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Over the past 12 business days, OpenAI has announced a new product or demoed an AI feature every weekday, calling the PR event “12 days of OpenAI.” We’ve covered some of the major announcements, but we thought a look at each announcement might be useful for people seeking a comprehensive look at each day’s developments.

The timing and rapid pace of these announcements—particularly in light of Google’s competing releases—illustrates the intensifying competition in AI development. What might normally have been spread across months was compressed into just 12 business days, giving users and developers a lot to process as they head into 2025.

Humorously, we asked ChatGPT what it thought about the whole series of announcements, and it was skeptical that the event even took place. “The rapid-fire announcements over 12 days seem plausible,” wrote ChatGPT-4o, “But might strain credibility without a clearer explanation of how OpenAI managed such an intense release schedule, especially given the complexity of the features.”

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On Friday, during Day 12 of its “12 days of OpenAI,” OpenAI CEO Sam Altman announced its latest AI “reasoning” models, o3 and o3-mini, which build upon the o1 models launched earlier this year. The company is not releasing them yet but will make these models available for public safety testing and research access today.

The models use what OpenAI calls “private chain of thought,” where the model pauses to examine its internal dialog and plan ahead before responding, which you might call “simulated reasoning” (SR)—a form of AI that goes beyond basic large language models (LLMs).

The company named the model family “o3” instead of “o2” to avoid potential trademark conflicts with British telecom provider O2, according to The Information. During Friday’s livestream, Altman acknowledged his company’s naming foibles, saying, “In the grand tradition of OpenAI being really, truly bad at names, it’ll be called o3.”

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Over the past month, we’ve seen a rapid cadence of notable AI-related announcements and releases from both Google and OpenAI, and it’s been making the AI community’s head spin. It has also poured fuel on the fire of the OpenAI-Google rivalry, an accelerating game of one-upmanship taking place unusually close to the Christmas holiday.

“How are people surviving with the firehose of AI updates that are coming out,” wrote one user on X last Friday, which is still a hotbed of AI-related conversation. “in the last <24 hours we got gemini flash 2.0 and chatGPT with screenshare, deep research, pika 2, sora, chatGPT projects, anthropic clio, wtf it never ends.”

Rumors travel quickly in the AI world, and people in the AI industry had been expecting OpenAI to ship some major products in December. Once OpenAI announced “12 days of OpenAI” earlier this month, Google jumped into gear and seemingly decided to try to one-up its rival on several counts. So far, the strategy appears to be working, but it’s coming at the cost of the rest of the world being able to absorb the implications of the new releases.

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It’s been a really busy month for Google as it apparently endeavors to outshine OpenAI with a blitz of AI releases. On Thursday, Google dropped its latest party trick: Gemini 2.0 Flash Thinking Experimental, which is a new AI model that uses runtime “reasoning” techniques similar to OpenAI’s o1 to achieve “deeper thinking” on problems fed into it.

The experimental model builds on Google’s newly released Gemini 2.0 Flash and runs on its AI Studio platform, but early tests conducted by TechCrunch reporter Kyle Wiggers reveal accuracy issues with some basic tasks, such as incorrectly counting that the word “strawberry” contains two R’s.

These so-called reasoning models differ from standard AI models by incorporating feedback loops of self-checking mechanisms, similar to techniques we first saw in early 2023 with hobbyist projects like “Baby AGI.” The process requires more computing time, often adding extra seconds or minutes to response times. Companies have turned to reasoning models as traditional scaling methods at training time have been showing diminishing returns.

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Another company has publicly cut ties with Broadcom’s VMware. This time, it’s Ingram Micro, one of the world’s biggest IT distributors. The announcement comes as Broadcom eyes services as a key part of maintaining VMware business in 2025. But even as some customers are reducing reliance on VMware, its trillion-dollar owner is laughing all the way to the bank.

IT distributor severs VMware ties

Ingram is reducing its Broadcom-related business to “limited engagement with VMware in select regions,” a spokesperson told The Register this week.

“We were unable to reach an agreement with Broadcom that would help our customers deliver the best technology outcomes now and in the future while providing an appropriate shareholder return,” the spokesperson said.

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On Thursday, a large group of university and private industry researchers unveiled Genesis, a new open source computer simulation system that lets robots practice tasks in simulated reality 430,000 times faster than in the real world. Researchers can also use an AI agent to generate 3D physics simulations from text prompts.

The accelerated simulation means a neural network for piloting robots can spend the virtual equivalent of decades learning to pick up objects, walk, or manipulate tools during just hours of real computer time.

“One hour of compute time gives a robot 10 years of training experience. That’s how Neo was able to learn martial arts in a blink of an eye in the Matrix Dojo,” wrote Genesis paper co-author Jim Fan on X, who says he played a “minor part” in the research. Fan has previously worked on several robotics simulation projects for Nvidia.

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The AI-generated video scene has been hopping this year (or twirling wildly, as the case may be). This past week alone we’ve seen releases or announcements of OpenAI’s Sora, Pika AI’s Pika 2, Google’s Veo 2, and Minimax’s video-01-live. It’s frankly hard to keep up, and even tougher to test them all. But recently, we put a new open-weights AI video synthesis model, Tencent’s HunyuanVideo, to the test—and it’s surprisingly capable for being a “free” model.

Unlike the aforementioned models, HunyuanVideo’s neural network weights are openly distributed, which means they can be run locally under the right circumstances (people have already demonstrated it on a consumer 24 GB VRAM GPU) and it can be fine-tuned or used with LoRAs to teach it new concepts.

Notably, a few Chinese companies have been at the forefront of AI video for most of this year, and some experts speculate that the reason is less reticence to train on copyrighted materials, use images and names of famous celebrities, and incorporate some uncensored video sources. As we saw with Stable Diffusion 3‘s mangled release, including nudity or pornography in training data may allow these models achieve better results by providing more information about human bodies. HunyuanVideo notably allows uncensored outputs, so unlike the commercial video models out there, it can generate videos of anatomically realistic, nude humans.

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Arm and Qualcomm’s dispute over Qualcomm’s Snapdragon X Elite chips is continuing in court this week, with executives from each company taking the stand and attempting to downplay the accusations from the other side.

If you haven’t been following along, the crux of the issue is Qualcomm’s purchase of a chip design firm called Nuvia in 2021. Nuvia was originally founded by ex-Apple chip designers to create high-performance Arm chips for servers, but Qualcomm took an interest in Nuvia’s work and acquired the company to help it create high-end Snapdragon processors for consumer PCs instead. Arm claims that this was a violation of its licensing agreements with Nuvia and is seeking to have all chips based on Nuvia technology destroyed.

According to Reuters, Arm CEO Rene Haas testified this week that the Nuvia acquisition is depriving Arm of about $50 million a year, on top of the roughly $300 million a year in fees that Qualcomm already pays Arm to use its instruction set and some elements of its chip designs. This is because Qualcomm pays Arm lower royalty rates than Nuvia had agreed to pay when it was still an independent company.

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On Wednesday, OpenAI launched a 1-800-CHATGPT (1-800-242-8478) telephone number that anyone in the US can call to talk to ChatGPT via voice chat for up to 15 minutes for free. The company also says that people outside the US can send text messages to the same number for free using WhatsApp.

Upon calling, users hear a voice say, “Hello again, it’s ChatGPT, an AI assistant. Our conversation may be reviewed for safety. How can I help you?” Callers can ask ChatGPT anything they would normally ask the AI assistant and have a live, interactive conversation.

During a livestream demo of “Calling with ChatGPT” during Day 10 of “12 Days of OpenAI,” OpenAI employees demonstrated several examples of the telephone-based voice chat in action, asking ChatGPT to identify a distinctive house in California and for help in translating a message into Spanish for a friend. For fun, they showed calls from an iPhone, a flip phone, and a vintage rotary phone.

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T-Mobile today said it opened registration for the “T-Mobile Starlink” beta service that will enable text messaging via satellites in dead zones not covered by cell towers.

T-Mobile’s announcement said the service using Starlink’s low-Earth orbit satellites will “provid[e] coverage for the 500,000 square miles of land in the United States not covered by earth-bound cell towers.” Starlink parent SpaceX has so far launched over 300 satellites with direct-to-cell capabilities, T-Mobile noted.

A registration page says, “We expect the beta to begin in early 2025, starting with texting and expanding to data and voice over time. The beta is open to all T-Mobile postpaid customers for free, but capacity is limited.”

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