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AI & Machine Learning

Models, breakthroughs, and the race to AGI

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Why Owl Post covers AI & Machine Learning

AI moves faster than any single feed can keep up with. Frontier model releases, capability benchmarks, regulation filings, and the steady drip of research papers that actually matter: the signal-to-noise ratio is brutal, and most coverage is either uncritical hype or reflexive doomerism.

Owl Post tracks AI across lab announcements, academic preprints, policy documents, and the downstream product implications that most general tech outlets miss. When a new model ships, the question is not which benchmark it topped. The question is what it changes in practice, which sectors feel it first, and which regulatory responses are already in motion. That is the framing you get here.

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The beat spans foundation models and the infrastructure underneath them, the enterprise and consumer applications being built on top, and the policy layer that is still catching up. Owl Post filters out the benchmark theater and the doom-cycle takes, and surfaces what actually shifted: capability jumps with real-world implications, deployment moves with business consequences, and regulation with actual teeth.

How you read it adapts to you. If you want deep technical context that respects a smart audience without turning into a lecture, your digest can read that way. If you want a measured, analyst-style take that names the implications without overstating them, that works too. The curation stays rigorous either way.

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Canva launches Code 2.0, offering AI website building to every user — including free accounts

Canva on Tuesday launched Canva Code 2.0, a major upgrade to its AI-powered coding tool that lets users build interactive websites, apps, and experiences using plain-language prompts — and then edit the results as easily as tweaking a Canva presentation. The feature is now available to all of the company's more than 265 million monthly users across every pricing tier, including free accounts. The move is Canva's most aggressive push yet into the fast-growing "vibe coding" market, a category that barely existed 18 months ago but has already minted billion-dollar startups and reshaped how non-developers think about building software. But where rivals like Lovable, Replit, and Bolt.new have focused primarily on generating functional code from text prompts, Canva is making a different bet: that the real bottleneck isn't creating the code — it's making the output actually look good. "Most vibe coding tools stop at functional — generating output that looks the same as everyone else's," Canva states in its announcement. "You might get a working prototype, but making it actually look like yours requires a complex editing surface, a separate design tool, a developer, or endless back-and-forth prompting that rarely lands where you want it.” Danny Wu, Canva's Head of AI Products, framed the product's positioning in stark terms during an exclusive interview with VentureBeat ahead of the launch. "We are deliberately targeting non-technical users," Wu said. "Canva Code isn't a tool we're building for developers. What we're trying to do is bring the power of AI coding — and really lightweight coding — into the Canva platform, while answering our users' requests for more interactivity, more customization, and more flexibility, from websites to interactive presentations." Canva Code 2.0 brings drag-and-drop editing, HTML import, and 75% faster generation to AI-built websites The update introduces several capabilities designed to collapse the distance between generating code and publ

venturebeat.com

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