wilson, Robert J. Snelling, and Stephen W. Johnson, are said to have worked through the US National Security Agency (NSA).
The attacks reportedly targeted systems critical to the Games’ operations, including athlete registration, travel, and competition management, which held sensitive personal data.
Chinese state media further claimed that the cyber intrusions extended beyond the sporting event, affecting key infrastructure in Heilongjiang province. Targets allegedly included energy, transport, water, telecoms, defence research institutions, and technology giant Huawei.
Authorities said the NSA used encrypted data to compromise Microsoft Windows systems in the region, with the aim of disrupting services and undermining national security.
The Foreign Ministry of China denounced the alleged cyberattacks as ‘extremely malicious,’ urging the United States to halt what it called repeated intrusions and misinformation.
The UD Embassy in Beijing has yet to respond, and the allegations come amid ongoing tensions, with both nations frequently accusing each other of state-backed hacking.
Only last month, the US government named and charged 12 Chinese nationals in connection with cyberespionage efforts against American interests.
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From GPT-4 to 4.5: What has changed and why it matters
In March 2024, OpenAI released GPT-4.5, the latest iteration in its series of large language models (LLMs), pushing the boundaries of what machines can do with language understanding and generation. Building on the strengths of GPT-4, its successor, GPT-4.5, demonstrates improved reasoning capabilities, a more nuanced understanding of context, and smoother, more human-like interactions.
What sets GPT-4.5 apart from its predecessors is that it showcases refined alignment techniques, better memory over longer conversations, and increased control over tone, persona, and factual accuracy. Its ability to maintain coherent, emotionally resonant exchanges over extended dialogue marks a turning point in human-AI communication. These improvements are not just technical — they significantly affect the way we work, communicate, and relate to intelligent systems.
The increasing ability of GPT-4.5 to mimic human behaviour has raised a key question: Can it really fool us into thinking it is one of us? That question has recently been answered — and it has everything to do with the Turing Test.
The Turing Test: Origins, purpose, and modern relevance
In 1950, British mathematician and computer scientist Alan Turing posed a provocative question: ‘Can machines think?’ In his seminal paper ‘Computing Machinery and Intelligence,’ he proposed what would later become known as the Turing Test — a practical way of evaluating a machine’s ability to exhibit intelligent behaviour indistinguishable from that of a human.
In its simplest form, if a human evaluator cannot reliably distinguish between a human’s and a machine’s responses during a conversation, the machine is said to have passed the test. For decades, the Turing Test remained more of a philosophical benchmark than a practical one.
Early chatbots like ELIZA in the 1960s created the illusion of intelligence, but their scripted and shallow interactions fell far short of genuine human-like communication. Many researchers have questioned the test’s relevance as AI progressed, arguing that mimicking conversation is not the same as true understanding or consciousness.
Despite these criticisms, the Turing Test has endured — not as a definitive measure of machine intelligence, but rather as a cultural milestone and public barometer of AI progress. Today, the test has regained prominence with the emergence of models like GPT-4.5, which can hold complex, context-aware, emotionally intelligent conversations. What once seemed like a distant hypothetical is now an active, measurable challenge that GPT-4.5 has, by many accounts, overcome.
How GPT-4.5 fooled the judges: Inside the Turing Test study
In early 2025, a groundbreaking study conducted by researchers at the University of California, San Diego, provided the most substantial evidence yet that an AI could pass the Turing Test. In a controlled experiment involving over 500 participants, multiple conversational agents—including GPT-4.5, Meta’s LLaMa-3.1, and the classic chatbot ELIZA—were evaluated in blind text-based conversations. The participants were tasked with identifying whether they spoke to a human or a machine.
The results were astonishing: GPT-4.5 was judged to be human in 54% to 73% of interactions, depending on the scenario, surpassing the baseline for passing the Turing Test. In some cases, it outperformed actual human participants—who were correctly identified as human only 67% of the time.
That experiment marked the first time a contemporary AI model convincingly passed the Turing Test under rigorous scientific conditions. The study not only demonstrated the model’s technical capabilities—it also raised philosophical and ethical questions.
What does it mean for a machine to be ‘indistinguishable’ from a human? And more importantly, how should society respond to a world where AI can convincingly impersonate us?
Measuring up: GPT-4.5 vs LLaMa-3.1 and ELIZA
While GPT-4.5’s performance in the Turing Test has garnered much attention, its comparison with other models puts things into a clearer perspective. Meta’s LLaMa-3.1, a powerful and widely respected open-source model, also participated in the study.
It was identified as human in approximately 56% of interactions — a strong showing, although it fell just short of the commonly accepted benchmark to define a Turing Test pass. The result highlights how subtle conversational nuance and coherence differences can significantly influence perception.
The study also revisited ELIZA, the pioneering chatbot from the 1960s designed to mimic a psychotherapist. While historically significant, ELIZA’s simplistic, rule-based structure resulted in it being identified as non-human in most cases — around 77%. That stark contrast with modern models demonstrates how far natural language processing has progressed over the past six decades.
The comparative results underscore an important point: success in human-AI interaction today depends on language generation and the ability to adapt the tone, context, and emotional resonance. GPT-4.5’s edge seems to come not from mere fluency but from its ability to emulate the subtle cues of human reasoning and expression — a quality that left many test participants second-guessing whether they were even talking to a machine.
The power of persona: How character shaped perception
One of the most intriguing aspects of the UC San Diego study was how assigning specific personas to AI models significantly influenced participants’ perceptions. When GPT-4.5 was framed as an introverted, geeky 19-year-old college student, it consistently scored higher in being perceived as human than when it had no defined personality.
The seemingly small narrative detail was a powerful psychological cue that shaped how people interpreted its responses. The use of persona added a layer of realism to the conversation.
Slight awkwardness, informal phrasing, or quirky responses were not seen as flaws — they were consistent with the character. Participants were more likely to forgive or overlook certain imperfections if those quirks aligned with the model’s ‘personality’.
That finding reveals how intertwined identity and believability are in human communication, even when the identity is entirely artificial. The strategy also echoes something long known in storytelling and branding: people respond to characters, not just content.
In the context of AI, persona functions as a kind of narrative camouflage — not necessarily to deceive, but to disarm. It helps bridge the uncanny valley by offering users a familiar social framework. And as AI continues to evolve, it is clear that shaping how a model is perceived may be just as important as what the model is actually saying.
Limitations of the Turing Test: Beyond the illusion of intelligence
While passing the Turing Test has long been viewed as a milestone in AI, many experts argue that it is not the definitive measure of machine intelligence. The test focuses on imitation — whether an AI can appear human in conversation — rather than on genuine understanding, reasoning, or consciousness. In that sense, it is more about performance than true cognitive capability.
Critics point out that large language models like GPT-4.5 do not ‘understand’ language in the human sense – they generate text by predicting the most statistically probable next word based on patterns in massive datasets. That allows them to generate impressively coherent responses, but it does not equate to comprehension, self-awareness, or independent thought.
No matter how convincing, the illusion of intelligence is still an illusion — and mistaking it for something more can lead to misplaced trust or overreliance. Despite its symbolic power, the Turing Test was never meant to be the final word on AI.
As AI systems grow increasingly sophisticated, new benchmarks are needed — ones that assess linguistic mimicry, reasoning, ethical decision-making, and robustness in real-world environments. Passing the Turing Test may grab headlines, but the real test of intelligence lies far beyond the ability to talk like us.
Wider implications: Rethinking the role of AI in society
GPT-4.5’s success in the Turing Test does not just mark a technical achievement — it forces us to confront deeper societal questions. If AI can convincingly pass as a human in open conversation, what does that mean for trust, communication, and authenticity in our digital lives?
From customer service bots to AI-generated news anchors, the line between human and machine is blurring — and the implications are far from purely academic. These developments are challenging existing norms in areas such as journalism, education, healthcare, and even online dating.
How do we ensure transparency when AI is involved? Should AI be required to disclose its identity in every interaction? And how do we guard against malicious uses — such as deepfake conversations or synthetic personas designed to manipulate, mislead, or exploit?
On a broader level, the emergence of human-sounding AI invites a rethinking of agency and responsibility. If a machine can persuade, sympathise, or influence like a person — who is accountable when things go wrong?
As AI becomes more integrated into the human experience, society must evolve its frameworks not only for regulation and ethics but also for cultural adaptation. GPT-4.5 may have passed the Turing Test, but the test for us, as a society, is just beginning.
What comes next: Human-machine dialogue in the post-Turing era
With GPT-4.5 crossing the Turing threshold, we are no longer asking whether machines can talk like us — we are now asking what that means for how we speak, think, and relate to machines. That moment represents a paradigm shift: from testing the machine’s ability to imitate humans to understanding how humans will adapt to coexist with machines that no longer feel entirely artificial.
Future AI models will likely push this boundary even further — engaging in conversations that are not only coherent but also deeply contextual, emotionally attuned, and morally responsive. The bar for what feels ‘human’ in digital interaction is rising rapidly, and with it comes the need for new social norms, protocols, and perhaps even new literacies.
We will need to learn not only how to talk to machines but how to live with them — as collaborators, counterparts, and, in some cases, as reflections of ourselves. In the post-Turing era, the test is no longer whether machines can fool us — it is whether we can maintain clarity, responsibility, and humanity in a world where the artificial feels increasingly real.
GPT-4.5 may have passed a historic milestone, but the real story is just beginning — not one of machines becoming human, but of humans redefining what it means to be ourselves in dialogue with them.
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Nvidia is shifting its AI supercomputer manufacturing operations to the United States for the first time, instead of relying on a globally dispersed supply chain.
In partnership with industry giants such as TSMC, Foxconn, and Wistron, the company is establishing large-scale facilities to produce its advanced Blackwell chips in Arizona and complete supercomputers in Texas. Production is expected to reach full scale within 12 to 15 months.
Over a million square feet of manufacturing space has been commissioned, with key roles also played by packaging and testing firms Amkor and SPIL.
The move reflects Nvidia’s ambition to create up to half a trillion dollars in AI infrastructure within the next four years, while boosting supply chain resilience and growing its US-based operations instead of expanding solely abroad.
These AI supercomputers are designed to power new, highly specialised data centres known as ‘AI factories,’ capable of handling vast AI workloads.
Nvidia’s investment is expected to support the construction of dozens of such facilities, generating hundreds of thousands of jobs and securing long-term economic value.
To enhance efficiency, Nvidia will apply its own AI, robotics, and simulation tools across these projects, using Omniverse to model factory operations virtually and Isaac GR00T to develop robots that automate production.
According to CEO Jensen Huang, bringing manufacturing home strengthens supply chains and better positions the company to meet the surging global demand for AI computing power.
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US President Donald Trump is preparing to introduce new tariffs on semiconductor imports, aiming to shift more chip production back to the United States.
Semiconductors, or microchips, are essential components in everything from smartphones and laptops to medical devices and renewable energy systems.
Speaking aboard Air Force One, Trump said new tariff rates would be announced soon as part of a broader effort to end American reliance on foreign-made chips and strengthen national security.
The global semiconductor supply chain is heavily concentrated in Asia, with Taiwan’s TSMC producing over half of the world’s chips and supplying major companies like Apple, Microsoft, and Nvidia.
Trump’s move signals a more aggressive stance in the ongoing ‘chip wars’ with China, as his administration warns of the dangers of the US being dependent on overseas production for such a critical technology.
Although the US has already taken steps to boost domestic chip production—like the $6.6 billion awarded to TSMC to build a factory in Arizona—progress has been slow due to a shortage of skilled workers.
The plant faced delays, and TSMC ultimately flew in thousands of workers from Taiwan to meet demands, underscoring the challenge of building a self-reliant semiconductor industry on American soil.
Why does it matter?
Trump’s proposed tariffs are expected to form part of a wider investigation into the electronics supply chain, aimed at shielding the US from foreign control and ensuring long-term technological independence. As markets await the announcement, the global tech industry is bracing for potential disruptions and new tensions in the international trade landscape.
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Nvidia is significantly ramping up its presence in the United States by commissioning over a million square feet of manufacturing space in Arizona and Texas to build and test its powerful AI chips. The tech giant has begun producing its Blackwell chips at TSMC facilities in Phoenix and is developing large-scale ‘supercomputer’ manufacturing plants in partnership with Foxconn in Houston and Wistron in Dallas.
The company projects mass production to begin within the next 12 to 15 months, with ambitions to manufacture up to half a trillion dollars’ worth of AI infrastructure in the US over the next four years. CEO Jensen Huang emphasised that this move marks the first time the core components of global AI infrastructure are being built domestically.
He cited growing global demand, supply chain resilience, and national security as key reasons for the shift. Nvidia’s decision follows an agreement with the Trump administration that helped the company avoid export restrictions on its H20 chip, a top-tier processor still eligible for export to China.
Nvidia joins a broader wave of AI industry leaders aligning with the Trump administration’s ‘America-first’ strategy. Companies like OpenAI and Microsoft have pledged massive investments in US-based AI infrastructure, hoping to secure political goodwill and avoid regulatory hurdles.
Trump has also reportedly pressured key suppliers like TSMC to expand American operations, threatening tariffs as high as 100% if they fail to comply. Despite the enthusiasm, Nvidia’s expansion faces headwinds.
A shortage of skilled workers and potential retaliation from China—particularly over raw material access—pose serious risks. Meanwhile, Trump’s recent moves to undermine the Chips Act, which provides critical funding for domestic chipmaking, have raised concerns about the long-term viability of US semiconductor investment.
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Smartphones, computers, and key tech components have been granted exemption from the latest round of US tariffs, providing relief to American technology firms heavily reliant on Chinese manufacturing.
The decision, which includes products such as semiconductors, solar cells, and memory cards, marks the first major rollback in President Donald Trump’s trade war with China.
The exemptions, retroactively effective from 5 April, come amid concerns from US tech giants that consumer prices would soar.
Analysts say this move could be a turning point, especially for companies like Apple and Nvidia, which source most of their hardware from China. Industry reaction has been overwhelmingly positive, with suggestions that the policy shift could reshape global tech supply chains.
Despite easing tariffs on electronics, Trump has maintained a strict stance on Chinese trade, citing national security and economic independence.
The White House claims the reprieve gives firms time to shift manufacturing to the US. However, electronic goods will still face a separate 20% tariff due to China’s ties to fentanyl-related trade. Meanwhile, Trump insists high tariffs are essential leverage to renegotiate fairer global trade terms.
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Crosswalk buttons in several Californian cities have been hacked to play AI-generated voices impersonating tech moguls Elon Musk and Mark Zuckerberg, delivering bizarre and satirical messages to pedestrians.
The spoof messages, which mock the CEOs with lines like ‘Can we be friends?’ and ‘Cooking our grandparents’ brains with AI slop,’ have been heard in Palo Alto, Redwood City, and Menlo Park.
US Palo Alto officials confirmed that 12 intersections were affected and the audio systems have since been disabled.
While the crosswalk signals themselves remain operational, authorities are investigating how the hack was carried out. Similar issues are being addressed in nearby cities, with local governments moving quickly to secure the compromised systems.
The prank, which uses AI voice cloning, appears to layer these spoofed messages on top of the usual accessibility features rather than replacing them entirely.
Though clearly comedic in intent, the incident has raised concerns about the growing ease with which public systems can be manipulated using generative technologies.
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As the US tax filing deadline of April 15 approaches, cybercriminals are ramping up phishing attacks designed to exploit the urgency many feel during this stressful period.
Windows users are particularly at risk, as attackers are targeting Microsoft account credentials by distributing emails disguised as tax-related reminders.
These emails include a PDF attachment titled ‘urgent reminder,’ which contains a malicious QR code. Once scanned, it leads users through fake bot protection and CAPTCHA checks before prompting them to enter their Microsoft login details, details that are then sent to a server controlled by criminals.
Security researchers, including Peter Arntz from Malwarebytes, warn that the email addresses in these fake login pages are already pre-filled, making it easier for unsuspecting victims to fall into the trap.
Entering your password at this stage could hand your credentials to malicious actors, possibly operating from Russia, who may exploit your account for maximum profit.
The form of attack takes advantage of both the ticking tax clock and the stress many feel trying to meet the deadline, encouraging impulsive and risky clicks.
Importantly, this threat is not limited to Windows users or those filing taxes by the April 15 deadline. As phishing techniques become more advanced through the use of AI and automated smartphone farms, similar scams are expected to persist well beyond tax season.
The IRS rarely contacts individuals via email and never to request sensitive information through links or attachments, so any such message should be treated with suspicion instead of trust.
To stay safe, users are urged to remain vigilant and avoid clicking on links or scanning codes from unsolicited emails. Instead of relying on emails for tax updates or returns, go directly to official websites.
The IRS offers resources to help recognise and report scams, and reviewing this guidance could be an essential step in protecting your personal information, not just today, but in the months ahead.
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A surge in AI applications transforming selfies into Studio Ghibli-style artwork has captivated social media, but UAE cybersecurity experts are raising concerns over privacy and data misuse.
Dr Mohamed Al Kuwaiti, Head of Cybersecurity for the UAE Government, warned that engaging with unofficial apps could lead to breaches or leaks of personal data. He emphasised that while AI’s benefits are clear, users must understand how their personal data is handled by these platforms.
He called for strong cybersecurity standards across all digital platforms, urging individuals to be more cautious with their data.
Media professionals are also sounding alarms. Adel Al-Rashed, an Emirati journalist, cautioned that free apps often mimic trusted platforms but could exploit user data. He advised users to stick to verified applications, noting that paid services, like ChatGPT’s Pro edition, offer stronger privacy protections.
While acknowledging the risks, social media influencer Ibrahim Al-Thahli highlighted the excitement AI brings to creative expression. He urged users to focus on education and safe engagement with the technology, underscoring the UAE’s goal to build a resilient digital economy.
For more information on these topics, visit diplomacy.edu.
