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Stay updated with our most recent articles. Here, you’ll find the latest insights, research findings, and industry news in AI and technology.
Stay updated with our most recent articles. Here, you’ll find the latest insights, research findings, and industry news in AI and technology.
AI is still improving, yet investors and enterprises are asking a more difficult question: are those improvements translating into returns fast enough to justify the cost? The emerging debate around an “AI slowdown” is therefore less about whether artificial intelligence has stopped advancing, and more about whether the economics of AI can keep pace with the scale of investment behind it.
What if the breakthrough that finally scales robotics isn’t more robot data, but the billions of hours of physical experience humans generate every day?
The iPhone Duo stole Apple’s September event, while the iPhone 18 Pro delivered the less dramatic—but arguably more practical—upgrades. After the keynote, the prevailing response is a mixture of genuine excitement, sticker shock, and a sensible desire to wait for real-world testing.
LLMs scaled by consuming the internet. AI agents may scale differently—by entering millions of executable worlds where they can act, fail, learn, and try again.
At UGREEN’s Smart Living event at Gillette Stadium, HomeAgent stood out as the clearest sign yet that the company wants to move beyond accessories and into the heart of the smart home.
The US consumer drone market is experiencing a profound contraction, and the recent controversy surrounding the HoverAir Versa is the clearest indicator yet of where things are heading.
Google once again took center stage in New York City for its highly anticipated Made by Google fall hardware event. Here is the ultimate, detailed breakdown of every major announcement and product unveiled.
Closed AI APIs are fantastic for rapid prototyping, but they are a financial trap for high-volume scaling. Conversely, open-source AI is essentially "free" until you realize you have to pay for the MLOps team and GPU clusters to run it. Now that the intelligence gap between the two has evaporated, how do you choose?