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AI NewsGoogle Introduces Gemini 3.5 Flash Low to Help Antigravity Users Maximise Usage

Google Introduces Gemini 3.5 Flash Low to Help Antigravity Users Maximise Usage

3:03 PM IST · May 26, 2026

Google Introduces Gemini 3.5 Flash Low to Help Antigravity Users Maximise Usage

Ever since Google restructured its Gemini plans to a compute-based usage system, it has struggled to provide users of its agentic coding platform, Antigravity, with enough tokens. The Mountain View-based tech giant, last week, announced a shift from the message-based usage to one that measures the number of tokens exhausted. Once the new system was rolled out, users began complaining about hitting rate limits on Antigravity very quickly. Things were so bad that the tech giant had to increase the Antigravity rate limit twice, but it appears even that was less. Now, the company is solving the problem with a new Gemini 3.5 Flash variant.

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TechCrunch Disrupt 2026 Early Bird ticket rates end May 29

TechCrunch Disrupt 2026 Early Bird ticket rates end May 29

Four days. That’s all that’s left to decide, not just whether you’ll be atTechCrunch Disrupt 2026, but also how you’ll show up from October 13 to 15 at San Francisco’s Moscone West and how much momentum you create once you’re there. Right now, you cansave up to $410 on your Disrupt passbefore prices increase on May 29 at 11:59 p.m. PT. After that, rates go up, and so does the cost of missing the conversations, visibility, and connections that can accelerate what happens next for your company. Because at a certain point, growth is no longer just about building. It’s about being seen, understood, and taken seriously by the people who influence what comes next. You only have four days left to secure your savings.Choose your ticket typeand lock in the lowest available rates before prices rise. Mostfoundersdon’t struggle to generate attention. There are more channels than ever to get in front of people and more ways to create surface-level visibility. What’s harder, and far more important, is earning credibility. Investorsdon’t respond to visibility alone; they respond to confidence. Partners don’t engage based on awareness; they engage based on trust. Even early customers are making decisions about what feels established, what feels validated, and what feels worth their time. Across six industry stages, Disrupt is designed to show how companies earn trust at every phase of growth by putting founders, investors, and operators in environments where credibility is built in real time through practical, hands-on sessions.Visit the Disrupt agendato see the new sessions added to each stage. Builders and operators break down how companies actually scale. Learning from founders who’ve done it, and applying those frameworks, helps you speak with more authority when discussing growth, fundraising, and execution. Explore how leading companies are applying AI in practice. Hearing directly from builders and investors working at the frontier helps founders anchor their approach in what’s proven, not just what’s promised, strengthening credibility with both technical and business audiences. Beyond software, AI is reshaping the physical world. Hear from founders and operators building trusted, scalable systems in robotics, biotech, and edge environments where real-world constraints define success. Money is being rebuilt in real time. Explore how founders are shaping the future of finance through stablecoins, payments, and fintech infrastructure while cutting through hype to reveal what’s actually working in a digital economy. Software is transforming energy, climate, and industrial systems. Explore how founders are rebuilding infrastructure, from data center power to grid bottlenecks, while deploying smarter, scalable systems for a more resilient future. The main stage where top founders, investors, and operators define what matters next. Being part of these conversations, and referencing them, positions you within the broader narrative of where the market is heading. From October 13–15 in San Francisco,Disruptbrings together 10,000+ founders, investors, and operators in one concentrated environment built for evaluation and discovery. Across250+ sessions, roundtables, and discussions, and with300+ startups showcasing, companies aren’t seen once. They’re seen repeatedly in front of the same investors, partners, and media. That repetition is what turns visibility into credibility. A quick introduction becomes recognition. Recognition becomes familiarity, and familiarity builds trust. The founders and operators who gain the most from Disrupt aren’t just attending sessions. They’re building relationships, reinforcing their presence across conversations, and positioning themselves within the networks that shape what happens next in tech. For the next four days, you still have time tosecure your pass before rates increase. Savings of up to $410 end May 29 at 11:59 p.m. PT. If you’re already planning to be there, the decision now isn’t whether to attend — it’s whether you show up ready to move things forward.Register here.

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Universal Music Group and TikTok renew agreement to combat unauthorized AI music

Universal Music Group and TikTok renew agreement to combat unauthorized AI music

Universal Music Group (UMG) and TikTok recentlyannouncedthe renewal of their licensing agreement, which includes a commitment to get rid of unauthorized AI-generated music from the platform improve how artists and songwriters are credited. In their joint announcement, UMG stated the agreement “extends TikTok and UMG’s groundbreaking commitment to AI protections that promote human artistry and ensure platform economics effectively flow through to artists and songwriters. TikTok and UMG will work together to remove unauthorized AI-generated music from the platform, while further improving artist and songwriter attribution.” This new agreement represents a notable shift in the relationship between UMG and TikTok. For years, UMG has pushed platforms, streaming services, and AI companies to implement stricter content moderation policies. Tensions betweenUMG and TikTokescalated in 2024 when UMG accused TikTok of inadequately addressing issues related to AI-generated music and copyright. This public dispute led to UMG temporarily pulling its music catalog from TikTok — a decision that underscored the app’s growing reliance on major label licenses as popular tracks vanished from user videos overnight. The timing of TikTok’s commitment to crack down on fake or unlicensed music is significant especially as the music industry wrestles with an influx of AI-generated content. Over the past couple of years, the industry has been increasingly worried about AI tools that can mimic artists’ voices or create counterfeit songs that exploit streaming algorithms. Viral AI-generated tracks imitating big names like Drake and The Weeknd sparked widespread concern, especially when some racked up millions of streams before being taken down. The deal may also serve as a template for how the broader tech industry navigates the collision of AI, intellectual property, and platform accountability. As the EUtightens its regulatory gripon AI-generated content (and U.S. states increasinglyfollow suit) around AI-generated content, the pressure on other platforms to formalize similar governance frameworks is growing. TikTok has been working to demonstrate to the music industry that it can deliver significant earnings for artists and rights holders. Last year, the platform launched “TikTok for Artists,” an insights platform designed to help artists strengthen their promotional efforts and provide music labels with access to data.

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This startup is betting India’s gig economy can train the world’s robots

This startup is betting India’s gig economy can train the world’s robots

In the last few years, India’sonline food delivery markethas grown significantly, with both Zomato and Swiggy going public and the number of cloud kitchens increasing. Meanwhile, startups working on home services, such as on-demand household staffing platforms like Urban Company,Snabbit, andPronto, have gained popularity. Silicon Valley-based startupHuman Archiveis tapping into this trend, partnering with these companies to have workers wear special caps with cameras to collect egocentric (first-person point of view) video data of everyday tasks that could be used to train robots. Without naming specific partners, the startup said it is working with companies in the home services, hotel, and restaurant sectors to collect egocentric data, and it says it has more than 1,000 active headsets deployed across multiple locations. On the back of that traction, Human Archive said Tuesday it has raised $8.2 million in funding from Wing Venture Capital, NVP Capital, Y Combinator, and angels from OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, and Meta. The startup was founded by three students from UC Berkeley and one from Stanford — Samay Maini, Rushil Agarwal, Shloke Patel, and Raj Patel, the latter two being cousins. (Raj Patel is CEO.) All four have research backgrounds spanning robotics, hardware, and tactile data. The company’s founding is a direct bet on where the AI industry is heading. As robotics labs and frontier AI companies race to build machines that can perform physical tasks in the real world, they face a critical bottleneck — a shortage of high-quality, real-world training data showing humans doing everyday work. Human Archive’s bet is that the workers staffing India’s booming gig economy represent an untapped and scalable source of exactly that data. While Human Archive is working with multiple partners, the startup said it was rejected by many Indian home services companies, including Pronto and Urban Company, for a collaboration. The company’s rejection by major players became public fodder last weekend, when Indian outlet Entrackrreportedthat Pronto is actively seeking partnerships to collect worker data for robotics training and that Snabbit had held early discussions with Human Archive before the project fell apart. Urban Company CEO Abhiraj Singh Bhalrespondedon X, stating the company would not engage in such arrangements — prompting Patel tofire backthat Urban Company would soon be forced to reconsider or risk losing relevance to customer churn. Co-founder Rushil Agarwal was blunter still, posting that Pronto founder Anjali Sardana hadlaughedat him and called him “stupid” when he raised the idea of a data partnership. Pronto acknowledged the conversations but said it chose not to move forward. Across the country, other startups are collecting egocentric data fromdifferent work environments, including factory floors. To differentiate itself, Human Archive is using and developing additional devices, such as tactile gloves, a full-body motion capture suit, and wrist cameras to capture data, including motion and tactile force, synchronously aligned with RGB-D (color imagery paired in real time with depth information), to sell to AI labs. The startup believes that video data alone is not sufficient but that pairing it with other sensor data makes it much more valuable. Initially, Human Archive used makeshift setups or off-the-shelf rigs to capture the data. Now it is working on custom hardware that works together and captures different kinds of data. It already has more than 50 different devices deployed to collect different data points. “To capture data, we started with iPhones; then we built our own custom rigs and caps. Now we have more than seven different hardware products that we use interchangeably across different modalities. After data collection from different devices, we worked on synchronizing data from all these different sources,” Patel said in a call. The company said it is developing ways to fine-tune AI models with its own data and test them on robots to evaluate task effectiveness. By doing this, the startup can demonstrate the quality of its data to potential customers and post-train internal models. Zach DeWitt, a partner at Wing VC, said the startup has a unique advantage in collecting data from multiple sensors. “No one else in the world has been able to synchronize and collect headset RGB-D, force feedback, full-body motion capture, and synchronized chest and wrist camera data at scale. They’ve been doing internal model training on this data, and every major lab and university is interested in running experiments on it due to the novelty of the sensors and the scale of the new dataset they are releasing soon,” he told TechCrunch. Despite rejection from notable players in the home services industry, Human Archive teamed up with smaller startups to offer discounted services to customers. When a worker arrives at a home, consumers are offered a choice through the app: pay a discounted price in exchange for consenting to data collection, or pay the full price for an unrecorded visit. Patel mentioned that customers have been happy to opt for the former, as disputes about service quality are common, and video recordings can help resolve them. The company pays workers a base rate of $1 per hour for participating in egocentric data collection. A report from the Economic Times suggests that other companies pay ₹250 to ₹400 per hour (roughly $2.63 to $4.20). Patel said competitors pay more than Human Archive, but its on-the-ground presence in India allows it to keep compensation lower. “Human Archive’s network provides immediate, flexible earning opportunities globally, lowering the barrier to participating in the AI economy. We see this as a critical bridge that funds immediate livelihoods while building the infrastructure for a safer, more productive future,” DeWitt said. Beyond wage payment, there are privacy concerns around data collection via video recording. It is not clear what information Human Archive gives workers about how their footage is used. The company said that its commercial contracts are compliant with India’sDigital Personal Data Protection (DPDP) Act, as it displays a privacy policy notice, along with consent information detailing the purpose of data collection and how it is processed. The company said all data is anonymized and faces are blurred from recordings. Last week, Moneycontrolreportedthat India’s Ministry of Electronics and Information Technology is looking into the consent mechanisms and data-collection practices of startups collecting egocentric data through home service workers. While Human Archive largely collects data in India, it has started expanding into Southeast Asia and the U.S. The company is also building a platform for anyone to participate in data collection and earn money. It also wants to offer customers in the U.S. services like cleaning or cooking in exchange for data collection by participating workers — though these programs are just in an early pilot stage. Multiple well-funded startups areracingto buildphysical AI. Doing so requires massive amounts of training data showing humans at work — and Human Archive is one of the players competing to serve that demand. Whether its approach can scale will hinge on the partnerships it strikes and the uniqueness and volume of the data it can collect to satisfy the appetite of physical AI labs.

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DeepSeek Slashes V4 Pro Prices by 75% Permanently

DeepSeek Slashes V4 Pro Prices by 75% Permanently

The company’s aggressive pricing strategy is expected to increase pressure on AI companies globally.

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