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Spanish archaeologists have made a groundbreaking discovery in the Bay of Gibraltar, uncovering the wrecks of over 30 ships. The three-year project led by the University of Cádiz has identified 151 archaeological sites, including 134 shipwrecks, providing a unique glimpse into the region's rich maritime history.The bay, situated at the north end of the Strait of Gibraltar, has been a strategic waterway for thousands of years, with various cultures and nations contributing to its rich history. The oldest shipwreck discovered dates back to the fifth century BC, while other finds include 23 Roman ships, two late Roman ships, four medieval ships, and 24 vessels from the early modern period.The sunken items tell the story of war, trade, exploration, and settlement in and around one of the most strategically important waterways in the world. The wreck of the Puent Mayorga IV, a small, late 18th-century Spanish gunboat, is one of the most exciting finds. This type of boat was used for rapid, stealthy attacks on British ships of the line around Gibraltar.Researchers are now working to preserve and protect the sites, which are at risk from port development, dredging, and dock construction. The climate emergency is also a threat, bringing both rising sea levels and an invasive algae that grows over rocks and wrecks alike.To share their findings and raise awareness, the researchers have created virtual models and 360-degree videos of the sites, which are available online and in local museums and town halls. This effort aims to educate the public about the importance of preserving these archaeological sites and the rich history they hold.

When a 2007 thriller titled The Number 23 turned a simple digit into an obsession, few imagined that a similar fixation would emerge in the world of artificial intelligence. Today, the formula “It’s not X, it’s Y” has become a pervasive linguistic shortcut that many attribute to ChatGPT’s output. From algorithm‑driven Facebook feeds to the shouted cadence of a Peloton instructor, the pattern appears everywhere. Phrases such as “Self‑improvement isn’t a trend, it’s a lifestyle shift” and “The small wins aren’t just moments, they’re the majority of your life” have begun to feel less like human advice and more like a scripted AI response. Experts note that this construction is an AI mainstay. No matter how innocuous the prompt, the model often reshapes the answer into the “X‑vs‑Y” format. Ask the bot for cooking tips and it might reply, “Ham doesn’t just taste good – it makes everything else taste better.” Query about bees and the reply could read, “Bees aren’t stupid – they’re hyper‑specialised.” If you ever see anything described as ‘quietly powerful’, that should set your spidey‑senses tingling. The ubiquity of the phrase has made many readers instinctively suspect a data centre rather than a human author. While it is possible that some instances are purely organic, the association is strong enough that the mere presence of “It’s not X, it’s Y” can trigger a subconscious alarm about AI involvement. Historically, the construction predates ChatGPT. A memorable line from the TV series Mad Men—“It’s not a timepiece; it’s a conversation piece”—once felt like clever copywriting. Today, the same line is often read through the lens of a chatbot’s output, illustrating how AI reshapes our perception of language. Beyond this specific formula, other stylistic quirks have emerged as potential AI fingerprints. Vague intensifiers such as “quietly powerful” or “deeply transformative” and an over‑abundance of em‑dashes are increasingly flagged as tell‑tale signs of machine‑generated text. For writers, the constant vigilance has become exhausting. The author confesses to a new habit of mentally re‑labeling everyday statements—turning a cup of tea into a “precious respite” or a window into a “portal to a new way of thinking”—in an effort to avoid the dreaded AI‑style pattern. Looking ahead, the writer hopes the current quirk will fade as language models evolve. Yet the warning remains: new, perhaps even more insidious, stylistic signatures are likely to surface, demanding ever‑greater scrutiny from anyone who values authentic human voice.

The Valuation Explosion: From $7.5B to $18BFluidstack is currently in advanced talks to secure a $1 billion funding round that would value the AI infrastructure startup at $18 billion. This represents a more than doubling of its valuation from the previous round in December, which reportedly raised around $700 million at a $7.5 billion valuation. The potential lead investor for this new round is Jane Street, a major trading firm expanding into venture capital.Previous Round Details: Led by Situational Awareness, an AGI-focused fund founded by former OpenAI researcher Leopold Aschenbrenner.Supporters: The round was backed by the Collison brothers from Stripe, former GitHub CEO Nat Friedman, and entrepreneur Daniel Gross.Google's Interest: Reports indicate Google was considering a $100 million contribution to the round in February.The Anthropic Partnership: A $50 Billion Bet on InfrastructureThe primary driver behind Fluidstack's skyrocketing valuation is its strategic partnership with Anthropic. In November, Anthropic signed a massive $50 billion deal with Fluidstack to build custom-designed data centers in Texas and New York.Custom Infrastructure: Unlike hyperscalers like AWS or Google Cloud that offer general-purpose computing, Fluidstack builds specialized hardware specifically for AI workloads.Strategic Independence: This deal allows Anthropic to bypass the capacity constraints of public cloud providers and gain greater control over its infrastructure.Market Context: Anthropic primarily relies on AWS and Google Cloud for Claude, but the rapid growth of AI models necessitates bespoke solutions.Strategic Pivot: Relocating HQ and Exiting European ProjectsThe deal with Anthropic has fundamentally altered Fluidstack's global strategy, shifting its focus entirely toward the United States.Headquarters Move: The startup, originally spun out of Oxford and a rising star in Europe, has relocated its headquarters from the U.K. to New York.European Exit: Fluidstack pulled out of a key €10 billion AI project in France to focus exclusively on U.S. opportunities.Client Base: Beyond Anthropic, the company counts Meta, Poolside, Black Forest Labs, and Mistral as key customers.The Future of AI Infrastructure: Specialization Over GeneralizationFluidstack's rapid ascent signals a critical shift in the AI industry. As AI models become more complex and compute-intensive, general-purpose cloud providers are struggling to keep up with demand. The market is increasingly favoring specialized infrastructure providers that can offer bespoke hardware and dedicated capacity, a trend that validates Fluidstack's aggressive expansion strategy.

In 2020, several nations—including the UK and India—announced ambitious bans on new internal‑combustion‑engine vehicles, while Norway already saw around 60% of new car sales being electric. Australia, however, remained on a different trajectory. Former Prime Minister Scott Morrison dismissed a Labor proposal for a non‑binding 50% electric‑vehicle target by 2030, claiming it would “end the weekend.” The Coalition ignored analyses suggesting that a robust emissions‑cut scheme could deliver a $14 billion net benefit by 2040, and later abandoned plans for an EV‑specific strategy. Five years on, the Albanese government has introduced a vehicle‑efficiency standard mandating annual reductions in average emissions from new cars. Though a long‑awaited move, the policy’s impact will be incremental rather than transformative. March saw a record number of Australians purchasing EVs, yet the market share remains modest—still under 15% of new car sales, up only slightly from 13% in 2025. With fuel prices soaring amid the Iran conflict, the majority of vehicles leaving showrooms are still powered by petrol or diesel, and many will stay on the road for the next 15‑20 years. One bright spot is the surge in second‑hand EV sales, which more than doubled last month despite a tiny baseline. Higher resale values are encouraging broader adoption by making electric cars financially accessible to a larger pool of buyers. Globally, electric vehicles accounted for roughly 25% of new car sales last year. In Australia, the price differential between comparable petrol and electric models averages around 20%, a significant barrier for many consumers. That gap is narrowing, and the potential savings for EV drivers are substantial. Data from energy analyst Simon Holmes à Court—using Amber electricity retailer figures—show that an EV can travel over 40 km per $1 of energy, whereas a conventional car manages less than 5 km per $1 of fuel. Amber’s own smart‑charging platform suggests the distance could reach 160 km per $1 under optimal conditions. Despite such evidence, Australian political discourse often struggles to envision a low‑fossil‑fuel future. Calls for expanded oil exploration, such as Queensland Premier David Crisafulli’s claim of a “sea of oil” in the Taroom trough, lack substantiation and would likely involve costly, long‑term development with uncertain returns. Compounding the issue, the mining sector—Australia’s biggest diesel consumer—receives a 52‑cent‑per‑litre rebate under a national fuel‑tax credit scheme, effectively subsidising over $1 billion annually for diesel use in coal mines. This incentive discourages investment in cleaner truck technologies, even as the safeguard mechanism attempts to curb emissions. Policy recommendations include tightening the vehicle‑efficiency standard to accelerate the shift toward cleaner cars, removing parallel‑import restrictions to boost the supply of affordable second‑hand EVs (as practiced in New Zealand), and reconsidering any road‑user charges on electric vehicles, which currently represent less than 2% of the total fleet. International examples offer guidance: China jump‑started its EV boom by issuing “green” licence plates and imposing hefty fees for fossil‑fuel plates, effectively raising the cost of owning a petrol car by up to $20,000. In sum, Australia’s delayed embrace of electric mobility not only hampers climate goals but also forfeits billions in economic gains. A decisive, well‑targeted policy overhaul could unlock significant consumer savings, reduce emissions, and align the nation with global EV trends.

The way large language models are trained could have a profound impact on human communication. These models are primarily trained on written text, such as textbooks and social media posts, and our speech as captured in movies and television shows. However, this limited scope excludes the vast majority of human speech, which occurs through face-to-face conversations and voice interactions.As a result, the increased use of AI-generated text could lead to a homogenization of language, with humans adopting the linguistic patterns and behaviors of these models. This could affect not only how we communicate with one another but also how we think about ourselves and the world around us. Our perception of reality may become distorted in ways we have yet to fully comprehend.One potential consequence is that our language may become more concise and formulaic, similar to the effects of texting and social media. However, the impact of AI-generated language could be more profound, potentially eroding courteousness and encouraging a more commanding tone in our interactions. A 2022 study found that children who used voice commands with tools like Siri and Alexa became curt when speaking with humans, often using imperative language and expecting obedience.Moreover, the influence of AI-generated text could lead to a narrowing of vocabulary and sentence structure, as machines tend to produce smooth and polished but emotionless language. This could have significant implications for how we express ourselves and connect with others. Additionally, the reinforcement of confirmation bias through AI-generated text could make us more entrenched in our views and less open to opposing ideas.It is essential to consider the potential consequences of relying on AI-generated language and to explore ways to develop more nuanced and human-like language models. By excluding the majority of human language production – informal conversations and natural speech – these models may be mirroring a distorted version of human communication. This could have far-reaching implications for our relationships, our culture, and our understanding of ourselves.

China has emerged as a leader in global AI governance, contrasting with the US, which is pursuing AI development in a 'wild west' manner, according to Prof Dame Wendy Hall, a former UN and UK government adviser. Hall told the House of Commons business and trade committee that China is backing multinational attempts to introduce global governance of AI, while the US has set up a race between profit-hungry companies that rely on hype.Hall, who is director of the Web Science Institute at the University of Southampton, said Chinese AI researchers are efficient, innovative, and willing to release their models on an open-source basis. However, she noted that it has become increasingly difficult for UK experts to collaborate with China on research, limiting her academic freedom.The UK's reliance on US tech companies, including Google, Microsoft, OpenAI, and Amazon, risks a repeat of the Post Office Horizon scandal, warned Neil Lawrence, Cambridge University's DeepMind professor of machine learning. He expressed concerns that the UK is outsourcing AI model development to private billionaires with zero loyalty to the British state and consumer.Hall and Lawrence also highlighted that promises from US-backed tech companies may not be delivered as planned. For example, OpenAI has put a UK datacentre project on hold, and a government plan to open a large UK sovereign AI datacentre is behind schedule.The tech industry has identified a lack of power as a key problem, with Microsoft saying a planned datacentre in the north of England will not come online until at least 2033 due to a shortage of power from the grid.

Nissan announced a sweeping overhaul that places AI‑defined vehicles at the core of its revival strategy. Chief executive Ivan Espinosa said the automaker will eventually embed autonomous‑driving technology in 90% of its cars, positioning the brand for a future where self‑driving functions become standard. As part of the same initiative, Nissan will reduce its lineup from 56 to 45 models, redirecting capital toward higher‑margin offerings. The move follows a painful restructuring that has already seen seven factory closures and the loss of 20,000 jobs since Espinosa took the helm last year. Speaking at Nissan’s Yokohama headquarters, Espinosa warned that “structural challenges have compounded over time,” noting that the company’s portfolio has aged faster than the market and that fixed costs remain high despite declining scale. The Japanese automaker also unveiled its new battery‑electric Juke, a crossover SUV that will be built at the Sunderland plant in northern England. This model is a keystone of Nissan’s broader electrification push in Europe. While accelerating its EV agenda, Nissan reaffirmed a commitment to hybrid technology, unveiling a new hybrid Rogue (known as the X‑Trail in some markets) aimed at the US, where recent policy shifts have reduced incentives for fully electric cars. To fuel growth, Nissan set ambitious sales targets: an additional 550,000 units in Japan by 2030 and one million units each in the United States and China. The rapid rollout of autonomous capabilities is expected to boost demand for the technology, benefitting partners such as Wayve, the British AI startup that signed its first deal with Nissan a year ago. Bernstein analyst Masahiro Akita called the plan “reasonable” but cautioned that “ongoing macro uncertainty makes it unclear whether Nissan can sustain top‑line growth and achieve a genuine turnaround.”

Goldman Sachs's chief executive, David Solomon, has expressed heightened awareness of the capabilities of Anthropic's Mythos AI model and is collaborating closely with the tech firm following warnings about the cybersecurity risk it poses.The US bank has been closely monitoring the rapid advancements in artificial intelligence, including large language models (LLMs), as part of broader efforts to protect itself from hackers.“Obviously the LLMs are making rapid progress and we’re hyper-aware of the enhanced capabilities of these new models with the help of the US government and the model publishers,” Solomon told analysts on an earnings call on Monday.Anthropic, the company behind the Claude family of AI tools, claimed last week that its latest model, Mythos, posed an unprecedented risk due to its ability to expose flaws in IT systems. The company warned that AI models have reached a level of coding capability where they can surpass all but the most skilled humans at finding and exploiting software vulnerabilities.Solomon emphasized that Goldman Sachs is working closely with Anthropic and all of its security vendors to harness frontier capabilities. “We are very focused on supplementing our cyber and infrastructure resilience. And this is part of our ongoing capabilities that we have been investing in, and are accelerating our investment in.”The news comes after the US Treasury secretary, Scott Bessent, summoned Solomon and other big American bankers to Washington to discuss the Mythos model last week. The meeting focused on heads of so-called systemically important banks, where regulators believe that a major disruption to their operations, or their potential collapse, would put financial stability at risk.On Monday, the UK government’s AI Security Institute (AISI) warned that Mythos was a “step up” over previous models in terms of the cyber threat it posed. AISI said Mythos could carry out attacks that required multiple actions and discover weaknesses in IT systems without human intervention.

Recent CDC data reveal a dramatic 1,200% increase in kratom‑related poisonings across the United States over the last ten years, with the most pronounced surge recorded in 2025. Researchers link this rise to the growing presence of 7‑hydroxymitragynine (7‑OH), a synthetically produced compound that mimics kratom’s effects but carries opioid‑like risks. Walter Prozialeck, pharmacology professor at Midwestern University, said the trend was expected, noting that the synthetic alkaloid has entered the market through energy drinks and other products since 2024. Christopher McCurdy of the University of Florida warned that marketing 7‑OH as “enhanced kratom” blurs the line for consumers, turning poison‑control calls into a conflated metric for both natural and synthetic products. By contrast, natural kratom (Mitragyna speciosa)—a Southeast Asian plant used for centuries as a pain reliever—has demonstrated a relatively favorable safety profile in animal and human studies. A 2018 statement from then‑HHS Secretary Brett Giroir rejected the DEA’s push to schedule kratom as a Schedule I substance, citing insufficient evidence of harm. Despite the scientific distinction, several states have moved to implement or propose blanket bans on all kratom products, prompting concern from clinicians and patient advocates. A recent user survey indicated that about 50% of respondents rely on kratom for chronic pain, while roughly 40% use it during addiction recovery. Personal testimonies underscore the plant’s therapeutic role. Jeff Maslan, a 68‑year‑old Californian with severe osteoarthritis, credits kratom with easing opioid withdrawal after multiple surgeries. Similarly, “Steven,” a disabled California resident, describes how kratom eliminated unbearable oxycodone withdrawal symptoms without producing the euphoric “warm fuzzy” feeling typical of opioids. Researchers emphasize that 7‑OH carries genuine opioid hazards, including addiction, severe withdrawal, and respiratory depression that can lead to fatal overdose. In animal models, 7‑OH demonstrated the same respiratory‑depression risk as classic opioids, whereas kratom’s primary alkaloid did not. Prozialeck and colleagues explain that kratom’s pharmacology is more nuanced: it partially activates opioid receptors while also engaging adrenergic and serotonin pathways, resembling a hybrid of a weak opioid and an SNRI‑type antidepressant. This multimodal action likely accounts for its lower euphoric potential and the reported boost in energy among users. Nevertheless, experts caution that kratom is not without risk. Fatal poisonings often involve co‑ingestion of potent opioids such as fentanyl, suggesting that some users may cycle between kratom and stronger substances, raising overdose danger due to reduced opioid tolerance. Additionally, heavy‑metal contamination has been detected in certain kratom batches, though the source—soil, processing, or storage—remains unclear. Given these complexities, the consensus among scholars like Austin Zamarripa (Johns Hopkins) is that natural kratom should remain accessible, while concentrated 7‑OH products merit stricter regulation. “These products may offer meaningful benefits to some individuals, and those benefits could be lost if access is restricted too broadly,” Zamarripa said, urging a differentiated policy approach. As the debate unfolds, patients like Steven worry that a sweeping ban would ignore the nuanced safety profile of the plant. “There’s corn on the cob, there’s high‑fructose corn syrup, there’s whiskey— all derived from corn but fundamentally different,” he remarked, highlighting the need for targeted, evidence‑based regulation rather than a one‑size‑fits‑all prohibition.