Enterprise AI company Cohere launched a new family of multilingual models on the sidelines of the ongoing India AI Summit. The models, dubbed Tiny Aya, are open-weight — meaning their underlying code is publicly available for anyone to use and modify — support over 70 languages, and can run on everyday devices like laptops without requiring an internet connection.

The model, launched by the company’s research arm Cohere Labs, supports South Asian languages such as Bengali, Hindi, Punjabi, Urdu, Gujarati, Tamil, Telugu, and Marathi. 

The base model contains 3.35 billion parameters — a measure of its size and complexity. Cohere has also launched TinyAya-Global, a version fine-tuned to better follow user commands, for apps that require broad language support. Regional variants round out the family: TinyAya-Earth for African languages; TinyAya-Fire for South Asian languages; and TinyAya-Water for Asia Pacific, West Asia, and Europe.

“This approach allows each model to develop stronger linguistic grounding and cultural nuance, creating systems that feel more natural and reliable for the communities they are meant to serve. At the same time, all Tiny Aya models retain broad multilingual coverage, making them flexible starting points for further adaptation and research,” the company said in a statement.

Cohere noted that these models, which were trained on a single cluster of 64 H100 GPUs (a type of high-powered chip by Nvidia) using relatively modest computing sources, are ideal for researchers and developers building apps for audiences that speak native languages. The models are capable of running directly on devices, so developers can use them to power offline translation. The company noted that it built its underlying software to suit on-device usage, requiring less computing power than most comparable models.

In linguistically diverse countries like India, this kind of offline-friendly capability can open up a diverse set of applications and use cases without the need for constant internet access.

The models are available on HuggingFace, the popular platform for sharing and testing AI models, and the Cohere Platform. Developers can download them on HuggingFace, Kaggle, and Ollama for local deployment. The company is also releasing training and evaluation datasets on HuggingFace and plans to release a technical report detailing its training methodology.

The startup’s CEO, Aidan Gomez, said last year that the company plans to go public “soon.” According to CNBC, the company ended 2025 on a high note, posting $240 million in annual recurring revenue, with 50% growth quarter-over-quarter throughout the year.

Airbnb said on Tuesday that it is launching its “Reserve Now, Pay Later” feature — which lets users secure bookings without immediate payment — globally. This allows users to cancel their bookings if there is a change of plans without losing money upfront.

The company launched the feature in the U.S. last year for domestic travel. Airbnb said that properties with a “flexible” or “moderate” cancellation policy are eligible for the upfront reservation. With this option, users get charged closer to their check-in date rather than at the time of booking. The feature mirrors “buy now, pay later” payment plans that have become popular in e-commerce, making expensive travel more accessible by spreading out costs. The company noted that since the launch, the feature saw 70% adoption for eligible bookings.

During its earnings calls for Q4 2025, Airbnb said that the feature helped grow nights booked in the quarter.

“Reserve Now, Pay Later saw significant adoption among eligible guests in Q4. It’s also led to longer booking lead times and a mix shift towards larger entire homes, especially those with four or more bedrooms, contributing to the increase in average daily rate,” Ellie Mertz, CFO of Airbnb, said during the call.

Mertz noted that Airbnb’s overall cancellation rate jumped from 16% to 17% for the quarter, and it was higher among customers who use the upfront booking product. However, she said that this was “not hugely material relative to the broader cancellations on the platform.”

Last year, the company surveyed U.S. travelers along with Focaldata, a London-based market research and polling company. Of those surveyed, 60% of participants said that a flexible payment option is important while booking a holiday, and 55% said that would use a flexible payment option.

The company has been experimenting with pay-later products for years now. Back in 2018, Airbnb launched a product that allowed users to book a property by paying 20% or 50% of the total charges. upfront, with the rest due later. In 2023, the company partnered with fintech firm Klarna to let users pay for their stays in four installments over six weeks.

Indian conglomerate Adani Group said on Monday it would invest $100 billion over the next decade to build data centers specialized for AI across the country, a move that underscores India’s ambition to play a larger role in the global AI race.

The investment, which will run through 2035, is aimed at building renewable-energy-powered data centers designed to support AI workloads, the company said. It expects the plan to catalyze an additional $150 billion in related investments and result in a $250 billion AI infrastructure ecosystem in India over the decade.

Adani is making this commitment against a backdrop of skyrocketing investments in AI infrastructure as companies increasingly look beyond the U.S. for computing power, energy and friendly regulation. India, with its expanding digital economy and growing renewable-energy capacity, has emerged as a major destination for data centers and AI-related infrastructure over the past couple of years.

The announcement coincides with India’s ongoing AI Impact Summit in New Delhi this week, where leaders from some of the world’s top AI companies, including OpenAI, Nvidia, Anthropic, Microsoft and Google, are meeting policymakers and industry executives.

Adani Group chairman Gautam Adani (pictured above) described the plan as a long-term bet on the convergence of energy and computing. “India will not be a mere consumer in the AI age,” he said, adding that the group aims to help build a domestic AI infrastructure base.

The plan is to build atop Adani’s own existing data-center platform and its partnerships with companies like Google and Microsoft. The conglomerate is developing large-scale AI data-center campuses in Visakhapatnam and Noida, and has plans for more facilities in Hyderabad and Pune. An expanded partnership with Walmart-owned Flipkart will focus on another AI data center.

Adani said the broader plan calls for deploying up to 5 gigawatts of data-center capacity. The company said the facilities will be developed as a unified system that would scale power generation and processing capacity in parallel.

The effort builds on AdaniConneX, a joint venture between Adani Enterprises and U.S.-based EdgeConneX, a developer and operator of data centers for hyperscale and enterprise customers. The JV, Adani said, has already developed about 2 gigawatts of data-center capacity across India.

Central to the strategy is Adani’s renewable-energy portfolio, which the group said will supply carbon-neutral power to the data centers. The company pointed to its 30-gigawatt Khavda renewable project in western India — more than 10 gigawatts of which is already operational — and said it plans to invest an additional $55 billion to expand renewable generation and battery energy storage over the coming years.

To reduce exposure to global supply-chain disruptions, Adani said it plans to co-invest in domestic manufacturing of critical components, such as transformers, power electronics and thermal management systems.

Adani did not respond to questions about how much of the $100 billion investment is already committed capital, how the spending will be phased over the coming years, and when the first large-scale AI workloads are expected to become operational.