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Tech leaders often brand themselves as disruptorsand few fit that label more snugly than Elon Musk. In the three months since joining Donald Trump in the White House following Trumps election, Musk has certainly disrupted Washington. Now, reports suggest Musk is preparing to exit his government post, having led the Department of Government Efficiency (DOGE), and overseen sweeping cuts across numerous federal agencies. Musks time in government may be short-lived, but his political legacy is already sealed. As the architect of aggressive budget slashes, his tenure has sparked backlash that could linger far beyond the halls of powerand into the boardrooms of his private ventures. Musk stepping out the political firing line might calm the headlines, but the brand damage is already done, says social media expert Matt Navarra. The internet doesnt forget, and neither do his investors. Navarra believes Musks recent behaviorwhat he calls Musks political anticshas become a heavy drag on the entrepreneurs public image. Teslas stock has plummeted nearly 30% this year, while the recent merger of X, the social platform Musk acquired in 2022, with his AI startup xAI, has drawn ridicule for its apparent lack of financial return. At the heart of the reputational and financial downturn is a growing perception that Musk has prioritized political theater over operational focus. His reputation as a visionary founder has dimmed as his companies have stumbled. The Musk DOGE initiative and spending 110% of his time with the Trump administration in the White House/Palm Beach since January inauguration has been exacerbating and so troubling for investors and Tesla’s stock, says Dan Ives, managing director and senior equity research analyst at Wedbush Securities. Though Ives remains optimistic about Teslas long-term potential, he acknowledges the fallout from Musks high-profile role in government austerity. Tesla has unfortunately become a political symbol because of Musk, and this is a very bad thing for the future of this technology stalwart, Ives says. With major protests erupting globally at Tesla dealerships, Tesla cars being keyed, and a full brand crisis tornado now underway, this has turned into a life of its own and cast a dark black cloud over Tesla’s stock. Navarra notes that this moment is particularly damaging because Musks companies were once buoyed by his persona. Tesla, X, and even SpaceX all used to benefit from his cult of personality, but now I think that charisma is curdled, he says. I think there’s a growing gap between Musk the innovator and Musk the provocateur, and it’s hard for any brand to thrive when its CEO behaves like a chaos agent on the timeline. So far, Musk appears unmovedor unawareof the toll his political turn has taken on his empire. (He did not respond to a request for comment sent to both his government and Tesla email addresses.) But Navarra warns the consequences may be long-lasting. Even if he fades from the political narrative, his digital footprint stays loud, he says. Every tweet, every jab at the media, or every partisan swipe, it all feeds into how the public sees Tesla and X. He’s not just shaping the narrative, he is the narrative, and the longer that continues, the harder it becomes for his companies to tell a different story.
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The Panama Canal is one of the most important waterways in the world, with about 7% of global trade passing through. It also relies heavily on rainfall. Without enough freshwater flowing in, the canals locks cant raise and lower ships traveling between the Atlantic and Pacific oceans. Droughts mean fewer ships per day, and that can quickly affect Panamas finances and economies around the world. But the same freshwater is also essential for Panamas many other needs, including drinking water for about two million Panamanians, use by Indigenous people and farmers in the watershed, as well as hydropower. When the region experiences droughts, as it did in 20232024, the resulting water shortages can lead to increasing water conflicts. One of those conflicts involves a new dam the Panama Canal Authority plans to begin building in 2027. It would be designed to secure enough water to keep the canal, which contributes about 4.2% to the countrys gross domestic product, operating into the future, but it would also submerge farming communities and displace over 2,000 people from their homes. This recent drought wasnt an anomaly. As an academic who studies the effects of rising temperatures on water availability and sea level rise, Im aware that as the climate warms, Panama will likely face more extremes, both long dry spells and also periods of too much rain. That will force more trade-offs between residential needs and the canal over water use. Complex engineering remade the landscape The Panama Canal was built over a century ago at the narrowest point of the country and in the heart of its population center. The route was historically used by the Spanish colonies and later for a rail line between the oceans. The idea of a canal connecting the Atlantic and Pacific oceans began as a French endeavor, led by architect Ferdinand D. Lesseps, designer of the Suez Canal in Egypt. After the French effort failed, the U.S. government signed a treaty with newly independent Panama in 1903 to take over the project. The U.S. acquired the rights to build and operate the Panama Canal in exchange for U.S.$10 million and annual payments of $250,000. Later, the Torrijos-Carter Treaty in 1977 committed the U.S. to transfer the control of operations to Panama at the end of 1999. The canal project was designed to take advantage of the regions tropical climate and abundant average rainfall. It harnessed the water of the Chagres River basin to run three sets of lockschambers that, filled with fresh water, act like elevators, lifting or lowering ships to compensate for the difference in water levels between the two oceans. To ensure enough water would be available for the locks, the canals designers changed the shapes of the regions mountains and rivers to create a large watershedover 1,325 square miles (3,435 square kilometers)that drains toward the canals human-made lakes, Gatun and Alajuela. About 65% of the water that flows from the watershed today goes to operate the locks. The majority of that water is quickly lost to the oceans. Even the two newest locks, built in 2016, only reuse about 60% of water on each transit40% is flushed to avoid saltwater from the oceans intruding into the watershed. Threats to water security Panamas wet tropical weather is predominantly influenced by its location near the equator, the trade winds, and the oceans. Most of its rain falls during the wet season, from May to November. However, weather records show a drop in average precipitation starting around 1950. The driest years resulted in dangerously low water levels in Gatun Lake that made canal operations difficult, including in 1998, 2016, and most recently 20232024. El Nio weather patterns can mean particularly low rainfall. In December 2023, the Panama Canal Authority was forced to limit the number of daily transits to 22, compared with 36 to 38 usual crossings, because too little freshwater was available. Water levels at Gatun Lake since 1965 show how low 2023 and 2024 were. [Image: EIA] To avoid steep financial losses, the Panama Canal Authority raised prices and auctioned transit opportunities to the highest bidders. Without those measures, the authority estimated it would lose $100 million a month from reduced ship traffic because of the water shortage. Ecosystems also need enough water, and changes in forest tree composition have become evident on Barro Colorado Island in Gatun Lake in response to rising temperatures and more frequent droughts. Climate change is also creating greater variability in rainfall. Too much rain can also be a problem for canal operations. In December 2010, the biggest storm on record caused landslides and $150 million in damage that interrupted transits on the canal. Sustaining Panamas canal and its people Temporary measures for saving water have been already implemented. The Panama Canal Authority shortened the chamber size in some of its locks to use less water for smaller vessels and minimized direction changes. In January 2025, the authority approved plans to build the new dam on the Indio River to increase water available for the canal. The dam could solve some water concerns during drier periods for the canal. However, it also illustrates the countrys water conflicts. Once filled, the dams reservoir will submerge over 1,200 homes by some counts, and more people in the region will lose access to land and travel routes. The Panama Canal Authority promises that residents will be relocated, but some of those living in the region fear they will lose their livelihoods, along with the communities their families have lived in for generations. Residents across Panama, meanwhile, regularly hear media campaigns that encourage them to save water. An Environmental Economic Incentives Program promotes forest conservation and sustainable family agriculture to conserve water resources. The Panama Canal is a crucial part of international trade, and it will face more periods of water stress. I believe responding to those future changes, as well as market and societal demands, will require innovative solutions that respect ecosystem limits and the needs of the population. Karina Garcia is a researcher and lecturer in climate at Universidad Tecnológica de Panamá. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Welcome to AI Decoded, Fast Companys weekly newsletter that breaks down the most important news in the world of AI. You can sign up to receive this newsletter every week here. OpenAI says it will release an open-source modelbut why now? OpenAI CEO Sam Altman said Monday that his company intends to release a powerful new open-weight language model with reasoning in the next few months. That would mark a major shift for a company that has kept its models proprietary and secret since 2019. The announcement wasnt a total surprise: After the groundbreaking Chinese open-source model DeepSeek-R1 showed up in January, Altman said during a Reddit AMA that he realized his company was on the wrong side of history and suggested an OpenAI open-source model was a real possibility. Open models typically come with a permissive license that requires little or no payment to the model developer. Open-weight models can be more cost-effective for corporations trying to leverage AI since they allow businesses to host (and secure) the models themselvesavoiding the often risky prospect of sending proprietary data through an API to a third-party provider and paying fees to do it. More businesses are moving in this directionespecially those holding sensitive user data in regulated industries. The catch: A corporate user doesnt have to pay to use the open model. Some AI labs release open models to gain credibility in the marketpotentially paving the way to eventually sell API access to their more powerful closed models. By releasing open models early on, the French AI company Mistral established itself as a top-tier AI lab and a legitimate alternative to U.S. players. Some AI labs release open-source models, then earn consulting fees by helping large enterprises deploy and optimize the models over time. Metas Llama models are the most widely deployed open modelsthough the company restricts reuse and redistribution and keeps the training data and code secret, meaning they are not by definition open source. Meta had different reasons for giving away its models. Unlike Mistral and others, it makes money by surveilling users and targeting adsnot by renting out AI models. Zuckerberg continues funding Llama research because the models are a disruptive force in the industry and earn Meta the right to be called an AI company. OpenAI now has its own reasons for releasing an open-weight model. Eighteen months ago, OpenAI was the undisputed champion of state-of-the-art AI models. But in the time since, the release of LLMs like Googles formidable Gemini 2.0 and DeepSeeks open-source R1 have cracked the competition wide open. The market has changed, and OpenAI itself has evolved. Like Meta, OpenAI doesnt depend directly and solely on its models for its revenue. Selling access to its models via an API is no longer the companys main source of revenue. Now, most of its revenue, not to mention its staggering $300 billion valuation, comes from selling subscriptions to ChatGPT (most of them to individual consumers). OpenAIs real superpower is being a household-name consumer AI brand. OpenAI will definitely continue pouring massive resources into developing ever-better models, but its main reason for doing so isnt to collect rent from developers for direct access to them, but rather to continue making ChatGPT smarter for consumers. AI video generation is getting scary good AI-video-generation tools are rapidly leaping over the uncanny valley, making it increasingly difficult for everyday internet users to distinguish between real and generated video. This could bode well for smaller companies looking to produce glossy, creative, or ambitious ads at a fraction of the normal cost. But it could spell bad news if bad actors use the technology in phishing scams or to spread disinformation. Its also yet another threat to the film sectors livelihood. The issue is back in the spotlight following several announcements, starting with Runways release of its new Gen-4 video-generation system, which the company says produces production ready video. AI startup Runway says the new system of models understands much of the worlds physics (a claim supported by this video of a man being overtaken by an ocean wave). The company also touts improvements in video consistency and realism, as well as user control during the generation process. Runway posted a demo video of Gen-4s control tools, which makes the production process look pretty easy, even for non-technicals). Some of the samples of finished videos posted on X look somehow more real than real (see Jean Baudrillard, Simulacra and Simulation). Runway faces some stiff competition in the AI video space in the form of perennial contenders including Googles Veo 2 model, OpenAIs Sora, Adobe Firefly, Pika, and Kling. A new math benchmark aims to beat test question contamination People in the AI community have been debating for some time whether our current methods of testing models math skills are broken. The concern is that while existing math benchmarks contain some very hard problems, those problems (and their solutions) tend to get published online pretty quickly. This of course makes the problem-solution sets fair game for AI companies sweeping up training data for their next models. The worry is that, come evaluation time, the models may have already encountered the test problems and answers in their training data. A new benchmark called MathArena was designed to eliminate those issues. MathArena takes its math problems from very recent math competitions and Olympiads, which have obvious incentives to keep their problems secret. The researchers from MathArena also created their own standard method of administering the evaluation, meaning the AI model developers cant give their own models an edge via changes to the evaluation setup. MathArena has just released the results of the most recent benchmark, which includes questions from the 2025 USA Math Olympiad. Heres one of the questions: Let H be the orthocenter of the acute triangle ABC, let F be the foot of the altitude from C to AB, and let P be the reflection of H across BC. Suppose that the circumcircle of triangle AFP intersects line BC at two distinct points, X and Y. Prove that C is the midpoint of XY. Ouch. And to make matters worse, the test requires not only the correct answer but a decription of each reasoning step the model took along the way. The results are, well, ugly. Some of the most powerful and celebrated models in the world took the test, and none scored above 5%. The top score went to DeepSeeks R1 model, which earned a 4.76%. Googles Gemini 2.0 Flash Thinking model scored 4.17%. Anthropics Claude 3.7 Sonnet (Thinking) scored 3.65%. OpenAIs most recent thinking model, o3 mini, scored 2.08%. The results suggest one of several possibilities: Maybe MathArena contains far harder questions than other benchmarks, or LLMs arent great at explaining their reasoning steps, or earlier math benchmark scores are questionable because the LLMs had already seen the answers. Looks like LLMs still have some homework to do. More AI coverage from Fast Company: An AI watchdog accused OpenAI of using copyrighted books without permission Amazon unveils Nova Act, an AI agent that can shop for you What is AI thinking? Anthropic researchers are starting to figure it out How Hebbia is building AI for in-depth research Want exclusive reporting and trend analysis on technology, business innovation, future of work, and design? Sign up for Fast Company Premium.
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