This DJI Osmo Action 4 Standard Combo Drops to Lowest Price Ever While Amazon Clears Stock
Thankfully, you can currently get your hands on the excellent DJI Osmo Action 4 Camera while it's down to just $209. That's a 30% discount on the standard price of $299, and a really impressive deal. It's an Amazon deal too, so a lot of people can save money on postage thanks to Prime, but it does mean we don't know when the discount will end.
See at Amazon
Action cameras are especially well-suited to more adventurous users for a few reasons, but it helps that it's quite literally what they're designed for. Being able to rely on your camera when you're trying to take one-off photos is a must, and that's where this style of camera really shines.
The DJI Cosmo Action 4 Standard is capable of both 4K quality images and 120 frames per second, both of which are essential for ensuring that any photo or video you take will be of the quality you'll want when looking back at it as often as you want. It's also great in low-light thanks to a special sensor that makes it easy to keep things in focus at pretty much all times. It's also capable of surviving not only massive temperature fluctuations, with it being fine in -4 degree weather, perfect for snowboarding, but also with water as well.
It's easy to switch between horizontal and vertical shooting, and it has three different stabilization modes to help you capture the action when it'd normally be too hard to do so. The camera feeds perfectly into the special DJI Mimo app as well, which allows it to easily update when needed, and just generally lets you get more out of the device.
We think this is an excellent option, even if you're paying the standard price of $299 for it, so being able to get it for just $209 is a chance you shouldn't pass up. It's an excellent camera with plenty of features, so it's more than worth it.
See at Amazon
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Forbes
7 minutes ago
- Forbes
How ‘Vibe Coding' Is Creating A New AI Economy
In early January, 18‑year‑old Justin Jin launched Giggles — an AI-powered social entertainment app that's reportedly attracted over 120,000 waitlist sign-ups and generated 150 million impressions — all without a venture capital war chest, a marketing budget, or a traditional engineering team. Instead, he and his team of young co-founders leveraged AI to build an app for Gen Alpha and Gen Z, where users interact through AI-generated content, digital collectibles and gamified social engagements. A few weeks later, another startup arrived on the scene — Base44, founded by a non-technical creator who used AI to 'vibe code' a no-code development platform. Within six months and under ten people, it reached profitability, pulled in 300,000 users and sold to Wix for $80 million in cash, according to TechCrunch. Suddenly, a new archetype emerged: Companies not founded on traditional engineering teams, but shaped by creativity, culture and AI orchestration. This is the story of the moment. AI is redefining entrepreneurship, allowing people with a vision and cultural understanding — but not necessarily computer-science degrees — to ship platform-level products. But questions are mounting: Can this new model of entrepreneurship scale beyond prototype success without deeper engineering muscle? The Rise Of Vibe Coding Two years ago, the phrase 'vibe coding' barely existed. Today, it's everywhere. The term — coined by Andrej Karpathy, former AI lead at Tesla and cofounder of OpenAI — describes writing with AI by simply speaking ideas. 'You fully give in to the vibes, embrace exponentials and forget that the code even exists,' Karpathy tweeted in February. It's shorthand for a new era, where programming is done through a natural language like English. According to Garry Tan, CEO of Y Combinator, many startups now use AI to generate up to 95% of their codebase — achieving results that once required teams of 50 to 100 engineers with fewer than ten people. Meanwhile, in a recent article for Business Insider, Alistair Barr highlighted how 'non‑traditional, AI‑native developers' are turning natural language into apps, fundamentally altering SaaS economics. This shift is democratizing entrepreneurship. Product managers, artists, even high-schoolers can now ship products faster than ever before, all without technical expertise. But it also comes with some problems. As Nigel Douglas, head of developer relations at Cloudsmith, cautioned in the Financial Times, 'If you're creating an app in your spare time, a 'DIY disaster' might just mean an ugly interface. But in a business setting, the wrong tool can do real damage and result in data breaches, service outages, or a compromised software supply chain.' GitHub CEO Thomas Dohmke echoed this warning at the just-concluded VivaTech in Paris: 'A non‑technical founder will find it difficult to build a startup at scale without developers,' adding that tools like vibe coding don't provide the depth needed to justify serious investment. Even AI-native founders acknowledge the model's limitations. 'There's a need to build technical depth. We know that's important and are expanding engineering operations and bringing on advisors,' said Edwin Wang, co-founder of Giggles. 'The future, however, must be a community-governed and decentralized future where there's a balance between creativity and coding.' When Creativity Replaces Code: The Giggles Test Case Giggles is a microcosm of this transformation. Jin, alongside co-founders Edwin Wang and music artist Matthew Hershoff, built a system where users are rewarded for digital expression through game-like interactions — including AI-generated videos, collectible content, and daily quests. The result was a storytelling-centric platform developed without a traditional coding team — a structure that reflects the emerging blueprint behind many Gen Z–led apps. Jin previously founded Mediababy, which sold for $3.8 million, according to Reuters. That experience, he said, shaped his belief that platforms thrive when they prioritize user expression and fluid engagement over rigid structure. At Giggles, that belief translated into a product anchored in prompt-driven creativity, gamified feedback loops, and community-led interaction. As Wang noted, the company positions itself not just as an alternative to TikTok, but as a platform tailored for a generation it believes is increasingly disengaged from traditional social formats. And according to Hershoff, 'creators aren't limited to just posting photos and videos. They can vibe code a game, develop an app, create a whole virtual world and post it on Giggles.' Can AI-First Startups Scale? For all the momentum behind AI-native startups, there's a hard truth facing founders like Jin: culture can spark attention, but infrastructure sustains it. Platforms like Giggles, which thrive on virality and creator energy, eventually confront the same foundational question as any company with ambition. Can they scale securely, reliably, repeatedly and with technical discipline? At this stage, Giggles is less an anomaly and more a litmus test for how AI is transforming digital entrepreneurship. It's a living experiment in what happens when creativity, not technical expertise, drives product development. But to evolve from prompt-powered outfits into structured business ecosystems, these companies will need more than just vibes. They will need systems, safeguards and engineering depth. That's where founders must reckon with the limits of what vibe coding can achieve. Dohmke's warning at VivaTech isn't a dismissal of AI's potential, but a reminder of where the handoff happens. While AI can accelerate the zero-to-one moment, scaling responsibly requires the engineering rigor to turn a clever idea into a truly dependable platform. Jin and his team appear to recognize that. While Giggles was built without a traditional engineering stack, the company is now investing in its technical foundation. Wang, the platform's co-founder and lead developer, acknowledges that 'scaling creativity still requires coding discipline.' That doesn't diminish their AI-first origin; it refines it. The next test for Giggles — and others like it — isn't whether AI can launch a product. It's whether that product can become the infrastructure others depend on. A Hybrid Future For Founders What might the next decade yield? The trends point at a wave of hybrid founders: People with vivid creative vision and AI fluency who bring in veteran operators and engineers to solidify their product. That's the emerging blueprint: rapid prototyping, followed by structural discipline. Industry stalwart Reid Hoffman sees that promise, noting that 'bringing AI into your toolkit makes you enormously attractive.' But he and others caution that early AI advantage doesn't equal long-term lead. As AI-generated code gets better, so too must practices around testing, review, and security. In the end, the rise of vibe coding is real, but it's only half the story. Architecture, execution and human judgment are what matters most. While Giggles, Base44 and the rising 'AI-native' wave might be writing the prologue, the plot turns on whether these founders can turn vibe into real structure. 'In the end,' Jin told me, 'it's not just about who can build fast. It's about who can build something that lasts.'
Yahoo
35 minutes ago
- Yahoo
Yankees are paying 3 players a combined $43.8 million to not play for them
The New York Yankees have always been known for having a lot of money. They may not be the richest franchise in baseball anymore, though. The New York Mets and Los Angeles Dodgers seem to be shelling out even more dough. But the Yankees have one financial flex going for them, if it can be called a flex. And it's this: They're currently paying three players a combined $43.8 million not to play for them. Those three guys are DJ LeMahieu, Aaron Hicks and Marcus Stroman. The number works out to $43,785,714, to be exact. MORE: Cubs' Matthew Boyd has mastered the balk pickoff move Baseball contracts, unlike many of those in other professional sports, are fully guaranteed upon signing. That means when the Yankees get rid of Hicks in the past, or LeMahieu and Stroman this season, they're still owed their money. Stroman was just released after his last start, a bit of a surprise move. And like Stroman, both Hicks and LeMahieu were better before getting their latest Yankees contracts than they were afterward. MORE: Red Sox leapfrog the Yankees in the standings for first time since March As a big-market club with deep pockets, the Yankees can afford to make mistakes in contracts every once in a while. It's still not ideal that these mistakes are costing more than $43 million to guys not currently wearing the pinstripes in any form. The $43 million might not come in handy now, but it could matter greatly down the line. That's very real money that the Yankees won't have from production they aren't getting anyway. MORE MLB NEWS: White Sox batters have turned into 1927 Yankees Steven Kwan shows kindness on the most stressful day of his MLB career Marlins' Jakob Marsee starts his MLB career in a way no one ever has Rockies' Warming Bernabel is red hot Oneil Cruz makes one of the best throws in MLB history Red Sox phenom Roman Anthony makes MLB history not done since Elmer Valo in 1940
Forbes
40 minutes ago
- Forbes
Myth Or Reality: Will AI Replace Computer Programmers?
Have computer programmers innovated themselves out of a job? That's the fear driving theories that AI will remove the need for humans who can write computer code. Today's most sophisticated large language models like GPT-4o and Claude Sonnet are just as fantastically efficient at coding as they are at drafting emails and essays in human languages. Anthropic CEO Dario Amodei recently said he believes AI will soon be writing 90 percent of all code. And Amazon CEO and President Andy Jassy said his company will hire fewer software engineers thanks to AI. So does this mean that learning to program—since the start of the computer age, an accessible gateway to a lucrative career for many—is pointless now? Regardless of the capabilities of today's AI, is there any way that someone setting out to learn software development now can hope to be able to compete with the AI coders of five years in the future? With 30 percent of coders saying they believe that AI will replace them, there's fear and uncertainty in the air, but how does this affect the reality of the situation? Let's take a look: Why Are Programmers Worried They Will Be Replaced? Evidence certainly seems to be growing that generative AI tools can carry out many of the tasks associated with coding and programming. Commonly cited use cases include creating new code, optimizing existing code, detecting bugs, explaining code, maintaining documentation and detecting security vulnerabilities. Although quantitative research is limited at this point, one study found that programmers assisted by Microsoft's AI coding assistant, GitHub Copilot, have been able to complete tasks 55 percent faster than those without. It's frequently speculated that entry-level programming roles are the most likely to be affected because their work is more easily automated. Senior roles such as team leaders and lead engineers, requiring a broader skillset and the ability to deal with strategic challenges, may be less exposed. But there's still the question of where the next generation of human software development leadership will come from if there are no jobs for beginners! According to the Washington Post, computer programmer jobs have declined by almost 30% compared to the previous two years. It's important to note that this isn't reflected in the figures for software development as a whole, which has declined by only around 3%. Jobs with the title of "programmer", however, are more likely to be entry-level roles that can more easily be replaced by automation. This does point towards the possibility of major shifts in the labor landscape. But it also gives anyone who programs computers for a living useful clues about what they need to do to stay relevant. Evolving Roles The truth is that the role of the programmer, in line with just about every other professional role, will change. Routine, low-level tasks such as customizing boilerplate code and checking for coding errors will increasingly be done by machines. But that doesn't mean basic coding skills won't still be important. Even if humans are using AI to create code, it's critical that we can understand it and step in when it makes mistakes or does something dangerous. This shows that humans with coding skills will still be needed to meet the requirement of having a 'human-in-the-loop'. This is essential for safe and ethical AI, even if its use is restricted to very basic tasks. This means entry-level coding jobs don't vanish, but instead transition into roles where the ability to automate routine work and augment our skills with AI becomes the bigger factor in the success or failure of a newbie programmer. Alongside this, entirely new development roles will also emerge, including AI project management, specialists in connecting AI and legacy infrastructure, prompt engineers and model trainers. We're also seeing the emergence of entirely new methods of developing software, using generative AI prompts alone. Recently, this has been named "vibe coding" because of the perceived lack of stress and technical complexity in relation to traditional coding. In truth, these are really just new methodologies that require developers to focus on more strategic tasks like project management and program architecture, rather than the nuts and bolts of getting code to do what we want it to do. The term is sometimes used by traditional coders in a derogatory way to imply that those coding with AI are scared of getting their hands dirty with 'real' coding. However, the practice also serves as an indicator of how software development is likely to change, and what skills coders and engineers should be developing now if they want to remain relevant. A glimpse of one potential future is provided in this quote from Adjrej Karpathy, director of AI at Tesla: 'A large portion of programmers of tomorrow do not maintain complex software repositories, write intricate programs, or analyze their running times. They collect, clean, manipulate, label, analyze and visualize data that feed neural networks.' Myth Or Reality? Software development and programming jobs are not going to disappear, in the short term at least. But the role will change immeasurably, and there are firm clues in place as to the direction of that change. What's the key learning here? I'd say it's that the ability to learn new skills and continuously stay ahead of change is the one skill everyone involved in programming, software engineering and development needs to develop if they don't want to be left behind. Creativity, innovation and real-world problem-solving skills are vital to ensuring AI can be used to improve people's lives. While I believe emerging and future generations of AI technology will deliver wonders, humans will still be at the heart of the process. Partly this is down to the ethical responsibility to ensure there is always human oversight. But also because it will be some time (if ever) before AI has the strategy-focused, people-centric skills needed to replace programmers.
