Bets tend to appear in the 'For you' section of Google News, which is supposed to be tailored to a person's particular interests. Futurism notes that the platform actually placed a Polymarket bet as the top news result when inquiring about the price of Bitcoin.
If I fast-forward, a lot of what are just information-seeking queries will be agentic in Search. You'll be completing tasks. You'll have many threads running.
Buyers no longer open ten tabs, skim through blog posts, and slowly form an opinion over weeks. Instead, they ask a single question to an AI system and receive a shortlist in return, usually two or three companies that feel familiar, credible, and safe enough to justify internally. That shortlist often becomes the entire market in the buyer's mind.
Meta is working on two proprietary frontier models: Avocado, a large language model, and Mango, a multimedia file generator. The open-source variants are expected to be made available at a later date.
The majority of AI products remain tethered to a single, monolithic UI pattern: the chat box. While conversational interfaces are effective for exploration and managing ambiguity, they frequently become suboptimal when applied to structured professional workflows. To move beyond "bolted-on" chat, product teams must shift from asking where AI can be added to identifying the specific user intent and the interface best suited to deliver it.
If you're familiar with the world of SEO, I probably don't have to tell you there's been a serious shift in its landscape. Marketers are no longer just optimizing content for Google's traditional blue links; we're now optimizing for AI. The shift is called Answer Engine Optimization, or AEO. Some practitioners also refer to it as AI engine optimization, and both terms are used interchangeably. But what does it mean to optimize your content for AI engines? I'll explain.
By comparing how AI models and humans map these words to numerical percentages, we uncovered significant gaps between humans and large language models. While the models do tend to agree with humans on extremes like 'impossible,' they diverge sharply on hedge words like 'maybe.' For example, a model might use the word 'likely' to represent an 80% probability, while a human reader assumes it means closer to 65%.
Content discovery is the passive or active process of finding information on the internet using keywords. It displays previously created or indexed content, requiring users to sift through generic search results and to read through multiple long pages. Unsurprisingly, this approach often has the familiar drawbacks of content saturation and noise, leading to frustration and wasting users' time. According to a 2022 study, people who have difficulty finding content rate it as 53% less useful and accurate.
