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The housing market just crossed an important thresholdone thats especially good news for anyone who might be planning on buying a home any time soon. The massive wave of COVID-19-era mortgages with ultra-low rates were a huge boon for many homebuyers, but the housing market hasnt been the same since. A huge swath of homeowners in the U.S. suddenly had mortgage interest rates well below 4%and very little incentive to sell their homes for less affordable options with todays higher rates. That dilemma has created a nightmarish scenario for the U.S. housing market. Many potential buyers and aspiring first-time homeowners remain priced out due to high home prices and higher interest rates. With more homeowners staying put whether they want to or not, housing inventory dried up considerably, shrinking the pool of options for home shoppers. Thats beginning to change. According to new data from Realtor.com, the share of U.S. homeowners with mortgage rates over 6% is now greater than the share hanging onto those ultra low sub-3% rates. In the third quarter of 2025, 21% of outstanding mortgages carried a rate above 6% compared to the 20% of mortgages with rates below 3%. That change signals a meaningful shift from the gridlock thats defined the last few years in the U.S. housing market. Mortgage rates above 6% now represent a larger share of outstanding loans than the ultra-low rates that defined the pandemic-era housing boom, Realtor.com Chief Economist Danielle Hale said in a press release. This crossover reflects a gradual resetting as some households trade in low-rate mortgages for higher-rate loans or enter the market for the first time, even as rate lock-in continues to limit the pace of inventory recovery. Lasting impact of low rates and lock-in Those ultra-low rates are on their way out, but many homeowners still have rates well below what theyd be offered today. According to the new data, over 50% of mortgages still have rates at or below 4% and almost 70% have rates of 5% or lower. As long as that remains the case, the average homeowner might see their monthly mortgage payment spike by as much as $1,000 if they sold their home and took on a mortgage with todays rates. Still, the new mortgage data is a promising sign. Rates are very unlikely to get as low as they did during the early days of COVID-19 again in our lifetimesparticularly now that we know just what a lasting disruptive impact the low rate homebuying frenzy had on the market at large. The period between July 2020 and September 2021 is the only time that the U.S. 30-year fixed mortgage rate has gone below 3% since those records began being kept in the early 1970s. The high cost of buying a home is more salt in the wound for many Americans, who have seen the price of everything from groceries to used cars soar in recent years. With little relief in 2025, the unaffordability crisis seems to be on everyones mind lately. If interest rates settle down and the present trends continue, at least the housing market might be getting back to something a little closer to normal this year. Even with rates still elevated, modest mortgage rate decreases into the low-6% range could encourage additional home buying activity, Hale said. Further easing in inflation and mortgage rates would be key to unlocking more seller participation, helping to relieve price pressure and competition in an under-supplied market.
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Fujifilms newest camera model, the Instax Mini Evo Cinema, is a gadget thats designed for the retro camera craze. The device is a vertically oriented instant camera that can take still images, videos (an Instax camera first), connect with your smartphone to turn its photos into physical prints, and capture images in a wide range of retro aesthetics. Its debuting in North American markets in early February for $409.95. Fujifilms new model taps into a younger consumer bases growing interest both in retro tech and film photography aestheticsa trend thats been driven, in large part, by platforms like TikTok. The Instax Mini Evo Cinema turns that niche into a clever feature called the Gen Dial: a literal dial that lets users toggle between decades to capture their perfect retro shot. [Photo: Fujifilm] How the Gen Dial works Almost everything about the Instax Mini Evo Cinema screams nostalgia, from its satisfying tactile buttons to its vertical orientationand thats by design. According to Fujifilm, the cameras silhouette is inspired by the 1965 Fujica Single-8, an 8-millimeter camera initially introduced as an alternative to Kodaks Super 8. While the Instax Mini Evo Cinema does come with a small LCD display, its main functions are controlled with a series of dials, buttons, and switches, which Fujifilm says are designed to evoke the feel of winding film by hand, add to the analog charm, and expand the joy of shooting and printing. The most innovative of these is undoubtedly the Gen Dial. While there are plenty of existing editing apps and filter presets to give a photo a certain vintage look in-post, this may be the first instant camera to actually brand in-camera filters by era. [Photo: Fujifilm] The dial is labeled in 10-year increments, from 1930 to 2020. To choose an effect, users can simply click to the era theyd like to replicate, then shoot and print. According to the company, selecting 1940 will result in a look inspired by the vivid color expression of the three-color film processes, for example; 1980 pulls cues from 35-millimeter color negative film; and 2010 evokes the style of early smartphone photo-editing apps (throwback!). “Overall, our goal with Mini Evo Cinema is to deepen options for creative expression,” says Ashley Reeder Morgan, VP of consumer products for Fujifilm’s North America division. “Beyond video, the Gen Dial provides an experience to transcend time and space over 100 years (10 eras), applying both visual and audio to the mini Evo Cinema output.” From left: 1940, 1980, and 2010 styles [Photos: Fujifilm] For amateur photographers looking to achieve a certain vintage aesthetic without spending endless hours in Adobe Lightroom or fiddling with complicated camera settings, its the perfect intuitive solution. Retro cameras get a TikTok-driven boost For Fujifilm, the Instax Mini Evo Cinema is part of a broader, internet-driven revival of the brands camera division. While Fujifilm previously spent years moving away from its legacy camera business to focus on healthcare, its $1,599 retro-themed X100V camerawhich went viral on TikTokrecently triggered a resurgence in its sales. The companys most recent financials, released in September, show that its imaging division (which includes cameras) experienced a 15.6% revenue increase year over year, which Morgan says is attributable to the success of its instant and digital cameras. “Overall, we have been thrilled to see younger generations rediscovering the joy of photography, whether instant, analog, or digital,” Morgan says. The X100Vs popularity online is likely driven by Gen Z and Gen Alphas interest in retro tech aesthetics (see: Urban Outfitters iPod revival), as well as a more general resurgence in film photography in recent years. Analog cameras are having a moment, and companies like Polaroid and Fujifilm are cashing in.
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It’s hard to avoid the conclusion that the market for artificial intelligence and its associated industries are over inflated. In 2025, just five hyperscalersAlphabet, Meta, Microsoft, Amazon, and Oracleaccounted for a capital investment of $399 billion, which will rise to over $600 billion annually in coming years. For the first nine months of last year, real GDP growth rate in the U.S. was 2.1%, but would have been 1.5% without the contribution of AI investment. This dependence is dangerous. A recent note by Deutsche Bank questioned whether this boon might in fact be a bubble, noting the historically unprecedented concentration of the industry, which now accounts for around 35% of total U.S. market capitalization, with the top 10 U.S. companies making up more than 20% of the global equity market value. For such an investment to yield no benefit would be a failure of unprecedented proportions. In their book Power and Progress, Nobel Prize-winning economists Daron Acemoglu and Simon Johnson narrate the calamitous failure of the French Panama Canal project in the late 19th century. Thousands of investors, large and small, lost their fortunes, and 20,000 people who worked on the project died for no benefit. The problem, Acemoglu and Simon write, was that the vision for progress did not include everyoneand failure to incorporate feedback from others resulted in poor quality decision making. As they observe, what you do with technology depends on the direction of progress you are trying to chart and what you regard as an acceptable cost.Fast forward 150 years and a significant chunk of the U.S. economy is similarly dependent on a small coterie of grand visionaries, ambitious investors, and techno-optimists. Their capacity to ignore their critics and sideline those forced to bear the costs of their mission risks catastrophic consequences. Trustworthy AI systems cannot be conjured by marketing magic. We must ensure those building, deploying, and working with these systems can have a say in how we direct the progress of this technology. Mistrust and a general lack of optimism The data suggests that there is an urgent need to chart a new course. Even a generous analysis of the market for generative AI products would likely struggle to show how a decent return on the gargantuan investment in capital is realistic. A recent report from MIT found that notwithstanding $30 billion to $40 billion in enterprise investment into GenAI, 95% of organizations are getting zero return. It is difficult to imagine another industry raising so much capital despite producing so little to show for it. But this appears to be Sam Altmans true superpower, as Brian Merchant has documented extensively. This is coupled with significant levels of mistrust and a general lack of optimism from everyday people about the potential of this technology. In the most comprehensive global survey of 48,000 people across 47 countries, KPMG found that 54% of respondents are wary about trusting AI. They also want more regulation: 70% of respondents said regulation is necessary, but only 43% believe current laws are adequate. The report concludes that the most promising pathway towards improving trust in AI was through strengthening safeguards, regulation, and laws to promote safe AI use. This, most obviously, sits in stark contrast with the position of the Trump administration, which has repeatedly framed regulation of the industry as an impediment to innovation. But the trust deficit cannot simply be hyped out of existence. It represents a significant structural barrier to the take up and valuable deployment of emerging technologies. One of the key conclusions of the MIT report is that the small subset of companies that actually saw productivity gains from generative AI products were doing so because they build adaptive, embedded systems that learn from feedback. Highly centralized decisions about procurement were more likely to result in employees being required to use off-the-shelf products unsuited to the enterprise environment and generating outputs that employees mistrusted, especially for higher-stakes tasks, resulting in work arounds or dwindling rates of usage. The problem is that these tools fail to learn and adapt. In turn, there are too few opportunities for executives to receive that feedback or incorporate it meaningfully into model development and adaptation. The narrative spun by politicians and media commentators that the AI industry is full of visionary leaders inadvertently points to a key cause of why these products are failing. Trust in AI systems can only be earned if feedback is both sought and acted onwhich is a significant challenge for the hyperscalers, because their foundational models are less capable of adapting and responding to unique and varied contexts. Unless we decentralize the development and governance of this, the benefits may remain elusive. The workers’ view There are useful ideas lying around that could help navigate a different path of technological progress. The Human Technology Institute at the University of Technology Sydney published research about how workers are treated as invisible bystanders in the roll out of AI systems. Through deep, qualitative consultations with nurses, retail workers, and public servants to solicit feedback about automated systems and their impact on their work. Rather than exhibiting backward or unhelpful attitudes to AI, workers expressed nuanced and constructive contributions to the impact on their workplaces. Retail workers, for example, talked about the difficulties of automated systems that disempowered workers, and curtailed their discretion: unlike a production line, retail is an unpredictable environment. You have these things called customers that get in the way of a nice steady flow. A nurse noted how “the increasing roll-out of automated systems and alerts causes severe alarm fatigue among nurses. When an (AI system) alarm goes off, we tend to ignore or not take it seriously. Or immediately override to stop the alarm. One might think that increased investment in such systems would contend with the problem of alarm fatigue. But without worker input, its easy to miss this as a problem entirely. The upshot is that, as one public servant put it, in workplaces whre channels for worker feedback are absent, a necessary quality of employees was “the gift of the workaround.” Traditionally, this kind of consultation and engagement would happen through worker organizations. But with the rate of unionization slipping below 10% in the U.S., this becomes a problem not just for workers but also employers, who are left with few methods to meaningfully engage with their workforce at scale. Some unions are nonetheless leading on this issue, and in the absence of political leadership, might be the best hope of making change. The AFL-CIO has developed a promising model law aimed at protecting workers from harmful AI systems. The proposal focuses on limiting the use of worker data to train models, as well as introducing friction into the automation of significant decisions, such as hiring and firing. It also emphasizes giving workers the right to refuse to follow directives from AI systemsessentially, building in feedback loops for when automation goes wrong. The right to refuse is an essential failsafe that can also cultivate a culture of critical engagement with technology, and serve as a foundation for trust. Businesses are welcome to ignore workers views, but workers may end up making themselves heard in other ways. Recent surveys indicate that 31% of employees admit to actively sabotaging their companys AI strategy, and for younger workers, the rates are even higher. Even companies that fail to seek feedback from workers may still end up receiving it all the same. Our current course of technological progress relies on narrow understandings of expertise and places too much faith in small numbers of very large companies. We need to start listening to the people who are working with this technology on a daily basis to solve real world problems. This decentralization of power is a necessary step if we want technology that is both trustworthy and effective.
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