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📰 The Local Germany📅 2026-04-29enSalute · ambiente
German cabinet set to approve health reforms and budget plans, bid to rescue 'Timmy' the whale passes key hurdle, German birth rate falls to lowest level since 1946 and more news on Wednesday, April 29th.
German cabinet set to approve health reforms and budget plans, bid to rescue 'Timmy' the whale passes key hurdle, German birth rate falls to lowest level since 1946 and more news on Wednesday, April 29th. Wednesday's top story: German cabinet set to approve health reforms and budget plans Germany’s governing coalition is facing mounting strain as it attempts to press ahead with major policy decisions amid sinking poll ratings and growing internal dissent. Less than a year into the term, relations between the CDU and SPD are described in Berlin as toxic, with the far‑right AfD leading national polls and the SPD languishing around 13 percent. Prominent CDU figures are openly questioning whether the government will last a full term. Against this backdrop, the cabinet is nonetheless expected to approve a sweeping healthcare reform on Wednesday put forward by Health Minister Nina Warken. The package aims to deliver €16.3 billion in savings – more than the projected deficit in statutory health insurance – by raising the contribution assessment ceiling and introducing a tax on sugary drinks. READ ALSO:How Germany's public health insurance shake-up will affect families Planned cuts to sick pay have reportedly been dropped, but the burden is still expected to fall disproportionately on contributors and patients needing dental treatment. Also on Wednesday, cabinet attention will turn to the 2027 federal budget, where Finance Minister Lars is expected to attempt to close a €34‑billion funding gap through new levies on plastic, alcohol, tobacco and cryptocurrencies. Germany opens rare earth magnet recycling plant A plant to recycle and produce rare earth magnets opened in Germany on Tuesday, as Europe seeks to reduce its dependence on China for minerals key to industries from car-making to renewable energy. The new plant -- in the southwest city of Pforzheim and operated by German start-up HyProMag -- is among several such projects being launched in Europe. The facility, which aims to produce 750 tonnes of magnets a year by 2028, is "an important step towards strengthening Europe's secure and sustainable supply of critical raw materials," said the company in a statement. The plant's construction was partly funded by the EU as well as the German government. Rare earth magnets are used in many products, from electric vehicles to wind turbines and consumer electronics. Current European Union demand totals about 20,000 tons a year. China, which dominates the rare earths industry, last year dramatically ramped up export curbs on the materials, sending shockwaves through global supply chains. READ ALSO:'China shock' - Germany struggles as key market turns business rival German bid to rescue 'Timmy' the whale passes key hurdle German rescuers on Tuesday hauled a stranded humpback whale into a special boat due to carry it to deeper waters, in the latest attempt to free the cetacean whose ordeal has captured hearts in Germany for weeks. The latest rescue effort -- financed by two entrepreneurs -- involves transporting the sea mammal in a barge, which has a water-filled hold and is usually used to carry other boats, from Germany's Baltic Sea coast to deeper waters. READ ALSO:'Free Timmy!' - How a beached whale has gripped and divided Germany Starting earlier Tuesday, rescuers attached straps to the whale and heaved the creature down a channel that had been specially dug in the sand to allow it to reach the barge, close to the island of Poel. After some distance, the whale, with rescuers swimming alongside it, sped up and then swam into the barge, sparking cheers of delight from the rescue team and others watching from the shore. "I can't even say how happy I am," Karin Walter-Mommert, one of the entrepreneurs financing the rescue bid, told the Bild daily. "You could see that the whale fought and wanted to live. Knowing he's now in the barge is simply wonderful and shows that the fight for Timmy was worth it." The plan is now for the barge to be transported to the North Sea, and hopefully for the whale to be released if it is strong enough. German birth rate falls to lowest level since 1946 Germany’s birth rate has fallen to its lowest level since the second World War, underscoring the growing demographic challenges facing the country. Official figures from the statistics office Destatis show that around 654,300 children were born in 2025, a decline of 3.4 percent compared with the previous year. This marks the fourth consecutive annual drop in births. At the same time, deaths far outstripped births. Around 1.01 million people died last year, leaving a “birth deficit” of roughly 352,000 – the largest recorded in the post‑war period. Destatis attributes the trend primarily to two factors: the relatively small cohort born in the 1990s now reaching typical child‑bearing age, and a steady fall in the fertility rate since 2022. READ ALSO:Why Germany’s rapidly aging population affects everyone in the country The figures come as Germany’s population continues to age rapidly. In 2024, about 19 million people – roughly 23 percent of the population – were aged 65 or over, up from 15 percent in 1991. The demographic shift is intensifying pressure on pension and welfare systems. A government pensions commission is due to present reform proposals by the end of June, after Chancellor Friedrich Merz sparked controversy by describing the state pension as only a “basic provision” – comments later walked back amid strong criticism. Germany tests ‘invisible’ river turbines to deliver power after dark Germany is testing a new kind of renewable power plant on the Middle Rhine that can generate electricity even when the sun has set and the wind drops. Near the town of Sankt Goar, engineers have begun deploying what officials describe as the world’s first fully approved “swarm power plant” using river currents rather than dams. The project consists of up to 124 small hydrokinetic turbines, known asEnergyfish, which sit beneath the water’s surface and draw energy from the constant flow of the Rhine. Unlike conventional hydropower, the system does not involve building a barrier or reservoir, helping to limit visual and environmental impact. READ ALSO:German 'green village' rides out Mideast energy storm Three turbines are already operating, with gradual expansion planned. Each unit can produce up to six kilowatts, and officials estimate that 100 turbines could generate around 1.5 gigawatt-hours of electricity per year – enough to supply roughly 400 to 500 households. Supporters say the steady output could help plug gaps left when solar and wind generation fall. Environmental effects, particularly on fish, are being closely studied by researchers, while the state government sees the project as a potential model for low-impact, round-the-clock renewable energy. With reporting by AFP, DPA and Paul Krantz. Please sign up or log in to continue reading
SHANGHAI, April 29, 2026 /PRNewswire/ -- Envision Energy, a global leader in green technology, today announced its participation in the pilot phase of the AEA Ammonia Certification System, a global certification system designed by the Ammonia Energy Associati…
SHANGHAI,April 29, 2026/PRNewswire/ --Envision Energy, a global leader in green technology, today announced its participation in the pilot phase of the AEA Ammonia Certification System, a global certification system designed by theAmmonia Energy Association(AEA) to facilitate the transparent, trusted international trade of low-emission ammonia. The AEA Ammonia Certification System is a voluntary system that allows producers, traders, and consumers to demonstrate key environmental attributes – namely carbon footprint and origin – using independently verified data. The AEA Ammonia Registry, built and operated by MiQ, provides participants with a digital infrastructure that enables secure data transfer, transparency, and traceability across the ammonia supply chain, from certificate generation, through trading, to retirement. The AEA Ammonia Certification System is a voluntary system that allows producers, traders, and consumers to demonstrate key environmental attributes – namely carbon footprint and origin – using independently verified data. The AEA Ammonia Registry, built and operated by MiQ, provides participants with a digital infrastructure that enables secure data transfer, transparency, and traceability across the ammonia supply chain, from certificate generation, through trading, to retirement. The pilot supports three distinct chain of custody models — Segregated, Mass Balance, and Book & Claim. Envision uses Book & Claim to address the logistical challenges of long-distance physical delivery and facilitate the growth of a global green ammonia market. Book & Claim enables trading of environmental attributes without physical transport, reducing cost and emissions and effectively decoupling the green attributes from the physical supply chain. Similar models already exist in renewable power and SAF (Sustainable Aviation Fuel) and this is the first application for ammonia. "We are excited to join the AEA Ammonia Certification System and use its Book & Claim feature to streamline the global distribution of verified low-emission molecules." said Frank Yu, Senior Vice President of Envision Energy. "This allows our customers to confidently decarbonize their operations regardless of their geographical proximity to our production hubs, accelerating the adoption of green ammonia as a bankable, net-zero commodity." Trevor Brown, Executive Director of the AEA, said "we are delighted to welcome Envision as one of the first participants of the AEA Ammonia Certification System pilot. We look forward to demonstrating with them the ability of our system's robust chain of custody models to meet diverse customer requirements in the dynamic new markets that we see emerging for low-emission ammonia across the Asia-Pacific region." In March 2026, Envision completed the first end-to-end commercial delivery of green ammonia from its Net Zero Industrial Park in Chifeng, China to the Port of Ulsan, South Korea, validating the entire value chain – from renewable power-to-X businesses to complex international maritime logistics. Envision officially commissioned the world's largest and most advanced AI-powered green hydrogen and ammonia production facility in July 2025, with 320,000 tons annual capacity, achieving real-time optimization and stability at an industrial scale. Frank Yu will present Envision's projects and its participation in the AEA Ammonia Certification System pilot at theWorld Hydrogen 2026 Summitin Rotterdam, Netherlands, on May 19, in a panel session moderated by the AEA's Trevor Brown. Photo -https://mma.prnewswire.com/media/2968738/image3.jpg
President Donald Trump launched Operation Epic Fury against Iran on Feb. 28, 2026, striking nuclear sites despite campaign promises to end endless wars. Iran closed the Strait of Hormuz to tanker traffic within the first week, cutting off oil and gas shipment…
📰 Transformernews.ai📅 2026-04-29📍 New York/NJenClima · decarbonizzazione
Unlock the potential of AI for progressive causes. Discover actionable strategies and key insights to leverage artificial intelligence for social change and political impact. Return for practical tools and a roadmap to empower the left in the AI era.
“Somehow all of the interesting energy for discussions about the long-range future of humanity is concentrated on the right,”wroteJoshua Achiam, head of mission alignment at OpenAI, on X last year. “The left has completely abdicated their role in this discussion. A decade from now this will be understood on the left to have been a generational mistake.” It’s a provocative claim: that while many sectors of the world, from politics to business to labor, have begun engaging with what artificial intelligence might soon mean for humanity, the left has not. And it seems to be right. As a movement, it appears the left has not been willing to engage seriously with AI — despite its potential to affect the lives and livelihoods of billions of people in ways that would normally make it just the kind of threat, and opportunity, left politics would concern itself with. Instead, the left has, for a mix of reasons good and bad, convinced itself that AI is at the same time something to hate, to mock, and to ignore. “The GenAI sector’s foremost feat of marketing has been the termintelligenceitself,”N+1, one of America’s foremost left publications, recently wrote. “A much more important question: What if China develops time travel or warp speed before we do?” asked Will Menaker, a host of the popular left podcast Chapo Trap House, when responding on X in December to a discussion of the possibilities of advanced AI. “Large language models do not, cannot, and will not ‘understand’ anything at all,”arguedTyler Austin Harper, the self-described “leftist, sort of Marxist-skewing” former professor, nowThe Atlanticstaff writer, last summer. Whether you hate AI or not — that’s up to you. There are many things to dislike about how it’s currently being developed, and valid reasons to dislike its very existence. But disliking something and ignoring it are different activities, and only one positions you to do anything about it. There are, of course, high-profile voices on the left who talk about AI; perhaps the most famous American leftist, Bernie Sanders, is nowwarningabout its dangers. But just as he has often been a lonely voice in Congress, on AI he stands apart from those within his own part of the political spectrum. Take another high-profile voice associated with the left, at least when it comes to tech, Cory Doctorow, one of the world’s most esteemed sci-fi and technology writers. In December, Doctorow published thetext of a speechgiven to the University of Washington called “The Reverse-Centaur’s Guide to Criticizing AI.” His purpose was to “explain what I think is going on here with this AI bubble, and sort out the bullshit from the material reality.” At its heart is the claim that “AI is just a word guessing program, because all it does is calculate the most probable word to go next.” In case you missed the point, Doctorow repeated it elsewhere in plainer words: AI is merely a “spicy autocomplete machine.” This idea, that large-language models merely produce statistically plausible word sequences based on training data, without having any idea about what the words refer to, has become the baseline across much of the left-intellectual landscape. Thanks to it, fundamental questions about AI’s capabilities, now and in the future, are considered settled. The publications that play a key (if diminished) role in the left-wing argumentative ecosystem have converged on this line. Here are four. The Nation: “AI only ‘knows’ anything in the same way that a calculator knows that 2 plus 3 is 5, which is why it cannot be counted on to learn and develop in the same way that a human would.” The New Republic: “Generative AI chatbots simply ‘predict’ the next word in a sequence using methods that require vast computational resources, data, and labor. . . they cannot ‘think’ or ‘understand’ language. . .” The New York Review of Books: “Chatbots regurgitate and rearrange fragments mined from all the text previously written. As plagiarists, they obscure and randomize their sources but do not transcend them.” N+1: “Large language models, which promise so much today, do not offer judgment, let alone intelligence, but unrivaled pattern-processing power, based on a vast corpus of precedents.” Social media reinforces this consensus, so that anyone who turns from theNYRBto Reddit or Bluesky, or the remaining left corners of X, will see the same thing. “Ppl don’t know how ChatGPT works,” one recent post said. “It doesn’t ‘know’ things. It autocompletes sentences. It makes things up.” The post has more than 70,000 likes. As with many left ideas these days, the autocomplete view of AI is a popular adaptation of the views held by critical academics. People who follow AI closely will know this, though they may not know how deeply embedded in left discourse in particular these views have become. “If you take the phrase ‘artificial intelligence,’ in a sentence like ‘does AI understand?’ or ‘can AI help us make better decisions?’, and you replace it with ‘mathy maths’ or ‘SALAMI’ [an acronym for Systematic Approaches to Learning Algorithms and Machine Inferences], it’s immediately obvious how ridiculous it is. You know, does the SALAMI understand?” Theaboveis from Emily Bender, a University of Washington computational linguist and the person probably most responsible for the autocomplete view and its adoption in left circles. Except she gives it another name, the “stochastic parrots” hypothesis, which explains the impression of intelligence that LLMs offer in the immediately graspable image of a bird that talks but doesn’t know anything. This was a stroke of mimetic genius: the 2021paperit was coined for, written by Bender with Timnit Gebru, Angelina McMillan-Major, and Margaret Mitchell, has been cited around 8,000 times. From there, it’s echoed throughThe NationandN+1and Bluesky, sometimes without attribution. In 2023, when chatbots were more toy than tool, AI-as-autocomplete was maybe a defensible position. But now? That view takes next-token prediction, the technical process at the heart of large-language models, and makes it sound like a simple thing — so simple it’s deflating. And taken in isolation, next-token prediction is a relatively simple process: do some math to predict and then output what word is likely to come next, given everything that’s come before it, based on the huge amounts of human writing the system has trained on. But when that operation is done millions, and billions, and trillions of times, as it is when these models are trained? Suddenly the simple next token isn’t so simple anymore. Instead, a web of associations grows so complex and so clearly productive it reminds one of Stalin’s apocryphal comment that quantity has a quality all its own. Yet the properties of scale do not often enter the left conversation. Nor do several other factors. Factors such as the likelihood that training a system to predict across millions of different cases forces it to build representations of the world that then, even if you want to reserve the word “understanding” for beings that walk around talking out of mouths, produce outputs that look a lot like understanding. Or that reserving words like “understanding” for humans depends on eliding the fact that nobody agrees on what it or “intelligence” or “meaning” actually mean. And that, if you’re arguing for human uniqueness, you need to show that the trillions of neuron-connections in the brain aren’t also doing next-token prediction, or something like it. As if that weren’t enough, it’s now debated whether “predicts the next token” remains an accurate and comprehensive description of what current systems are up to. Reinforcement learning has shifted the training objective from “what word would appear next on the internet” to “what response would a human prefer” — and today’s reasoning models are trained to work through problems step by step rather than answer in a single pass. Given all this, the fraction of meaning in the autocomplete view of current AI is alarmingly akin to the random, not always incorrect observations about temperature cycles conservatives used to throw around in debates about climate change. In both cases, a debatable description of mechanism is mistaken for proof of (in)significance. CO2 makes up only 0.04% of the atmosphere, which sounds much too little for it to drive global warming — until you learn CO2’s molecular structure lets it absorb infrared radiation in ways nitrogen and oxygen can’t. Similarly, “AI just predicts the next token” sounds deflating — until you consider what predicting the next token involves and start to ask if there’s really such a difference between predicting and learning. Indeed, it’s a little disturbing how closely this discourse follows climate-debate patterns set down 20 years ago by the right. Either a man-made phenomenon isn’t happening or, if it is, it’s not important. The common words in those articles, “just,” “simply,” “only,” are there because the argument doesn’t stand up without them. As it has for conservatives and climate change, dismissing a phenomenon that is already showing evidence of significant impact on the world puts a fair amount of epistemic stress on the people who do it. If AI is just “spicy autocomplete,” then what’s responsible for the current frenzy of attention? Autocorrect could explain away pre-ChatGPT interest levels without too much trouble. But it doesn’t come close to accounting for the trillions now invested, the data centers appearing around every corner, or the daily reports of AI automating task after task. Another piece of framing is therefore needed to shore the argument up. What’s responsible for the AI frenzy? False consciousness and trickery. “Artificial intelligence, if we’re being frank, is a con: a bill of goods you are being sold to line someone’s pockets,” write Bender and Alex Hanna in their bookThe AI Con, published in 2025 to grateful reviews in literary and intellectual quarters. In this view, the money and attention flowing into AI aren’t reflections of anything real, they’re simply the con in action. This belief is echoed in Doctorow’s essay. To him, tech CEOs are hucksters trying to Ponzi in more investment. “The primary goal is to keep the market convinced that your company will continue to grow, and to remain convinced until the next bubble comes along,” he writes. Of course, the 5-10x annual increases in AI lab revenues, that ChatGPT was the most rapidly adopted consumer technology in history, that consumer is another word for ordinary person and not tycoon — nowhere do these facts enter the picture. What’s left is a view of capitalism not as a system that can unfairly externalize harm, or as a negative system altogether, but as essentially a fake one. This impression is enhanced by the bizarre way the issue of AI taking human jobs comes up in these discussions. The left hates tech CEOs and knows they’re out to get the ordinary worker, but the left also thinks the CEOs are idiots and can’t actually pull it off. Thus, Doctorow claims, “Bosses are mass-firing productive workers and replacing them with janky AI, and when the janky AI is gone, no one will be able to find and re-hire most of those workers, we’re going to go from dysfunctional AI systems to nothing.” Or, in Bender and Hanna’s words, “AI is not going to replace your job. But it will make your job a lot shittier.” The picture is practically Cubist: management is trying to fill your role — with something that’s not real and can’t do it. Right at this mystifying point is where some understandable reasons for skepticism enter. It’s not as if the tech world hasn’t spent billions of dollars on iffy technologies before. Matt Bruenig, the left writer, founder of the People’s Policy Project, and someone who doesn’t share the autocorrect view of AI, explained those reasons sympathetically in an email. “The tech sector has a credibility problem as well because, in the decade or so prior to LLMs,” he wrote, “it seemed to be primarily fixated on blockchain and cryptocurrencies which do appear to be completely useless, at least as far as production goes.” It is hard to argue with that. Likewise, there are clear contradictions in how tech talks about AI. Seán Ó hÉigeartaigh, director of the AI: Futures and Responsibility Programme at the University of Cambridge and someone who has decades of experience trying to discuss advanced AI in left-leaning intellectual circles, described the skepticism that results from these contradictions. “CEOs say, ‘We think our technology might destroy the world,’ and then they go and build it,” he said. “To people coming to this topic fresh, those actions don’t match up with the belief. If they think what they’re doing is destroying the world, why are they doing it? Either they’re complete psychopaths or they don’t really believe that.” There are plenty of reasons to be suspicious of the motivations and claims of the people in charge of AI companies. The question that the left seems determined to avoid, however, is why that necessarily means you should dismiss the underlying technology, especially given the evidence so far. The gap between what AI systems can do now and what previously hyped technologies ever delivered is already vast. Crypto, for all its flaws,becauseof all its flaws, never got a fraction of the energy and attention from non-boosters AI now gets; to take another example, the metaverse remains a joke to everyone except for Mark Zuckerberg. But try to point this out in these circles and it might not go well. In May, Ethan Mollick, a Wharton professor and a measured voice on AI, announced he was limiting his posts on Bluesky because “talking about AI here is just really fraught.” In reply, a reasonably well-known left journalist said, “Maybe we can chase him off the goddamn earth too.” Ó hÉigeartaigh, for his part, said he regularly gets called a useful idiot running interference for Big Tech. No one person designed the system of buttressed beliefs that’s built up across left-intellectual discourse; no doubt it grew together because each has trouble carrying weight on its own. But it does come from somewhere. As the Bender and Mollick and Ó hÉigeartaigh examples suggest, the closer to academia one gets, it seems, the more surrounded by this thinking — which is a bit strange, since, as the many alarmed reports of students handing over their studies to ChatGPT indicate, the university is one of the places AI has already affected most. On the other hand, it’s a bit less strange if you consider it as an example of an intellectual war that’s escaping into the world from academia. Here Bender is again the way to understanding. Her view of AI is based on a firm belief about the nature of knowledge that comes from her work in linguistics. “The language modeling task, because it only uses form as training data, cannot in principle lead to learning of meaning,” she writes in one paper, meaning, basically, that because LLMs are disembodied, they cannot connect words to the things in the world they describe — which is a problem, since connecting words to things is the essence of meaning. The key term in that claim is “in principle.” It means that no amount of improvement in LLM ability could ever change the claim, and indeed, as LLMs have improved, Bender has shown little sign of altering her view. This description of how AI works is in other words more a philosophical definition than an empirical description. That’s why the main energy of her work lately is to reframe — to drag things from process and output back to philosophy. That’s why “understanding” becomes “parroting,” “neural networks” become “mathy maths,” “LLMs” become “synthetic text extruding machines.” She who best changes the terms wins the debate is the approach, and Bender has in many ways done just that. (Of course, that “Can mathy maths help us make better decisions?” is a perfectly cogent question, to which the answer is almost certainly yes, shows the limits of this approach.) Bender is entitled to her philosophy. She knows what she’s committing to and what risks she’s running. And, to be fair, she doesn’t think that AI is always useless. “There are applications of machine learning that are well scoped,” she’s written. “These include such everyday things as spell-checkers.” But, for the most part, the people who parrot the parrots hypothesis thirdhand don’t know this. They don’t know they’ve signed up in a long-running philosophical war. They think they are talking about capabilities, about scientific measurement. And that mismatch is leading them into worrying places. In part, they’re not aware of this because an opaque sorting has happened in academic AI research in recent years. “The people who are most optimistic about rapid progress,” said Ó hÉigeartaigh, have “disproportionately seen industry as a place to do their work, in part because you need a lot of compute and resources to do it.” The bullish ones have left academia, which means those who remain are by definition more bearish. Academic practices play into this process too. Publishing in journals requires peer review, and peer review is slow. As Zvi Mowshowitz, who writes perhaps the world’s most exhaustive newsletter on AI, said, “Nobody in real academia can adhere to their norms and actually be in the conversation, because by the time you’re publishing, everything you were trying to say is irrelevant,” a generation or two behind the cutting edge. Another incentive for researchers to leave for industry, then. This splitting of a field that once would have been forced to coexist has probably made industry too optimistic about the pace of progress and made academia too skeptical. That then skews what’s heard by people who listen to academia but not industry — and nearly everyone with that tendency, today, is on the left. They hear only the skeptics, unaware that real science is taking place in the AI labs too (or especially), done by PhD’d researchers they might trust if only they sat in a faculty office. How long can this situation hold? The example of climate change shows such attitudes can linger for quite a long time in a rump group dedicated to them. So perhaps it’s better to ask how long these attitudes will continue to spread outside that group. Here, things look brighter. Epistemic distress is not the whole story of the left-of-center world. Though sometimes you can hear parrots squawking in the background, the left-leaning, general-interest outlets that tend to have New York in the name —TheNew YorkerandNew YorkandThe New York Times, for instance — are much more willing to consider a wide range of views about what’s happening with AI. And AI is entering left electoral discussion in a meaningful way. The Biden administration took AI seriously in its last years. Bernie Sanders is suddenly frantic. “Despite the extraordinary importance of this issue and the speed at which it is progressing, AI is getting far too little discussion in Congress,” hewroteinThe Guardianrecently. “Right now, there is an amazing lack of political discourse for something that will be a very high priority later,” a Sanders adviser and founder of More Perfect UniontoldAxiosthis fall. A strategist for Zohran Mamdani said that “every candidate should be embracing an aggressive vision” on AI regulation. On the whole, then, and refreshingly, given the low view of politicians these days, the politicians left of center are in better shape on “take AI seriously, please” than the intellectuals. Alex Bores, a New York state assemblymember running for Congress on a platform heavy on AI regulation, ascribes that to daily contact with the public. When people come up to him now, he hears worry about AI’s capabilities, not dismissal of them. “We’re hearing it from our constituents. This is a concern that is brought up to me,” he said. “When you see things happening quickly, when you see your neighbors being impacted, our job is to take action. This has moved very, very quickly from the theoretical to the real.” Still, despite the relative alertness from political quarters, it’s hard to avoid the impression that the right is more alert, both to AI’s opportunity and its danger. That doesn’t mean they are masters of wise AI policy. Both the accelerationists and the industrialists influential in the current administration show it is alarmingly often the opposite. It simply means that, between them and the Steve Bannon anti-tech wing, more or less the entirety of the movement agrees AI is not a fake technology. One key sign: conservative intellectual magazines are in better shape than their left counterparts, generally blending a reasonably accurate grasp of the technology with concerns about social costs, along with — and this is something missing from nearly any portion of the left — some hope for what AI might mean for humanity. Take this, fromCommentary: “As we learn to live with AI, I believe we’ll become more comfortable with the notion that these models ‘think.’ After all, the LLMs are getting better all the time.” OrAmerican Affairs: “AI may serve as a powerful force multiplier for a well-honed native intelligence, or as a substitute for developing it in the first place.” And there’s really nothing on the left compared to the philosophical depth with whichThe New Atlantishas approached AI over the last few years. There are many costs of the left-intellectual world not taking AI seriously, and they will be paid by many quarters — with the left first in line. As Achiamput it, “when there’s a Big Problem that is going to be top of mind for everyone in a decade, whoever is first to the Big Problem gets to set all the rules for discussion and debate about it. In politics it’s a miss if you sit that out.” More concretely, not taking AI seriously might blind the left to its political uses. “One possible concern might be the left-wing abstaining from using the tools when the right-wing does not, in politics, campaigning, policy,” Bruenig worried. There is already some data to this effect: 44% of Republican political consultants use AI for work daily, compared to 28% of Democratic ones, according to the American Association of Political Consultants. Then there are the costs beyond the left — costs to the public and policy. The left’s current stance leads to a focus not on dealing with AI by regulating it wisely or preparing for it but on popping the economic bubble, which here is a baked-in fact of history and not a possibility of the future. After all, if AI is fake, nothing needs to be done except dispel the myth that it is real. And sometimes even that isn’t required: the bubble will pop itself; AI development is always already stopping. “The AI bubble . . . will burst,”N+1writes. “The technology’s dizzying pace of improvement, already slowing with the release of GPT-5, will stall.” This stirring call to non-action was published in fall 2025 — in other words, weeks before the release of the three models, Gemini 3, GPT 5.1, and Opus 4.5, that pulled AI capable of changing daily life from the future into the present. (Since it must be said: it is entirely possible a bubble-popping crash happens — but even that likely won’t stop AI development.) So it’s probably not ideal that just before what might — or might not — be the moment of greatest job dispossession in history, or of democratic dispossession, or worse, or better, part of the group historically most concerned with such things is plugging its ears. What should it be doing instead? There’s a huge amount of open room for left contributions to shaping the near and far futures. These are more the subject for another essay, but it’s worth gesturing to a few, in order from most concrete to most exotic. On the near future, Dean W. Ball, until recently one of the White House’s key AI policy writers, is adamant that by not taking AI abilities seriously, the left is going to miss important ways of improving government. “The left persuasion requires a state that’s good at doing things,” he said. “If I were the left, the first thing I would be doing” would be to ask, “How can we use this to massively advance state capacity and massively expand the ability of the government to deliver public services to people?” Bores thinks AI offers an opportunity to speed the US to cleaner energy. “We desperately need to upgrade our electric grid,” he said. “Now we have a system where you have basically unlimited private capital willing to invest in our electric grid, but the incentives right now are to turn on or buy power privately from old coal or oil places, because it’s just quicker to get approval for that than it is to hook up a renewable source.” As for the far or more exotic futures: what’s the best shape to universal basic income if it’s needed? What if it’s wanted? Can treaties be designed to slow a race to superintelligence and reduce the risk of a catastrophe? What is the ethical view of post-humanism? Hardly any on the left is considering these questions in ways worth agreeing or disagreeing with. Aaron Bastani, the hard left British journalist, is one exception. His 2019 bookFully Automated Luxury Communismenvisions the ways technological development could eventually abolish material scarcity and free humanity from toil. “The demand would be a 10- or 12-hour working week, a guaranteed social wage, universally guaranteed housing, education, healthcare and so on,” hesaidin 2015. Far from revealing a thrall to capitalism, these attitudes reflect a belief in industrial power that goes all the way back to Karl Marx. But who’s listening? Instead, you sometimes get the discomfiting sense you’re watching ghosts — people who were so unprepared for the future, because they were so certain they knew it, that they were already out of it. Tempering that feeling is one thing the AI observers spoken to here emphasized: it isn’t yet too late to change direction. How much time, who knows. Ball, who doesn’t believe AI poses a strong risk to human civilization, thinks “there’ll always be time” to catch up. Mowshowitz, who does believe that, said, “I don’t think it’s too late. The world yearns for more and better thoughts.” Ó hÉigeartaigh was more urgent. “There’s potentially a narrowing window to really engage on this,” he said. “It would be really nice to get perspectives across the political spectrum just in case this giant transformation in human society does come along.” Share
Back in December, Godox unveiled the LiteWafer UP150R Full-Color LED Panel. Essentially, it is roughly a little larger than a 2×1-sized panel. The fixture has full HSI/RGBW control, a wide 1800K–10,000K CCT range, and 14 effects. Godox’s LiteWafer-UP150R feat…
Back in December, Godox unveiled theLiteWafer UP150R Full-Color LED Panel. Essentially, it is roughly a little larger than a 2×1-sized panel. The fixture has full HSI/RGBW control, a wide 1800K–10,000K CCT range, and 14 effects. Godox’s LiteWafer-UP150R features a slim profile that allows it to fit into tight spaces. It was designed to stay thin even when fully assembled, and it is claimed to be easy to pack, transport, and rig. The Godox LiteWafer UP150R has physical dimensions of 67.99 x 35.4 x 2.4cm / 26.77 x 13.94 x 0.95″. As a comparison, the Nanlite PavoSlim 120C has dimensions of 60.2 x 30.63 x 1.86 cm / 23.7 x 12.06 x 0.73″. The light is pretty thin, which allows it to be squeezed into tight spaces. The light utilizes a separate power supply/controller that features an integrated V-mount plate, allowing direct battery use without external adapters. In a nice touch, the control box also comes with a shoulder strap, which you can also use to attach it to a light stand. The Godox LiteWafer UP150R weighs 3.2kg / 7.05 lb, and the Power Supply/Controller is 0.85 kg / 1.87 lb. As a comparison, the Nanlite PavoSlim 120C weighs in at 1.76kg / 3.88lb, and the power supply/controller is 1.84kg / 4.06lb. Lights such as the Godox LiteWafer UP150R and Nanlite PavoSlim 120C are going to be heavier than flexible panel lights of a similar size. The Godox LiteWafer UP150R, as I previously mentioned, is not a flexible LED panel that you can fold up to make smaller. It is like a Nanlite PavoSlim 150C or LiteMat that has a hard backing plate. For anyone who travels a lot, the LiteWafer UP150R may arguably not be the best option given its physical footprint, although, in saying that, the case it comes in is still relatively compact. The Godox LiteWafer UP150R draws 180W. The fixture can be run at 100% output using a single 14.4V or 26V battery. For anyone who travels a lot and wants to run the light remotely, this is handy. You can also run the light at a 80% battery output mode. More on that later in the review. So, how does this power draw of the Godox LiteWafer UP150R compare to some of the competition? Well, above you can see. The Godox LiteWafer UP150R utilizes an RGBWW light engine. We have seen everything from RGBW/RGBWW to 6-color systems (RGBLAC), to Aputure’s BLAIR CC, NANLUX’s new C8 Full Color Light Engine, which is claimed to be the industry’s first eight-color light engine, and the Profoto CORE-6 RGBWWW LED Engine RGBWW lights tend to struggle to create saturated colors like yellow, and they don’t always have as much output when generating saturated colors. They can also have a large drop-off in output at different CCT settings. I am not a fanboy of any one particular brand, who is going to give you a biased assessment of a light. I have seen, used, and reviewed hundreds of lights over the years, so I think I have a pretty solid background in giving you a professional opinion that isn’t influenced by marketing hype. The lighting kits consist of: The case, the light comes in, is pretty well made and in line with other Godox products. But I’m in no position to comment on how it would handle the rigors of air travel. That is something you would only find out over time. As the case is included, you can’t really complain. You could use it if you want, or if you prefer another option, you can decide what works best for you. If you are going to use the case for the Godox LiteWafer UP150R, then I would put other items inside there to maximize the space. It is actually long enough that you could easily sneak in a light stand and a battery to have a fully self-contained lighting set-up. The overall build quality of the Godox LiteWafer UP150R is decent enough. The backing plates are made out of some sort of lightweight metal material.. The light doesn’t have an acrylic screen on the front that protects the LEDs, like the competing Nanlite PavoSlim 120C. The power supply/control unit is nice and small and lightweight. It is decently made considering its small size and weight. The power supply/controller features a nice color display on the front of the controller/power supply. This is very easy to see, and it shows you clearly and concisely what your operating parameters are. The buttons and dials are tactile and easy to use. They are also solidly made. The mounting plate system is similar to what you would find on a Nanlite PavoSlim 120C. The adjustable mount works well, and it allows for a good range of adjustment. As I previously mentioned, the LiteWafer UP150R comes with a separate power supply/controller. The LiteWafer UP150R’s power supply/controller features a single V-mount battery plate. This allows you to run a V-mount battery if you want to remotely power the light. The plate allows you to run either a 14.4V battery or a 26V battery. In the Menu inBattery Settings, you can change the power setting fromFull Powerto80% Power. You can also power the light via a 100-240V AC input. The power supply/controller for the light is intuitive and straightforward to use. You can clearly see all of the parameters on the display screen. There is nothing overly complicated about the operation. Godox includes an extension head cable in the kit, which is handy if you need to hand the light out off a boom arm. LED mats are great because they are compact and lightweight, but they still require power like any other light. They can’t magically produce a lot of output without a fairly large power supply. I like that Godox has managed to keep the weight of the power supply/controller to a minimum. The LiteWafer UP150R has the following inputs & outputs: As a comparison, the PavoSlim 120C Power Supply/Controller has the following inputs & outputs: The power supply/controller does have an in-built fan; however, there are no fan controls or options. The fan noise is basically non-existent, and the light is extremely quiet, which is fantastic. Above, you can see an operation tutorial video that Godox has for the LiteWafer UP150R. The power supply/controller has a MODE button, a MENU button, and a Select Dial (rotate/press). TheMODEbutton toggles between the following operating modes: In the CCT mode, you can make adjustments to the CCT from 1800K to 10,000K. You can also change the intensity and the +/- G/M from -100% ～ +100%. It is nice that the light features the ability to adjust the +/- G/M bias. This can really help you match other lighting sources. In theHSI mode,you can individually adjust the Hue, Saturation, and Intensity. In theRGBW Mode, you can individually adjust Red, Green, Blue, and white. In theGEL Mode, you can choose from a vast array of digital gels. You can also set the base CCT to either 3200K or 5600K. In theFX Mode, you can choose from a decent collection of special effects. If you press theMENUbutton, you can choose to view or alter various settings, including the Control Mode, DMX, Bluetooth, Dimming Curve, Language, etc. Overall, the UI is fairly intuitive and easy to use. This is also partly due to the fact that there are not a ton of menus or options to choose from. You don’t need a manual to be able to work out how to use this light. This is always a good thing, especially if you are handing the light off to someone who hasn’t used it before. You can also control the light using DMX. After inserting a separately purchased DMX adapter cable DMX-TRS1 (five-core) into the wired DMX port, the fixture is equipped with DMX output and input ports. A wired DMX connection can be used by connecting the DMX cable to the controller. Please note that the DMX adapter cable DMX-TRS1, DMX controller, and DMX cable are sold separately The light can be controlled via Bluetooth using the Godox Light App. You need to have Bluetooth turned on when using your smartphone or tablet. If you are using the light for the first time, you need to create a new Scene. It will then find any fixtures that are turned on with their Bluetooth activated. Once you select the fixture and hit confirm, it will set it up for use with the app. Once you tap on the fixture, you will be taken to the home screen of the app, where the light will be in the default CCT operating mode. Here you can change the CCT and intensity, as well as the +/- G/M bias. There is a range of parameters that you can adjust using the app. Godox doesn’t list anywhere what the beam angle of the LiteWafer UP150R is. The biggest downside of using a lot of flexible or foldable LED lights is that they are a pain to set up. You normally have to construct up frames and mounts and then hook them up to controller units and power supplies. The UP150R is a little different because it features a hard backing plate. This allows you to set it up very quickly, which is always handy. The Godox LiteWafer UP150R features a Quick-Release Mounting System, and it comes with a dedicated holder and quick-release softbox. Users can choose the included 5/8-inch baby pin or the optional UP150RUH01 Universal Swivel Holder, which offers a unibody design Unlike the competing Nanlite PavoSlim 150C, it doesn’t have multiple different positions where you can mount the plate. If you are working by yourself or in a small crew, you need to be able to set up lighting quickly. The quick-release softbox can literally be set up in a couple of minutes by a single person. The Godox LiteWafer UP150R comes with a softbox that can be left on the fixture when you need to transport or pack it away. This is a very similar concept to what Nanlite does with the PavoSlim. It simply pops out when you realease the velcro tabs. Speaking of the softbox, you also get two different strengths of diffusion in the kit, and a honeycomb grid. I actually found that you combine both pieces of diffusion and use them together if you want to create a softer source. Now, the Godox LiteWafer UP150R doesn’t feature any type of inbuilt diffusion in front of the LEDs, so if you want to create a softer source you will need to use the included softbox. One of the downsides, as I mentioned earlier, with these types of LED lights, is that you have to carry around a separate controller/power supply, the light, and a bunch of cables and accessories. A big factor for a lot of people when buying a light is how much output it can produce. I tested the lights’ output at a variety of CCT settings, both running on mains and battery power, using aSekonic C-800at a distance of 1m (3.28ft) in a controlled environment; you can see the results below. With any diffusion or attachment, I measure from the end of it and not from the light source. I do this with all my measurements for lights. The Godox LiteWafer UP150R is claimed to output 20,400 lux @1m / 3.3′ of soft, even light. It does this by using efficient LED chips paired with optical lenses to boost brightness. This is claimed to produce an output that is up to four times greater than standard panel designs. Above, you can see what Godox quotes as the output for the fixture when used at various CCT settings at a variety of distances. Above, you can see the Godox LiteWafer UP150R recorded an output of22,000 lx (2050 fc)when set at 5600K and run off mains power. 22,000 lx from an LED light of this size and with a power draw of just 180W is extremely impressive. The reading of 22,000 lx that I obtained was higher than the claimed output of 20,400 lx. *Manufacturers’ claims (not independently tested) As a comparison, above you can see how that output compares to some of the competition. The Godox LiteWafer UP150R had substantially more output than other similar lights, but it does have a slightly higher power draw. The Godox LiteWafer UP150R produced a CCT reading of5594K, which was almost perfect. As a comparison, the Nanlite PavoSlim 150C produced a CCT reading of 5754K. As another comparison, the Intellytech LC-160 LITECLOTH 2.0 produced a CCT reading of 5666K Above, you can see the Godox LiteWafer UP150R recorded an output of19,500lx (1810 fc)when set at 3200K and run off mains power. Again, 19.500 lx from an LED light of this size and with a power draw of just 180W is outstanding. *Manufacturers’ claims (not independently tested) As a comparison, above you can see how that output compares to some of the competition. The Godox LiteWafer UP150R produced a CCT reading of3164K, which was a very good result. As a comparison, the Nanlite PavoSlim 120C produced a CCT reading of3166K. The light’s output wasn’t overly consistent across its CCT range, and it varied by 18.86%. From 4500K to 10,000K it only varied by 10.96%. The results also show me that the light is extremely accurate when it comes to CCT reproduction from 2500-6500K. Only at 8000K and 10,000K was it a little off. So, now, let’s have a look at how much output you get when using the included softbox. The softbox comes with a 01 and a 02 diffusion. Above, you can see that when the light was using its included softbox and the 01 diffusion, it recorded an output of5760 lx (535 fc). This was 74.74% less output than when using the light without diffusion. Now, the softbox did alter the CCT by more than 250K, and I got a reading of 5319K. Above, you can see that when the light was using its included softbox and 02 diffusion, it recorded an output of4460 lx (433 fc). This was 80.44% less output than when using the light without diffusion. Again, the softbox with stronger diffusion did alter the CCT by more than 400K, and I got a reading of 5175K. Above, you can see that when the light was using its included softbox and combining the 01 and 02 diffusion, it recorded an output of3570 lx (332 fc). This was 84.34% less output than when using the light without diffusion. Again, the softbox with diffusion 01 and 02 combined did alter the CCT by more than 400K, and I got a reading of 5173K. Above you can see the light’s output when it was set at 3200K, and using the softbox and 01 diffusion was5120 lx (476 fc). As far as CCT accuracy goes, it recorded a reading of3065K, which was around 200K different from the reading when used without diffusion. Above, you can see that when the light was set at 3200K using its included softbox and 02 diffusion, it recorded an output of4160 lx (386 fc). Again, the softbox with stronger diffusion did alter the CCT by more than 240K, and I got a reading of 3029K. As the Godox LiteWafer UP150R can be run remotely via a battery, let’s have a look at how much output it can produce. Ok, so now let’s see what happens to the output if I try running the Godox LiteWafer UP150R via a 212Wh V-mount battery. Above, you can see that when the light was running off a 212Wh V-mount battery, it recorded an output of20,900 lx (1940 fc). This was 8.33% less output than when it is run via mains power. Ok, so now let’s see what happens to the output if I try running the Godox LiteWafer UP150R via a 150Wh V-mount battery. Above, you can see that when the light was running off a 150Wh V-mount battery, it recorded an output of20,800 lx (1940 fc). This was 100 lx lower than when using a 212Wh battery. Ok, so now let’s see what happens to the output if I try running the Godox LiteWafer UP150R via a 99Wh V-mount battery. Above, you can see that when the light was running off a 99Wh V-mount battery, it recorded an output of20,800 lx (1940 fc). This was 100 lx lower than when using a 212Wh battery. Ok, so now let’s see what happens to the output if I try running the Godox LiteWafer UP150R via a 212Wh V-mount battery with the Battery Power in the menu set to 80%. Above, you can see that when the light was running off a 212Wh V-mount battery, it recorded an output of15,800 lx (1460 fc). This was 24.4% lower than when using a 212Wh battery in the normal battery output mode. Now, what you should always do when testing lights is to see if the CCT remains consistent when dimming the light. Just because you set a light at say 5600K, that doesn’t mean that the CCT will remain stable as you start dimming the fixture down. I also wanted to see how linear the dimming curve was. I decided to do a series of tests at 100%/75%/50%/25%10% to see if the CCT being recorded changed. This was done at a distance of 1m / 3.3′ using a Sekonic C-800. These tests were done at 5600K with the light being used open face. Godox LiteWafer UP150R The Godox LiteWafer UP150R maintained very good CCT consistency as you start dimming the fixture. My testing showed that the CCT readings varied by 1just 52K from 100% to 10%. As far as how linear the output is when you start dimming the light, at 50% output, it had 51.82% less output than when used at 100%. At 25%, it had 75.45% less output than when used at 100%. At 10% output, it had 89.41% less output than when used at 100%. This shows me that the light’s dimming curve is very linear. So now that we have seen how much output the Godox LiteWafer UP150Rproduces, how does it perform when it comes to replicating accurate colors? Above, you can see that when the LiteWafer UP150R was set at 5600K and used open face, it recorded anaverage CRI (R1-R8) of 97.0and an extendedCRI (R1-R15) of 95.56. For replicating accurate skin tones, it recorded98.7 for R9 (red),99.4 for R13(closest to caucasian skin tones), and97.9 for R15(closest to Asian skin tones). These were excellent results, and only R12 (Blue) was below 90. The light, when set at 5600K, also recorded aTLCI score of 98. As a comparison, I compared the color rendering of the Godox LiteWafer UP150R against the Nanlite PavoSlim 120C, Godox KNOWLED F200Bi, Aladdin Bi-Flex2 Bi-Color LED Panel 1×2, and the Intellytech LC-160 LITECLOTH 2.0. The Aladdin and Intellytech both have excellent color rendering scores, and I personally consider them to be a benchmark for these types of thin LED panels. Above you can see a head-to-head comparison against the Nanlite PavoSlim 120C, Godox KNOWLED F200Bi, Aladdin Bi-Flex2 Bi-Color LED Panel 1×2, and the Intellytech LC-160 LITECLOTH 2.0 when used at 5600K. Above, you can see the scores for when the light was used at 3200K open face. It recorded anaverage CRI (R1-R8) of 97.6and an extendedCRI (R1-R15) of 96.28. For replicating accurate skin tones, it recorded95.5 for R9 (red),98.6 for R13(closest to caucasian skin tones), and99.4 for R15(closest to Asian skin tones). Just like at 5600K, these were excellent results, and only R12 (Blue) was marginally below 90. The light, when set at 3200K, recorded aTLCI score of 97. Above you can see a head-to-head comparison against the Nanlite PavoSlim 120C, Godox KNOWLED F200Bi, Aladdin Bi-Flex2 Bi-Color LED Panel 1×2, and the Intellytech LC-160 LITECLOTH 2.0 when used at 3200K. Above, you can see that when the light was set at 5600K and used with its softbox and 01 Diffusion, it recorded anaverage CRI (R1-R8) of 97.4and an extendedCRI (R1-R15) of 95.99. For replicating accurate skin tones, it recorded98.5 for R9 (red),99.1 for R13(closest to caucasian skin tones), and97.6 for R15(closest to Asian skin tones). Only R12 (Blue) was below 90. Above, you can see how those scores compare to when you are using the light without diffusion. These tests tell me that the color rendering performance is basically identical whether you use the light with the softbox or without. I also wanted to test the Godox LiteWafer UP150R to see how it performed when creating super-saturated colors. Above, you can see that the light recorded an output of9300 lx (864 fc). As far as creating an accurate 0° RED, the Godox LiteWafer UP150R was 1° off. Above, you can see that the light recorded an output of11,500 lx (1070 fc). As far as creating an accurate 120° GREEN, the Godox LiteWafer UP150R was spot on with a 120° reading and 100% saturation. Above, you can see that the light recorded an output of2420 lx (225 fc). As far as creating an accurate 240° BLUE, the Godox LiteWafer UP150R had a perfect reading of 240°, with 100% saturation. Above, you can see that the light recorded an output of6240 lx (580fc). As far as creating an accurate 60° Yellow, the Godox LiteWafer UP150R was way off with a reading of 34°. Because the light is RGBWW, it is going to struggle to recreate some fully saturated colors, such as yellow, accurately. The CC Index displays the CC correction value and whether any magenta or green need to be added or subtracted. 1 CC corresponds to 035 Kodak CC values or 1/8 Rosco filter values. Any reading less than +1.00 or -1.00 and you’re probably not going to need to make any kind of adjustment. The ⊿uv is the value to show how much this light is away from being an ideal light source (black body radiation = incandescent lamp). As with the CC Index you want this number to theoretically be zero. Kelvin is not a linear value, so we need to convert from Kelvin to MK-1 to compare the values of color temperature. To calculate from Kelvin to Mired is MK-1= 1*1000000/Kelvin. While this may sound confusing, it is the only way of measuring if the Kelvin shift is significant enough to warrant having to use a filter for correction. Below are the results for the Godox LiteWafer UP150R : These figures might look confusing, but what they tell me is that the light is very, very CCT-accurate at all of its settings. Any MK-1 score that is under -9/9 means you wouldn’t have to use any color correction gels. The MK-1 scores for this light were excellent. Any MK-1 score that is under -6/6 is a very good result. At 2500K, 5600K, and 6500K, the scores were exceptionally good. The light had outstanding MK-1 consistency. Ok, now let’s look at the CC INDEX & ⊿uv. These were outstanding results across the board. There was nothing here that anyone should be concerned about, and the ⊿uv scores at all CCT values were right up there with the best lights I have ever tested. At 3200K and 5600K, it had a perfect ⊿uv score, and at 4500K, it was just a smidge from being perfect. TM-30 is a relatively new color rendering standard that was developed to deal with the limitations of CRI. TM-30 looks at 99 individual colors. These 99 colors are categorized into seven groups: nature, skin color, textiles, paints, plastics, printed material, and color systems. TM-30 scores go from 0 – 100. The higher the score, the more accurate a light is at producing colors. Any TM-30 Rf score in the ’90s is considered to be good. What is interesting and something that you need to be very aware of is that two separate light sources with the exact same CRI scores can render colors very differently. A light with a high CRI rating could have a low TM-30 score. Conversely, a light with a good TM-30 score could have a bad CRI score. Now, there are two measurements associated with TM-30, Rf and Rg. Rf (Color Fidelity)Rg (Color Gamut) With Rf value, ideally, you want a score in the 90’s. With Rg value, a score below 100 indicates that the light source renders colors with less saturation than the reference source. Any score above 100 means it is over-saturating colors. So ideally, you want this score to be 100. Above, you can see the scores for the Godox LiteWafer UP150R at various CCT settings. Below, I have listed the figures as well. Here are the results: The TM-30 scores were reasonably consistent across its CCT range, and it shows me that the light is very consistent at replicating accurate colors with full saturation. However, you can see that it did have a tendency to slightly over-saturate magenta/red colors at 2500K-5600K. SSI (Spectral Similarity Index) was developed by the Sci-Tech Council of the Academy. SSI gives me the ability to set any light as a standard, or use predefined standards (such as CIE D55), and then give other lights an SSI score based upon how well they will match standards such as CIE D55 measure spectral response and compares it directly against an ideal light source. SSI is a much better way to judge an LED light than CRI or TLCI, although they don’t tell the full story of any light, and you can’t judge a light by SSI scores alone. SSI is useful to see how well different lights will play together. As the Sekonic C-800 Spectromaster can measure SSI, I decided to test out the Godox LiteWafer UP150R to see how it performed. Above are the scores for the light when used at 3200K. The scores show that the light does a very good job of accurately replicating a 3200K (Tungsten) source. Any score in the mid to high 80’s is outstanding for an LED light. As a comparison, above you can see the scores for the Nanlite PavoSlim 120C. Above are the scores for the light when used at 5600K. The scores show that the light does a reasonably good job of accurately replicating a CIE D55 source. A score in the low to mid-70s is very typical for a 5600K LED light. As a comparison, above are the scores for the Nanlite PavoSlim 120C. The main reason we want to record SSI scores is so we can see how well they match with other lights. For example, let’s see how well the Godox LiteWafer UP150R matches the NANLUX Evoke 600C and Godox’s own KNOWLED 600R Hard P4 at both 3200K and 5600K. Below you can see the results. As you can see, the Godox LiteWafer UP150R is a very close match with the Godox KNOWLED 600R Hard P4, but not with the NANLUX Evoke 600C. As you can see, the Godox LiteWafer UP150R is a very close match with the Godox KNOWLED 600R Hard P4, and a pretty good match with the NANLUX Evoke 600C when used at 3200K. As another comparison, let’s see how it matches itself at 5600K when it is used with the softbox with 01 diffusion and with the 02 diffusion. As you can see, the Godox LiteWafer UP150R matches well when used with the softbox with 01 diffusion and with the 02 diffusion. Being able to measure SSI in advance and compare different lights you may be using together is a great way of finding out what lights will work together and what adjustments need to be made. Above, you can see the spectral distribution of the Godox LiteWafer UP150R when it is set at 3200K. The spectral distribution is nice and full, and the light only has the slightest bump in green. As a comparison, above you can see the spectral distribution of the Nanlite PavoSlim 120C when it is set at 3200K. The spectral distribution is nice and full and the light only has the slightest bump in green. As another comparison, above you can see what the spectral response of an ARRI Orbiter looks like when used at 3200K. Above, you can see the spectral distribution of the Godox LiteWafer UP150R when it is set at 5600K. The spectral distribution is not overly full. As a comparison, above you can see the spectral distribution of the Nanlite PavoSlim 120C when it is set at 5600K. The spectral distribution is reasonably good, but there is a slight push toward green. As another comparison, let’s compare that against one of the best LED lights I have ever tested at 5600K, the Maxima 3. As I always say, photometric scores only tell you part of the story. So do the scores from the Godox LiteWafer UP150R translate into real-world performance? Well, let’s find out. First, let’s have a look at color accuracy. For the above examples, I set the light at 5600K and 3200K presets and then set the camera’s WB to 5600K and 3200K, respectively. I then did a manual WB on the camera to see how much the image changed. As you can see, there was quite a big difference between the preset WB and the manual WB. As far as how the lights look, you can produce a nice soft source with the built-in softbox; however, this does come at the sacrifice of output. If you want to see how much output the light has when used without any diffusion and punched through a sheer curtain, above are some comparison frames. I have kept the camera settings the same for all of the shots. Above, you can see how much output the light has when used with one layer of diffusion. Above, you can see how much output the light has when used with two layers of diffusion and the honeycomb grid. Above, you can see a couple of quick frames when using the Godox with its included softbox and two layers of diffusion, with the honeycomb grid. For these examples, the light was set at around 18.3% output. The light will create some cross-hatched shadows if you use it without diffusion. Above, you can see what the light looks like when it is positioned out over a table using one layer of diffusion and a honeycomb grid. By using it with or without the honeycomb grid, you can choose how much spill you want. Also, because the fixture doesn’t weigh that much, you can put it a long way out on an arm, which is also very handy. The Godox LiteWafer UP150R is now available to purchase for$699 USD. Godox will also have a 2-light kit available for$1,199 USD. The nice aspect of thetwo-light kitis that two units can be connected horizontally or vertically to form a larger source. With the UP-C300 dual-light controller, both fixtures can be adjusted together. Other alternatives to the Nanlite PavoSlim 120C include the Nanlite PavoSlim 120C, amaran F21c 2 x 1′ RGB LED Flexible Light Mat, and the LiteMat Spectrum 1 Kit. *Currently on sale at B&H as of the 15/03/2026 Above, you can see how the price compares to some of the competition. The Godox LiteWafer UP150R provides a ton of output for a fixture of its size and power draw. It is decently made, and it is very CCT accurate with very good color rendering scores. It can be used as a hard source or a soft source with the included soft box and diffusion. The high output really helps when you want to create a more diffused lighting source, but you still require a decent amount of punch. Being able to run the light via a single flight-safe battery adds to its appeal. As the light is on hard backing plates, it is very quick to set up and use. The mounting system is substantially better than what you will find on most flexible LED panels. The Godox app works well, and it is relatively easy to use and navigate, as are the physical controls on the power supply/controller. Godox has done a very good job with the LiteWafer UP150R, and finally, there is some decent competition for the very good Nanlite PavoSlim 120C. Its standout feature is its high output and ability to run remotely via a V-mount battery. Matthew Allard is a multi-award-winning, ACS accredited freelance Director of Photography with over 35 years' of experience working in more than 50 countries around the world.He is the Editor of Newsshooter.com and has been writing on the site since 2010.Matthew has won 51 ACS Awards, including six prestigious Golden Tripods. In 2016 he won the Award for Best Cinematography at the 21st Asian Television Awards.Matthew is available to hire as a DP in Japan or for work anywhere else in the world.
📰 il Nord Est📅 2026-04-29📍 VeneziaitClima · decarbonizzazione
Primo maggio “nazionale” a Marghera: per un’altra “rivoluzione industriale” il Nord Est
La scommessa industriale e il primato petrolchimico, le lotte operaie e l’ambiente avvelenato, lo sradicamento delle fabbriche, la ripartenza ad ostacoli.
Cent’anni dopo il decollo del primo polo metallurgico e navale, i leader sindacali nazionali di Cgil, Cisl e Uil convergeranno a Porto Marghera per un Primo Maggio di memoria e speranza. Un secolo di storia economica e sociale ad un battito del cuore da Venezia, un progetto radicale senza precedenti nel Paese. Concepito da Piero Foscari, deputato della destra liberale, realizzato dall’élite finanziaria veneziana - Giovanni Volpi di Misurata, Giovanni Stucky, Nicolò Papadopoli Aldobrandini - con l’avallo della Banca Commerciale Italiana e il robusto sostegno dello Stato.
Corre il 23 luglio 1917, l’annus horribilis di Caporetto, quando il governo Boselli autorizza la Società Porto Industriale all’avvio dei lavori nell’area paludosa dei Bottenighi, espropriando nel contempo un quarto del territorio di Mestre: è il prologo alla bonifica dei terreni lagunari (oltre quindici milioni di metri quadrati strappati al “salso”), all’escavo di canali artificiali, alla costruzione di reti stradali e raccordi ferroviari.
Un disegno ambizioso e controverso quello di Volpi, influente tecnocrate nel Ventennio fascista, deciso a «sospingere Venezia nei tempi moderni» superandone l’esclusiva vocazione turistica. Che diventa realtà negli anni Venti, con la nascita del primo cantiere (Breda), l’inaugurazione del Canale Vittorio Emanuele tra la stazione marittima e Marghera (1922), l’apertura al traffico di merci e materie prime (1926), l’insediamento di una cinquantina di stabilimenti preceduto dall’accorpamento al capoluogo dei quattro comuni investiti dagli impianti. Che attinge alla manodopera rurale e procede per gradi.
Dapprima le lavorazioni di base, la distillazione del carbon fossile e la produzione di vetro, i fertilizzanti e gli anticrittogamici, le raffinerie, i depositi di oli minerali. In seguito, a partire dagli anni Trenta, lo sviluppo della meccanica, i metalli non ferrosi, l’ammoniaca sintetica per concimi e il ventaglio di produzioni minori che si valgono della centrale termica più potente nel circuito nazionale.
Duramente bombardati nel secondo conflitto mondiale, gli stabilimenti sono rapidamente ricostruiti e sorge anzi una seconda zona industriale, attraversata dal canale culminante nella Bocca di Malamocco.
Un boom frenetico e per molti versi selvaggio (il rialzo del piano campagna includerà l’interramento di rifiuti tossici) che moltiplica la popolazione a Mestre (90 mila abitanti), Marghera (25 mila) e nei borghi limitrofi di Favaro, Zelarino, Chirignago. Un’espansione di ciminiere e fonderie che garantisce profitti colossali ai monopolisti e negli anni Sessanta si traduce in duecento aziende attive con 40 mila lavoratori (dal proletariato urbano ai “metalmezzadri” provenienti dalla provincia) per un transito annuo superiore ai 7 milioni di tonnellate, invidiato dai maggiori terminal europei. È l’età del conflitto nell’oasi rossa del Veneto bianco: scioperi massicci, lotte unitarie per un salario equo (le «cinquemila lire uguali per tutti»), difesa della salute, denuncia dell’inquinamento.
Toni Negri, Massimo Cacciari, Gianni De Michelis: Potere operaio che mobilita gli studenti ai cancelli e sfida il riformismo della sinistra storica. Il miraggio della “terza zona siderurgica”, persino, progettata su tremila ettari, rimasta sostanzialmente sulla carta, che si aggrappa al record di traffico marittimo (1974) ma già sconta l’inversione di tendenza dei primi anni Ottanta.
Un decennio insanguinato dagli omicidi di Sergio Gori e Giuseppe Taliercio, dirigenti del Petrolchimico, vittime delle Brigate Rosse; sgretolato negli assetti societari produttivi. È il declino di un modello gigantista, simboleggiato dal processo ai “Signori della chimica”, imputati per la morte di 157 lavoratori di Montedison ed Enichem, esposti agli effetti cancerogeni del cloruro di vinile monomero.
Fino alla storia recente, alla profonda, faticosa, transizione in atto: la Zona logistica semplificata (2020) istituita per favorire il rilancio con incentivi fiscali e amministrativi, lo spegnimento della torcia nella raffineria nel 2023, l’incompiuta bonifica del suolo contaminato. Così i grandi gruppi cedono il passo, il terziario avanza e l’occupazione arretra a 12 mila addetti con 120 aziende spalmate su 2mila ettari. Così le rappresentanze dei lavoratori respingono la «monocoltura turistica» in nome di una «manifattura sostenibile».
Inquinamento porti e servizio Report: “Riflettere sulla sostanza del problema, senza dare troppo importanza ai fuori onda che non la meritano”. L’intervento di Livorno Porto Pulito Livornopress
MoreSense MS-07 indoor air quality monitor is built around the Sensirion SEN66 multisensor, powered by an ESP32-S3 microcontroller, and features a 3.5-inch capacitive IPS touchscreen for local data visualization and control. The MS-07 is a direct upgrade to t…