OPPO says AI phones are judged by whether they remember you; the new IP business in the AI era; and Musk wants to double the Nvidia chips in Colossus 2 before year-end.
GeekPark interviewed Jiang Yuchen, OPPO ColorOS Smart Product R&D Director. She gave a definition of the AI phone: the user says one sentence, and the phone gets the job done, without opening apps one by one. She measured products on the market with this ruler, including OPPO's own. The conclusion is that no phone currently qualifies. Her judgment is that there's no gap left at the model layer, and the gap between phones has only just started to open. OPPO is betting its effort on on-device models (models that run locally on the phone and aren't uploaded to the cloud) and memory. The "one-tap quick note" in the system is a cross-app collection box; for meal pickup codes alone, cumulative calls have exceeded 1 billion. This year at ODC they also launched a new chest-worn hardware called the "Heart Power Ball." When switching phones, you can first check whether it remembers you. The pre-purchase test is simple: ask the phone to find last year's air conditioner installation order and see whether it recognizes it. If it can do that, the AI features have actually landed in daily life.
This article reposted by TMTPost sorts through two kinds of content: America's "Backrooms" and East Asia's "dreamcore." The Backrooms started with a corridor photo posted on a forum in 2019, and over several years grew into films, games, offline immersive experiences, and merch. This year's Backrooms movie had a production cost of about $10 million and global box office of over $400 million. Its setting was filled in by netizens together, so the filmmakers didn't have to invent the story from scratch. Japan's small game "Exit 8" sold 3 million copies, following the same path. Domestically, the two terms "dreamcore" and "Chinese dreamcore" have a combined 20 billion plays on Douyin, and right now they're mostly buy-to-play games and user short films made by small teams. People making content can see the order of this path clearly: first gather people through emotional resonance, then turn the setting into a framework that can be reused. What Chinese dreamcore lacks is the second step, namely distribution and cross-media development. Teams sitting on nostalgic subject matter should first write a solid setting document; that's more practical.
Bloomberg reports that legal AI company Harvey is valued at $15.6 billion. In March this year it updated its AI assistant, customer usage surged, but gross margin fell from about 50% at the start of the year to -50% in June. The loss is on the bill. What these companies do is call large models (programs that write text like GPT) to process legal documents; the more usage, the more they pay upstream. In August, Harvey released its own model, built on China's Kimi K3, at much lower cost. People familiar with the matter say its gross margin has already returned to positive. Teams building AI applications can copy this one move: replace the most expensive call. The method is to first find which step costs the most, then put a cheaper open-source model on top, and tune it with your own data to fit the business better. Sequoia and General Catalyst are both betting on this path. Once costs come down, there's room to negotiate user renewal prices.
Bloomberg reports that Musk plans to double the number of Nvidia chips in Colossus 2 before the end of the year. This machine is what he uses to train AI. Doubling isn't just placing orders. Packing more chips into one machine means power, cooling, and data centers all have to expand along with it, and projects like this most easily get stuck on power. For Nvidia, this is an order that can be counted before year-end. People watching this thread can note one method: chip counts and the progress of power expansion say more about who's still running forward than the model scores at a launch event. Companies doing data centers, power, and cooling support usually see orders appear along this chain.
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