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Embracing Powertrain Diversity, GWM Continues to Enhance Clean Diesel Capabilities for Off-Roading

Embracing Powertrain Diversity, GWM Continues to Enhance Clean Diesel Capabilities for Off-Roading

Associated Press10 hours ago

BAODING, CHINA - Media OutReach Newswire - 15 June 2025 - While new energy vehicles continue to gain momentum worldwide, efficient diesel power remains a compelling choice—especially in challenging off-road environments where torque, range, and reliability are critical. GWM is advancing diesel technology with a focus on refinement, performance, and real-world usability. At the recent GWM Thailand Diesel Day event, the brand demonstrated how modern diesel can deliver a clean, quiet, and highly capable driving experience.
Traditional trade-offs—torque versus comfort, power versus fuel economy—are disappearing. With today's drivers demanding both performance and efficiency, GWM's TANK 300 Diesel delivers on all fronts.
In Thailand, the TANK 300 Diesel has earned high praise for its impressive torque (480N·m at just 1,500rpm), extended driving range (up to 1,200km), and smooth, quiet ride. As one reviewer noted, 'It drives like a gasoline SUV—quiet and refined—until you need the torque. Then, it just powers through.'
This refined balance comes from GWM's 2.4T diesel engine, combined with over 200 NVH (Noise, Vibration, and Harshness) enhancements—bringing idle noise down to just 65dB, comparable to gasoline-powered vehicles. The result: urban comfort with true off-road muscle.
GWM's advanced combustion technology—featuring columnar combustion chambers and dual tangential air ducts—cuts fuel consumption to under 7.3L/100km, making long journeys more economical and environmentally responsible.
Guided by its 'All Scenarios, All Powertrains, All Users' strategy, GWM's TANK 300 Diesel demonstrates that diesel, when done right, is still a powerful, relevant solution to real-world needs. In markets like Thailand, clean diesel has a promising future.
More than just a product launch, GWM's achievement reflects a user-centered innovation that sets a new benchmark. The message to drivers is clear: more power, fewer compromises, and a brand that truly listens.
https://youtu.be/LOVtBHWdN3o?si=8SkFmlVl0iTFvqiV
Hashtag: #GWM
The issuer is solely responsible for the content of this announcement.

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Robert Kubica seals emotional Le Mans 24 Hours victory for Ferrari
Robert Kubica seals emotional Le Mans 24 Hours victory for Ferrari

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Robert Kubica seals emotional Le Mans 24 Hours victory for Ferrari

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Alexa von Tobel has high hopes for ‘fintech 3.0'
Alexa von Tobel has high hopes for ‘fintech 3.0'

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Alexa von Tobel has high hopes for ‘fintech 3.0'

It's been 10 years since Alexa von Tobel sold her financial planning startup Learnvest to Northwestern Mutual for $250 million. Since then, von Tobel became Northwestern Mutual's first chief digital officer, then chief innovation officer, before launching an early-stage venture firm of her own, Inspired Capital, with former U.S. Secretary of Commerce Penny Pritzker. She's also a New York Times bestelling author, and she's about to launch a new interview podcast, 'Inspired with Alexa von Tobel.' In a conversation with TechCrunch, von Tobel recalled the hectic period around the acquisition, which closed literally days before the birth of her first child, and when she knew it was time to start her own firm. Von Tobel explained that she created Inspired to be the investor she'd dreamed of — one with a 'cultish commitment to entrepreneurship' — when she was a founder herself. 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Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Boston, MA | REGISTER NOW First, Northwestern Mutual is an incredible company, and our software became an incredibly important part of the customer experience. And I am so proud that so many of the LearnVest team stayed at Northwestern Mutual for so long, and it really was just a merger of actual values. It's just amazing how simple some things are, it comes down to the values of two companies and the missions of two companies. I sold on a Wednesday and went into labor with my first child that weekend. All jokes aside, I always say it took me about a year to mentally just recover from being, like, all systems were go, my brain was being pushed to manage so many things. Literally, I was having my first child. It was like the world threw a bus at me and I caught it. 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LearnVest as a product doesn't exist anymore, but it sounds like it was less about having LearnVest as a standalone product and more about transforming Northwestern Mutual. It was so much bigger than a product. [Northwestern Mutual's] John Schlifske, he's no longer CEO, but he is one of the people I look up to most in the world, just a formidable human being. And he kept being like, 'We're gonna merge the companies.' And I would laugh — one is a $40-billion-a-year company, and [the other is] little tiny LearnVest. But he really meant it. He was like, 'We're gonna use this as a catalyst.' It was a catalyst for an entire digital transformation. I became the company's first ever chief digital officer, and then chief innovation officer, and it was really about taking everything and merging it into the broader parent company. My CTO of LearnVest became the CTO of the parent company. You stayed for four years? Yeah, [my last day] was basically end of January 2019, and that day we launched Inspired. How did you know it was time to leave, and where did the idea for Inspired come from? I'm always at my best when I'm building something that I wish existed for me. And I've said many times that the idea for Inspired actually happened when I dropped out of business school, and I was a really all-in entrepreneur in every way — I dropped out basically December 18 of 2008, at the bottom of the worst recession in 81 years, not necessarily the the the most inviting time to start a company. And I really was looking for a capital partner that didn't exist. I had this vision of what it should look and feel like, this sort of rigor and camaraderie and in-the-trenches-ness of what an early stage capital partner could be, and I didn't see it in the market. That was New York in 2008, 2009, and I had this long-term plan of one day, I want to come back and build that. 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At many firms, you get one partner, that's the person they know, they know you, and if, God forbid, that partner leaves, it's like you've evaporated your social equity that you built up with that partner. We operate like a swarm, where you get all of us and we actively do weekly stand ups on the entire portfolio, so that everybody's up to speed. And then the final thing, because of [Inspired co-founder Penny Pritzker], she's on the board of Microsoft, was U.S. Secretary of Commerce. So we like to say that, there are many, many, many, many ways that we can help companies get access to things that are really hard to get as just a sole founder in your 20s or 30s, where we can actually be a tremendous business accelerant to our companies in a pretty unique way, with access to tech and government and many other vectors. So in short, that was the firm I wanted. I wanted a deeply cultish commitment to entrepreneurship. 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They have reasons to exist. They have less copycats. I think a lot of things got funded over the last period of, like, 2014 to 2021, that should've been getting a different source of capital. How are you feeling about the state of fintech in 2025? Where are there still opportunities for startups? I'm feeling both urgent and optimistic about the state of fintech today. Financial services remain foundational to a functioning society, but they haven't kept pace with the rapid technological, demographic, and social shifts we're experiencing. The growing federal debt, rising income inequality, and increasing poverty — especially among older Americans — underscore the need for more adaptive and inclusive financial tools. Not to mention the rapid job loss due to AI. This moment presents a major opportunity for startups to reimagine financial products from the ground up. We think of this wave as fintech 3.0. 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Multimodal AI: A Powerful Leap With Complex Trade-Offs
Multimodal AI: A Powerful Leap With Complex Trade-Offs

Forbes

timean hour ago

  • Forbes

Multimodal AI: A Powerful Leap With Complex Trade-Offs

Artificial intelligence is evolving into a new phase that more closely resembles human perception and interaction with the world. Multimodal AI enables systems to process and generate information across various formats such as text, images, audio, and video. This advancement promises to revolutionize how businesses operate, innovate, and compete. Unlike earlier AI models, which were limited to a single data type, multimodal models are designed to integrate multiple streams of information, much like humans do. We rarely make decisions based on a single input; we listen, read, observe, and intuit. Now, machines are beginning to emulate this process. Many experts advocate for training models in a multimodal manner rather than focusing on individual media types. This leap in capability offers strategic advantages, such as more intuitive customer interactions, smarter automation, and holistic decision-making. Multimodal has already become a necessity in many simple use cases today. One example of this is the ability to comprehend presentations which have images, text and more. However, responsibility will be critical, as multimodal AI raises new questions about data integration, bias, security, and the true cost of implementation. Multimodal AI allows businesses to unify previously isolated data sources. Imagine a customer support platform that simultaneously processes a transcript, a screenshot, and a tone of voice to resolve an issue. Or consider a factory system that combines visual feeds, sensor data, and technician logs to predict equipment failures before they occur. These are not just efficiency gains; they represent new modes of value creation. In sectors like healthcare, logistics, and retail, multimodal systems can enable more accurate diagnoses, better inventory forecasting, and deeply personalized experiences. In addition, and perhaps more importantly, the ability of AI to engage with us in a multimodal way is the future. Talking to an LLM is easier than writing and then reading through responses. Imagine systems that can engage with us leveraging a combination of voice, videos, and infographics to explain concepts. This will fundamentally change how we engage with the digital ecosystem today and perhaps a big reason why many are starting to think that the AI of tomorrow will need something different than just laptops and screens. This is why leading tech firms like Google, Meta, Apple, and Microsoft are heavily investing in building native multimodal models rather than piecing together unimodal components. Despite its potential, implementing multimodal AI is complex. One of the biggest challenges is data integration, which involves more than just technical plumbing. Organizations need to feed integrated data flows into models, which is not an easy task. Consider a large organization with a wealth of enterprise data: documents, meetings, images, chats, and code. Is this information connected in a way that enables multimodal reasoning? Or think about a manufacturing plant: how can visual inspections, temperature sensors, and work orders be meaningfully fused in real time? That's not to mention the computing power multimodal AI require, which Sam Altman referenced in a viral tweet earlier this year. But success requires more than engineering; it requires clarity about which data combinations unlock real business outcomes. Without this clarity, integration efforts risk becoming costly experiments with unclear returns on investment. Multimodal systems can also amplify biases inherent in each data type. Visual datasets, such as those used in computer vision, may not equally represent all demographic groups. For example, a dataset might contain more images of people from certain ethnicities, age groups, or genders, leading to a skewed representation. Asking a LLM to generate an image of a person drawing with their left hand remains challenging – leading hypothesis is that most pictures available to train are right-handed individuals. Language data, such as text from books, articles, social media, and other sources, is created by humans who are influenced by their own social and cultural backgrounds. As a result, the language used can reflect the biases, stereotypes, and norms prevalent in those societies. When these inputs interact, the effects can compound unpredictably. A system trained on images from a narrow population may behave differently when paired with demographic metadata intended to broaden its utility. The result could be a system that appears more intelligent but is actually more brittle or biased. Business leaders must evolve their auditing and governance of AI systems to account for cross-modal risks, not just isolated flaws in training data. Additionally, multimodal systems raise the stakes for data security and privacy. Combining more data types creates a more specific and personal profile. Text alone may reveal what someone said, audio adds how they said it, and visuals show who they are. Adding biometric or behavioral data creates a detailed, persistent fingerprint. This has significant implications for customer trust, regulatory exposure, and cybersecurity strategy. Multimodal systems must be designed for resilience and accountability from the ground up, not just performance. Multimodal AI is not just a technical innovation; it represents a strategic shift that aligns artificial intelligence more closely with human cognition and real business contexts. It offers powerful new capabilities but demands a higher standard of data integration, fairness, and security. For executives, the key question is not just, "Can we build this?" but "Should we, and how?" What use case justifies the complexity? What risks are compounded when data types converge? How will success be measured, not just in performance but in trust? The promise is real, but like any frontier, it demands responsible exploration.

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