Stablecoins have changed how people think about moving money, and their exponential rise over the past year has pushed mainstream payment networks to figure out how to adapt. Visa, one of the world’s largest payment processors, appears to be well on its way to adapting to this new paradigm. On Thursday, the company announced a new service to help its customers do the same. The Visa Stablecoin Platform is an internal system that lets banks and fintechs handle stablecoins, which are a form of cryptocurrency that are backed with reserves to maintain a 1-to-1 peg to the dollar, within their existing Visa payment and treasury workflows. Visa, which settles roughly $15 trillion in payments annually, already processes several billion dollars in stablecoin settlements and hopes to grow that by offering a simpler way for its network of about 15,000 financial institutions and more than 200 million merchants to use stablecoins. “It’s less about accessing stablecoins and more about how… this interoperate[s] with their treasury settlement, their money movement workflows, [and] their existing bank setups,” Rubail Birwadker Visa’s global head of growth, told Fortune. Read more [paywall removed for Redditors]: https://fortune.com/2026/07/16/exclusive-visa-new-platform-stablecoin-services-200-million-merchants/?utm_source=reddit/ submitted by /u/fortune [link] [Kommentare]

Hi everyone, I've been working independently on a recurrent architecture called **DABSN (Dynamic Adaptive Bias State Network)** for the past several months, and I finally reached the point where I feel comfortable sharing the first preprint. The paper is mainly about the architecture itself and its behavior on reasoning, memory, and long-sequence benchmarks (MQAR, Copy, Key-Value retrieval, A5/60, etc.). The code is also public with PyTorch, C++, and Triton implementations so everything can be reproduced. While finishing the paper, I also trained my first language model with the same cell: - 24M parameters - 1B pretraining tokens - GPT-2 tokenizer Those results ended up being much more interesting than I expected, so I'm now writing a second paper focused entirely on language modeling, long-context behavior, and scaling. This is where I'd love some help. I'm looking for people who might be interested in collaborating on the next paper, whether that's: - independent reproduction of the results, - helping design stronger baselines and evaluations, - or having access to larger GPU clusters so we can scale the architecture much further than I can on my own. Everything I'm doing is intended to be open and reproducible from day one. I'd really appreciate any feedback on the paper, and if the project sounds interesting, I'd love to chat. Preprint and Github are in the comments. submitted by /u/BleedingXiko [link] [Kommentare]

i'm subscribed to a ai/ml newsletter but i feel like its not enough. i need a complete and not too time consuming way to keep up with ai/ml news because i feel like im left behind. thanks in advance submitted by /u/mehmetflix_ [link] [Kommentare]

Prediction market platform Kalshi has called off plans for its latest offering: Contracts that would let users wager on upcoming flight cancellations. The decision comes after social media users expressed fears that bad actors could make mischief at airports in order to collect a payout, and after popular airline-tracking service FlightAware said Kalshi could not use its data to resolve the contracts. Kalshi had planned to begin listing flight cancellation contracts on Wednesday, according to a regulatory filing, but a spokesperson on Thursday told Fortune that the company has opted not to go forward for now. Kalshi’s proposed contracts applied to airport-wide cancellations, not individual flights, and included detailed rules prohibiting insiders—including TSA agents and airport and union officials—from placing wagers. Nonetheless, skeptics seized on the news to warn that airport workers seeking a payoff might collude to cancel a flight, or that crooks could call in fake threats to shut down air travel. It’s unclear to what degree the concern over the Kalshi flight contracts was justified given the prohibition of wagers by insiders, and in light of stiff criminal penalties for threats or hoaxes directed at the airport industry. Read more [paywall removed for Redditors]: https://fortune.com/2026/07/16/kalshi-flight-cancellations/?utm_source=reddit/ submitted by /u/fortune [link] [Kommentare]

SOLANA VIBES 10-16 JULY 2026 more vibes https://x.com/solana_digest/status/2077811846782820783 submitted by /u/SolBrothers_ [link] [Kommentare]

MyEtherWallet is continuing to go all on in tokenized stocks. They just launched a campaign incentivizing trade + hold. You trade $100+ in tokenized stock, hold it for 14 days, get $10 usdc. I used my rabby wallet to do it on their portfolio manager on my desktop here https://app.myetherwallet.com/ And then downloaded their mobile and did another hundred there. Looks like there are a bunch of stock options, I did QQQ and SPY to hedge and not go full regard on spacex or whatever. NFA The second RWA campaign ive seen then launch so far. Pretty interesting submitted by /u/Exarc799 [link] [Kommentare]

Background: I confounded a startup last year on Execution as a Service model. We're two confounders, and a core team of 5 guys. 4 of us used to be at xAI human data. And collectively we've worked for most of the leading genAI companies in the human data space. We started off as a managed outsourcing platform where we assign a frac COO to handle your entire outsourcing ops across functionalities which also included AI annotation and labelling. The problem: We were trying to secure contracts all over the place. Though we had 150+ registered fulfilment partners, and we secured some sizable contracts, I was genuinely confused about the growth and the direction of the company, specially with the kind of developments happening in the ops domain. I just brokered a deal valued at over 100k just for sharing internal ops data for AI training. We can't predict exactly how would the space look like. The present: The outsourcing business isn't fully justified to the kind of profiles the core team has. We were being reduced a software and marketing firm. We figured out that we need to stay relevant in the data industry. With the logistical edge that I have, and the trial run I did, I am very confident about working on physical data. We collected over 10 hours sample dataset spanning across household, industrial, construction, and electrical egocentric data. The question: Before we jump into physical data, I am genuinely looking for researchers' perspectives on ego-exocentric vs synthetic data. I understand that the upfront cost is high for synthetic, but long term cost is significantly cheaper, but how does the difference play out in the actual training workplace. TIA submitted by /u/Low_Can_4600 [link] [Kommentare]

A six-week UK trial paired Age UK volunteers with older adults through telepresence robots placed in their homes. Volunteers used the robots for regular social interaction and to guide participants through personalized exercise plans two to three times per week. Researchers reported small reductions in physical frailty, improved confidence and increased digital literacy. Some participants also became comfortable enough to begin socializing outside their homes again. The project is now being used to inform UK policy discussions around standards, procurement, regulation and implementation of assistive robots in health and social care. submitted by /u/Responsible-Grass452 [link] [Kommentare]