Technology Review: “One of the most fundamental challenges in building foundational AI models for India is the country’s sheer linguistic diversity. With 22 official languages, hundreds of dialects, and millions of people who are multilingual, India poses a problem that few existing LLMs are equipped to handle. Whereas a massive amount of high-quality web data is available in English, Indian languages collectively make up less than 1% of online content. The lack of digitized, labeled, and cleaned data in languages like Bhojpuri and Kannada makes it difficult to train LLMs that understand how Indians actually speak or search. Global tokenizers, which break text into units a model can process, also perform poorly on many Indian scripts, misinterpreting characters or skipping some altogether. As a result, even when Indian languages are included in multilingual models, they’re often poorly understood and inaccurately generated.”
NYTimes: “The goal of Ms. Tang and others like her is to make ads feel like anything but ads. The brand’s voice is embedded in the content, as are its products, but there’s no overt pitch, no awkward energy of a sponsored partnership. The videos are seemingly unpolished, even if they may have been meticulously planned. And, in many cases, viewers may not even realize they’re being marketed to. This approach, which has existed on some level for quite some time, is part of a growing shift in social media marketing. Rather than investing in work from external influencers or celebrity ambassadors, many fashion, beauty and lifestyle companies are turning their cameras inward, enlisting their own employees to be the faces of the brand, while striving to make it feel more casual than that.”
FT: “Today there is no single narrative about where we are, or what comes next. Instead, there are multiple competing ones around globalisation, inflation, capital markets, politics and technology. All this creates a kind of Rashomon effect — the same data and events can be interpreted in contradictory ways by different market participants.”
WSJ: “A new crop of startups are betting on the rapid demise of traditional Google search. At least a dozen new companies are pouring millions of dollars into software meant to help brands prepare for a world in which customers no longer browse the web and instead rely on ChatGPT, Perplexity and other artificial-intelligence chatbots to do it for them. The startups are developing tools to help businesses understand how AI chatbots gather information and learn how to steer them toward brands so that they appear in AI searches. Call it the search-engine optimization of the next chapter of the internet. “Companies have been spending the last 10 or 20 years optimizing their website for the ‘10 blue links’ version of Google,” said Andrew Yan, co-founder of Athena, one of the startups. “That version of Google is changing very fast, and it is changing forever.””
SaaStr: “While everyone’s watching the flashy AI startups and hyperscalers duke it out, two enterprise software giants are quietly crushing it in the Age of AI. Oracle and SAP—companies many wrote off as legacy dinosaurs—are now posting some of the most impressive growth metrics in the entire enterprise software landscape.”
