Argentina is the first market in Latin America where Bitso (Mexican Cryptocurrency Exchange) launches crypto payments through QR codes. This payment method will enable Bitso’s one million users in this country to pay their daily expenses from their apps at any merchant that accepts QR payments. To make a payment, the user can choose between Argentine pesos (ARS), USD stablecoins, Bitcoin (BTC), Ether (ETH), or DAI.
Mexicans can put their cryptocurrencies to a new use: using them as collateral for a credit card. This is thanks to the card launched this week by local startup Crecy, developed in collaboration with Pomelo, a payment infrastructure and card issuance company from Argentina. Those who want to obtain it must leave Bitcoin, Ethereum, Solana, Cardano, or Polkadot as collateral and will be able to access a line of credit ranging from 1,000 to 720,000 Mexican pesos (US$50 to US$35,000 approximately).
Better first-party data is often offered as a way to compensate for the loss of third-party data due to privacy changes. So it comes as a shock that CMOs in this Wunderkind survey rated first-party data the least useful tool for improve martech results. In fact, respondents were pretty negative on tech in general: just 9% felt their tech strategy improves their marketing performance, 90% felt resources gaps were hindering their success, and 71% plan to reduce online marketing spend in the future.
Unauthorized training data isn’t an existential threat to generative AI but it’s certainly a headache for users and developers alike. Most developers are trying to exclude materials that creators have explicitly labeled as unauthorized and citing “fair use” as justification for copying everything else. Getty Images has taken an opposite approach, building its gen AI tool only on materials that are explicitly licensed. It’s possible that tracing the provenance of training data will become a standard, similar to how organic food producers trace the origins of their ingredients.