Latest news with #AndreyRudakov
News24
4 days ago
- Automotive
- News24
Man dies after being sucked into plane engine at Italy's Bergamo Airport
A file image shows the engines of an Airbus A319 passenger jet. A man in Italy was sucked into the engine of a similar aircraft. Andrey Rudakov/Bloomberg via Getty Images
Forbes
26-04-2025
- Business
- Forbes
Diamond Price Decline: Are You Overpaying On Insurance?
Photographer: Andrey Rudakov/Bloomberg Insuring diamond jewelry has traditionally been simple. The owner would have the stone appraised, report the value to their insurer, and pay a premium based on its replacement cost. However, the diamond market has shifted over the last decade. Prices for natural diamonds have fallen, while lab-grown diamonds have become an affordable alternative. The combination of falling prices and increased concern over authenticity creates a financial dilemma that many consumers overlook. Does my diamond appraisal still reflect the premium I'm paying? Is the diamond still worth what the appraisal says? And if not, what should be done about insurance? Natural diamonds have long been marketed as durable stores of value. But that perception is changing. According to the IDEX Diamond Index, which tracks real-time diamond trading prices, average asking prices declined by 38% over the past three years. In some categories, the drop has been even steeper. According to industry estimates, much of this slide is tied to the rise of lab-grown diamonds, which now account for nearly half of engagement ring sales in the United States. These stones are physically and chemically identical to mined diamonds but cost up to 90% less. The price gap is widening as production technology improves and supply scales up. Consumers are increasingly opting for larger or higher-quality stones at lower prices, eroding demand for natural diamonds, particularly in the lower to mid-range of the market. The downturn in diamond prices may be structural in nature, not cyclical. For years, supply was tightly managed, and pricing was relatively stable. But the surge in lab-grown alternatives has disrupted that equilibrium. Meanwhile, macroeconomic headwinds have added further pressure, from a slowdown in Chinese luxury demand to a broader caution in discretionary spending. Most people insure their fine jewelry at the time of purchase, using the appraisal provided by a jeweler. These appraisals are often generous, listing values well above what the buyer paid. That can feel reassuring, but it also locks in a replacement cost that may no longer be accurate in today's market. Consider a natural diamond ring purchased in 2019 for $12,000 and appraised at $15,000. But today, that same ring might retail for closer to $8,000. The diamond owner may pay inflated premiums if the policyholder hasn't updated the appraisal. In addition, most collectibles policies automatically raise the insured value of covered collectibles—usually by 6% to 8% per year—in the event of a total loss. This annual increase is designed to help offset inflation and keep up with rising market values, but the feature can lead to an overinsured situation if prices fall. In the above example, the ring that was originally appraised for $15,000 may have an insured value of $20,000, which is much higher than the replacement cost. The outcome of a claim could be even worse. In the event of a loss, the insured could receive a lab-grown replacement if the policy includes open-ended replacement language, even if the lost or stolen stone was a natural diamond. Insurance policies vary. Some offer stated value coverage, where the insurer pays a fixed amount. Others offer replacement value, where the insurer provides a substitute as similar as possible to the original item. The latter creates ambiguity in today's market. If a policyholder loses a natural diamond, will the insurer replace it with another natural stone or a visually identical lab-grown version worth a fraction of the amount? Lab-grown diamonds have complicated more than just pricing—they've blurred the lines of authenticity. Until recently, testing an undocumented stone's origin required sending it to a lab and, in many cases, removing it from its setting. That created cost and friction in resale and insurance claims, where verifying whether a diamond was mined or lab-grown wasn't always straightforward. De Beers has just introduced a device that could change that. The company's new DiamondProof machine distinguishes between natural diamonds and other materials, even when mounted in jewelry. It is being marketed to retailers to give consumers confidence in their natural diamond purchases, with 0% false positives. In other words, it will never pass a lab stone as a natural diamond. This technology has significant implications for the secondary market. A diamond assumed to be mined—especially if it was bought secondhand or inherited—could be lab-grown. That would instantly reduce its resale value and potentially invalidate assumptions used in past appraisals. Knowing with certainty whether a stone is lab-grown or mined will help owners and sellers of mined diamonds prove authenticity. De Beers is hoping the new technology will restore confidence in the market. "Despite current market volatility, we believe in natural diamonds as a long-term store of value," says De Beers Group Natural Diamonds Market Lead Sally Morrison. 'For that reason, we believe it is critical for consumers to know exactly what they are buying so they can make informed choices. DiamondProof makes the technology widely available so that both retailers and their clients can be confident.' The technology also adds a new layer to insurance underwriting. Carriers may begin requesting lab reports or scanning results as part of the appraisal process. In the same way that a vintage watch without original papers trades at a discount, diamonds without confirmed origin could lose value. De Beers' DiamondProof technology Owners of natural diamonds paying for itemized collectibles insurance should take four simple but important steps. First, get a new appraisal. Ask for an assessment based on current market conditions, and ensure it reflects whether the stone is natural or lab-grown. Don't rely on a figure calculated five or ten years ago or even one based on retail markup alone. You may be overinsured. Second, review existing insurance policies. Understand how coverage is structured. Does it pay a cash value, or does it replace the item? If it replaces, will it guarantee a natural stone? If unsure, ask your carrier or broker for clarification. Third, consider having stones tested. If you plan to sell or even pass down jewelry to your family, having documentation proving the origin is helpful. With De Beers' new machine entering the market, expect to see more retailers and appraisers offering origin verification as part of their service. Fourth, evaluate how jewelry is stored. Collectibles policies typically charge 1% to 2% of an item's insured value annually in premium. However, if jewelry is stored in a permanent safe or a bank vault, insurance premiums could fall to as low as 0.3% per year. A good insurance broker can help optimize the policy. Patti Clement, executive vice president of Hub Private Client Group, says it is important for the underwriter to understand the wearing habits of the jewelry. 'There are creative ways to keep costs down based on how often items are worn outside the household on an average daily basis, along with how they are stored—whether in a home safe bolted to the ground, built into the home, or kept in a bank vault. For higher-valued items that are rarely worn, the savings could be substantial,' Clement says. The diamond market is experiencing a structural shift. Prices are lower, authenticity is being scrutinized, and the old rules of value and permanence are no longer taken for granted. These changes have real implications for diamond owners. Given the recent volatility in the stock market, it is easy to forget that diamonds may be part of your investment portfolio. However, if they are insured, appraised, or part of your estate planning, it is worth paying attention to the changes in the diamond market.
Yahoo
27-01-2025
- Business
- Yahoo
What Is DeepSeek, the New Chinese OpenAI Rival?
A welcome message on the DeepSeek artificial intelligence mobile app Credit - Andrey Rudakov—Bloomberg/Getty Images A new Chinese AI model, created by the Hangzhou-based startup DeepSeek, has stunned the American AI industry by outperforming some of OpenAI's leading models, displacing ChatGPT at the top of the iOS app store, and usurping Meta as the leading purveyor of so-called open source AI tools. All of which has raised a critical question: despite American sanctions on Beijing's ability to access advanced semiconductors, is China catching up with the U.S. in the global AI race? At a supposed cost of just $6 million to train, DeepSeek's new R1 model, released last week, was able to match the performance on several math and reasoning metrics by OpenAI's o1 model – the outcome of tens of billions of dollars in investment by OpenAI and its patron Microsoft. The Chinese model is also cheaper for users. Access to its most powerful versions costs some 95% less than OpenAI and its competitors. The upshot: the U.S. tech industry is suddenly faced with a potentially cheaper and more powerful challenger, unnerving investors, who sold off American tech stocks on Monday morning. Yet not everyone is convinced. Some American AI researchers have cast doubt on DeepSeek's claims about how much it spent, and how many advanced chips it deployed to create its model. Few, however, dispute DeepSeek's stunning capabilities. 'Deepseek R1 is AI's Sputnik moment,' wrote prominent American venture capitalist Marc Andreessen on X, referring to the moment in the Cold War when the Soviet Union managed to put a satellite in orbit ahead of the United States. So, what is DeepSeek and what could it mean for U.S. tech supremacy? DeepSeek was founded less than two years ago by the Chinese hedge fund High Flyer as a research lab dedicated to pursuing Artificial General Intelligence, or AGI. A spate of open source releases in late 2024 put the startup on the map, including the large language model 'v3', which outperformed all of Meta's open-source LLMs and rivaled OpenAI's closed-source GPT4-o. At the time, Liang Wenfeng, the CEO, reportedly said that he had hired young computer science researchers with a pitch to 'solve the hardest questions in the world"—critically, without aiming for profits. Early signs were promising: his products were so efficient that DeepSeek's 2024 releases sparked a price war within the Chinese AI industry, forcing competitors to slash prices. This year, that price war looks set to reach across the Pacific Ocean. Yet DeepSeek's AI looks different from its U.S. competitors in one important way. Despite their high performance on reasoning tests, Deepseek's models are constrained by China's restrictive policies regarding criticism of the ruling Chinese Communist Party (CCP). DeepSeek R1 refuses to answer questions about the massacre at Tiananmen Square, Beijing, in 1989, for example. 'Sorry, that's beyond my current scope. Let's talk about something else,' the model said when queried by TIME. At a moment when Google, Meta, Microsoft, Amazon and dozens of their competitors are preparing to spend further tens of billions of dollars on new AI infrastructure, DeepSeek's success has raised a troubling question: Could Chinese tech firms potentially match, or even surpass, their technical prowess while spending significantly less? Meta, which plans to spend $65 billion on AI infrastructure this year, has already set up four 'war rooms' to analyze DeepSeek's models, seeking to find out how the Chinese firm had managed to train a model so cheaply and use the insights to improve its own open source Llama models, tech news site The Information reported over the weekend. In the financial markets, Nvidia's stock price dipped more than 15% on Monday morning on fears that fewer AI chips may be necessary to train powerful AI than previously thought. Other American tech stocks were also trading lower. 'While [DeepSeek R1] is good news for users and the global economy, it is bad news for U.S. tech stocks,' says Luca Paolini, chief strategist at Pictet Asset Management. 'It may result in a nominal downsizing of capital investment in AI and pressure on margins, at a time when valuation and growth expectations are very stretched.' But American tech hasn't lost—at least not yet. For now, OpenAI's 'o1 Pro' model is still considered the most advanced in the world. The performance of DeepSeek R1, however, does suggest that China is much closer to the frontier of AI than previously thought, and that open-source models have just about caught up to their closed-source counterparts. Perhaps even more worrying for companies like OpenAI and Google, whose models are closed source, is how much—or rather, how little—DeepSeek is charging consumers to access its most advanced models. OpenAI charges $60 per million 'tokens', or segments of words, outputted by its most advanced model, o1. By contrast DeepSeek charges $2.19 for the same number of tokens from R1—nearly 30 times less. 'It erodes the industrial base, it erodes the margin, it erodes the incentive for further capital investment into western [AI] scaling from private sources,' says Edouard Harris, the chief technology officer of Gladstone AI, an AI firm that works closely with the U.S. government. DeepSeek's success was all the more explosive because it seemed to call into question the effectiveness of the U.S. government's strategy to constrain China's AI ecosystem by restricting the export of powerful chips, or GPUs, to Beijing. If DeepSeek's claims are accurate, it means China has the ability to create powerful AI models despite those restrictions, underlining the limits of the U.S. strategy. DeepSeek has claimed it is constrained by access to chips, not cash or talent, saying it trained its models v3 and R1 using just 2,000 second-tier Nvidia chips. 'Money has never been the problem for us,' DeepSeek's CEO, Liang Wenfeng, said in 2024. 'Bans on shipments of advanced chips are the problem.' (Current U.S. policy makes it illegal to export to China the most advanced types of AI chips, the likes of which populate U.S. datacenters used by OpenAI and Microsoft.) But are those claims true? 'My understanding is DeepSeek has 50,000 H100s,' Scale AI CEO Alexandr Wang recently told CNBC in Davos, referring to the highest-powered Nvidia GPU chips currently on the market. 'They can't talk about [them], because it is against the export controls that the U.S. has put in place.' (An H100 cluster of that size would cost in the region of billions of dollars.) In a sign of how seriously the CCP is taking the technology, Liang, Deepseek's CEO, met with China's premier Li Qiang in Beijing last Monday. In that meeting, Liang reportedly told Li that DeepSeek needs more chips. 'DeepSeek only has access to a few thousand GPUs, and yet they're pulling this off,' says Jeremie Harris, CEO of Gladstone AI. 'So this raises the obvious question: what happens when they get an allocation from the Chinese Communist Party to proceed at full speed?' Even though China might have achieved a startling level of AI capability with fewer chips, experts say more computing power will always remain a strategic advantage. On that front, the U.S. remains far ahead. 'It's never a bad thing to have more of it,' says Dean Ball, a research fellow at George Mason University. 'No matter how much you have of it, you will always use it.' The short answer: from Washington's perspective, in uncertain waters. In the closing days of the Biden Administration, outgoing National Security Adviser Jake Sullivan warned that the speed of AI advancement was 'the most consequential thing happening in the world right now.' And just days into his new job, President Trump announced a new $500 billion venture, backed by OpenAI and others, to build the infrastructure vital for the creation of 'artificial general intelligence'— the next leap forward in AI, with systems advanced enough to make new scientific breakthroughs and reason in ways that have so far remained in the realm of science fiction. Read More: What to Know About 'Stargate,' OpenAI's New Venture Announced by President Trump And although questions remain about the future of U.S. chip restrictions on China, Washington's priorities were apparent in President Trump's AI executive order, also signed during his first week in office, which declared that 'it is the policy of the United States to sustain and enhance America's global AI dominance in order to promote human flourishing, economic competitiveness, and national security.' Maintaining this dominance will mean, at least in part, understanding exactly what Chinese tech firms are doing—as well as protecting U.S. intellectual property, experts say. 'There's a good chance that DeepSeek and many of the other big Chinese companies are being supported by the [Chinese] government, in more than just a monetary way,' says Edouard Harris of Gladstone AI, who also recommended that U.S. AI companies harden their security measures. Since December, OpenAI's new o1 and o3 models have smashed records on advanced reasoning tests designed to be difficult for AI models to pass. Read More: AI Models Are Getting Smarter. New Tests Are Racing to Catch Up DeepSeek R1 does something similar, and in the process exemplifies what many researchers say is a paradigm shift: instead of scaling the amount of computing power used to train the model, researchers scale the amount of time (and thus, computing power and electricity) the model uses to think about a response to a query before answering. It is this scaling of what researchers call 'test-time compute' that distinguishes the new class of 'reasoning models,' such as DeepSeek R1 and OpenAI's o1, from their less sophisticated predecessors. Many AI researchers believe there's plenty of headroom left before this paradigm hits its limit. Some AI researchers hailed DeepSeek's R1 as a breakthrough on the same level as DeepMind's AlphaZero, a 2017 model that became superhuman at the board games Chess and Go by purely playing against itself and improving, rather than observing any human games. That's because R1 wasn't 'pretrained' on human-labeled data in the same way as other leading LLMs. Instead, DeepSeek's researchers found a way to allow the model to bootstrap its own reasoning capabilities essentially from scratch. 'Rather than explicitly teaching the model on how to solve a problem, we simply provide it with the right incentives, and it autonomously develops advanced problem-solving strategies,' they claim. The finding is significant because it suggests that powerful AI capabilities might emerge more rapidly and with less human effort than previously thought, with just the application of more computing power. 'DeepSeek R1 is like GPT-1 of this scaling paradigm,' says Ball. Ultimately, China's recent AI progress, instead of usurping U.S. strength, might in fact be the beginning of a reordering—a step, in other words, toward a future where, instead of a hegemonic power, there are many competing centers of AI power. 'China will still have their own superintelligence(s) no more than a year later than the US, absent [for example] a war,' wrote Miles Brundage, a former OpenAI policy staffer, on X. 'So unless you want (literal) war, you need to have a vision for navigating multipolar AI outcomes.' Write to Billy Perrigo at
