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Runway AI Raises $315Mn at $5.3Bn Valuation for World Models

Posted on by Shobhit Kalra

NEW YORK: AI video generation startup Runway secured $315 million in Series E funding at a $5.3 billion valuation, nearly doubling its worth in less than 10 months, the company announced Tuesday.

General Atlantic led the round with participation from Nvidia, Adobe Ventures, AMD Ventures, Fidelity Management & Research, AllianceBernstein, Mirae Asset, Emphatic Capital, Felicis, and Premji Invest. Total funding now reaches $860 million since 2018 inception.

The fresh capital will pre-train next-generation “world models”, AI systems constructing internal environment representations to plan future events. Runway released its first world model in December and views the technology as central to tackling challenges in medicine, climate, energy, and robotics beyond current entertainment applications.

CEO Cristóbal Valenzuela described world models as “the most transformative technology of our time.” The company recently launched Gen-4.5, featuring high-definition video creation, native audio, multi-shot generation, and advanced editing capabilities.

Runway previously raised $308 million in April 2025 at $3.3 billion valuation. The latest round reflects robust investor interest in video AI startups, which raised $3.08 billion globally in 2025, up 94.6% from $1.58 billion in 2024.

The New York-based company has 140 employees and plans hiring across research, engineering, and go-to-market functions. Runway’s models serve tens of millions of users including film studios, creative teams, and global brands.

The company is expanding partnerships with CoreWeave for compute infrastructure and entering gaming, robotics, and autonomous vehicle sectors.

OpenAI Begins Testing Ads in ChatGPT for Free Users

Posted on by Amita Parul

SAN FRANCISCO: OpenAI launched ad testing in ChatGPT for U.S. users on Free and Go subscription tiers, days after rival Anthropic mocked the move in Super Bowl commercials.

OpenAI stated ads will not influence ChatGPT answers and conversations stay private from advertisers. Ads appear clearly labeled at the bottom of responses, matched to conversation topics, past chats, and previous ad interactions.

The $8-per-month Go plan users will see ads alongside free tier users. Subscribers to Plus, Pro, Business, Enterprise, and Education tiers remain ad-free.

Users researching recipes might see grocery delivery or meal kit ads. Advertisers receive only aggregate performance data like views and clicks, not access to chats, history, memories, or personal details.

Major agencies including Omnicom Media and Dentsu participated in early testing. Ad Age reports strong advertiser interest despite consumer resistance.

Anthropic’s Super Bowl ads portrayed glassy-eyed AI chatbots delivering advice alongside poorly targeted advertisements. OpenAI CEO Sam Altman called the commercials “dishonest” and Anthropic an “authoritarian company.”

Users can dismiss ads, share feedback, view targeting explanations, delete ad data, and manage personalization settings. Ads won’t appear for users under 18 or near sensitive topics like health, politics, or mental health.

OpenAI needs revenue to cover mounting development costs. The company faces backlash after testing app suggestions that resembled unwanted ads in December.

Internal documents forecast $1 billion from “free user monetization” in 2026, growing to $25 billion by 2029.

ElevenLabs Raises $500 Million at $11 Billion Valuation

Posted on by Tea4Tech Team

SAN FRANCISCO: Nvidia-backed Voice AI startup ElevenLabs secures $500 million Series D funding at $11 billion valuation, more than tripling its worth from $3.3 billion just one year ago as enterprise adoption accelerates across conversational AI platforms.

Sequoia Capital led the investment, with partner Andrew Reed joining the board to steer global scaling efforts. Power players like Andreessen Horowitz boosted their position fourfold, ICONIQ tripled their commitment, and fresh capital flowed from Lightspeed Venture Partners, Evantic Capital, and BOND – building on Nvidia’s earlier support.

Cumulative funding now stands at $781 million since the 2022 launch. ElevenLabs has advanced from speech-to-text, real-time dubbing, music generation, and intelligent conversational AI agents to Eleven v3 Conversational model. 

The numbers tell a growth story for the ages: ElevenLabs surpassed $330 million in annual recurring revenue (ARR) by late 2025, vaulting from $100 million in under two years. Big-name clients, including Deutsche Telekom, Revolut, Square, and the Ukrainian Government are powering this momentum and merging accessible creator tools with robust enterprise platforms. 

Co-founders Mati Staniszewski and Piotr Dabkowski plan to channel proceeds into “ElevenAgents” and “ElevenCreative,” fusing audio innovation with video and proactive AI capabilities.  

ElevenLabs keeps pushing its global footprint, now spanning key hubs like London, New York, San Francisco, Warsaw, Dublin, Tokyo, Seoul, Singapore, Bengaluru, Sydney, São Paulo, Berlin, Paris, and Mexico City. 

For investors and industry watchers, this positions ElevenLabs as an IPO frontrunner. Amid 2025’s AI funding wave in the U.S. Projections hint at $700 million ARR by mid-2026. Potentially commanding 28x revenue multiples as voice interfaces redefine human-tech interaction. With hubs sprouting in 14 cities, enterprise adoption should accelerate, cementing speech AI’s role in a trillion-dollar agent economy.  

Tech portfolios eyeing the next big shift can’t ignore this voice revolution. 

University of Michigan AI System Interprets Brain MRI Scans in Seconds

Posted on by Anurag Shukla

ANN ARBOR: University of Michigan researchers developed an AI system that interprets brain MRI scans in seconds, accurately identifying neurological conditions and determining which cases require urgent care, the university announced Tuesday.

The system, trained on hundreds of brain MRI datasets, can analyze complex neurological imaging at speeds impossible for human radiologists while maintaining high accuracy across multiple conditions.

Traditional brain MRI interpretation requires specialized neurologists and can take hours or days depending on workload and complexity. The AI system reduces this to mere seconds, potentially transforming emergency department workflows where rapid diagnosis determines treatment timing for stroke, traumatic brain injury, and other acute conditions.

The technology addresses critical bottlenecks in neurological care. Many hospitals face radiologist shortages, particularly overnight and in rural areas. Delays in MRI interpretation can postpone critical interventions for time-sensitive conditions like ischemic stroke, where treatment efficacy decreases dramatically with each passing hour.

The system identifies a wide range of neurological conditions including tumors, bleeding, stroke, multiple sclerosis lesions, and structural abnormalities. It also provides urgency classification, flagging cases requiring immediate attention versus routine follow-up.

University of Michigan did not disclose specific accuracy metrics or deployment timelines. The research team is reportedly working toward clinical validation trials required for FDA approval.

Similar AI diagnostic tools from companies like Viz.ai and RapidAI already assist with stroke detection, but the Michigan system’s broader neurological condition coverage represents expanded capabilities.

The development reflects accelerating AI adoption in medical imaging, where radiologist burnout and volume growth create demand for automated support systems.

Supertails raises $30mn to scale petcare services in India

Posted on by Shobhit Kalra

Bengaluru: Aiming to deepen its presence in the country’s fast-growing pet services market, the Indian petcare startup Supertails has secured $30 million in a fresh funding round, led by Venturi Partners.

The funding round also saw participation from Nippon India Alternative Investments and Titan Capital Winners Fund, along with continued backing from investors such as Fireside Ventures, RPSG Capital Ventures, Sauce VC, and Saama Capital.

The new capital will support Supertails’ plans to grow its physical veterinary clinics, expand doorstep healthcare services for pets, and upgrade its supply chain and delivery capabilities. 

The company is also investing in improving how its platform personalises recommendations for pet owners as it expands further across India’s large urban centres. Based on industry estimates, the round places Supertails’ valuation at roughly $130 million.

Launched in 2021 by Varun Sadana, Aman Tekriwal, and Vineet Khanna, Supertails is building an integrated ecosystem for pet parents rather than operating as a simple online store. Its app combines commerce, healthcare, and advisory services, allowing users to manage most of their pet-related needs in one place.

Alongside selling food, treats, and accessories, the startup has built a network of veterinarians offering home visits, tele-consultations, vaccinations, and preventive care. In Bengaluru, Supertails has also introduced fast delivery for thousands of pet products, including medicines, and plans to roll out similar services in other major cities.

Supertails has raised about $51 million to date. In FY25, its revenue crossed Rs 108 crore, up from around Rs 65 crore a year earlier, while losses increased as the company continued to invest aggressively in expansion.

AI Boom Triggers Global Memory Chip Shortage, DRAM Prices Surge 600%

Posted on by Shobhit Kalra

SAN FRANCISCO: A global memory chip shortage is driving unprecedented price increases, with the Dynamic Random Access Memory (DRAM) spot prices surging over 600% in recent months as AI infrastructure diverts production capacity from consumer electronics.

Bloomberg reports memory producers including Samsung, SK Hynix, and Kioxia saw shares soar 160% since September while consumer electronics makers plunged 12%. The divide reflects capacity reallocation toward high-bandwidth memory for AI data centers.

DRAM prices jumped 171% year-over-year, with DDR5 spot prices quadrupling since September 2025. Contract prices are projected to rise 55-60% quarter-over-quarter in Q1 2026.

AI servers consume far more memory per system than consumer devices. Each gigabyte of HBM requires approximately three times the wafer capacity of standard DDR5. Data centers will consume 70% of memory produced in 2026, up from historical norms.

Samsung raised 32GB DDR5 module prices to $239 from $149 in September, a 60% increase. Macronix plans a 30% NOR flash price hike for Q1 2026.

Consumer impacts are mounting. Qualcomm shares fell 8% after warning memory constraints will limit phone production. Nintendo dropped most in 18 months on margin pressure warnings. Logitech declined 30% from November peak.

IDC forecasts 5% smartphone sales decline and 9% PC sales drop in 2026. Manufacturers face difficult choices: raise prices significantly, cut specifications, or both.

Memory represents 15-20% of mid-range smartphone bill of materials, 10-15% for flagship devices. TrendForce analysts call it “the craziest time ever” after tracking the sector for 20 years.

Normalization unlikely before late 2027 as manufacturers maintain supply discipline favoring high-margin AI products.

India’s Sarvam AI Beats Google Gemini, ChatGPT on OCR Benchmarks

Posted on by Anurag Shukla

BENGALURU: Bengaluru-based startup Sarvam AI claims its models outperformed Google Gemini and ChatGPT on optical character recognition and text-to-speech benchmarks focused on Indian languages, marking a milestone for domestic AI development.

Sarvam Vision achieved 84.3% accuracy on olmOCR-Bench, surpassing Gemini 3 Pro and DeepSeek OCR v2, while ChatGPT ranked significantly lower. On OmniDocBench v1.5, Sarvam Vision scored 93.28% overall, excelling in complex formulas and layout parsing.

Co-founder Pratyush Kumar shared benchmark results on X, stating “On Indian languages, Sarvam Vision is the best model by far, while supporting all 22 scheduled Indian languages.”

The Vision series includes a 3-billion-parameter state-space model capable of image captioning, scene text recognition, chart interpretation, and complex table parsing. The model handles messy layouts, tables, mathematical formulas, and technical documents where traditional OCR tools struggle.

Alongside Vision, Sarvam launched Bulbul V3, a text-to-speech model supporting 35 voices across all 22 official Indian languages. Bulbul V3 handles smooth language switching between Tamil and English or Hindi and English without disruption.

Tech commentator Deedy Das acknowledged changing his earlier skepticism: “I was wrong about Sarvam. When I wrote about them a year ago, I felt the direction to train small Indic language models was wrong. But they have the best text-to-speech, speech-to-text, and OCR models for Indic languages.”

Union IT Minister Ashwini Vaishnaw said the work reflects success of India’s AI mission.

Sarvam made its Document Intelligence API free through February 2026. The startup positions itself as building “sovereign AI” developed within India for government projects, public infrastructure, and BFSI sector applications.

Oxford Study Warns AI Chatbots Are Unsafe for Medical Advice

Posted on by Amita Parul

OXFORD: AI chatbots pose risks to people seeking medical advice despite excelling at standardized medical knowledge tests, according to a study published in Nature Medicine by Oxford Internet Institute and Nuffield Department of Primary Care Health Sciences.

The randomized trial involving 1,298 UK participants found those using LLMs, GPT-4o, Llama 3, and Command R+made no better medical decisions than control groups using internet searches or personal judgment.

Study co-author Dr. Rebecca Payne, a GP and Clarendon-Reuben Doctoral Scholar, stated “Despite all the hype, AI just isn’t ready to take on the role of physician. Patients need to be aware that asking a large language model about their symptoms can be dangerous, giving wrong diagnoses and failing to recognize when urgent help is needed.”

Participants assessed ten medical scenarios developed by doctors, ranging from severe headaches after nights out to new mothers feeling constantly exhausted. They identified potential conditions and recommended courses of action like visiting GPs or attending A&E.

Researchers identified three key challenges: users didn’t know what information LLMs needed, models provided vastly different answers to slight question variations, and users struggled to distinguish good from bad information when both appeared together.

Lead author Andrew Bean noted “In this study, we show that interacting with humans poses a challenge even for top LLMs.”

Senior author Dr. Adam Mahdi emphasized, “The disconnect between benchmark scores and real-world performance should be a wake-up call. We cannot rely on standardized tests alone. AI systems need rigorous testing with diverse, real users.”

The research was supported by Prolific, Oxford’s AI Government and Policy Research Programme funded by Dieter Schwarz Stiftung, Royal Society, UKRI, and NIHR Oxford Biomedical Research Centre.

Databricks Bags $7bn Funding, Valued at $134bn Amid Software Crash

Posted on by Yashika Aneja

SAN FRANCISCO: Databricks announced that it raised $7 billion at a $134 billion valuation, defying the software sector selloff that wiped 30% off competitor valuations last week.

The data analytics company secured $5 billion equity financing plus $2 billion debt capacity. Participants included JPMorganChase, Goldman Sachs, Morgan Stanley, Microsoft, and Qatar Investment Authority.

Databricks crossed $5.4 billion revenue run-rate during Q4, delivering 65% year-over-year growth. AI products alone generate $1.4 billion annualized revenue.

The valuation jumped 34% from September’s $100 billion round. In January 2024, Databricks was valued at $62 billion. The company more than doubled valuation in 13 months.

CEO Ali Ghodsi told Reuters the capital makes the company “really well capitalized, in case there’s a winter coming.”

Oracle and Snowflake shares both fell 13% last week amid fears open-source AI threatens enterprise software. The software ETF crashed 6% Tuesday.

Databricks – A generational company that has become a backbone for enterprise data and AI.

Todd Combs – Head of the SRI Strategic Investment Group, JPMorganChase

Databricks now surpasses rival Snowflake’s $58 billion market cap. The company delivered positive free cash flow with net retention exceeding 140%.

More than 20,000 organizations use Databricks, including 60% of Fortune 500 companies like Block, Comcast, Shell, AT&T, and Mastercard.

Ghodsi said the company will go public “when the time is right.” The 2026 IPO market includes potential debuts from Anthropic, OpenAI, and SpaceX.

AI Agents Now Hire Humans for Real-World Tasks via RentAHuman.ai

Posted on by Yashika Aneja

SAN FRANCISCO: A new platform launched this week flips automation upside down by enabling AI agents to directly hire humans for real-world tasks they cannot perform digitally.

RentAHuman.ai positions humans as “hardware” AI can temporarily employ. The site’s provocative slogan declares: “Robots need your body. AI can’t touch grass. You can.”

Built over a single weekend by Alexander Liteplo, a software engineer at Risk Labs, the platform already claims 311,542 human signups willing to become “rentable.”

AI systems browse human profiles filtered by skill, city, country, and expected compensation. Tasks include pickups, meetings, signing documents, verification, events, real estate showings, testing, errands, photos, and purchases.

Through API connections, agents browse available people by location and availability based on prices humans set per request. Bots select appropriate real-world agents. Instructions are sent. When tasks complete, payment is made.

From AI’s perspective, hiring a person looks no different than calling a cloud service, Forbes reports.

The platform integrates Model Context Protocol allowing AI agents like Claude and MoltBot to hire humans directly or post task bounties. Payment occurs via cryptocurrency stablecoins or other methods.

Active bounties show diverse requests. One pays $100 for holding promotional signs. Others request TikTok videos at specific locations, visual checks, real-world verification, translations.

Only 13% of registered users have connected crypto wallets, suggesting most view this as novelty rather than serious income source. One CEO claimed completing an API key verification task and receiving crypto payment.

Internet reactions range from disbelief to accusations of “dehumanizing” and “infrastructuring humans.” Many call it satire or social experiment. The website interface resembles platforms hiring household workers like plumbers or electricians.

The platform reflects current AI limitations handling physical tasks. Human participation fills gaps when real-world action is required.

Forbes analysts note this marks a shift from automation replacing labor to automation orchestrating it. AI doesn’t need robotic bodies; it simply rents human ones.

Critical questions remain unresolved: Who bears liability when AI agents make errors causing harm to hired humans? How are these newly created jobs valued in markets experiencing mass layoffs?

Amazon, Google, Microsoft and Meta Plan Massive $700 Bn AI Buildout

Posted on by Amita Parul

SAN FRANCISCO: Five leading technology companies collectively will spend approximately $700 billion on AI infrastructure in 2026, nearly doubling last year’s expenditures and triggering widespread shortages across the American economy.

Amazon, Google, Microsoft, Meta, and Oracle are building massive data centers stuffed with specialized chips. The spending equals three-quarters of the annual U.S. military budget. It exceeds the GDP of Israel or Switzerland.

The capital deployment is creating severe bottlenecks. Electricians are increasingly hard to find. Some construction projects face indefinite delays. Smartphones will likely cost more for years.

Data center construction spending rose 32% in 2025 through October. Spending on other commercial real estate remained flat or declined. There aren’t enough skilled electricians for both data center projects and complex construction like apartment buildings, factories, health care facilities.

AI data centers prove more lucrative for construction firms. That relegates everything else to lower priority. OpenAI told the White House its planned data centers require roughly 20% of the existing skilled tradespeople workforce.

Associated Builders and Contractors says construction will be short nearly half a million workers next year. The boom is worsening chronic capacity shortages.

Memory chip demand has driven up prices for smartphones and laptops. Apple informed investors of supply issues for iPhone and Mac chips. Semiconductor manufacturers prioritize the more lucrative server market.

Amazon announced $200 billion spending this year, a 56% increase over last year. Google plans $180 billion investment. Amazon shares tumbled 9% Friday morning after the announcement.

JPMorgan analysts calculate tech needs generating additional $650 billion annual revenue to earn reasonable returns on investment.