Large Language Model
China's DeepSeek unveils latest models a year after upending global tech
China's DeepSeek unveils latest models a year after upending global tech China's DeepSeek has unveiled the latest versions of its signature artificial intelligence-powered chatbot, a year after its flagship model sent shockwaves through the global tech scene. The Chinese start-up launched preview versions of DeepSeek-V4-Pro and DeepSeek-V4-Flash on Friday as it touted its ability to go toe-to-toe with US rivals such as OpenAI and Google. The "flash" model has similar reasoning abilities to the "pro" version, while offering faster response times and more cost-effective pricing, the Hangzhou-based startup said. Like DeepSeek's previous chatbots, V4-Pro and V4-Flash follow an open-source model, meaning developers are free to use and modify them at will. The release comes after DeepSeek-R1 stunned the tech sector upon its launch in January last year with capabilities broadly comparable with those of ChatGPT and Gemini.
Bootstrapping Vision-Language Learning with Decoupled Language Pre-training
We present a novel methodology aimed at optimizing the application of frozen large language models (LLMs) for resource-intensive vision-language (VL) pre-training. The current paradigm uses visual features as prompts to guide language models, with a focus on determining the most relevant visual features for corresponding text. Our approach diverges by concentrating on the language component, specifically identifying the optimal prompts to align with visual features. We introduce the Prompt-Transformer (P-Former), a model that predicts these ideal prompts, which is trained exclusively on linguistic data, bypassing the need for image-text pairings.
Apple's Next Chapter, SpaceX and Cursor Strike a Deal, and Palantir's Controversial Manifesto
In this week's episode of, we talk about Tim Cook's legacy as CEO at Apple and what his long-rumored departure means for the future of one of the world's biggest companies. They also go into the reasoning behind SpaceX and Cursor's surprising deal, and why Palantir's self-published manifesto drew a lot of heat online. Also, we discuss why some conspiracy theorists are leaving Trump's side, and how a scammer created an AI-generated woman to attract and grift MAGA men. Tim Cook's Legacy Is Turning Apple Into a Subscription This Scammer Used an AI-Generated MAGA Girl to Grift'Super Dumb' Men Write to us at [email protected] . You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link . Zoë, Leah, and I have really enjoyed being your new hosts these past few weeks, and we want to hear from you. If you like the show and have a minute, please leave us a review in the podcast or app of your choice. It really helps us reach more people, and for any questions and comments, you can always reach us at [email protected] . I missed you so much. And I missed you the exact same amount. I'm going to go away more often. Absence makes the heart go fonder, as we all know, and I'm thrilled to be here. This week on the show, we're saying goodbye to Apple CEO, Tim Cook, who announced that he is stepping down from the top gig at the company. And, more than just talking about his legacy at Apple, we'll be looking into what this long-awaited shift actually means for the future of one of the world's biggest companies. We'll also get into why SpaceX and Cursor's potential $60 billion deal announced this week is pretty staggering, and we'll get into Palantir's controversial 22-point manifesto. I feel like manifesto's inherently controversial, otherwise they'd be memos that they posted on X this week.
At 'AI Coachella,' Stanford Students Line Up to Learn From Silicon Valley Royalty
CS 153 has gone viral on the Palo Alto campus--and on X. Not everyone is happy about it. As thousands of influencers descended on southern California earlier this month for the annual Coachella Music Festival, a very Silicon Valley program dubbed "AI Coachella" was taking shape a few hundred miles north in Palo Alto. The class, CS 153, is one of Stanford's buzziest offerings this semester, and like the music festival, it features a star-studded lineup of celebrities--in this case, not pop artists, but Big Tech CEOs. The course is co-taught by Anjney Midha, a former Andreessen Horowitz general partner, and Michael Abbott, Apple's former VP of engineering for cloud services.
The Guardian view on Anthropic's Claude Mythos: when AI finds every flaw, who controls the internet? Editorial
'The US government's embrace of Anthropic marks a shift.' 'The US government's embrace of Anthropic marks a shift.' The Guardian view on Anthropic's Claude Mythos: when AI finds every flaw, who controls the internet? A nthropic announced its latest AI model, Claude Mythos, this month but said it would not be released publicly, because it turns computers into crime scenes. The company claimed that it could find previously unknown "zero-day" flaws, exploit them and, in principle, link these weaknesses in order to take over major operating systems and web browsers . Mythos did so autonomously, writing code and obtaining privileges.
The Download: introducing the Nature issue
Plus: Trump signaled he's open to reversing the Anthropic ban. When we talk about "nature," we usually mean something untouched by humans. But little of that world exists today. From microplastics in rainforest wildlife to artificial light in the Arctic Ocean, human influence now reaches every corner of Earth. In this context, what even is nature? And should we employ technology to try to make the world more "natural"?
ChatGPT predicted the first round of the NFL Draft and here's what it said
Curt Cignetti was so focused this offseason, he turned down all external requests: 'I'm 95% football' Former MLB owner claims'despicable' San Francisco Giants are the reason the A's left Oakland Longtime NASCAR crew chief tells wild story about one of the sport's biggest characters WNBA finally embraces Caitlin Clark's stardom with unprecedented national TV schedule Why are the Mets so bad? Flyers mascot Gritty pens letter to fans ahead of first playoff game... eight years after he debuted NFL Draft prospect Rueben Bain Jr. mum about 2024 crash when publicly asked about it for first time Troy Aikman is selling'fire suites,' which are exactly what they sound like Fernando Mendoza's first pitch at Marlins game draws harsh reviews Steve Hilton praised for'offering solutions' in CA gubernatorial debate Middle East tensions escalate over US blockade, Iran's actions Michael Easter and Gary Brecka discuss the'choice' to live to be 100 Sen Ted Cruz calls new deadline with Iran'really consequential' RFK Jr confronted over'raccoon parts' on Capitol Hill Our democracy is not'in crisis,' Sen John Fetterman says The DOJ is'on the offense' here, Andrew Kolvet says OutKick ChatGPT predicted the first round of the NFL Draft and here's what it said Ultimate human vs. machine showdown as OutKick's Dan Z. takes on ChatGPT in a mock draft battle Where Is The Value In This NFL Draft? Jonathan Hutton & Chad Withrow ask Armando Salguero what position has the most value in this year's NFL draft I'm not sure why I do these things to myself, but I decided to go head-to-head with ChatGPT in a mock draft competition. I recently released my final mock draft, and then I asked ChatGPT to predict the entire first round. Below, you will see where we are the same and where we are different.
What Will It Take to Get A.I. Out of Schools?
What Will It Take to Get A.I. Out of Schools? The tech world assumes that A.I.-aided education is necessary and inevitable. A growing number of parents, educators, and cognitive scientists say the opposite. I don't like A.I., and I am raising my children not to like it. I've been telling them for years now that chatbots are manipulative and dangerous, that A.I.-image generators are loosening our collective grip on reality, that large language models are built atop industrial-scale intellectual-property theft. At times, I find myself speaking with my kids about A.I. in the same terms that we might discuss a creepy neighbor who lives down the block: avoid eye contact, cross the street when you walk past his house, and, when in doubt, call on a trusted adult. Yes, I, too, have suspected that the creepy neighbor walks on cloven hooves inside his Yeezy Boosts, but he probably isn't going anywhere--in fact, he keeps buying up properties around town--so just try your best not to engage. Somehow, I was not prepared for the creepy neighbor to start hanging around my kids' schools; somehow, I thought we had until high school.
Cold-Start Forecasting of New Product Life-Cycles via Conditional Diffusion Models
Zhou, Ruihan, Zhang, Zishi, Han, Jinhui, Peng, Yijie, Zhang, Xiaowei
Forecasting the life-cycle trajectory of a newly launched product is important for launch planning, resource allocation, and early risk assessment. This task is especially difficult in the pre-launch and early post-launch phases, when product-specific outcome history is limited or unavailable, creating a cold-start problem. In these phases, firms must make decisions before demand patterns become reliably observable, while early signals are often sparse, noisy, and unstable We propose the Conditional Diffusion Life-cycle Forecaster (CDLF), a conditional generative framework for forecasting new-product life-cycle trajectories under cold start. CDLF combines three sources of information: static descriptors, reference trajectories from similar products, and newly arriving observations when available. Here, static descriptors refer to structured pre-launch characteristics of the product, such as category, price tier, brand or organization identity, scale, and access conditions. This structure allows the model to condition forecasts on relevant product context and to update them adaptively over time without retraining, yielding flexible multi-modal predictive distributions under extreme data scarcity. The method satisfies consistency with a horizon-uniform distributional error bound for recursive generation. Across studies on Intel microprocessor stock keeping unit (SKU) life cycles and the platform-mediated adoption of open large language model repositories, CDLF delivers more accurate point forecasts and higher-quality probabilistic forecasts than classical diffusion models, Bayesian updating approaches, and other state-of-the-art machine-learning baselines.